@article{pmid42522874b,

title = {Pathways to schizophrenia: Divergent effects of childhood trauma and polygenic risk on cognition and subcortical dynamics},

author = {Danqing Huang and Yicheng Long and Zhening Liu and Wenjian Tan and Xiawei Liu and Yunzhi Pan and Feiwen Wang and Lena Palaniyappan},

doi = {10.1192/j.eurpsy.2026.12246},

issn = {1778-3585},

year  = {2026},

date = {2026-07-01},

journal = {Eur Psychiatry},

pages = {1--39},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42476975b,

title = {Structural brain complexity is associated with linguistic complexity in psychosis},

author = {Alexandra Korda and Wolfram Hinzen and Rui He and Peter van Dyken and Michael Mackinley and Eric Toyota and Mihai Avram and Christina Andreou and Stefan Borgwardt and Lena Palaniyappan},

doi = {10.1192/j.eurpsy.2026.12242},

issn = {1778-3585},

year  = {2026},

date = {2026-07-01},

journal = {Eur Psychiatry},

pages = {1--30},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42471042b,

title = {Resting magnetoencephalography alterations in severe mental illnesses: A systematic review},

author = {Fernando Gonzales-Aste and Jessica Ahrens and Dominic Boutet and Hsi Tiana Wei and Sylvain Baillet and Lena Palaniyappan},

doi = {10.1016/j.neubiorev.2026.106867},

issn = {1873-7528},

year  = {2026},

date = {2026-07-01},

journal = {Neurosci Biobehav Rev},

volume = {189},

pages = {106867},

abstract = {Schizophrenia, major depressive disorder (MDD), and bipolar disorder (Severe Mental Illnesses: SMIs), share genetic risk and brain structural changes, but their neural mechanisms remain unclear. Magnetoencephalography (MEG), with millisecond precision, enables direct examination of shared and disorder-specific disturbances in the timing of spontaneous brain activity. We reviewed resting-state MEG evidence on spectral power, connectivity, information-theoretic complexity, and brain dynamics across SMIs. A comprehensive search yielded 62 studies. Three reviewers screened, retrieved, and extracted data on MEG-related variables across regional activity (power), coordination of activity (connectivity, coherence, synchrony), regularity of activity (complexity, entropy), and overall dynamics. Three principal findings come forth. Beta oscillations emerge as a promising, albeit yet unconfirmed, candidate transdiagnostic signal, with increased power now reported across independent investigations of all three disorders and correlating with hallucinations, sleep disturbances, and cognitive deficits, consistent with disrupted predictive processing. However, direct within-study cross-diagnostic comparisons remain sparse (2 of 62 studies). Preliminary support exists for complexity-age dissociation to partition SMIs into neuroprogressive and state-dependent trajectories: neural complexity declines with age in schizophrenia and bipolar disorder (opposite to healthy aging), while depression preserves the normative trajectory. Slow-wave activity diverges sharply: schizophrenia shows a widespread increased slow-wave dominance, while mood disorders show a decrease in activity. We propose a temporal disorganisation spectrum of SMI from excessive fragmentation (schizophrenia) to pathological rigidity (depression), with bipolar disorder occupying an intermediate position. This framework offers biomarker-type utility for stratifying illness severity, tracking neuroprogression, and identifying transdiagnostic therapeutic targets, particularly beta-modulatory neuromodulation interventions applicable across SMIs. Protocol registration: Open Science Framework (http://osf.io/v2gtb/).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42367670b,

title = {Associations of local white matter geometry with network efficiency, macrostructural abnormalities, and clinical severity in behavioural variant frontotemporal dementia},

author = {Qinyao Sun and Yu Zhang and Xin Jin and Jian Cheng and Jianyu Li and Ting Qiu and Zhanbing Ren and Ke Li and Huixiong Zhang and  and Kewei Chen and Lena Palaniyappan and Yifan Chen and B Blair Braden and Yuanchao Zhang},

doi = {10.1093/braincomms/fcag226},

issn = {2632-1297},

year  = {2026},

date = {2026-01-01},

journal = {Brain Commun},

volume = {8},

number = {3},

pages = {fcag226},

abstract = {Behavioural variant frontotemporal dementia (bvFTD), marked by profound changes in behaviour and personality, is the most common subtype of frontotemporal dementia, driven by neurodegeneration in frontotemporal regions. This neurodegeneration pattern is partially shaped by white matter abnormalities arising from the spread of protein aggregates along axonal pathways. While prior studies mainly focused on diffusion tensor imaging metrics such as fractional anisotropy and mean diffusivity, the alteration in local white matter geometry remains largely unexplored. Using a novel Director Field Analysis (DFA) method, 51 patients with bvFTD and 51 healthy controls were studied to examine alterations in the local geometry of white matter fibres in bvFTD, and their associations with macrostructural morphology, global network parameters, and clinical manifestations. Unlike the unidirectional decrease in fractional anisotropy and increase in mean diffusivity, we identified significant bidirectional alterations in white matter local geometry, characterized by increased geometric distortion in the forceps minor and dorsal cingulum and decreased distortion in widespread frontotemporal association tracts, including the inferior fronto-occipital fasciculus, superior longitudinal fasciculus, uncinate fasciculus, frontal aslant tract, and arcuate fasciculus. Patients with bvFTD also showed reduced cerebral white and grey matter volumes (both  < 0.0026), enlarged lateral ventricles and choroid plexus (both  < 0.0001), decreased global network efficiency ( = 0.0010), and increased local efficiency ( = 0.0014). Importantly, decreased white matter geometric distortion across affected tracts was strongly associated with greater clinical severity, as reflected by higher Clinical Dementia Rating scores ( = -0.68,  < 0.0001). Mediation analyses further demonstrated that white matter geometric distortion significantly mediated the effects of macrostructural atrophy and reduced global network efficiency on clinical severity. Furthermore, neuroimaging-transcriptional association analysis on the group differences in nodal efficiency of the white matter networks identified several biological processes/pathways critical for the formation and propagation of TAR-DNA-binding protein 43/microtubule-associated protein tau pathologies along axonal pathways, as well as processes related to cellular homeostasis and oligodendrocyte-related pathways that may exacerbate these proteinopathies. Our findings advance understanding of the neural bases of the functional impairments in bvFTD and suggest potential mechanistic pathways for developing novel treatment strategies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42360412b,

title = {Speech and Language Markers of Bipolar Disorder: Challenges and Opportunities},

author = {Farida Zaher and Jessica Ahrens and Delphine Raucher-Chéné and Alban Voppel and Lena Palaniyappan},

doi = {10.1111/bdi.70119},

issn = {1399-5618},

year  = {2026},

date = {2026-08-01},

journal = {Bipolar Disord},

volume = {28},

number = {5},

pages = {e70119},

abstract = {BACKGROUND: Clinicians aspire to predict the emergence of Bipolar Disorder (BD) in a timely manner. To accomplish this, markers reflecting mental states that can be gathered non-invasively and at large scale are needed. Here, we systematically evaluate evidence relating speech-based markers to mood states in BD.nnMETHODS: We searched Medline and Google Scholar for all published studies in English up to February 2026 on the use of speech markers in BD. We undertook thematic analysis on abstracts using topic modeling and a qualitative gap analysis to identify potential opportunities for future research.nnRESULTS: 43 out of 867 studies were included after screening. Topic analysis revealed an emerging focus on mapping mood states to automated speech features. Most studies focused on cross-sectional detection of bipolar mood states, or BD as a diagnosis, rather than the prediction of upcoming mood states. Speech features distinguished BD from schizophrenia, depression, and healthy controls. Manic states were characterized by quantifiable measures of pressured speech, derailment, grammatical errors, and word repetition; depressive states by an increased use of personal pronouns, reduced verbal fluency, and speech quantity. Overall, attempts to replicate observations were limited.nnCONCLUSION: Acoustic and lexical-semantic markers vary with manic, psychotic, or depressive states. At present, the evidence is insufficient for clinical utility in relapse prediction, response monitoring, or diagnosing mixed episodes or state changes in BD. We recommend that future research leverages the growing capabilities of natural language processing through longitudinal and cross-linguistic studies to strengthen the evidence base and advance the clinical utility of speech markers for BD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42340705b,

title = {Neurometabolites and Antipsychotic Response in Psychosis: A Mega-Analysis},

author = {Bridget King and Kirsten Borup Bojesen and Charlotte Crisp and Andrea de Bartolomeis and Lieuwe de Haan and Camilo de la Fuente-Sandoval and Kara Dempster and Richard J Drake and Paola Dazzan and Bjørn H Ebdrup and Lejia Fan and Ariel Graff-Guerrero and Birte Yding Glenthøj and Shiori Honda and Oliver Howes and Li-Chung Huang and Rene Kahn and James MacCabe and Marta Matrone and Kate Merritt and Meghan McIlwain and Philip McGuire and Shinichiro Nakajima and Stephen M Lawrie and Lena Palaniyappan and Francisco Reyes-Madrigal and Bruce Russell and Akira Sawa and Sukhi Shergill and Krish D Singh and Iris E Sommer and James M Stone and Junyu Sun and Sakiko Tsugawa and Fumihiko Ueno and Marieke van der Pluijm and Elsmarieke van de Giessen and James T R Walters and Kun Yang and Yen Kuang Yang and Matthew J Kempton and Alice Egerton},

doi = {10.1001/jamapsychiatry.2026.1674},

issn = {2168-6238},

year  = {2026},

date = {2026-06-01},

journal = {JAMA Psychiatry},

abstract = {IMPORTANCE: Revealing neurobiological markers of antipsychotic nonresponse in psychosis may aid outcome prediction and inform novel treatment targets.nnOBJECTIVE: To examine differences in neurometabolites in antipsychotic nonresponsive compared to antipsychotic-responsive psychosis using individual participant data and meta-analysis.nnDATA SOURCES: Web of Science was searched for studies published between January 1, 1980, and November 1, 2025. Authors of 21 eligible studies identified before August 2024 were invited to contribute individual participant data.nnSTUDY SELECTION: Eighteen studies examining neurometabolites by treatment response in psychosis contributed individual participant data for the mega-analysis. These studies plus a further 5 studies were included in the meta-analyses of standardized mean differences and variability.nnDATA EXTRACTION AND SYNTHESIS: Individual participant data were analyzed using linear mixed models with study as a random effect. Subgroup analyses examined prospective designs and treatment-resistant samples. Published group means and standard deviations were extracted for meta-analyses.nnMAIN OUTCOMES AND MEASURES: Group differences in glutamate, glutamate plus glutamine, choline, myo-inositol, N-acetylaspartate, γ-aminobutyric acid, and glutathione in the medial frontal cortex, dorsolateral prefrontal cortex, thalamus, and basal ganglia.nnRESULTS: The mega-analysis included 1189 participants from 18 studies; of these, 476 were treatment nonresponders (mean [SD] age, 33.0 [12.5] years; 340 male), 427 were treatment responders (mean [SD] age, 30.3 [11.5] years; 299 male), and 286 were healthy control individuals (mean [SD] age, 31.0 [12.5] years; 170 male). Compared with the antipsychotic response group, nonresponders showed elevations in medial frontal glutamate (Glass Δ = 0.21; P = .02), glutamate plus glutamine (Glass Δ = 0.29; P = .002), choline (Glass Δ = 0.22; P = .03), and myo-inositol (Glass Δ = 0.35; P = .001); similar elevations were observed relative to control individuals. Elevated medial frontal glutamate plus glutamine in antipsychotic nonresponders compared with responders was also observed prospectively in first-episode psychosis (Glass Δ = 0.41; P = .002), whereas myo-inositol elevations were greatest in individuals meeting criteria for treatment-resistance (Glass Δ = 0.64; P = .001). The meta-analysis of 23 studies (1844 participants) also showed elevated medial frontal choline and myo-inositol in antipsychotic nonresponse compared with response.nnCONCLUSIONS AND RELEVANCE: These findings provide evidence of an association between antipsychotic nonresponse in psychosis with elevations in medial frontal glutamate, choline, and myo-inositol. The presence of elevations in these markers supports the continued investigation of glutamate-acting and inflammatory pathway-associated interventions for psychosis and schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42296054b,

title = {Operationalizing the Whole of Psychic Life: Toward a Structured Framework for Psychopathology},

author = {Ary Gadelha and Bernardo Haguiara and Pedro Gabriel Lorencetti and Gabriela Koga and Igor Studart and Lena Palaniyappan},

doi = {10.1159/000552393},

issn = {1423-033X},

year  = {2026},

date = {2026-06-01},

journal = {Psychopathology},

pages = {1--12},

abstract = {BACKGROUND: Contemporary psychiatry has advanced by decomposing behavior into discrete constructs, improving reliability but fragmenting conceptual foundations. Excessive comorbidity, blurred diagnostic boundaries, and the reification of operational criteria have created a gap between empirical data and the understanding of mental life as a coherent, lived whole - the modern paradox of "more data, less coherence."nnSUMMARY: We revisit Karl Jaspers' notion of the whole of psychic life (Ganze des Seelenlebens) as a foundational reference. After clarifying Jaspers' methodological framework - emphasizing the complementary roles of phenomenological description, understanding (Verstehen), and causal explanation (Erklären) - we propose an "upframing" of his concept through 5 guiding principles: relationality, historicity, subjectivity, intentionality, and indeterminacy. These principles translate classical phenomenology into a conceptual framework that can be operationalized in contemporary psychiatry, statistics, and neuroscience. We also develop practical tools to isolate patterns of experience without treating them as autonomous entities, allowing reductionism to function as a local methodological tool rather than a global explanatory framework. Finally, we discuss implications for diagnostic systems, transdiagnostic research, and emerging technologies.nnKEY MESSAGES: Re-centering inquiry on the whole of psychic life restores context to clinical practice and integrates subjective experience with biological data. The 5 proposed principles offer a structured, operationalizable approach to Jaspers' legacy. This framework provides a coherent point of reference for psychiatric education, research design, and the interpretation of neurobiological findings without losing the human core of the discipline.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42204548b,

title = {Putative glymphatic dysfunction links extracellular fluid dysregulation to white matter degeneration and clinical impairment in amyotrophic lateral sclerosis},

author = {Xin Jin and Yan Fu and Ting Qiu and Jianyu Li and Huixiong Zhang and Yifan Chen and Kewei Chen and Yuanchao Zhang and Junling Wang and Xiaoping Yi and Lena Palaniyappan and B Blair Braden},

doi = {10.1186/s12916-026-04948-z},

issn = {1741-7015},

year  = {2026},

date = {2026-05-01},

journal = {BMC Med},

volume = {24},

number = {1},

abstract = {BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disorder characterized by progressive motor neuron degeneration and prominent extra-motor involvement. Impaired clearance of neurotoxic proteins has led to increasing interest in the brain glymphatic system; however, its in vivo associations with brain microstructure and clinical heterogeneity remain incompletely understood.nnMETHODS: One hundred forty-six patients with ALS and 149 demographically matched healthy controls (HCs) underwent multimodal MRI and comprehensive clinical assessments. Putative glymphatic function was quantified using diffusion tensor imaging along perivascular space (DTI-ALPS). Extracellular free water fraction (FWF) and free-water-corrected fractional anisotropy (fwcFA) were derived to characterize extracellular fluid and white matter microstructure. Group differences were assessed using vertex-wise and voxel-wise analyses with correction for multiple comparisons. Associations among imaging metrics and clinical measures were evaluated using correlation and serial mediation analyses.nnRESULTS: Compared with HCs, patients with ALS exhibited significantly reduced DTI-ALPS index, widespread increases in cortical FWF, bidirectional alterations in white matter FWF, and extensive reductions in fwcFA across major white matter tracts. Reduced DTI-ALPS was associated with changes in extracellular free water and white matter microstructural integrity, whereas FWF and fwcFA measures were associated with functional, cognitive, and emotional outcomes. Mediation analyses identified significant indirect associations between DTI-ALPS and both functional and cognitive measures through a pathway involving cortical FWF, white matter FWF, and fwcFA, although direct associations were not observed.nnCONCLUSIONS: These findings provide in vivo evidence that putative glymphatic dysfunction co-occurs with extracellular fluid alterations, white matter microstructural changes, and clinical impairment in ALS. Multi-compartment diffusion imaging may offer complementary markers for characterizing brain microstructure and its clinical relevance in ALS.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42187272b,

title = {The functional relevance of a short assessment of formal thought disorder in psychosis},

author = {Fatme Abboud and Jessica Ahrens and Estèe Ballès and Valentina Bambini and Bill Deakin and Neil A Harrison and Tilo Kircher and Gina Kuperberg and Peter F Liddle and Rohit Lodhi and Michael Mackinley and Susan L Rossell and Krish D Singh and Iris E Sommer and Alban Voppel and Farida Zaher and Nadia Zeramdini and Lena Palaniyappan},

doi = {10.1192/bjp.2026.10650},

issn = {1472-1465},

year  = {2026},

date = {2026-05-01},

journal = {Br J Psychiatry},

pages = {1--9},

abstract = {BACKGROUND: Formal thought disorder (FTD) is a highly disabling transdiagnostic feature that impedes communication and social ties. Progress in understanding and treating FTD has been hampered by the uncertainties in its assessment.nnAIMS: We examined if a short 3-5min assessment of transcribed speech can capture the latent dimensions and network structure of FTD and predict functional outcomes.nnMETHOD: In a transdiagnostic sample ( = 666) with a single longitudinal follow-up over 3-12 months ( = 244), we administered the short form of the Thought and Language Index to measure eight individual features of FTD. We determined the baseline factor structure of FTD, its temporal invariance at follow-up, and the predictive validity of FTD dimensions on the global single-item Social and Occupational Functioning Assessment Scale scores at baseline and follow-up. We identified the most influential and putative primary phenomena within the FTD syndrome, using network analysis.nnRESULTS: Factor analyses revealed a stable three-factor model of FTD: impoverishment (poverty of speech, weakening of goal), loosening (looseness, illogicality) and peculiarities (peculiar words, peculiar sentences), with excellent fit (Comparative Fit Index: 0.997, root mean square error of approximation: 0.040) and metric invariance over time. Impoverishment and peculiarities predicted functioning at baseline and 3-12 months later (cross-sectional:  = -0.196,  < 0.001 and  = -0.298,  = 0.001, respectively; longitudinal:  = -0.201,  = 0.037 and  = -0.336,  = 0.042, respectively). Looseness and poverty of speech were putative primary features influencing other FTD phenomena. Weakening of goal and peculiar sentences were the most connected phenomena.nnCONCLUSIONS: By integrating latent variable and network approaches, we provide a unified, empirically grounded framework to interpret FTD assessed using a brief speech task. We report a replicable three-dimensional structure, identify central symptoms that may maintain the FTD syndrome, and the specific dimensions that influence functional disability. These findings clarify the prognostically valuable features of FTD for future mechanistic and interventional research.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42142295b,

title = {Development and in vivo proof-of-concept of delayed alternating nutation tailored excitation point resolved spectroscopy (dante-press): a frequency-selective single voxel spectroscopy sequence applied to in vivo measurements of naa and glu at 7.0 T},

author = {Kesavi Kanagasabai and Omer Oran and Lena Palaniyappan and Jean Théberge},

doi = {10.1007/s10334-026-01365-4},

issn = {1352-8661},

year  = {2026},

date = {2026-05-01},

journal = {MAGMA},

abstract = {OBJECTIVE: Single-voxel proton magnetic resonance spectroscopy (1H-MRS) is a non-invasive in vivo imaging technique used to quantify the concentration of human brain metabolites. Frequency-selective 1H-MRS techniques reduce spectral complexity and simplify spectral modeling. We introduce a single-shot frequency-selective sequence known as Delays-Alternating-Nutation-Tailored-Excitation-Point-RESolved-Spectroscopy (DANTE-PRESS) and test its precision when measuring glutamate and NAA at 7 Tesla in phantoms and human brain in vivo.nnMATERIAL AND METHODS: DANTE-PRESS was programmed within the software environment of the Siemens Magnetom 7 Tesla MR scanner at the Centre for Functional Metabolic Mapping in London, Ontario. Two scans were obtained on phantoms and in 4 healthy volunteers (20 × 20x20mm voxel at the dorsal anterior cingulate cortex) as an in vivo proof-of-concept to refocus glutamate or NAA.nnRESULTS: DANTE-PRESS preserves the signal of the metabolite of interest while suppressing unwanted signals via a narrow-band frequency-selective refocusing pulse. DANTE-PRESS produces metabolite spectral signatures with J-evolution equivalent to that seen in a PRESS sequence with less than half the echo time. The inter-individual coefficients of variance were low and Cramer-Rao Lower Bounds were less than 5.1% for glutamate and NAA.nnDISCUSSION: Future work involving test-retest in vivo study in healthy volunteers to get measurements of glutamate along with other metabolites such as glutathione and GABA.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42142164b,

title = {Age of onset: static and dynamic brain regional activity in first-episode drug-naïve schizophrenia},

author = {Maoxing Zhong and Jie Yang and Miao Zhang and Feiwen Wang and Yiju Wang and Lifu Tan and Zhening Liu and Lena Palaniyappan},

doi = {10.1007/s00787-026-03056-w},

issn = {1435-165X},

year  = {2026},

date = {2026-05-01},

journal = {Eur Child Adolesc Psychiatry},

abstract = {The age at which schizophrenia manifests is a critical factor influencing long-term outcomes. It is essential to distinguish the effects of the illness phase from those of the age of onset. We assessed static/dynamic brain regional activity from 428 participants, split into four groups based on onset-age (early-onset schizophrenia [EOS] and adult-onset schizophrenia [AOS]) and treatment status: (1) drug-naïve first-episode patients (48 EOS and 62 AOS); (2) patients treated for ≤ 12 months (60 EOS and 53 AOS); (3) patients treated for > 12 months (56 EOS and 56 AOS); and (4) 93 healthy controls (32 age-matched with EOS, 61 age-matched with AOS). We conducted a principal component analysis and subsequent 2 × 2 factorial analysis on the extracted first component representing static/dynamic regional activity, followed by an out-of-sample imaging transcriptomics analysis. The stability of results from the drug-naïve groups were tested on the treated groups to account for antipsychotic effects. Onset-age had a notable interaction with diagnosis on the static activity of the thalamus, mid-cingulate cortex (MCC), cerebellum posterior lobe (CPL), precuneus, and putamen, and on the dynamic stability of the CPL, thalamus, and superior parietal lobule (SPL). Phase of illness and medication exposure did not affect the onset-age effect seen at the MCC, thalamus, and SPL. Transcriptomics analysis pointed to the possibility of a shared disruption in neuronal differentiation across the MCC, thalamus and SPL. Onset-age affects thalamo-fronto-parietal regional hemodynamic activity, possibly through disrupted neuronal differentiation, in schizophrenia. Exposure to antipsychotics do not reverse this functional imprint of the earlier illness onset, raising the question of alternate therapeutic approaches to close the observed "neurophysiological gap".},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42109592b,

title = {TOPSY: A picture description dataset to examine speech, language and communication in untreated first episode psychosis},

author = {Sharan Bhullar and Chaimaa El Mouslih and Michael Mackinley and Julie Richard and Lena Palaniyappan},

doi = {10.1016/j.dib.2026.112788},

issn = {2352-3409},

year  = {2026},

date = {2026-06-01},

journal = {Data Brief},

volume = {66},

pages = {112788},

abstract = {Recordings of human behaviour provide a rich source of data to detect features of conditions such as psychosis. Advanced technologies can now detect subtle speech aberrations that often go unnoticed by clinicians and family members. This is particularly important given that behavioral data, especially from untreated samples, are scarce. Speech is a crucial verbal behavioral data point for understanding psychosis, but the lack of comprehensive datasets has been a major limitation in research. Furthermore, long-term antipsychotic treatment can significantly affect speech, impacting both its tone and content. This makes it critical to collect longitudinal data to understand these effects. Tracking Outcomes of Psychosis (TOPSY) study aims to address these gaps by providing a rich dataset that includes not only speech data collected using a semi-structured picture description protocol but also a range of other valuable measures based on a validated Thought and Language Index. The TOPSY dataset offers naturalistic speech samples from individuals in an early-stage psychosis treatment program (<2 median days of antipsychotic treatment) and demographically matched healthy controls. This data is complemented by a comprehensive neurobiological and clinical battery, including: MRS (Magnetic Resonance Spectroscopy), Structural MRI, T1 structural data with myelin mapping, DTI (Diffusion Tensor Imaging), Resting fMRI (functional Magnetic Resonance Imaging). In addition to the neuroimaging data, we have collected detailed clinical and cognitive information, including TLI scores (Thought and Language Index) verbal fluency, modified DSST, and PANSS-8 item scores. The protocol and clinical assessments were repeated after a 12-month interval to assess the longitudinal stability of speech, symptom burden, and functional status. Transcripts were extracted from conversations lasting between 3 and 5 min, allowing for in-depth analysis of acoustic, semantic, syntactic, and pragmatic measures related to psychosis. We expect this dataset to be invaluable for future investigations into the clinical utility of speech measures for assessing thought disorder and other psychosis-related symptoms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42102602b,

title = {Are you recording this chat?" Experiential perspectives on audiovisual data collection in psychiatric care and research},

author = {Murthy, C., Zelikovic. I, Ganesh. H, Palaniyappan. L},

url = {https://www.sciencedirect.com/science/article/abs/pii/S0920996426001398?via%3Dihub},

doi = {10.1016/j.schres.2026.04.025},

issn = {1573-2509},

year  = {2026},

date = {2026-08-01},

urldate = {2026-08-01},

journal = {Schizophr Res},

volume = {294},

pages = {164--165},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42061696b,

title = {Reading between the lines: Combining pause dynamics and semantic coherence for automated assessment of thought disorder},

author = {Feng Chen and Weizhe Xu and Changye Li and Serguei Pakhomov and Alex Cohen and Simran Bhola and Sandy Yin and Sunny X Tang and Michael Mackinley and Lena Palaniyappan and Dror Ben-Zeev and Trevor Cohen},

doi = {10.1016/j.neuropsychologia.2026.109473},

issn = {1873-3514},

year  = {2026},

date = {2026-07-01},

journal = {Neuropsychologia},

volume = {228},

pages = {109473},

abstract = {Formal thought disorder (FTD), a hallmark of schizophrenia spectrum disorders, manifests as incoherent speech and poses challenges for clinical assessment. Traditional clinical rating scales, though validated, are resource-intensive and lack scalability. Automated speech recognition (ASR) allows for objective quantification of linguistic and temporal features of speech, offering scalable alternatives. Furthermore, ASR-derived utterance timestamps provide access to pause dynamics, which are thought to reflect the cognitive processes underlying speech production. Yet, their added value beyond semantic measures remains insufficiently explored. In this study, we evaluated a scalable multimodal framework that integrates pause features with semantic coherence metrics across three datasets: naturalistic self-recorded diaries (AVH, n = 140 participants), structured picture descriptions (TOPSY, n = 72 participants), and dream narratives (PsyCL, n = 43 participants). Pause-related features were evaluated alongside established coherence measures using support vector regression (SVR) to predict clinical FTD scores. Models using pause features alone robustly predict manually rated FTD severity consistently across datasets. Integrating pause features with semantic coherence metrics enhanced predictive performance compared to coherence-only models, with late fusion yielding the most robust and consistent gains in all three datasets. On average across datasets, Spearman correlation increased from ρ = 0.413 for semantic-only models to ρ = 0.455 with late fusion. The performance gains from semantic and pause features integration held consistently across all contexts, though the nature of the most informative pause patterns was dataset-dependent. These findings suggest that both pause dynamics and semantic coherence reflect complementary aspects of thought disorganization. Our integration framework provides a scalable approach for refining the assessment of disorganized speech to advance automated speech analysis in psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42037310b,

title = {Increasing participation of people with thought disorder in clinical research},

author = {Lena Palaniyappan and Sylvain Baillet and Valentina Bambini and Etienne Barou-Laforie and Marta Bosia and Oli Delgaram-Nejad and Hashwin Ganesh and Ranjini Garani and Neil Harrison and Vegas Hodgins and Ridha Joober and Tilo Kircher and Gina Kuperberg and Chantal Murthy and Susan Rossell and Krish D Singh and Iris E Sommer and Sunny X Tang and Debra Titone and Alban Voppel and Tosh Watson and Irnes Zeljkovic},

doi = {10.1192/j.eurpsy.2026.12211},

issn = {1778-3585},

year  = {2026},

date = {2026-04-01},

journal = {Eur Psychiatry},

volume = {69},

number = {1},

pages = {e56},

abstract = {BACKGROUND: Thought disorder (TD) is a core feature of severe mental illnesses such as schizophrenia, characterized by disruptions in speech, language, and communication. People with TD face unique barriers that hinder their involvement in research, both as participants and as partners. Their systematic underrepresentation in psychiatric research is driven by pervasive assumptions about their decisional capacity, willingness to participate, and ability to engage in research. This perpetuates a biased evidence base, likely hindering the therapeutic progress toward addressing this core problem.nnMETHODS: This review, informed by professional (clinical and research) and lived (bottom-up and phenomenological) experience of TD, examines how flawed assumptions regarding capacity, engagement, and participatory abilities serve as active barriers to inclusion.nnRESULTS: We argue for a shift toward supported inclusion through tailored capacity assessments, enhanced informed consent procedures, targeted training of research personnel, and systemic institutional practices. Incorporating lived experiences of those with TD as research partners is integral to this approach, fostering co-production of research that is more valid, inclusive, and applicable.nnCONCLUSIONS: Without these inclusion-focused changes, the development of treatments for TD is likely to have very slow progress and a critical segment of the severely unwell population will continue to be underrepresented from the scientific process, undermining both the utility and generalizability of psychiatric research.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid42033337b,

title = {High-Risk Human-AI Engagement: Clinical Assessment and Management Considerations},

author = {Lena Palaniyappan and Vincent Paquin and Etienne Barou-Laforie},

doi = {10.1177/07067437261445770},

issn = {1497-0015},

year  = {2026},

date = {2026-04-01},

journal = {Can J Psychiatry},

pages = {7067437261445770},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41969055b,

title = {What is being measured by formal thought disorder scales? An item-level content analysis},

author = {Vanteemar S Sreeraj and Alban Voppel and Ganesan Venkatasubramanian and Lena Palaniyappan},

doi = {10.1017/S0033291726104152},

issn = {1469-8978},

year  = {2026},

date = {2026-04-01},

journal = {Psychol Med},

volume = {56},

pages = {e106},

abstract = {BACKGROUND: Formal thought disorder (FTD), characterized by disruptions in the flow and form of thought, is a core feature of psychosis. But its measurement is fragmented across numerous rating scales, leading to its continued neglect in both research and clinical practice. To determine if different FTD scales measure the same underlying construct, we need to assess the degree to which the content of commonly used FTD scales overlaps with each other.nnMETHODS: We conducted a systematic review to identify all standardized, clinician-rated scales used to measure FTD in psychotic disorders. From this set, we extracted individual items and derived a consensus list of 56 discrete FTD phenomena. Two independent clinical experts conducted item-to-item mapping for every scale item onto these FTD phenomena. Content overlap between scales was quantified using Jaccard Similarity Index (JSI). We determined the overall coverage achieved via several combinations of FTD scales.nnRESULTS: The 15 scales, comprising 207 items, showed weak content overlap. The mean JSI across all scale pairs was low, and no single phenomenon featured across all scales. While some core FTD phenomena (e.g. 'incoherence', 'poor speech content', 'drifting-off') were represented in many scales, 20% of all identified features were idiosyncratic, appearing in only one scale.nnCONCLUSIONS: Existing FTD rating scales capture a wide but heterogeneous array of symptoms with poor content overlap. This lack of harmonization challenges the comparability of mechanistic and interventional studies. We highlight the need for a consensus-based, standardized measurement of FTD and provide a comprehensive checklist to advance the research and clinical practice.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41943939b,

title = {Dynamic frontoparietal flexibility and cognitive dysfunction in schizophrenia: disentangling the roles of symptom burden and childhood trauma},

author = {Danqing Huang and Zhening Liu and Wenjian Tan and Michel Sopodenkiewicz and Xiawei Liu and Jun Yang and Feiwen Wang and Weiqing Huang and Jie Yang and Yicheng Long and Lena Palaniyappan},

doi = {10.1017/S0033291726103869},

issn = {1469-8978},

year  = {2026},

date = {2026-04-01},

journal = {Psychol Med},

volume = {56},

pages = {e93},

abstract = {BACKGROUND: Working memory (WM) impairment is a core cognitive deficit in schizophrenia, associated with dysfunction of large-scale brain networks, particularly the triple-network system comprising the default mode, frontoparietal, and salience networks. Given the role of environmental risks like childhood trauma (CT) in cognitive deficits, we investigated whether trauma relates to altered triple-network flexibility and WM in schizophrenia.nnMETHODS: We enrolled 190 patients with schizophrenia (SZ) and 117 healthy controls (HCs). Among them, 162 SZ and 99 HCs underwent -back task-based functional magnetic resonance imaging. We computed temporal variability (TV) in the triple-network connectivity, defining ΔTV as the change between 0-back and 2-back conditions. Subgroup comparisons of ΔTV were conducted within each group based on trauma status. Associations of ΔTV with WM performance and clinical symptoms were examined in SZ, followed by mediation analyses testing whether ΔTV mediates the relationship between trauma and WM.nnRESULTS: Among HCs, individuals with childhood trauma showed reduced ΔTV across triple-network connections, whereas no such differences appeared in SZ. In SZ, greater ΔTV within the frontoparietal network (FPN) was correlated with lower positive symptom severity ( = -0.211, -fdr = 0.046) and better -back target accuracy ( = 0.303, -fdr = 0.002). Furthermore, ΔTV within the FPN partially mediated the association between trauma and -back accuracy.nnCONCLUSIONS: Our findings highlight the central role of FPN flexibility in mediating childhood trauma's effect on working memory in schizophrenia. This outlines a key pathway through which an early environmental risk (trauma) translates into cognitive and clinical manifestations in schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41876826b,

title = {Putative glymphatic function and free water in schizophrenia: A 7T DTI study across psychosis stages},

author = {Guitao Qi and Yuanchao Zhang and Yingqi Laetitia Wang and Freeha Anjum and Jean Theberge and Yuchao Jiang and Ali Khan and Lena Palaniyappan},

doi = {10.1038/s41386-026-02391-5},

issn = {1740-634X},

year  = {2026},

date = {2026-07-01},

journal = {Neuropsychopharmacology},

volume = {51},

number = {8},

pages = {1387--1394},

abstract = {Schizophrenia is characterized by impaired brain health, including gray matter reductions and cognitive dysfunction, with vascular and glymphatic dysfunction emerging as key contributors. The glymphatic system, which clears metabolic waste via perivascular pathways, is measurable using Diffusion Tensor Imaging-Along the Perivascular Space (DTI-ALPS) and its dysfunction is suspected to increase extracellular free water (FW). Prior studies reported potential glymphatic impairment in schizophrenia, but its relationship to the stage of illness and impact on interstitial fluid dynamics remains unclear. This study employed ultra-high field (7-Tesla) DTI to quantify DTI-ALPS and FW in white and gray matter in 125 subjects, including clinical high-risk (CHR), untreated first-episode psychosis (FEP), established schizophrenia (>3 years), and healthy controls (HC). We investigated: (1) the presence of DTI-ALPS alterations in CHR and its relative magnitude across disease stages; (2) its association with symptom severity; (3) its correlation with FW; and (4) its relationship to likely origins of neuroanatomical progression in schizophrenia from the hippocampal region. Compared with HC, the established, FEP and CHR all showed lower DTI-ALPS (p < 0.01 for all, Hedge's g = 0.73-1.13) and higher white matter FW (p < 0.05 for all, g = 0.59-1.57). Lower DTI-ALPS was correlated with higher FW, longer duration of untreated psychosis, and was selectively pronounced in the FEP subgroup, whose structural changes may originate from the hippocampal region. Our findings suggested that the putative glymphatic dysfunction indexed by DTI-ALPS predates antipsychotics, drives interstitial fluid accumulation, and contributes to schizophrenia's structural and clinical progression, offering mechanistic insights into its pathophysiology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41863378b,

title = {Longitudinal Trajectories of Cortical Folding in Schizophrenia Spectrum Disorders: A 13-Year Follow-Up Study},

author = {Lara A Wallenwein and Laura A Wortinger and Claudia Barth and Pravesh Parekh and Kjetil N Jørgensen and Lena Palaniyappan and Daniela Mier and Erik G Jönsson and Ingrid Agartz and Stener Nerland},

doi = {10.1093/schbul/sbaf245},

issn = {1745-1701},

year  = {2026},

date = {2026-03-01},

journal = {Schizophr Bull},

volume = {52},

number = {2},

abstract = {BACKGROUND AND HYPOTHESIS: Altered cortical folding is a well-established finding in schizophrenia spectrum disorders (SSD). Patients with SSD have been hypothesized to exhibit an accelerated decline in age-related cortical folding, quantified with the local gyrification index (LGI). Here, we assessed longitudinal and cross-sectional LGI differences in patients with chronic SSD relative to healthy controls across 13 years.nnSTUDY DESIGN: The sample comprised patients with SSD (mean baseline age = 41.28 years) and healthy controls (mean baseline age = 41.56 years), with magnetic resonance imaging acquisitions at baseline (103 SSD patients and 99 controls) and follow-up after 5 (50 SSD patients and 57 controls) and 13 years (42 SSD patients and 60 controls). T1-weighted images were processed with the longitudinal pipeline in FreeSurfer. Spatiotemporal linear mixed-effects models were used to test for longitudinal and cross-sectional case-control differences in LGI, as well as the impact of symptom severity and antipsychotic medication dose among patients.nnSTUDY RESULTS: Although cross-sectional LGI was lower in patients in extensive frontal, parietal, and occipital regions, we observed no significant differences in longitudinal trajectories between patients and controls after FDR correction. Medication dose was linked cross-sectionally to lower LGI of the anterior cingulate, orbitofrontal cortex, and postcentral gyrus.nnCONCLUSION: In the longest longitudinal study on cortical folding in SSD patients to date, we found no evidence for accelerated progressive decline in cortical folding. Rather, chronic SSD appears to be characterized by a state of stable hypogyria relative to healthy controls, consistent with the interpretation of LGI as a marker of early gyrification disturbances in SSD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41836652b,

title = {Grounding psychosis research: why observable signs should anchor biological investigations},

author = {Lena Palaniyappan},

doi = {10.3389/fpsyt.2026.1777099},

issn = {1664-0640},

year  = {2026},

date = {2026-01-01},

journal = {Front Psychiatry},

volume = {17},

pages = {1777099},

abstract = {Biological psychiatry faces a significant epistemic challenge in identifying valid objects for mechanistic research. Both diagnostic constructs and individual symptoms are abstract symbols defined circularly within a closed hermeneutic system, creating a symbol grounding problem that hinders the discovery of biophysical substrates (biomarkers). I argue that progress requires an epistemological separation between the ungrounded symptoms such as delusions and hallucinations, which are co-constructed through personal and clinical interpretation from  that are directly observable features anchored in shared sensorimotor reality. I propose that a Minimal Grounding Set (MGS) can be recovered from the commonly used criteria for psychosis. This MGS, exemplified by disorganization and impoverishment, offers a privileged pathway for the neuroscientific inquiry of psychosis. In this case, (1) biological correlates will be most replicable for MGS than other symptoms; (2) MGS will serve as modular anchors in symptom networks; and (3) progress in precision medicine programs like Computational Psychiatry and quantitative psychopathology frameworks such as hierarchical taxonomy (HiTOP) will depend on explicitly separating MGS from ungrounded symptoms. This approach of  will provide a non-circular foundation to tether abstract constructs affiliated with psychosis to biological realities that have eluded us for long.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41820654b,

title = {Setting digital psychiatry in motion: towards dynamic digital markers for digital phenotyping},

author = {Axel Constant and C Emre Koksal and Lena Palaniyappan},

doi = {10.1038/s44277-026-00059-y},

issn = {2948-1570},

year  = {2026},

date = {2026-03-01},

journal = {NPP Digit Psychiatry Neurosci},

volume = {4},

number = {1},

abstract = {Digital phenotyping uses data from smartphones and wearables to extract behavioural and biosocial markers of psychopathology in situ. Traditional entropy-based measures capture static system properties that neglect temporal dependencies critical to psychiatric phenomena. We propose a "dynamic" approach to the modelling of digital data capturing the time-varying aspects of processes of mental disorders. We defend that the resulting dynamic digital markers better capture variability in regulatory mechanisms of psychopathology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41704505b,

title = {The DISCOURSE in psychosis (London Ontario): A speech dataset to examine communication disturbances in early-stage psychosis},

author = {Brian Cho and Estée Balles and Michael Mackinley and Paulina Dzialoszynski and Sabrina Ford and Rohit Lodhi and Lena Palaniyappan},

doi = {10.1016/j.dib.2026.112517},

issn = {2352-3409},

year  = {2026},

date = {2026-04-01},

journal = {Data Brief},

volume = {65},

pages = {112517},

abstract = {Advances in speech technology and Natural Language Processing (NLP) have demonstrated promise in using speech as a valid source of data to detect features of psychosis. These technologies can potentially detect subtle speech aberrations that often go unnoticed by clinicians and family members. However, research in this area is hindered by a significant limitation: a lack of sufficient and appropriate speech corpora from psychosis patients, especially datasets containing naturalistic speech that reflects typical clinical interactions. This scarcity limits the development, testing, and generalization of new computational methods for psychosis prediction. To address this gap, our new dataset offers naturalistic speech samples collected using the semi-structured DISCOURSE protocol. This resource includes both raw audio recordings and transcribed speech from individuals participating in an early-stage psychosis treatment program (<5 years of illness), alongside demographically matched healthy controls, in English. In addition to speech data, the dataset provides comprehensive clinical, cognitive, and demographic information for each participant. Importantly, the DISCOURSE protocol and clinical assessments were repeated after a 12-month follow-up to assess stability and change in speech, symptom burden and functional status. As the inaugural dataset released by the DISCOURSE consortium, this resource marks the beginning of a series of harmonized data collection efforts across multiple countries and languages. This multi-site, multi-language approach enables validation of findings in diverse psychosis populations, allowing researchers to address questions that cannot be resolved at individual research sites. Transcripts were extracted from conversations lasting between 15 and 35 minutes in total. This data herein can be used to perform analyses on acoustic, semantic, syntactic and pragmatic measures related to psychosis, as well as in understanding the nature of communication difficulties faced by patients. We expect this dataset to be useful for future investigations into speech data's clinical utility in assessing thought disorder and psychosis-related symptoms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41700363b,

title = {An indescribable suffering - Reflections},

author = {Lena Palaniyappan},

doi = {10.1192/bjp.2025.10441},

issn = {1472-1465},

year  = {2026},

date = {2026-03-01},

journal = {Br J Psychiatry},

volume = {228},

number = {3},

pages = {285},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41690994b,

title = {Expressive pragmatic language in mood and psychotic disorders: a systematic review and meta-analysis},

author = {Fiona Meister and Martin Sellier Silva and Gleb Melshin and Chaimaa El Mouslih and Farida Zaher and Roozbeh Sattari and Hsi T Wei and Neyra Mekideche and Valentina Bambini and Alban Voppel and Lena Palaniyappan},

doi = {10.1038/s41537-026-00733-2},

issn = {2754-6993},

year  = {2026},

date = {2026-02-01},

journal = {Schizophrenia (Heidelb)},

volume = {12},

number = {1},

abstract = {Pragmatic language impairments-difficulties using language effectively in social contexts-are common in adults suffering from severe mental illnesses (SMIs) such as schizophrenia spectrum disorders (SSD), major depressive disorder (MDD), and bipolar disorder (BD). These impairments hinder social functioning and recovery but have been explored most widely using comprehension tasks, with pragmatic production being poorly described. We undertook a systematic review and meta-analysis of studies assessing expressive pragmatic language in adults with SMIs versus healthy controls. 18 items were tested, including Coherence, Cohesion, Gricean maxims, figurative language, Prosody, and Turn-Taking. The searches were PRISMA-compliant and were conducted in PubMed and Scopus. 51 studies were included; 28 were meta-analyzed. Results showed significant impairments in Cooperativity, Anaphora and Cohesion, moderate impairments in Coherence, and low impairments in Metaphor. No significant moderator was detected. Our results emphasize the need for standardized pragmatic testing and intervention for language production in clinical settings.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41656336b,

title = {Reduced linguistic coherence in psychosis defies semantic similarity accounts and relates to altered large-scale cortical hierarchy},

author = {Rui He and Radosław Grodzki and Nihal Altay and Benjamin Aston and Maria Francisca Alonso-Sánchez and Philipp Homan and Iris Sommer and Lena Palaniyappan and Wolfram Hinzen},

doi = {10.1038/s41598-026-39025-1},

issn = {2045-2322},

year  = {2026},

date = {2026-02-01},

journal = {Sci Rep},

volume = {16},

number = {1},

abstract = {Coherence in speech is clinically significant in mental disorders but remains difficult to quantify. We tested the widely-held assumption that semantic similarity metrics derived from large language models capture human-rated coherence. Across three large neurotypical datasets in different languages, semantic similarity failed to correlate with human ratings, while six other metrics, especially the probability-based metrics, showed significant but weak correlations. In an additional English dataset of 94 individuals, including healthy controls and patients with schizophrenia spectrum disorders (SSD), speech coherence was reduced in SSD. Incoherence in the drug-naïve first-episode samples related to altered whole-brain intrinsic functional gradients, and to the probabilistic metric of perplexity in speech. Together, these findings call into question semantic similarity as a proxy for coherence, motivate greater emphasis on probabilistic predictability measures for evaluating coherence, and substantiate the perspective of spontaneous speech as an overt readout of an alteration of hierarchical cortical organization in schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41579632b,

title = {Formal thought disorder and familial risk in first-episode psychosis: A study of cortical thickness and neuroimaging-transcriptomic association analysis},

author = {Tuğçe Çabuk and Yuanchao Zhang and Lena Palaniyappan and Didenur Şahin-Çevik and Hanife Avcı and Işık Batuhan Çakmak and Helin Yılmaz Kafalı and Bedirhan Şenol and Kader Karlı Oğuz and Timothea Toulopoulou},

doi = {10.1016/j.pscychresns.2026.112148},

issn = {1872-7506},

year  = {2026},

date = {2026-04-01},

journal = {Psychiatry Res Neuroimaging},

volume = {357},

pages = {112148},

abstract = {Formal thought disorder (FTD), a prominent feature of schizophrenia, encompasses disruptions in thought, language, and communication. This study examines cortical thickness (CT) alterations in first-episode psychosis (FEP) patients (N = 24), their siblings (SIB) (N = 21), and healthy controls (CON) (N = 21) to explore potential neural correlates of FTD. Using structural MRI, we analyzed whole-brain CT and its relationship with positive and negative FTD measured by Thought and Language Index. Out-of-sample spatial correlations of gene expression with regional CT were also performed using a transcriptomic dataset. FEP had significant CT reductions in right middle frontal gyrus (MFG) compared with SIB and CON and in superior frontal gyrus (SFG) compared to CON; but SIB did not differ from CON. GLM analyses demonstrated that negative FTD exerted a significant main effect on CT in the MFG and SFG. By contrast, positive FTD showed no significant associations with CT. Neuroimaging-transcriptomic association analysis identified key biological pathways linked to cortical morphology. These findings emphasize the specific association between negative FTD and CT alterations in frontal brain regions, confirming prior reports. Future research should examine larger cohorts and investigate additional FTD subtypes to further elucidate neural correlates and potential familial risks of schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41523190b,

title = {Microstructure and gene expression influence gyrification in amyotrophic lateral sclerosis},

author = {Yihan Jiang and Yan Fu and Xinyu Song and Xueying Wang and Jianyu Li and Luqi Cheng and Yifan Chen and Yuanchao Zhang and Junling Wang and Xiaoping Yi and Lena Palaniyappan},

doi = {10.1093/braincomms/fcaf491},

issn = {2632-1297},

year  = {2026},

date = {2026-01-01},

journal = {Brain Commun},

volume = {8},

number = {1},

pages = {fcaf491},

abstract = {Amyotrophic lateral sclerosis is a fatal neurodegenerative disease involving progressive degeneration of upper and lower motor neurons. Beyond well-established grey and white matter pathology, alterations in cortical gyrification have recently been observed, yet their clinical relevance and molecular underpinnings remain to be understood. Here, we investigated this premise by examining its microstructural and transcriptional basis in 60 patients with amyotrophic lateral sclerosis (median age = 55, range = 25-72 years) and 60 matched controls (median age = 56, range = 27-72 years) using structural and diffusion MRI. Patients exhibited a significant reduction in local gyrification index within bilateral precentral and postcentral gyri, left middle frontal gyrus and left superior parietal lobule. This was accompanied by reduced fractional anisotropy in the white matter tracts, primarily involving the corticospinal tract and corpus callosum. Higher local gyrification index and fractional anisotropy values were associated with better motor function as measured by the Amyotrophic Lateral Sclerosis Functional Rating Scale-Revised, and local gyrification index also showed positive associations with global cognitive status. A mediation analysis indicated that fractional anisotropy partially accounted for the relationship between local gyrification index and functional disability, suggesting that disrupted white matter pathways contribute to the clinical impact of gyrification changes. To explore underlying mechanisms, we integrated neuroimaging findings with transcriptomic data from the Allen Human Brain Atlas. Regions of reduced local gyrification index showed spatial convergence with cortical expression of amyotrophic lateral sclerosis-related genes such as  and , enriched for biological processes related to protein aggregation, axon guidance and synaptic signalling. Together, these findings suggest that cortical gyrification abnormalities in amyotrophic lateral sclerosis are closely linked to white matter degeneration, functional impairment and genetic vulnerability, thereby offering an integrative window into the multiscale pathology of amyotrophic lateral sclerosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41507058b,

title = {dGAMLSS: an exact, distributed algorithm to fit Generalized Additive Models for Location, Scale, and Shape for privacy-preserving population reference charts},

author = {Fengling Hu and Jiayi Tong and Margaret Gardner and  and Andrew A Chen and Richard A I Bethlehem and Jakob Seidlitz and Hongzhe Li and Aaron Alexander-Bloch and Yong Chen and Russell T Shinohara},

doi = {10.1093/bioinformatics/btaf625},

issn = {1367-4811},

year  = {2026},

date = {2026-01-01},

journal = {Bioinformatics},

volume = {42},

number = {1},

abstract = {MOTIVATION: There is growing interest in estimating population reference ranges across age and sex to better identify atypical clinically-relevant measurements throughout the lifespan. For this task, the World Health Organization recommends using Generalized Additive Models for Location, Scale, and Shape (GAMLSS), which can model non-linear growth trajectories under complex distributions that address the heterogeneity in human populations.Fitting GAMLSS models requires large, generalizable sample sizes, especially for accurate estimation of extreme quantiles, but obtaining such multi-site data can be challenging due to privacy concerns and practical considerations. In settings where patient data cannot be shared, privacy-preserving distributed algorithms for federated learning can be used, but no such algorithm exists for GAMLSS.nnRESULTS: We propose distributed GAMLSS (dGAMLSS), a distributed algorithm that can fit GAMLSS models across multiple sites without sharing patient-level data. This includes specific considerations for the fitting of smooth functions at varying levels of communication efficiency. We demonstrate the effectiveness of dGAMLSS in constructing population reference charts across clinical, genomics, and neuroimaging settings and show that dGAMLSS is able to reproduce pooled reference charts and inference down to numerical differences.nnAVAILABILITY AND IMPLEMENTATION: An R package providing examples of the dGAMLSS algorithm, as well as functions for sharing and aggregating site-specific parameters, is available at https://github.com/hufengling/dGAMLSS.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41359582b,

title = {Deciphering the impact of childhood trauma on schizophrenia: A qualitative case study of dialogical aspects},

author = {Dalia Elleuch and Lena Palaniyappan},

doi = {10.1037/tra0002095},

issn = {1942-969X},

year  = {2026},

date = {2026-03-01},

journal = {Psychol Trauma},

volume = {18},

number = {3},

pages = {517--526},

abstract = {OBJECTIVE: Grounded in a phenomenology framework, this qualitative case study interrogates the structural embedding of childhood trauma within the linguistic and phenomenological aspects of schizophrenia. It posits that traumatic experiences are not merely reflected in but actively reorganize communicative patterns, becoming grammatically and narratively encoded in psychotic discourse.nnMETHOD: A multilevel discourse analysis was applied to verbatim transcripts from two historical, publicly available recordings of a clinically diagnosed male patient: a structured clinical interview and an unstructured home visit. Employing a triangulation design, the analysis integrated patient narrative, clinician assessments, and familial observations. Coding was conducted through an iterative, deductive-inductive process focused on linguistic strata: syntactic structure, lexical semantics, narrative coherence, and dialogical dynamics.nnRESULTS: The analysis delineated a distinct psycholinguistic configuration indicative of trauma reorganization. Dominant themes include the following: (a) syntactic reenactment-rigid, persecutory interrogatives fossilizing victim-perpetrator frameworks; (b) lexical hypervigilance-a semantically constrained lexicon centered on violation and somatic threat; (c) narrative dissociation-abrupt thematic shifts and displaced trauma disclosures that disrupt autobiographical coherence; and (d) dialogical rupture-interlocutor-specific speech patterns reenacting attachment conflicts. These markers form a coherent, trauma-organized communicative system persistent across contexts.nnCONCLUSIONS: Trauma in schizophrenia may operate as a structural determinant of communication, not a comorbid overlay. Personalized, linguistically informed, trauma-focused interventions may reduce the accompanying interpersonal distress. We provide an outline for studying discursive markers to investigate therapies targeting trauma-derived syntactic and narrative frameworks. (PsycInfo Database Record (c) 2026 APA, all rights reserved).},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41327800b,

title = {"I felt like that was a safe place to go": a qualitative study of help-seeking experiences for early psychosis in primary care},

author = {Rebecca Rodrigues and Candice Madakadze and Jordan Edwards and Richard Booth and Suzanne Archie and Lena Palaniyappan and Sarah Chan and Kerri Nagy and Kelly K Anderson and },

doi = {10.1080/09638237.2025.2595617},

issn = {1360-0567},

year  = {2026},

date = {2026-04-01},

journal = {J Ment Health},

volume = {35},

number = {2},

pages = {199--207},

abstract = {BACKGROUND: Contacts with primary care for early psychosis are common, and there is a need for further insight into help-seeking patterns.nnAIMS: We sought to describe the help-seeking experiences in primary care for people with early psychosis and their caregivers.nnMETHODS: Using a qualitative descriptive approach, we recruited 22 clients with first-episode psychosis and 13 caregivers from seven specialized clinics to participate in a semi-structured interview. Interviews were audio recorded, transcribed, and coded thematically using conventional content analysis.nnRESULTS: Help-seeking experiences in primary care were varied. We identified themes describing client- and caregiver-level challenges and supports: impaired mental state, help-seeking decisions and support, and conflicting cultural beliefs and values (between clients and physicians). We also identified physician-level challenges and supports: physician knowledge (perceived as adequate or inadequate), follow-up (close or lack thereof), and supportive relationship with the client and/or caregiver. Finally, we identified health system-level themes: appointment availability and virtual care (described as insufficient).nnCONCLUSIONS: Interventions to increase help-seeking for early psychosis more broadly may facilitate earlier primary care help-seeking. Primary care physician education, closer follow-up of young people with mental health issues, timely access, and in-person care could improve pathways to care in early psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41254324b,

title = {Investigating the disturbance in cortical glutamate and GABA function in psychosis and its origins and consequences},

author = {Bill Deakin and Elizabeth Liddle and Mohanbabu Rathnaiah and Catherine C Gregory and Mohammad Z Katshu and Gemma Williams and Silke Conen and Richard Smallman and Loes C Koelewijn and Adriana Anton and Jyothika Kumar and Lauren E Gascoyne and Chen Chen and Naghmeh Nikkheslat and John Evans and Bernard Lanz and James Walters and Peter S Talbot and Lena Palaniyappan and Krish D Singh and Peter Morris and Stephen R Williams and Peter F Liddle},

doi = {10.1038/s41380-025-03337-x},

issn = {1476-5578},

year  = {2026},

date = {2026-04-01},

journal = {Mol Psychiatry},

volume = {31},

number = {4},

pages = {1983--1991},

abstract = {We investigated the longstanding idea that the onset of psychotic symptoms in schizophrenia arises from an early phase of glutamate neurotoxicity, possibly related to loss of GABA restraint, oxidative stress or inflammation, that cumulatively results in a later phase of synaptic loss in keeping with magnetic resonance spectroscopy (MRS) evidence of reduced glutamate in schizophrenia, especially in older patients. We evaluated this hypothesis in a 3-centre MRS study to determine whether abnormalities in glutamate in dorsal anterior cingulate cortex (dACC) differed between people with minimally treated 'Recent' onset schizophrenia and an 'Established' group with > 10 years of illness. We tested the hypothesised mechanisms of reduced GABA in either or both dACC and occipital cortex, and depletion of dACC glutathione, a measure of central inflammation. We explored predicted associations between MRS variables, circulating cytokines and clinical symptoms. The Established group showed significantly greater dACC glutamate deficit than the Recent group which was not accounted for by lifetime exposure to antipsychotic drugs or by their greater CRP or IL-6 levels nor was the deficit associated with glutathione depletion. The greater dACC glutamate deficit in established illness is compatible with loss of synapses occurring after onset of symptoms but there was little to suggest underpinning excitotoxicity, inflammation, or oxidative stress. GABA was reduced in patients versus controls across dACC and occipital voxels. Only dACC GABA content correlated significantly with symptoms, lower content with greater positive and negative symptoms across both groups and this is supportive of a pathophysiological role of GABA in psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41146942b,

title = {Exploring the interplay between language use and cognitive function in schizophrenia spectrum disorders: Insights from patients, first degree relatives, and healthy controls},

author = {Rosa Ayesa-Arriola and Carlos Martinez-Asensi and Alexandre Díaz-Pons and Víctor Ortiz-García de la Foz and Claudia Parás and Chaimaa El Mouslih and Roozbeh Sattari and Sara Incera and Lena Palaniyappan},

doi = {10.1016/j.scog.2025.100398},

issn = {2215-0013},

year  = {2026},

date = {2026-03-01},

journal = {Schizophr Res Cogn},

volume = {43},

pages = {100398},

abstract = {BACKGROUND: For people with schizophrenia spectrum disorders (SSD), communication characterized by disrupted language use is common. However, the role of cognitive function in everyday language disruptions in SSD remains unclear. Family studies help control for confounding factors such as symptom burden, medication use and environment, offering insight into the interplay between language and cognition in SSD.nnSTUDY DESIGN: We examined linguistic features in naturalistic speech from 176 individuals (51 with SSD, 77 first-degree relatives [50 parents, 27 siblings], and 48 healthy controls). Tasks included conversations, picture descriptions, story narration, reading and recall. We assessed cognitive domains: attention, verbal/visual memory, working memory, executive function, processing speed, motor dexterity, and theory of mind. We then studied associations between cognition and language.nnRESULTS: Different patterns emerged across groups. In controls, longer speech and fewer pronouns were linked to better cognition. In SSD, greater adposition use and fewer pronouns related to better memory, executive function, and IQ. Among parents, more coordinating conjunctions during narration correlated with better visual memory and motor dexterity. Siblings showed the strongest, broadest associations: better cognition predicted richer language and fewer pronouns, especially tied to global and motor function. Story narration revealed the richest cognitive-linguistic links.nnCONCLUSIONS: In people with SSD and their relatives, specific cognitive deficits are reflected in everyday speech, regardless of content. These findings highlight the role of discourse context in shaping language-cognition relationships and support future research using language markers in psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41050346b,

title = {Clinical psychopathology-based early relapse prediction model using speech and language in psychosis},

author = {Tyler C Dalal and Min Tae M Park and Angelica M Silva and Svetlana Iskhakova and Alban Voppel and Noah J Brierley and Michael MacKinley and Emmanuel Olarewaju and Lena Palaniyappan},

doi = {10.1016/j.scog.2025.100392},

issn = {2215-0013},

year  = {2026},

date = {2026-03-01},

journal = {Schizophr Res Cogn},

volume = {43},

pages = {100392},

abstract = {INTRODUCTION: Prediction of psychotic relapse using speech-derived markers promises targeted early intervention. However, the sheer number of speech markers and the 'black box' nature of predictive models challenges clinical translation.nnMETHODS: We propose a psychopathology-based systematic approach to identify likely relapse. We draw on the notion that the predictors of relapse should mark (1) the presence of schizophrenia in its untreated early stages and (2) track disorganization in psychosis. By leveraging Natural Language Processing, we derive 3 lexical, syntactic and narrative markers -semantic similarity, clause complexity, and analytic thinking index from speech samples of people with acute psychosis ( = 68) followed up for subsequent relapses over a year (12 out of 68).nnRESULTS: Speech-based model predicted relapse status with strong evidence (Bayes Factor BF = 79.5) against the clinical intuition model.nnCONCLUSION: Using a Bayesian approach, this preliminary study demonstrates the utility of psychopathology-guided variable selection for speech-based relapse prediction complementing clinical intuition in practice.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40974052b,

title = {Age of Onset, Brain Controllability, and Working Memory Performance in First-Episode Schizophrenia},

author = {Feiwen Wang and Zhening Liu and Jun Yang and Peng Cheng and Wenjian Tan and Danqing Huang and Xiawei Liu and Maoxing Zhong and Jie Yang and Lena Palaniyappan},

doi = {10.1093/schbul/sbaf156},

issn = {1745-1701},

year  = {2026},

date = {2026-07-01},

journal = {Schizophr Bull},

volume = {52},

number = {4},

abstract = {BACKGROUND AND HYPOTHESIS: The onset-age of schizophrenia introduces considerable heterogeneity in cognitive functions such as working memory (WM) among patients. One of the key properties of the brain that varies with age-related development is the network-level controllability of brain state transitions. We tested the effect of onset-age on brain controllability to evaluate its impact on WM deficits in schizophrenia.nnSTUDY DESIGN: We examined the average and modal controllability of the brain connectome in 85 first-episode early-onset schizophrenia (EOS), 62 younger healthy controls (yHC), 71 first-episode adult-onset schizophrenia (AOS), and 85 older healthy controls (oHC) during N-back tasks. We first detected the regions with illness and onset-age interaction in a whole-brain search, and then conducted a correlation analysis with WM performance and clinical characteristics, followed by an out-of-sample gene annotation analysis.nnSTUDY RESULTS: We detected the illness*onset-age interaction in the sensorimotor network, auditory network, and subcortical network for average controllability and the default mode network, visual network, and salience network for modal controllability (p-fdr < 0.05). The interaction effects in the visual and subcortical networks primarily resulted from the AOS vs. oHC differences; the effects in the default mode network resulted from EOS vs. yHC differences. We observed no significant correlation between controllability with cognitive performance or clinical characteristics. The affected regions had preferential expression of genes relevant to synaptic signaling and neurodegenerative processes (p-fdr < 0.05).nnCONCLUSION: Onset-age introduces considerable heterogeneity in the controllability over brain state transition during WM tasks among patients with schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40908273b,

title = {Pharmacological and Mechanistic Interventions for Cognitive Impairment Associated With Schizophrenia: A Review of Registered Clinical Trials},

author = {Bahareh Peyrovian and Lena Palaniyappan and Theodore T Kolivakis and Howard C Margolese},

doi = {10.1111/acps.70034},

issn = {1600-0447},

year  = {2026},

date = {2026-05-01},

journal = {Acta Psychiatr Scand},

volume = {153},

number = {5},

pages = {402--431},

abstract = {BACKGROUND: Schizophrenia is characterized by positive, negative, and cognitive symptoms. Current pharmacological treatments often fail to address cognitive deficits. In this review of clinical trials, we aim to identify studies that explore neurobiological (non-psychological) strategies to address Cognitive Impairment Associated with Schizophrenia (CIAS).nnMETHODS: A search of clinical trial databases was conducted through US National Institutes of Health's ClinicalTrials.gov and the World Health Organization's International Clinical Trials Registry Platform (ICTRP) on August 2, 2024, with complementary searches performed on July 4 and 10, 2025, for each respective database to update the results.nnRESULTS: We identified 510 relevant interventional studies that objectively measured cognitive performance. Most trials were conducted in the United States (36.4%) and focused on treatment (79%), with randomized designs (88%), investigating drugs (56%), devices (33%), and dietary supplements (10%). Of these trials, 17% reported positive pro-cognitive evidence. Glutamate modulators were the most studied drug category (63 trials), with positive results for sarcosine, BI425809 (Iclepertin), d-serine, d-cycloserine, and minocycline in small-scale trials, although the results were not replicated in larger studies. Nicotinic receptor modulators like ABT-126 and encenicline also showed some cognitive benefits. Device-based interventions, particularly rTMS and iTBS, demonstrated improvements in global cognition, working memory, attention, and processing speed in a subset of trials.nnCONCLUSION: In this comprehensive overview of clinical trials on pro-cognitive agents in schizophrenia, we identify emerging opportunities but also acknowledge a lack of replicated evidence. Despite extensive attempts to address CIAS, it remains an undertreated domain, and future trials should explore better ways to treat this important condition.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40506005b,

title = {Selective Insensitivity to Global Versus Local Linguistic Context in Speech Produced by Patients With Untreated Psychosis and Positive Thought Disorder},

author = {Victoria Sharpe and Michael Mackinley and Samer Nour Eddine and Lin Wang and Lena Palaniyappan and Gina R Kuperberg},

doi = {10.1016/j.biopsych.2025.06.001},

issn = {1873-2402},

year  = {2026},

date = {2026-01-01},

journal = {Biol Psychiatry},

volume = {99},

number = {2},

pages = {154--164},

abstract = {BACKGROUND: Early psychopathologists proposed that certain features of positive thought disorder, the disorganized language output produced by some people with schizophrenia, suggest an insensitivity to global, relative to local, discourse context. This idea has received support from carefully controlled psycholinguistic studies in language comprehension. In language production, researchers have so far remained reliant on subjective qualitative rating scales to assess and understand speech disorganization. However, recent advances in large language models mean that it is possible to quantify sensitivity to global and local context objectively by probing lexical probability (the predictability of a word given its preceding context) during natural language production.nnMETHODS: For each word in speech produced by 60 patients with first-episode psychosis and 35 healthy, demographically matched control participants, we extracted lexical probabilities from GPT-3 based on contexts that ranged from very local-a single preceding word: P(Wn | Wn-1)-to global-up to 50 preceding words: P(Wn | Wn-50, Wn-49, …, Wn-1).nnRESULTS: We show that disorganized speech is characterized by disproportionate insensitivity to global versus local linguistic context. Critically, this global versus local insensitivity selectively predicted clinical ratings of positive thought disorder, above and beyond overall symptom severity. There was no evidence of a relationship with negative thought disorder (impoverishment).nnCONCLUSIONS: We provide an automated, interpretable measure that can potentially be used to quantify speech disorganization in schizophrenia. Our findings directly linked the clinical phenomenology of thought disorder to neurocognitive constructs that are grounded in psycholinguistic theory and neurobiology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40505888b,

title = {Neurite Density and Kurtosis in the Gray Matter of People With Early Schizophrenia},

author = {Peter C Van Dyken and Ali R Khan and Lena Palaniyappan},

doi = {10.1016/j.bpsc.2025.06.001},

issn = {2451-9030},

year  = {2026},

date = {2026-01-01},

journal = {Biol Psychiatry Cogn Neurosci Neuroimaging},

volume = {11},

number = {1},

pages = {103--115},

abstract = {BACKGROUND: Classic models of diffusion-weighted imaging, especially diffusion tensor imaging, are unsuitable for application to the cortical gray matter given its high microstructural complexity. As such, most neuroimaging studies have focused on gross structural effects of schizophrenia, such as cortical thickness differences. More recently developed models, such as neurite orientation dispersion and density imaging (NODDI) and diffusion kurtosis imaging (DKI), incorporate higher-resolution data and may provide more sensitive descriptions of schizophrenia pathology with more specific interpretations.nnMETHODS: We applied the NODDI and DKI models to the cortical gray matter of people with early schizophrenia (n = 54) and healthy control participants (n = 51) from the Human Connectome Project for Early Psychosis dataset. Comparisons between groups were made using region-of-interest and clustering approaches. The effect sizes of these approaches were compared with those of cortical thickness differences. We also investigated the relationship between these parameters and lifetime antipsychotic usage.nnRESULTS: Cortical thickness differences were most prominent between groups in terms of global effect size and spatial extent. We also observed a diffuse, right hemisphere-dominant increase in mean kurtosis and isotropic diffusion fraction throughout the gray matter, which was not fully explained by partial volume effects. Additionally, a lower neurite density index (NDI) correlated with greater lifetime antipsychotic usage.nnCONCLUSIONS: Increases in mean kurtosis and isotropic diffusion fraction are both markers of schizophrenia, consistent with inflammation models of the gray matter in schizophrenia. NDI reduction, reflecting intraneurite pathology, becomes prominent only in individuals with greater disease burden.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40172688b,

title = {Disorganisation and depression: a re-examination of how we think and speak when depressed},

author = {Lena Palaniyappan and Yingqi Laetitia Wang and Fiona Meister},

doi = {10.1007/s00406-025-01994-1},

issn = {1433-8491},

year  = {2026},

date = {2026-03-01},

journal = {Eur Arch Psychiatry Clin Neurosci},

volume = {276},

number = {2},

pages = {435--450},

abstract = {Disorganised thinking in severe mental illness seriously cripples social functions. Historically, the study of disorganisation has primarily concentrated on schizophrenia, utilizing tools designed to assess formal thought disorder (FTD). This review examines the characteristics, prevalence, and possible neural correlates of FTD within the framework of depressive disorders. Our focus is on disturbances in thought, language, and communication associated with depression, alongside the relevant subjective experiences. We also discuss the challenges and opportunities in using FTD as a predictor of future illness trajectory and advocate for using the broader construct of depressive disorganisation. We review the disruption of brain networks associated with FTD, such as the salience, language, and default mode networks, within the context of depression. In conclusion, we advocate for increased focus on personal narratives, computational psychopathology, and a broader emphasis on thought dynamics to enhance the identification of disorganisation in depression. Renewed emphasis on this neglected area of psychopathology could provide insights on improving employment and social functioning for individuals affected by mood disorders.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40037577b,

title = {Default Mode Network, Disorganization, and Treatment-Resistant Schizophrenia},

author = {Huan Huang and Xuan Qin and Rui Xu and Ying Xiong and Keke Hao and Cheng Chen and Qirong Wan and Hao Liu and Wei Yuan and Yunlong Peng and Yuan Zhou and Huiling Wang and Lena Palaniyappan},

doi = {10.1093/schbul/sbaf018},

issn = {1745-1701},

year  = {2026},

date = {2026-01-01},

journal = {Schizophr Bull},

volume = {52},

number = {1},

abstract = {BACKGROUND AND HYPOTHESIS: Disorganized thinking is a prominent feature of schizophrenia that becomes persistent in the presence of treatment resistance. Disruption of the default mode network (DMN), which regulates self-referential thinking, is now a well-established feature of schizophrenia. However, we do not know if DMN disruption affects disorganization and contributes to treatment-resistant schizophrenia (TRS).nnSTUDY DESIGN: This study investigated the DMN in 48 TRS, 76 non-TRS, and 64 healthy controls (HC) using a spatiotemporal approach with resting-state functional magnetic resonance imaging. We recovered DMN as an integrated network using multivariate group independent component analysis and estimated its loading coefficient (reflecting spatial prominence) and Shannon Entropy (reflecting temporal variability). Additionally, voxel-level analyses were conducted to examine network homogeneity and entropy within the DMN. We explored the relationship between DMN measures and disorganization using regression analysis.nnRESULTS: TRS had higher spatial loading on population-level DMN pattern, but lower entropy compared to HC. Non-TRS patients showed intermediate DMN alterations, not significantly differing from either TRS or HC. No voxel-level differences were noted between TRS and non-TRS, emphasizing the continuum between the two groups. DMN's loading coefficient was higher in patients with more severe disorganization.nnCONCLUSIONS: TRS may represent the most severe end of a spectrum of spatiotemporal DMN dysfunction in schizophrenia. While excessive spatial contribution of the DMN (high loading coefficient) is specifically associated with disorganization, both excessive spatial contribution and exaggerated temporal stability of DMN are features of schizophrenia that become more pronounced with refractoriness to first-line treatments.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{nokey,

title = {How to elicit thought disorder during clinical interviews: a practical guide},

author = {Lena Palaniyappan and Oliver Delgaram-Nejad and Eric Yu Hai Chen



},

url = {https://www.cambridge.org/core/journals/bjpsych-advances/article/how-to-elicit-thought-disorder-during-clinical-interviews-a-practical-guide/CCCFE691E34E21560CF2F873A5E49834},

doi = {10.1192/bja.2026.10213},

year  = {2026},

date = {2026-05-28},

urldate = {2026-05-28},

journal = {BJPsych Advances},

number = {1},

pages = {11},

abstract = {The reliable assessment of formal thought disorder (FTD), a collection of observable signs of suspected problems in generating organised thoughts, is the cornerstone of interviewing a person with psychosis. A significant gap persists between the success of assessments reported in published FTD rating scales and the practical constraints of a clinical interview. Validated rating scales largely focus on operationalised criteria for describing items; the procedural aspects of how to elicit these signs often remain implicit. We synthesise the principles and procedures of FTD assessment embedded in rating scales, translating their design into a framework for routine clinical use. Systematic employment of several manoeuvres can help elicit FTD signs: conversational stimulation, cognitive loading, social modulation and pointed clarifications to stress-test thought, language and communication processes. By making these procedures explicit, we aim to equip clinicians and trainees with a strategic, measurement theory-informed approach to the psychiatric interview when assessing for FTD.



},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41398324b,

title = {Analysis of conceptual overlap among formal thought disorder rating scales in psychosis: a systematic semantic synthesis},

author = {Alban Voppel and Silvia Ciampelli and Tilo Kircher and Peter F Liddle and Raffael Massuda and Frederike Stein and Sunny X Tang and Manaan Kar Ray and Sohee Park and Lena Palaniyappan},

doi = {10.1038/s41537-025-00712-z},

issn = {2754-6993},

year  = {2025},

date = {2025-12-01},

journal = {Schizophrenia (Heidelb)},

volume = {12},

number = {1},

pages = {9},

abstract = {Measuring Formal Thought Disorder (FTD), a common, cross-diagnosed symptom dimension across mental disorders, is plagued by numerous inconsistencies. Clinicians use either FTD-specific scales or items from generic scales. While these tools are based on extensive clinical observations, they suffer from inconsistent terminology. Different scales may use the same term for distinct concepts or different terms for the same concept. This lack of conceptual standardization prevents the identification of underlying FTD subconstructs. By using natural language processing, we compared the definitions, labeling and overlap of FTD symptoms, i.e., the definitions of single items, across psychopathological scales. We used a three-pronged validation approach to analyze semantic clusters of single definitions of FTD scale psychopathological items. First, we used sentence-BERT to divide 30 Thought and Language Disorder scale (TALD) items into positive or negative FTD clusters, validating this approach by checking for correspondence with published factor-analytic divisions (approach validation). Second, we created a sparse item-to-item similarity matrix from 103 items across seven scales to identify semantically converging cross-scale FTD items; a clinician-researcher described the resulting four clusters, and we compared our automated classification with that of six blinded experts to establish expert-machine semantic correspondence. Finally, we analyzed data from 98 participants (49 healthy controls and 49 schizophrenia/affective psychosis), identifying the highest-correlating Clinical Language Disorder Scale (CLANG) item for each Thought, Language and Communication (TLC) scale item and mapping these to our BERT-derived clusters to establish data-level correspondence. When assigning TALD items to BERT-derived positive or negative FTD groupings, we observed a 73% match with prior factor analyses. The BERT-informed clustering of cross-scale items highlighted four coherent FTD groupings: (1) muddled communication & incomprehension, (2) abrupt topic shifts, (3) inconsistent narrative structure, (4) restricted speech. Expert raters showed moderate-to-high overlap (Fleiss' kappa = 0.617) with computational clusters. A binomial test indicated that at the level of individual participants, correlations among CLANG-TLC item pairs were significantly more likely than chance to fall into the expected semantic cluster (p < 0.001). FTD rating scales measure overlapping, semantically related constructs that drive item-level correlations. Semantic clustering acts as a novel method to harmonize multi-scale data and pinpoint discrepancies between expert and machine classifications. Computational linguistics has the potential to improve consistency across rating scales especially when measuring complex constructs such as FTD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41350597b,

title = {Lexical meaning is lower dimensional in psychosis},

author = {Claudio Palominos and Frederike Stein and Tilo Kircher and Rosa Ayesa-Arriola and Lena Palaniyappan and Philipp Homan and Iris E Sommer and Wolfram Hinzen},

doi = {10.1038/s41598-025-30443-1},

issn = {2045-2322},

year  = {2025},

date = {2025-12-01},

journal = {Sci Rep},

volume = {16},

number = {1},

pages = {859},

abstract = {Diverse language models (LMs), including large language models (LLMs) based on deep neural networks, allow us to chart how people organize meanings in speech and how this process breaks down in conditions. Recent evidence has pointed to higher mean semantic similarities between words in people with psychosis, conceptualized as a 'shrunk' (more compressed) semantic space. Based on this, we hypothesized that the dimensionality of the vector spaces as defined by the embeddings of speech samples from LMs would also be easier to reduce in psychosis. To test this, we used principal component analysis (PCA) to calculate different metrics serving as proxies for reducibility, including the number of components needed to reach 90% of variance, and the cumulative variance explained by the first two components. For further exploration, intrinsic dimensionality (ID) was also estimated. Results consistent over datasets in three languages confirmed significantly higher reducibility of the semantic space in psychosis. This result points to the existence of an underlying intrinsic geometry of the space of semantic associations in speech, which may underlie more surface-level measurements such as semantic similarity. It also offers a new foundational approach to speech in mental disorders.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41243554b,

title = {Barriers and Opportunities for Collaboration With Primary Care: Perspectives of Early Psychosis Intervention Programs in Ontario, Canada},

author = {Rebecca Rodrigues and Jordan Edwards and Candice Madakadze and Richard Booth and Suzanne Archie and Arlene G MacDougall and Lena Palaniyappan and Chiachen Cheng and Sarah Chan and Kerri Nagy and Kelly K Anderson and },

doi = {10.1111/eip.70108},

issn = {1751-7893},

year  = {2025},

date = {2025-11-01},

journal = {Early Interv Psychiatry},

volume = {19},

number = {11},

pages = {e70108},

abstract = {BACKGROUND: Collaboration between early psychosis intervention (EPI) services and primary care is crucial for continuity of care for first-episode psychosis. The aim of this study was to describe the perceptions of staff at EPI programs on barriers and opportunities for collaboration with primary care.nnMETHODS: We conducted a qualitative descriptive study using focus groups with staff at six EPI programs across Ontario, Canada (2 rural, 4 urban) with 2-9 participants per focus group (total n = 39). Focus group sessions were audio recorded and transcribed verbatim. We used thematic analyses to code the transcripts and identify emergent themes.nnRESULTS: Participants highlighted three points in the EPI treatment process where collaboration with primary care is important: during the referral/intake process, shared care throughout treatment, and at discharge from the EPI program. We identified four themes relating to broader structural issues impacting collaboration with primary care through the treatment process: client access to primary care, family physician knowledge of early psychosis, siloed communication structures, and time constraints for both EPI staff and family physicians.nnCONCLUSIONS: Improving primary care access in young people, increasing family physician knowledge of psychosis and EPI services, and allowing dedicated time for communication for both family physicians and EPI clinicians may improve collaboration and patient care through the processes of intake, ongoing care, and discharge from EPI services.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41237332b,

title = {Sleep and Activity Patterns as Transdiagnostic Behavioral Biomarkers in Psychiatry: Longitudinal Observational Study From the DeeP-DD Study},

author = {Dylan Hamitouche and Tihare Zamorano and Youcef Barkat and Deven Parekh and Lena Palaniyappan and Sara Jalali and David Benrimoh},

doi = {10.2196/81107},

issn = {2561-326X},

year  = {2025},

date = {2025-11-01},

journal = {JMIR Form Res},

volume = {9},

pages = {e81107},

abstract = {BACKGROUND: Despite widespread use of symptom rating scales in psychiatry, these tools are limited by reliance on self-report, infrequent administration, and lack of predictive power. This constrains clinicians' ability to monitor illness trajectories or anticipate adverse outcomes like relapse. Actigraphy, a passive wearable-based method for measuring sleep and physical activity, offers objective, high-resolution behavioral data that may better reflect symptom fluctuations. Prior research has shown associations between actigraphy features and mood or psychosis symptoms, but most studies have focused on narrow diagnostic groups or fixed time windows, limiting clinical translation.nnOBJECTIVE: This study aims to examine whether actigraphy-derived sleep and activity features correlate with psychiatric symptom severity in a transdiagnostic psychiatric sample, and to identify which features are most clinically relevant across multiple temporal resolutions.nnMETHODS: We present a feasibility case series study analyzing preliminary data from 8 outpatients (ages 18-52 years) enrolled in the Deep Phenotyping and Digitalization at Douglas (DeeP-DD) study, a prospective transdiagnostic study of digital phenotyping. Participants wore wrist-based actigraphy devices (GENEActiv) for up to 5 months. Symptom severity was measured using a variety of self- and clinician-rated scales. We performed intraindividual Spearman correlations and interindividual repeated measures correlations across daily, weekly, monthly, and full-duration averages.nnRESULTS: Intraindividual analyses revealed that later rise times were significantly associated with higher weekly 9-item Patient Health Questionnaire (PHQ-9) scores in participant 7 (ρ=0.74, P<.001) and participant 4 (ρ=0.78, P=.02), as well as higher weekly 7-item General Anxiety Disorder (GAD-7) scores in participant 7 (ρ=0.59, P=.03). While similar trends were observed at daily and monthly timescales, the weekly resolution yielded the most robust significance. Interindividual analyses showed that weeks with later average rise time correlated with higher PHQ-9 (r=0.48, P<.001) and GAD-7 scores (r=0.38, P=.03), with the PHQ-9 association remaining significant after Bonferroni correction (Bonferroni-corrected P=.02). Increased light physical activity was linked to lower PHQ-9 scores weekly (r=-0.44, P=.001) and monthly (r=-0.53, P=.01). Over the whole duration of the study, increased levels of sedentary activity were associated with lower GAD-7 scores (ρ=0.74; P<.001).nnCONCLUSIONS: Our findings highlight actigraphy-derived sleep and activity features, particularly rise time and physical activity, as promising transdiagnostic markers of psychiatric symptom burden. Their consistent associations across temporal scales and diagnostic groups underscore their potential utility for scalable, real-world clinical monitoring. Future work should validate these findings in larger cohorts and explore advanced analytical methods to capture circadian rhythmicity and symptom dynamics more precisely.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41170774b,

title = {Sexual reactivation under aripiprazole in schizophrenia: a note for prescribers},

author = {Theo Korchia and Lena Palaniyappan},

doi = {10.1139/jpn-25-0148},

issn = {1488-2434},

year  = {2025},

date = {2025-10-01},

journal = {J Psychiatry Neurosci},

volume = {50},

number = {5},

pages = {E334--E336},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41092762b,

title = {Activity-dependent modulation of glutamate, glutamine and glutathione in first-episode schizophrenia: A 7T functional MRS study},

author = {Peter Jeon and Michael Mackinley and Kara Dempster and Sabrina Ford and Jean Théberge and Lena Palaniyappan},

doi = {10.1016/j.schres.2025.10.008},

issn = {1573-2509},

year  = {2025},

date = {2025-11-01},

journal = {Schizophr Res},

volume = {285},

pages = {339--348},

abstract = {BACKGROUND AND HYPOTHESIS: Glutamatergic abnormalities have been implicated as an important component of schizophrenia symptoms. Functional magnetic resonance spectroscopy (fMRS) has emerged as a strong candidate for making dynamic observations of neurometabolites, overcoming the challenges of single-state observations in traditional magnetic resonance spectroscopy studies. To date, dynamic measurements of glutathione have not been presented in patients in the early stages of schizophrenia.nnSTUDY DESIGN: Dynamic glutamate, glutamine, and glutathione concentrations were quantified from the dorsal anterior cingulate cortex of 33 first-episode schizophrenia and 23 healthy control volunteers. A four-block 7 T fMRS paradigm was employed using the color-word Stroop task as the cognitive demand. Non-baseline blocks were also normalized relative to the baseline block for metabolite percentage change observations.nnSTUDY RESULTS: ANOVA revealed significant effects of time, metabolite and time x diagnosis x metabolite. Activation and prolonged elevation of glutathione in response to the cognitive stimuli were observed in healthy controls but only glutamate effects were notable in first-episode schizophrenia. Significantly lower glutamate concentrations during the second recovery blocks in both groups compared to their baseline glutamate levels. Normalized glutamate levels revealed a positive correlation between the recovery 2 block and both PANSS-8 Positive and PANSS-8 General scores.nnCONCLUSIONS: A potential inability to mount an appropriate antioxidant response to short-term oxidative stress may occur in the early stages of schizophrenia. A longitudinal study of fMRS is required to better understand the regulation of oxidative stress across the different stages of schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41049019b,

title = {Glutamate, Contextual Insensitivity, and Disorganized Speech in First-Episode Schizophrenia: A 7T Magnetic Resonance Spectroscopy Study},

author = {Yingqi Laetitia Wang and Victoria Sharpe and Michael Mackinley and Gina R Kuperberg and Kaustubh Supekar and Jean Theberge and Lena Palaniyappan},

doi = {10.1016/j.bpsgos.2025.100593},

issn = {2667-1743},

year  = {2025},

date = {2025-11-01},

journal = {Biol Psychiatry Glob Open Sci},

volume = {5},

number = {6},

pages = {100593},

abstract = {BACKGROUND: In people with schizophrenia, formal thought disorder is a core symptom that emerges early and persists into chronic stages despite treatments. It manifests as disorganized speech and is often associated with poor long-term outcomes. A key feature of this disorganization is an impairment in the buildup and use of context provided by preceding words when choosing upcoming words. Recent work has shown that spoken words are less predictable based on global linguistic context in schizophrenia, but the neural basis of this remains unknown. Glutamate dysfunction in the anterior cingulate cortex has long been implicated in schizophrenia, but its connection to behavioral impairments remains unclear.nnMETHODS: In this study, we investigated the relationship between linguistic contextual sensitivity and glutamate level in the dorsal anterior cingulate cortex in 39 patients with first-episode psychosis (33 men) and 33 sociodemographically matched healthy control participants (22 men). Contextual sensitivity was measured using a large language model (GPT-3), and glutamate levels were measured using 7T magnetic resonance spectroscopy.nnRESULTS: We found a significant interaction between diagnosis and glutamate level in predicting contextual sensitivity: Patients with lower glutamate levels had poor contextual sensitivity, a relationship not seen in healthy control participants. Glutamate variation was specifically explained by contextual sensitivity after controlling for other clinical and language variables, underscoring the robustness and specificity of this association.nnCONCLUSIONS: These results highlight a potential glutamatergic basis for disorganized speech in schizophrenia and suggest that contextual sensitivity in speech could reflect anterior cingulate glutamate variations in early psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41047156b,

title = {Speech and Language Markers as Longitudinal Predictors of Youth Mental Health: A Systematic Review},

author = {Martin Sellier Silva and Jessica Ahrens and Fiona Meister and Lena Palaniyappan},

doi = {10.1111/eip.70102},

issn = {1751-7893},

year  = {2025},

date = {2025-10-01},

journal = {Early Interv Psychiatry},

volume = {19},

number = {10},

pages = {e70102},

abstract = {INTRODUCTION: Severe mental disorders in young people (< 25 years) are often preceded by subtle changes in communication and thinking, detectable in speech. Speech and language markers are promising for early detection; however, no systematic review has evaluated their prospective utility in predicting mental disorders in youth. We comprehensively reviewed longitudinal studies assessing speech/language markers as predictors of major mental disorder onset or symptom progression in youth.nnMETHODS: We searched for longitudinal studies using recorded speech samples from youth or family members to predict diagnostic changes or symptom severity in major depressive disorder (MDD), psychosis, ADHD, substance use disorder, bipolar disorder, OCD and eating disorders. Risk of bias was assessed using the Newcastle-Ottawa Scale. Our protocol was pre-registered (CRD42024579798).nnRESULTS: Of 2260 articles, 11 studies met inclusion criteria, covering MDD (n = 3), psychosis (n = 5) and ADHD (n = 3). No eligible studies were found for OCD, substance use, bipolar or eating disorders. Both manual and computational speech analyses were used, with speech samples from parents and youth. Predictive speech/language markers included parental expressed emotion (MDD, ADHD), formal thought disorder (psychosis) and acoustic/linguistic features (psychosis, ADHD). Study quality was moderate to good (mean score: 5.45/8).nnCONCLUSIONS: Externally validated longitudinal studies on the predictive value of speech/language markers of youth-onset mental disorders are scarce, restricted to a few target disorders and do not allow for variations due to the developmental stage of the samples. Nonetheless, existing studies highlight the potential of applying Natural Language Processing methods to speech samples from both youth and parents for early identification.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40867373b,

title = {Linguistic Markers of Theory of Mind in Spontaneous Speech: A Narrative Review},

author = {Chaimaa El Mouslih and Vegas Hodgins and Lena Palaniyappan and Debra A Titone},

doi = {10.3390/bs15081016},

issn = {2076-328X},

year  = {2025},

date = {2025-07-01},

journal = {Behav Sci (Basel)},

volume = {15},

number = {8},

abstract = {The relationship between theory of mind (ToM) or mentalizing, i.e., the cognitive ability to attribute mental states to oneself and others, and language has been widely explored across disciplines. Identifying reliable linguistic markers of ToM extractable from individuals' speech provides a promising path for both research and clinical practice. In this narrative review, we aimed to synthesize findings from studies identified through a PSYCINFO search to provide an overview of speech-based markers associated with ToM abilities. Our results revealed six primary categories of relevant speech markers: mental state terms, general linguistic ability, embedded clauses, referring expressions, and pragmatic markers. Standardizing these markers could enhance the replicability and applicability of ToM assessments across diverse populations. We encourage future research to build on these findings to examine how mentalizing is expressed through language in varied social, cultural, and clinical contexts. Advancing this line of inquiry will deepen our understanding of the interplay between language and mentalizing and contribute to broader insights into language and cognition.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40765993b,

title = {Task-Related Controllability of Functional Connectome During a Working Memory Task in Schizophrenia, Bipolar Disorder, and Major Depressive Disorder},

author = {Jun Yang and Zhening Liu and Feiwen Wang and Wenjian Tan and Danqing Huang and Xuan Ouyang and Haojuan Tao and Guowei Wu and Yunzhi Pan and Jie Yang and Lena Palaniyappan},

doi = {10.34133/research.0792},

issn = {2639-5274},

year  = {2025},

date = {2025-01-01},

journal = {Research (Wash D C)},

volume = {8},

pages = {0792},

abstract = {Working memory (WM) deficit is a prominent and common cognitive impairment in major psychiatric disorders (MPDs). Altered control of brain state transitions may underlie the neural basis of WM deficit. We investigate whether shared and illness-specific alterations in controllability underlie WM deficits in MPDs. We examined functional magnetic resonance imaging data during an -back WM task from 105 patients with schizophrenia (SZ), 67 with bipolar disorder (BD), 51 with major depressive disorder (MDD), and 80 healthy controls (HCs). We calculated each brain region's capacity to steer transitions to connectomic states with less input (average controllability) and to difficult-to-reach states with high input (modal controllability). The effect of altered controllability on clinical and cognitive characteristics and their likely genetic and neurotransmitter basis were investigated. All MPDs demonstrated a common but graded pattern of reduced modal controllability within the frontoparietal network compared to HC, with SZ showing the most pronounced impairment. Relative to BD and MDD, SZ exhibited the broadest profile of reduced average and modal controllability across the cortex, particularly in sensory, default mode, and salience networks. The affected brain regions preferentially expressed genes that determine synaptic biology and chemoarchitecture involving glutamate/γ-aminobutyric acid (GABA) and monoamine [dopamine and 5-hydroxytryptamine (5-HT)] neurotransmitter systems. A graded, transdiagnostic reduction in the influence of the sensory networks and triple network system in implementing state transitions underlies WM deficits in MPDs. This deficit, especially pronounced in SZ, has its likely basis in synaptic biology and in glutamate/GABA and monoamine (dopamine and 5-HT) neurotransmitters.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40764808b,

title = {Profiling brain morphology for autism spectrum disorder with two cross-culture large-scale consortia},

author = {Xue-Ru Fan and Ye He and Yin-Shan Wang and Lei Li and  and  and Xujun Duan and Xi-Nian Zuo},

doi = {10.1038/s42003-025-08573-z},

issn = {2399-3642},

year  = {2025},

date = {2025-08-01},

journal = {Commun Biol},

volume = {8},

number = {1},

pages = {1157},

abstract = {We explore neurodevelopmental heterogeneity in Autism Spectrum Disorder (ASD) through normative modeling of cross-cultural cohorts. By leveraging large-scale datasets from Autism Brain Imaging Data Exchange (ABIDE) and China Autism Brain Imaging Consortium (CABIC), our model identifies two ASD subgroups with distinct brain morphological abnormalities: subgroup "L" is characterized by generally smaller brain region volumes and higher rates of abnormality, while subgroup "H" exhibits larger volumes with less pronounced deviations in specific areas. Key areas, such as the isthmus cingulate and transverse temporal gyrus, were identified as critical for subgroup differentiation and ASD trait correlations. In subgroup H, the regional volume of the isthmus cingulate cortex showed a direct correlation with individuals' autistic mannerisms, potentially corresponding to its slower post-peak volumetric declines during development. These findings offer insights into the biological mechanisms underlying ASD and support the advancement of subgroup-driven precision clinical practices.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40726139b,

title = {Disrupted Glucose Metabolism Covariance Network in Amyotrophic Lateral Sclerosis},

author = {Xin Jin and Xueying Wang and Dingxin Zheng and Pubing Yuan and Jianyu Li and Ting Qiu and Huixiong Zhang and Yifan Chen and Jinfan Zhang and Feifei Wu and Qing Liu and Alessandro Grecucci and Yuanchao Zhang and Junling Wang and Xiaoping Yi and Lena Palaniyappan and B Blair Braden},

doi = {10.1111/cns.70537},

issn = {1755-5949},

year  = {2025},

date = {2025-07-01},

journal = {CNS Neurosci Ther},

volume = {31},

number = {7},

pages = {e70537},

abstract = {AIMS: This study aimed to characterize the topological changes in glucose metabolism covariance networks in amyotrophic lateral sclerosis (ALS).nnMETHODS: We assessed the interregional coordination of F-FDG-PET data to examine topological alterations in individualized glucose metabolism covariance networks in 127 ALS patients compared to 128 healthy controls (HC).nnRESULTS: Compared to HC, ALS patients showed reduced small-worldness (lower normalized clustering coefficient, higher normalized characteristic path length) and decreased global and local efficiency, suggesting impaired global integration and local segregation. These network metrics correlated with disease progression and motor function. Regionally, altered degree centrality affected motor and default mode networks, and related to GABAa and mGluR5 receptor expression. Transcriptomic associations further linked these changes to immune function, synaptic signaling, and protein regulation. Bidirectional shifts in connectivity strength were observed, with both increased connectivity and disease progression independently predicting reduced survival.nnCONCLUSION: Our findings may provide valuable biomarkers for monitoring the progression of ALS and suggest potential mechanistic pathways for the development of innovative therapeutic strategies for this disorder.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40641506b,

title = {Taking a look at your speech: identifying diagnostic status and negative symptoms of psychosis using convolutional neural networks},

author = {Gleb Melshin and Anthony DiMaggio and Nadia Zeramdini and Michael MacKinley and Lena Palaniyappan and Alban Voppel},

doi = {10.1038/s44277-025-00040-1},

issn = {2948-1570},

year  = {2025},

date = {2025-01-01},

journal = {NPP Digit Psychiatry Neurosci},

volume = {3},

number = {1},

pages = {19},

abstract = {Speech-based indices are promising objective biomarkers for identifying schizophrenia and monitoring symptom burden. Static acoustic features show potential but often overlook time-varying acoustic cues that clinicians naturally evaluate-such as negative symptoms-during clinical interviews. A similar dynamic, unfiltered approach can be applied using speech spectrograms, preserving acoustic-temporal nuances. Here, we investigate if this method has the potential to assist in the determination of diagnostic and symptom severity status. Speech recordings from 319 participants (227 with schizophrenia spectrum disorders, 92 healthy controls) were segmented into 10 s fragments of uninterrupted audio ( = 110,246) and transformed into log-Mel spectrograms to preserve both acoustic and temporal features. Participants were partitioned into training (70%), validation (15%), and test (15%) datasets without overlap. Modified ResNet-18 convolutional neural networks (CNNs) performed three classification tasks; (1) schizophrenia-spectrum vs healthy controls, within 179 clinically-rated patients, (2) individuals with more severe vs less severe negative symptom burden, and (3) clinically obvious vs subtle blunted affect. Grad-CAM was used to visualize salient regions of the spectrograms that contributed to classification. CNNs distinguished schizophrenia-spectrum participants from healthy controls with 87.8% accuracy (AUC = 0.86). The classifier trained on negative symptom burden performed with somewhat less accuracy (80.5%; AUC = 0.73) but the model detecting blunted affect above a predefined clinical threshold achieved 87.8% accuracy (AUC = 0.79). Importantly, acoustic information contributing to diagnostic classification was distinct from those identifying blunted affect. Grad-CAM visualization indicated that the CNN targeted regions consistent with human speech signals at the utterance level, highlighting clinically relevant vocal patterns. Our results suggest that spectrogram-based CNN analyses of short conversational segments can robustly detect both schizophrenia-spectrum disorders and ascertain burden of negative symptoms. This interpretable framework underscores how time-frequency feature maps of natural speech may facilitate more nuanced tracking and detection of negative symptoms in schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40619893b,

title = {Early Psychosis Symptoms Noted by Family Physicians in Electronic Medical Records During Help-Seeking Visits in Primary Care: Symptômes précoces de psychose relevés par les médecins généralistes dans les dossiers médicaux électroniques lors de consultations en soins primaires pour demande d'aide},

author = {Joshua C Wiener and Rebecca Rodrigues and Jennifer N S Reid and Suzanne Archie and Saadia Hameed Jan and Arlene G MacDougall and Lena Palaniyappan and Liisa Jaakkimainen and Branson Chen and Neo Sawh and Kelly K Anderson and },

doi = {10.1177/07067437251355637},

issn = {1497-0015},

year  = {2025},

date = {2025-09-01},

journal = {Can J Psychiatry},

volume = {70},

number = {9},

pages = {713--722},

abstract = {BackgroundThe objectives of this study were (1) to describe the symptoms noted by family physicians during help-seeking visits for early psychosis, relative to a validated screening tool for early psychosis in primary care, and (2) to examine the referral disposition of patients meeting the screening tool cut-off.MethodsWe constructed a retrospective cohort of Ontario residents aged 14-35 years with an incident diagnosis of non-affective psychotic disorder between 2005-2015 in health administrative data, and at least one visit in the Electronic Medical Record Primary Care database during the 6 months prior to the date of psychotic disorder diagnosis ( = 572). We abstracted symptoms of psychosis noted by the family physician in the electronic medical records and compared these to the Primary Care Checklist (PCCL) for early psychosis.ResultsThe most frequent PCCL items noted were "tension or nervousness" (13.3%), "depressive mood" (12.5%), "increased stress or deterioration in functioning" (7.5%), and "sleep difficulties" (6.6%). The PCCL cut-off was met by 187 patients (33%) across 327 visits (8%). A greater proportion of visits meeting the PCCL cut-off had psychosis noted as the main presenting issue (55.4% vs. 6.8%) and resulted in referral to mental health services (33.3% vs. 6.0%) than those not meeting the cut-off. However, two in three visits where the screening cut-off for early psychosis was met did not result in a referral to mental health services.DiscussionThe findings of this study suggest that family physicians may benefit from a screening tool when early psychosis is suspected to improve identification and guide referral practices.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40598470b,

title = {Brain state dynamics and working memory in patients with schizophrenia and unaffected siblings},

author = {Feiwen Wang and Jie Yang and Jun Yang and Peng Cheng and Wenjian Tan and Danqing Huang and Maoxing Zhong and Xiawei Liu and Weiqing Huang and Zhening Liu and Lena Palaniyappan},

doi = {10.1186/s12916-025-04216-6},

issn = {1741-7015},

year  = {2025},

date = {2025-07-01},

journal = {BMC Med},

volume = {23},

number = {1},

pages = {376},

abstract = {BACKGROUND: Working memory (WM) deficits are a key feature of schizophrenia and are also seen in unaffected siblings. These deficits might arise  from disrupted transitions from one brain state to another. Using a robust algorithm called the Bayesian Switching Dynamical System (BSDS), we studied hidden brain states and their transitions during a WM task in people with schizophrenia.nnMETHODS: We used BSDS to identify brain states based on regions of interest (ROIs) within the default mode network and the frontoparietal network in 161 patients with schizophrenia, 37 unaffected siblings, and 96 healthy controls during N-back (0, 2, and resting fixation) tasks. We estimated group differences in the properties of brain states and studied the influence of WM performance and clinical characteristics on them using General Linear Models.nnRESULTS: We identified 4 brain states underlying the WM task: high-demand, low-demand, fixation, and non-dominant states. Compared with controls and siblings, patients showed reduced occupancy and lifetime of high-demand state during the "2-back," reduced lifetime of low-demand state during the "0-back," but increased occupancy and lifetime of fixation state during both task periods. Aberrant high-demand state mediated the association between WM performance and negative symptoms. Compared with controls and patients, siblings showed increased occupancy of high-demand and reduced fixation state during the resting fixation condition; this putative compensatory process correlated with better WM performance.nnCONCLUSIONS: Latent brain states of intrinsic connectivity that represent internal mental processes affect WM performance, influencing the expression of negative symptoms in schizophrenia and cognitive resilience in unaffected siblings.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40581176b,

title = {Imbalance of thalamocortical structural connectivity in adolescents with early-onset schizophrenia},

author = {Yonghui Xiang and Shuting Chen and Jinqiang Zhang and Guowei Wu and Xuan Ouyang and Zhening Liu and Chen Tan and Can Xu and Lange Zheng and Xinran Xu and Lena Palaniyappan and Weidan Pu},

doi = {10.1016/j.pnpbp.2025.111423},

issn = {1878-4216},

year  = {2025},

date = {2025-07-01},

journal = {Prog Neuropsychopharmacol Biol Psychiatry},

volume = {140},

pages = {111423},

abstract = {BACKGROUND: Thalamocortical circuit imbalance, characterized by decreased prefrontal-thalamic connectivity and increased sensorimotor-thalamic connectivity, has been well-documented in adult-onset schizophrenia. We have previously demonstrated functional imbalance of this circuit in adolescents with early-onset schizophrenia (EOS). We now investigate whether this functional imbalance stems from the thalamocortical structural connectivity in EOS, thereby further establishing its relevance to the neurodevelopmental modeling of psychosis.nnMETHODS: The study included 212 adolescents (145 EOS patients and 67 healthy controls). To further control the medication effect, the patients were divided into two subgroups (drug-naive vs drug-treated). Fourteen bilateral cortical regions of interest and bilateral thalamus were used as targets and seeds respectively for probabilistic tractography to quantify structural connectivity of the thalamocortical circuit.nnRESULTS: Compared to healthy controls, in EOS, structural connectivity of the thalamus with the dorsolateral prefrontal (dlPFC) and parietal cortices was decreased, while connectivity with the sensorimotor cortices was increased. We also observed an unexpected increase in connectivity of the medial prefrontal cortex (mPFC) with thalamus in EOS. The imbalance pattern was replicated in two subgroups regardless of medication status. Further correlation analysis showed that the thalamic hypoconnectivity with the dlPFC and the hyperconnectivity with the mPFC were both related with higher individual symptom burden in patients.nnCONCLUSIONS: The functional thalamocortical circuit imbalance in adolescents with schizophrenia is underwritten by a similar imbalance in the structural connectivity. A specific thalamocortical structural hyperconnectivity involving the mPFC, previously unobserved in adult-onset patients, may contribute to the distinct clinical manifestations in EOS.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40543361b,

title = {Norepinephrine system dysconnectivity in major depressive disorder: the effect of short term SSRI treatment},

author = {Shuting Chen and Jinqiang Zhang and Guowei Wu and Xuan Ouyang and Zhening Liu and Dongsheng Lv and Ziliang Han and Yonghui Xiang and Chen Tan and Can Xu and Lange Zheng and Xinran Xu and Lena Palaniyappan and Weidan Pu},

doi = {10.1016/j.euroneuro.2025.05.010},

issn = {1873-7862},

year  = {2025},

date = {2025-08-01},

journal = {Eur Neuropsychopharmacol},

volume = {97},

pages = {40--50},

abstract = {Despite the long history of norepinephrine hypothesis in depression, the neuropathology involving norepinephrine remains elusive. This study aims to map the whole-brain functional connectivity (FC) of the major norepinephrine nucleus locus coeruleus (LC) and further investigate the effect of escitalopram, an antidepressant with minimal direct norepinephrine effects, on the LCNE system in patients with major depressive disorder (MDD). Totally 253 MDD patients and 227 healthy controls (HCs) were recruited. The Philips-scanning dataset from Xiangya (52 patients and 88 HCs) served as the discovery sample, while the Siemens-scanning dataset from Xiangya (95 patients and 90 HCs) served as the across-scanner sample and the dataset from Inner Mongolia (88 patients and 53 HCs) as the across-center replication sample. Forty-eight patients entered a naturalistic observational trial of 8-weeks of escitalopram-only treatment. Bilateral LC were selected as regions of interest for FC analysis. Compared to HCs, patients exhibited decreased LCNE system connectivity with the multimodal association (dorsolateral/medial prefrontal) cortices and increased connectivity with the sensory/motor cortex. This imbalanced FC pattern replicated in two independent samples and consistently correlated with depressive symptom severity. The LCNE system dysconnectivity in MDD mapped with a significant overlap on the norepinephrine transporter distribution based on prior PET data. As expected, no significant changes of the LCNE connectivity occurred with 8-weeks of escitalopram treatment. We provide robust evidence for a striking sensory-multimodal imbalance in LCNE system connectivity across three independent samples, with a potential link to NE transporter chemoarchitecture, that is not alleviated by a serotonin selective antidepressant agent.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40523895b,

title = {Relationship between grammar and schizophrenia: a systematic review and meta-analysis},

author = {Dalia Elleuch and Yinhan Chen and Qiang Luo and Lena Palaniyappan},

doi = {10.1038/s43856-025-00944-1},

issn = {2730-664X},

year  = {2025},

date = {2025-06-01},

journal = {Commun Med (Lond)},

volume = {5},

number = {1},

pages = {235},

abstract = {BACKGROUND: Schizophrenia significantly impairs everyday communication, affecting education and employment. Such communication difficulties may arise from deficits in syntax-understanding and generating grammatical structures. Research on syntactic impairments in schizophrenia is underpowered, with inconsistent findings, and it is unclear if deficits are specific to certain patient subgroups, regardless of symptom profiles, age, sex, or illness severity.nnMETHODS: A pre-registered (Open Science Framework: https://doi.org/10.17605/OSF.IO/7FZUC ) search using PubMed, Scopus, PsycINFO, and Web of Science databases up to May 1, 2024, for all studies investigating syntax comprehension and production in schizophrenia vs. healthy controls. Excluding studies on those <18 years of age and qualitative research, we extracted Cohen's d and log coefficient of variation ratio and used Bayesian meta-analysis across 6 domains: 2 in comprehension and 4 in production in patient-control comparisons. Study quality was evaluated using a modified Newcastle-Ottawa Scale, with moderators (age, sex, study quality, language) tested via meta-regression.nnRESULTS: We identify 86 relevant articles, of which 45 have sufficient data for meta-analysis (n = 2960 participants, 64.4% English, weighted mean age(sd) = 32.3(5.6)). Bayesian meta-analysis shows strong evidence of syntactic deficits in schizophrenia across all domains (d = 0.65-1.01, overall random-effects d = 0.86, 95% CrI [0.67-1.03]), with syntax comprehension being most affected, with weak publication bias. People with schizophrenia show increased variability in comprehension and production of long and complex utterances (lnCVR = 0.21, 95% CrI [0.07-0.36]), hinting at subgroups with differing performance.nnCONCLUSIONS: Robust impairments in grammatical comprehension and production in schizophrenia suggest opportunities for targeted interventions focusing on syntax, a rule-based feature amenable to cognitive, educational, and linguistic interventions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40437012b,

title = {Distinct structural deficits in treatment-resistant schizophrenia and their putative neurotransmitter basis: a source-based morphometry analysis},

author = {Huan Huang and Xiaowei Wang and Xuan Qin and Rui Xu and Ying Xiong and Cheng Chen and Qirong Wan and Hao Liu and Chang Shu and Wei Yuan and Yunlong Peng and Yuan Zhou and Huiling Wang and Lena Palaniyappan},

doi = {10.1038/s41386-025-02135-x},

issn = {1740-634X},

year  = {2025},

date = {2025-11-01},

journal = {Neuropsychopharmacology},

volume = {50},

number = {12},

pages = {1807--1816},

abstract = {Schizophrenia is associated with widespread gray matter reduction. This is influenced by the underlying connectivity, resulting in covarying patterns of structural changes that are more pronounced in treatment-resistant individuals. However, it remains uncertain whether a distinct network of brain regions, with specific neurotransmitter basis, forms the substrate for treatment resistance in schizophrenia. We investigated the structural covariance networks (SCN) in 198 individuals; 55 with treatment-resistant schizophrenia (TRS) and 79 without TRS (non-TRS) in active symptomatic phase, and 64 healthy controls (HC) using Calhoun's Source-Based Morphometry. We mapped the putative neurotransmitter basis of the SCNs using a PET-based chemoarchitectural atlas. Twelve independent components (i.e., SCNs) were identified. A prefrontal-limbic SCN had lower gray matter volume (GMV) in TRS compared to HC and non-TRS (F = 7.757, p < 0.001, FDR-corrected). Spatial correlation with chemoarchitectural atlas revealed predominant contributions from serotonergic [5HT and 5HT], glutamatergic [mGluR], histaminergic [H], and opioid [MOR] receptors for this TRS-related SCN (all p < 0.05, FDR-corrected). A different SCN comprised of dorsal fronto-temporal and parieto-occipital regions, not associated with  any specific neurotransmitter distribution, exhibited reduced GMV in both TRS and non-TRS groups vs. HC (F = 7.239, p < 0.001, FDR-corrected). Amidst the generic GMV reduction that is shared with non-TRS patients, patients with TRS have specific prefrontal-limbic structural deficits with a unique non-dopaminergic chemoarchitecture. These findings indicate a putative molecular and structural basis for poor treatment response, guiding the development of second- and third-line pharmacotherapies for TRS.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40395545b,

title = {Symptom networks and working memory in schizophrenia: a multi-methodological cross-sectional study from phenotype to endophenotype},

author = {Peng Cheng and Zhening Liu and Feiwen Wang and Jun Yang and Fuping Sun and Zebin Fan and Jie Yang and Lena Palaniyappan},

doi = {10.1016/j.ijchp.2025.100577},

issn = {2174-0852},

year  = {2025},

date = {2025-01-01},

journal = {Int J Clin Health Psychol},

volume = {25},

number = {2},

pages = {100577},

abstract = {BACKGROUND: A notable deficit in working memory (WM) is well established in schizophrenia. Nevertheless, the intricate relationship between various symptoms and WM impairment is still not fully understood. We use three distinct methodologies-symptom network analysis (SNA), Connectome-Based Predictive Modeling (CPM), and brain gene annotation enrichment analysis-to explore the connectome patterns that link WM deficits and symptoms, and their related gene expression.nnMETHODS: 255 patients with schizophrenia were recruited as two distinct samples. SNA was used to pinpoint the core psychiatric symptoms influenced by WM performance. CPM identified the subnetwork of the functional connectome that was recruited under the 2-back load of the N-back WM task, and predicted the severity of the SNA-based key symptoms. Gene annotation enrichment analysis explored the likely molecular biological processes underlying the symptom-predictive functional WM network.nnRESULTS: SNA revealed that disorganized attention (G11 of PANSS) is most closely linked to WM performance in schizophrenia. The WM-based connectome significantly predicted disorganized attention ( = 0.278,  = 0.001, permutation- = 0.046), and this model was validated in the second dataset ( = 0.274,  = 0.014). The predictive network primarily involved the frontoparietal and frontolimbic networks. Gene enrichment analysis revealed a preferential role for cytoplasmic protein binding, indicating a potential molecular basis for the WM-related, symptom-predictive functional connectivity.nnCONCLUSIONS: Impaired WM performance in schizophrenia relates to frontoparietal and frontolimbic connectivity and preferentially influences the severity of disorganized attention, a clinically observable phenomenon. The potential role of cytoplasmic protein binding in WM deficits and attentional disorganization in schizophrenia warrants further investigation.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40368909b,

title = {Developing brain asymmetry shapes cognitive and psychiatric outcomes in adolescence},

author = {Xinran Wu and Kai Zhang and Nanyu Kuang and Xiangzhen Kong and Miao Cao and Zhengxu Lian and Yu Liu and Huanxin Fan and Gechang Yu and Zhaowen Liu and Wei Cheng and Tianye Jia and Barbara J Sahakian and Trevor W Robbins and Jianfeng Feng and Gunter Schumann and Lena Palaniyappan and Jie Zhang},

doi = {10.1038/s41467-025-59110-9},

issn = {2041-1723},

year  = {2025},

date = {2025-05-01},

journal = {Nat Commun},

volume = {16},

number = {1},

pages = {4480},

abstract = {Cerebral asymmetry, fundamental to various cognitive functions, is often disrupted in neuropsychiatric disorders. While brain growth has been extensively studied, the maturation of brain asymmetry in children and the factors influencing it in adolescence remain poorly understood. We analyze longitudinal data from 11,270 children aged 10-14 years in the Adolescent Brain Cognitive Development (ABCD) study. Our analysis maps the developmental trajectory of structural brain asymmetry. We identify significant age-related, modality-specific development patterns. These patterns link to crystallized intelligence and mental health problems, but with weak correlations. Genetically, structural asymmetry relates to synaptic processes and neuron projections, likely through asymmetric synaptic pruning. At the microstructural level, corpus callosum integrity emerged as a key factor modulating the developing asymmetry. Environmentally, favorable perinatal conditions were associated with prolonged corpus callosum development, which affected future asymmetry patterns and cognitive outcomes. These findings underscore the dynamic yet predictable interactions between brain asymmetry, its structural determinants, and cognitive and psychiatric outcomes during a pivotal developmental stage. Our results provide empirical support for the adaptive plasticity theory in cerebral asymmetry and offer insights into both cognitive maturation and potential risk for early-onset mental health problems.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40319470b,

title = {Latent Trajectories of Positive, Negative Symptoms and Functioning in Early Intervention Services for First-Episode Psychosis: A 2-Year Follow-Up Study},

author = {Olivier Percie du Sert and Joshua Unrau and Manish Dama and Lena Palaniyappan and Jai Shah and Ridha Joober and Delphine Raucher-Chéné and Ashok Malla and Martin Lepage},

doi = {10.1093/schbul/sbaf045},

issn = {1745-1701},

year  = {2025},

date = {2025-09-01},

journal = {Schizophr Bull},

volume = {51},

number = {5},

pages = {1428--1442},

abstract = {BACKGROUND: From the first episode (FEP), the course of psychosis is marked by substantial heterogeneity of clinical and functional outcomes which poses significant challenges in providing prognostic guidance to patients and families. To better understand such heterogeneity within the context of early intervention services (EIS), this study aimed to examine latent trajectories of positive and negative symptoms and functioning among FEP individuals undergoing EIS.nnSTUDY DESIGN: The Prevention and Early Intervention Program for Psychoses (PEPP-Montreal) is a 2-year EIS for FEP that conducted longitudinal assessments of 689 individuals aged 14-35, including sociodemographics, cognition, psychopathology, and functioning. Latent growth mixture modeling was used to identify distinct patterns of clinical and functional trajectories. The inter-relationship between trajectories, and the association of trajectory membership with baseline characteristics and distal outcomes were investigated using the manual 3-step approach.nnSTUDY RESULTS: Two positive symptom trajectories (Stable-low-32%, Fluctuating-68%,), 3 negative symptom trajectories (Decreasing-41%, Fluctuating-15%, and Stable-high-44%), and 2 functioning trajectories (Increasing-57%, Stable-moderate-43%) were identified. Early treatment response, particularly on negative symptoms, consistently and strongly predicted better outcome trajectories (OR = [3.4-5.5]). Trajectories of higher symptom severity were associated with trajectory of worse functioning (RR = [1.5-2.2]), which exhibited lower rates of clinical and functional remission.nnCONCLUSION: These findings offer insights into clinically meaningful subgroups of individuals that could inform the prognosis of FEP and the development of individually tailored EIS. Individuals who do not show early improvement in negative symptoms may benefit from earlier psychosocial interventions specifically targeting actionable factors that contribute to secondary negative symptoms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40231305b,

title = {Stable White Matter Structure in the First Three Years After Psychosis Onset},

author = {Peter C Van Dyken and Kun Yang and Andreia V Faria and Akira Sawa and Michael MacKinley and Ali R Khan and Lena Palaniyappan},

doi = {10.1016/j.bpsgos.2025.100472},

issn = {2667-1743},

year  = {2025},

date = {2025-05-01},

journal = {Biol Psychiatry Glob Open Sci},

volume = {5},

number = {3},

pages = {100472},

abstract = {BACKGROUND: White matter alterations observed using diffusion weighted imaging have become a hallmark of chronic schizophrenia, but it is unclear when these changes arise over the course of the disease. Nearly all studies reported to date have been cross-sectional, so despite their large sample sizes, they cannot determine whether changes accumulate as a degenerative process or patients with preexisting white matter damage are predisposed to more chronic forms of schizophrenia.nnMETHODS: We examined 160 scans comprising 2 years of annual follow-up data from 42 control participants and 28 patients with schizophrenia recruited in the first 2 years since their diagnosis, totaling 2 to 3 scans per participant. We also examined 6-month follow-up data obtained from an ultra-high field (7T) scanner (68 scans;  = 19 patients with first-episode schizophrenia,  = 15 control participants) as a validation dataset. A longitudinal model was used to compare the trajectory of diffusion tensor parameters in patients and control participants.nnRESULTS: Positive and negative symptom scores were correlated with diffusion parameters using region of interest-based approaches. No longitudinal differences between patients and control participants were observed for any diffusion tensor imaging parameter in either dataset. However, we did observe consistent associations between white matter alterations and negative symptoms in both datasets.nnCONCLUSIONS: White matter does not appear to be susceptible to schizophrenia-linked degeneration in the early stages of disease, but preexisting pathology may be linked to disease severity.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40202728b,

title = {Convergence of Cannabis and Psychosis on the Dopamine System},

author = {Jessica Ahrens and Sabrina D Ford and Betsy Schaefer and David Reese and Ali R Khan and Philip Tibbo and Rachel Rabin and Clifford M Cassidy and Lena Palaniyappan},

doi = {10.1001/jamapsychiatry.2025.0432},

issn = {2168-6238},

year  = {2025},

date = {2025-06-01},

journal = {JAMA Psychiatry},

volume = {82},

number = {6},

pages = {609--617},

abstract = {IMPORTANCE: Despite evidence that individuals with a cannabis use disorder (CUD) are at elevated risk of psychosis and that the neurotransmitter dopamine has a role in psychosis, the mechanism linking cannabis use and psychosis remains unclear.nnOBJECTIVE: To use neuromelanin-sensitive magnetic resonance imaging (MRI), referred to as the neuromelanin-MRI signal, a practical, proxy measure of dopamine function, to assess whether a common alteration in the dopamine system may be implicated in CUD and psychosis and whether this alteration can be observed in those with a CUD whether or not they have a diagnosis of first-episode schizophrenia (FES).nnDESIGN, SETTING, AND PARTICIPANTS: This longitudinal observational cohort study recruited individuals from 2019 to 2023 from an early psychosis service and the surrounding communities in London, Ontario. The sample included individuals with and without CUD, with some in each group also diagnosed with FES.nnEXPOSURES: FES and CUD diagnoses from the Structured Clinical Interview for DSM-5.nnMAIN OUTCOMES AND MEASURES: Neuromelanin-MRI signals within the midbrain (substantia nigra [SN]/ventral tegmental area [VTA]) including a subregion previously linked to the severity of untreated psychosis (a priori region of interest). Linear mixed-effects analyses were performed relating neuromelanin-MRI signals to clinical measures.nnRESULTS: A total of 36 individuals without CUD (mean [SD] age, 22.3 [3.2] years; 29 male [81%]; 12 with FES) and 25 individuals with CUD (mean [SD] age, 24.3 [4.7] years; 22 male [88%]; 16 with FES) participated in the study. One-year follow-up was completed for 12 individuals with CUD and 25 without CUD. CUD was associated with elevated neuromelanin-MRI signal in a set of ventral SN/VTA voxels (387 of 2060 SN/VTA voxels, corrected P = .03, permutation test). CUD was also associated with elevated neuromelanin-MRI signal in the psychosis-related region of interest (t92 = 2.12, P = .04) with a significant dose-dependent association (higher burden of CUD symptoms associated with higher neuromelanin-MRI signal, F1, 96 = 4.89; P = .03). In contrast, participants with FES did not exhibit a significant elevation in neuromelanin-MRI signal (241 SN/VTA voxels had elevated signal, corrected P = .09). There was no association between time and neuromelanin-MRI signal.nnCONCLUSIONS AND RELEVANCE: Elevated dopamine function in a critical SN/VTA subregion may be associated with psychosis risk in people with CUD. Cannabis was associated with the hypothesized final common pathway for the clinical expression of psychotic symptoms.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40157253b,

title = {Speaking of yourself: A meta-analysis of 80 years of research on pronoun use in schizophrenia},

author = {Dalia Elleuch and Yinhan Chen and Qiang Luo and Lena Palaniyappan},

doi = {10.1016/j.schres.2025.03.025},

issn = {1573-2509},

year  = {2025},

date = {2025-05-01},

journal = {Schizophr Res},

volume = {279},

pages = {22--30},

abstract = {People with schizophrenia experience significant language disturbances that profoundly affect their everyday social interactions. Given its relevance to the referential function of language, aberrations in pronoun use are of particular interest in the study of schizophrenia. This systematic review and meta-analysis, adhering to PRISMA guidelines, examines the frequency of pronoun use in schizophrenia. PubMed, PsycINFO, Scopus, Google Scholar, and Web of Science were searched up to May 1, 2024. All studies analyzing pronoun frequency in various spoken language contexts in schizophrenia were included. Bias was assessed using a modified Newcastle-Ottawa Scale. A Bayesian meta-analysis with model averaging estimated effect sizes and moderating factors. 13 studies with n = 917 unique participants and 13 case-control contrasts were included. 37.9 % of patient samples were women, with a weighted mean (SD) age of 34.45 (9.72) years. 53.85 % of the studies were in languages other than English. We report a medium-sized effect for first-person pronoun impairment in schizophrenia (model-averaged d = 0.89, 95 % CrI (0.44, 1.33)). There was significant heterogeneity moderated by age. Evidence for publication bias was weak, with a strong support for first-person pronoun impairment after accounting for bias and heterogeneity. There was a small reduction of inter-individual variability in first-person pronoun use in patients compared to healthy controls (lnCVR = -0.12, 95 % CrI [-0.35, -0.13]). While all pronoun use was also high in patients, this was not robust due to heterogeneity and publication bias. Individuals with schizophrenia excessively use first-person pronouns. This may be a marker of a disturbed sense of self in this illness.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40109883b,

title = {Seminal Contributions of Timothy J. Crow},

author = {Lena Palaniyappan and Peter F Liddle},

doi = {10.1017/S0033291725000182},

issn = {1469-8978},

year  = {2025},

date = {2025-03-01},

journal = {Psychol Med},

volume = {55},

pages = {e75},

abstract = {We recall the life and work of Timothy J. Crow, whose contributions provided great insights into the pathophysiology of schizophrenia and continue to shape many questions in the field. We compile his key works relating to psychotic disorders, focusing on the trajectory of his theoretical stance. Our account is interlaced with our own interpretation of the evidence that influenced Crow's arguments over the years as well as his scientific method. Crow has had a significant impact on the neuroscience of schizophrenia. Many of his observations are still valid and several questions he raised remain unanswered to date.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40097008b,

title = {Students in mental health crisis},

author = {Martin Sellier Silva and Irnes Zeljkovic and Lena Palaniyappan},

doi = {10.1503/cmaj.241439},

issn = {1488-2329},

year  = {2025},

date = {2025-03-01},

journal = {CMAJ},

volume = {197},

number = {10},

pages = {E272},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40044088b,

title = {Transcriptional substrates of cortical thickness alterations in anhedonia of major depressive disorder},

author = {Sugai Liang and Yuan Gao and Lena Palaniyappan and Xue-Mei Song and Tian Zhang and Jin-Fang Han and Zhong-Lin Tan and Tao Li},

doi = {10.1016/j.jad.2025.03.003},

issn = {1573-2517},

year  = {2025},

date = {2025-06-01},

journal = {J Affect Disord},

volume = {379},

pages = {118--126},

abstract = {BACKGROUND: Anhedonia is a core symptom of major depressive disorder (MDD), which has been shown to be associated with abnormalities in cortical morphology. However, the correlation between cortical thickness (CT) changes with anhedonia in MDD and gene expression remains unclear.nnMETHODS: We investigated the link between brain-wide gene expression and CT correlates of anhedonia in individuals with MDD, using 7 Tesla neuroimaging and a publicly available transcriptomic dataset. The interest-activity score was used to evaluation MDD with high anhedonia (HA) and low anhedonia (LA). Nineteen patients with HA, nineteen patients with LA, and twenty healthy controls (HC) were enrolled. We investigated CT alterations of anhedonia subgroups relative to HC and related cortical gene expression, enrichment and specific cell types. We further used Neurosynth and von Economo-Koskinas atlas to assess the meta-analytic cognitive functions and cytoarchitectural variation associated with anhedonia-related cortical changes.nnRESULTS: Both patient subgroups exhibited widespread CT reduction, with HA manifesting more pronounced changes. Gene expression related to anhedonia had significant spatial correlations with CT differences. Transcriptional signatures related to anhedonia-associated cortical thinning were connected to mitochondrial dysfunction and enriched in adipogenesis, oxidative phosphorylation, mTORC1 signaling pathways, involving neurons, astrocytes, and oligodendrocytes. These CT alterations were significantly correlated with meta-analytic terms involving somatosensory processing and pain perception. HA had reduced CT within the somatomotor and ventral attention networks, and in agranular cortical regions.nnLIMITATIONS: These include measuring anhedonia using interest-activity score and employing a cross-sectional design.nnCONCLUSIONS: This study sheds light on the molecular basis underlying gene expression associated with anhedonia in MDD, suggesting directions for targeted therapeutic interventions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40015076b,

title = {Commentary: Examining language and selfhood in hallucinations},

author = {Lena Palaniyappan and Oliver Delgaram-Nejad},

doi = {10.1016/j.schres.2025.02.014},

issn = {1573-2509},

year  = {2025},

date = {2025-03-01},

journal = {Schizophr Res},

volume = {277},

pages = {42--43},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39988244b,

title = {Cerebellum as a neural substrate for impoverishment in early psychosis},

author = {Eric Toyota and Michael Mackinley and Angelica M Silva and Yuchao Jiang and Tyler C Dalal and Caroline Nettekoven and Lena Palaniyappan},

doi = {10.1016/j.neuropsychologia.2025.109094},

issn = {1873-3514},

year  = {2025},

date = {2025-04-01},

journal = {Neuropsychologia},

volume = {210},

pages = {109094},

abstract = {BACKGROUND: Formal Thought Disorder and includes both positive (i.e., disorganized speech) and negative (i.e., impoverished speech) symptoms. Emerging evidence suggests that the cerebellum plays a critical role in cognitive functions, including language processing. This study leverages Natural Language Processing to objectively measure language disturbances in patients with first-episode psychosis and investigates the relationship between these disturbances and cerebellar structure.nnMETHODS: Fifty-four patients with schizophrenia, either drug-naïve or minimally medicated, were recruited from an early psychosis program. Impoverished thought was assessed using the Thought Language Index while lexico-semantic features (affect, cognitive, linguistic, perception, time) were identified from speech samples analyzed using the Linguistic Inquiry Word Count-22 software. Structural cerebellar analysis was completed on 7.0 Tesla MRI scans using voxel-based morphometry (VBM) to measure global and regional grey matter volume changes.nnRESULTS: Linear regression analysis revealed that reduced perceptual word usage was the strongest predictor of impoverished thinking. Correlational analysis identified reduced cerebellar volumes in patients with lower LIWC-based perception scores. VBM localized this relationship to a cluster in the right posterolateral cerebellar hemisphere, an area related to executive demand and verb generation function.nnCONCLUSION: The cerebellum contributes to impoverished thinking in early psychosis, likely by influencing the lexical expression of perceptual experiences. This underscores the cerebellum's role in higher-order cognitive processes relevant to psychotic disorders and its potential as a therapeutic target for language and cognitive deficits in schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39956789b,

title = {Quantitative natural language processing markers of psychoactive drug effects: A pre-registered systematic review},

author = {Sachin Ahuja and Farida Zaher and Lena Palaniyappan},

doi = {10.1177/02698811251319455},

issn = {1461-7285},

year  = {2025},

date = {2025-09-01},

journal = {J Psychopharmacol},

volume = {39},

number = {9},

pages = {940--949},

abstract = {Psychoactive substances used for recreational purposes have mind-altering effects, but systematic evaluation of these effects is largely limited to self-reports. Automated analysis of expressed language (speech and written text) using natural language processing (NLP) tools can provide objective readouts of mental states. In this pre-registered systematic review, we investigate findings from applying the emerging field of computational linguistics to substance use with specific focus on identifying short-term effects of psychoactive drugs. From the literature identified to date, we note that all the studied drugs - stimulants, 3,4-methylenedioxymethamphetamine (MDMA), cannabis, ketamine and psychedelics - affect language production. Based on two or more studies per substance, we note some emerging patterns: stimulants increase verbosity; lysergic acid diethylamide reduces the lexicon; MDMA increases semantic proximity to emotional words; psilocybin increases positive sentiment and cannabis affects speech stream acoustics. Ketamine and other drugs are understudied regarding NLP features (one or no studies). One study provided externally validated support for NLP and machine learning-based identification of MDMA intoxication. We could not undertake a meta-analysis due to the high degree of heterogeneity among outcome measures and the lack of sufficient number of studies. We identify a need for harmonised speech tasks to improve replicability and comparability, standardisation of methods for curating and analysing speech and text data, theory-driven inquiries and the need for developing a shared 'substance use language corpus' for data mining. The growing field of computational linguistics can be utilized to advance human behavioral pharmacology of psychoactive substances. Achieving this will require concerted efforts towards consistency in research methods.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39843416b,

title = {Neuroimaging stratification reveals the striatal vulnerability to stress as a risk for schizophrenia},

author = {Xiaoqian Ma and Nana Feng and Lena Palaniyappan and Luolong Cao and Zixin Gu and Jujiao Kang and Liu Yuan and Lijun Ouyang and Yujue Wang and Chunwang Li and Ke Jin and Xiaogang Chen and Jianfeng Feng and Ying He and Qiang Luo},

doi = {10.1038/s41398-025-03237-2},

issn = {2158-3188},

year  = {2025},

date = {2025-01-01},

journal = {Transl Psychiatry},

volume = {15},

number = {1},

pages = {18},

abstract = {The striatum, a core brain structure relevant for schizophrenia, exhibits heterogeneous volumetric changes in this illness. Due to this heterogeneity, its role in the risk of developing schizophrenia following exposure to environmental stress remains poorly understood. Using the putamen (a subnucleus of the striatum) as an indicator for convergent genetic risk of schizophrenia, 63 unaffected first-degree relatives of patients (22.08 ± 4.80 years) with schizophrenia (UFR-SZ) were stratified into two groups. Compared with healthy controls (HC; n = 59), voxel-based and brain-wide volumetric changes and their associations with stressful life events (SLE) were tested. These stratified associations were validated using two large population-based cohorts (the ABCD study; n = 1680, 11.92 ± 0.62 years; and UK Biobank, n = 20547, 55.38 ± 7.43 years). Transcriptomic analysis of brain tissues was used to identify the biological processes associated with the brain mediation effects on the SLE-psychosis relationship. The stratified UFR-SZ subgroup with smaller right putamen had a smaller volume in the left caudate when compared to HC; this caudate volume was associated with both a higher level of SLE and more psychotic symptoms. This caudate-SLE association was replicated in two independent large-scale cohorts, when individuals were stratified by both a higher polygenic burden for schizophrenia and smaller right putamen. In UFR-SZ, the caudate cluster mediated the relationship between SLE and more psychotic symptoms. This mediation was associated with the genes enriched in both glutamatergic synapses and response to oxidative stress. The stratified association between the striatum and stress highlights the differential vulnerability to stress, contributing to the complexity of the gene-by-environment etiology of schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39787740b,

title = {Exploring delusional themes and other symptoms in first episode psychosis: A network analysis over two timepoints},

author = {Fjolla Berisha and Vincent Paquin and Ian Gold and Bratislav Misic and Lena Palaniyappan and Ashok Malla and Srividya Iyer and Ridha Joober and Martin Lepage and Jai Shah},

doi = {10.1016/j.psychres.2024.116349},

issn = {1872-7123},

year  = {2025},

date = {2025-02-01},

journal = {Psychiatry Res},

volume = {344},

pages = {116349},

abstract = {Delusions are a defining feature of psychosis and play an important role in the conceptualization and diagnosis of psychotic disorders; however, the particular role that different delusions play in the prognosis of these disorders is not well understood. This study explored relationships between delusions and other symptoms in 674 first episode psychosis (FEP) individuals by comparing symptom networks between baseline and 12 months after intake to an early intervention service. Specifically, we (1) estimated regularized partial correlation networks at baseline and month 12, (2) identified the most central symptoms in each network, (3) identified clusters of highly connected symptoms, and (4) compared networks to examine changes in structure and connectivity. At baseline, the most central symptoms were depression, delusions of mind reading, and delusions of thought insertion. At month 12, they were hallucinations, persecutory delusions, and delusions of thought insertion. A symptom cluster was identified at both timepoints comprising of five delusions corresponding to passivity experiences. While network structures did not differ significantly, the month 12 network was significantly more highly connected. Our study captures a shift in illness trajectory over time, wherein transdiagnostic symptomatology at baseline becomes more consolidated around psychotic symptoms by month 12.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39763421b,

title = {Aberrant controllability of functional connectome during working memory tasks in patients with schizophrenia and unaffected siblings},

author = {Feiwen Wang and Zhening Liu and Ju Wang and Xiao Li and Yunzhi Pan and Jun Yang and Peng Cheng and Fuping Sun and Wenjian Tan and Danqing Huang and Jiamei Zhang and Xiawei Liu and Maoxing Zhong and Guowei Wu and Jie Yang and Lena Palaniyappan},

doi = {10.1192/bjp.2024.225},

issn = {1472-1465},

year  = {2025},

date = {2025-07-01},

journal = {Br J Psychiatry},

volume = {227},

number = {1},

pages = {463--472},

abstract = {BACKGROUND: Working memory deficit, a key feature of schizophrenia, is a heritable trait shared with unaffected siblings. It can be attributed to dysregulation in transitions from one brain state to another.nnAIMS: Using network control theory, we evaluate if defective brain state transitions underlie working memory deficits in schizophrenia.nnMETHOD: We examined average and modal controllability of the brain's functional connectome in 161 patients with schizophrenia, 37 unaffected siblings and 96 healthy controls during a two-back task. We use one-way analysis of variance to detect the regions with group differences, and correlated aberrant controllability to task performance and clinical characteristics. Regions affected in both unaffected siblings and patients were selected for gene and functional annotation analysis.nnRESULTS: Both average and modal controllability during the two-back task are reduced in patients compared to healthy controls and siblings, indicating a disruption in both proximal and distal state transitions. Among patients, reduced average controllability was prominent in auditory, visual and sensorimotor networks. Reduced modal controllability was prominent in default mode, frontoparietal and salience networks. Lower modal controllability in the affected networks correlated with worse task performance and higher antipsychotic dose in schizophrenia (uncorrected). Both siblings and patients had reduced average controllability in the paracentral lobule and Rolandic operculum. Subsequent out-of-sample gene analysis revealed that these two regions had preferential expression of genes relevant to bioenergetic pathways (calmodulin binding and insulin secretion).nnCONCLUSIONS: Aberrant control of brain state transitions during task execution marks working memory deficits in patients and their siblings.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39547922b,

title = {CYP2D6 and CYP2C19 ultrarapid metabolisms are associated with suicide attempts in schizophrenia},

author = {Théo Korchia and Melanie Faugere and Maud Tastevin and Sylvie Quaranta and Romain Guilhaumou and Olivier Blin and Aurélie Lereclus and Ridha Joober and Jai Shah and Lena Palaniyappan and Christophe Lançon and Guillaume Fond and Raphaëlle Richieri},

doi = {10.1016/j.encep.2024.09.003},

issn = {0013-7006},

year  = {2025},

date = {2025-08-01},

journal = {Encephale},

volume = {51},

number = {4},

pages = {418--423},

abstract = {INTRODUCTION: Genetic polymorphisms in genes encoding enzymes metabolizing psychotropics drugs result in various isoenzymes with different catalytic efficacies. Of particular interest, some of these isoenzymes are highly catalytic leading to an ultrarapid metabolism (UM) of their substrate medication, which in turn results in lower medication concentrations and possibly poor clinical outcomes, including a higher risk for suicidal behavior. In this study, we investigate the role of CYP2D6 (metabolizing most antidepressant medications) and CYP2C19 (important in metabolizing antipsychotics) UM isoenzymes on suicidal behavior among a cohort of patients with schizophrenia.nnMETHODS: One hundred and seventy-eight patients diagnosed with schizophrenia were recruited from the day hospital of a regional psychiatric academic hospital. Lifetime suicide attempts were compared between groups of patients stratified according to their enzymatic profile. Several socio-demographics and clinical covariates were controlled for.nnRESULTS: Among the 178 patients, 16 and 44 were UM as determined by their CYP2D6 and CYP2C19 genotype respectively. Univariate analysis showed a significant association between suicidal attempts and CYP2D6 and CYP2C19 UM status (P=0.041 and P=0.029 respectively). These associations remained significant in multivariate analyses (adjusted for age, sex, dose exposure and antidepressant use…) for both CYP2D6 (P=0.020, OR=4.096, 95% CI [1.25-13.48]) and CYP2C19 (P=0.016, OR=2.680, 95% CI [1.21-5.95]).nnCONCLUSION: This study suggests that the UM phenotypes for both CYP2D6 and CYP2C19 are associated with an increased risk for suicide attempts in patients with schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39523517b,

title = {Brain Age Gap as a Predictor of Early Treatment Response and Functional Outcomes in First-Episode Schizophrenia: A Longitudinal Study: L'écart d'âge cérébral comme prédicteur de la réponse en début de traitement et des résultats fonctionnels dans un premier épisode de schizophrénie : une étude longitudinale},

author = {Lejia Fan and Zhenmei Zhang and Xiaoqian Ma and Liangbing Liang and Liu Yuan and Lijun Ouyang and Yujue Wang and Zongchang Li and Xiaogang Chen and Ying He and Lena Palaniyappan},

doi = {10.1177/07067437241293981},

issn = {1497-0015},

year  = {2025},

date = {2025-03-01},

journal = {Can J Psychiatry},

volume = {70},

number = {3},

pages = {240--250},

abstract = {OBJECTIVES: Accelerated brain aging, i.e., the age-related structural changes in the brain appearing earlier than expected from one's chronological age, is a feature that is now well established in schizophrenia. Often interpreted as a feature of a progressive pathophysiological process that typifies schizophrenia, its prognostic relevance is still unclear. We investigate its role in response to antipsychotic treatment in first-episode schizophrenia.nnMETHODS: We recruited 49 drug-naive patients with schizophrenia who were then treated with risperidone at a standard dose range of 2-6 mg/day. We followed them up for 3 months to categorize their response status. We acquired T1-weighted anatomical images and used the XGboost method to evaluate individual brain age. The brain age gap (BAG) is the difference between the predicted brain age and chronological age.nnRESULTS: Patients with FES had more pronounced BAG compared to healthy subjects, and this difference was primarily driven by those who did not respond adequately after 12 weeks of treatment. BAG did not worsen significantly over the 12-week period, indicating a lack of prominent brain-ageing effect induced by the early antipsychotic exposure per se. However, highly symptomatic patients had a more prominent increase in BAG, while patients with higher BAG when initiating treatment later showed lower gains in global functioning upon treatment, highlighting the prognostic value of BAG measures in FES.nnCONCLUSIONS: Accelerated brain aging is a feature of first-episode schizophrenia that is more likely to be seen among those who will not respond adequately to first-line antipsychotic use. Given that early poor response indicates later treatment resistance, measuring BAG using structural MRI in the first 12 weeks of treatment initiation may provide useful prognostic information when considering second-line treatments in schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38600593b,

title = {Speech based natural language profile before, during and after the onset of psychosis: A cluster analysis},

author = {Tyler C Dalal and Liangbing Liang and Angelica M Silva and Michael Mackinley and Alban Voppel and Lena Palaniyappan},

doi = {10.1111/acps.13685},

issn = {1600-0447},

year  = {2025},

date = {2025-03-01},

journal = {Acta Psychiatr Scand},

volume = {151},

number = {3},

pages = {332--347},

abstract = {BACKGROUND AND HYPOTHESIS: Speech markers are digitally acquired, computationally derived, quantifiable set of measures that reflect the state of neurocognitive processes relevant for social functioning. "Oddities" in language and communication have historically been seen as a core feature of schizophrenia. The application of natural language processing (NLP) to speech samples can elucidate even the most subtle deviations in language. We aim to determine if NLP based profiles that are distinctive of schizophrenia can be observed across the various clinical phases of psychosis.nnDESIGN: Our sample consisted of 147 participants and included 39 healthy controls (HC), 72 with first-episode psychosis (FEP), 18 in a clinical high-risk state (CHR), 18 with schizophrenia (SZ). A structured task elicited 3 minutes of speech, which was then transformed into quantitative measures on 12 linguistic variables (lexical, syntactic, and semantic). Cluster analysis that leveraged healthy variations was then applied to determine language-based subgroups.nnRESULTS: We observed a three-cluster solution. The largest cluster included most HC and the majority of patients, indicating a 'typical linguistic profile (TLP)'. One of the atypical clusters had notably high semantic similarity in word choices with less perceptual words, lower cohesion and analytical structure; this cluster was almost entirely composed of patients in early stages of psychosis (EPP - early phase profile). The second atypical cluster had more patients with established schizophrenia (SPP - stable phase profile), with more perceptual but less cognitive/emotional word classes, simpler syntactic structure, and a lack of sufficient reference to prior information (reduced givenness).nnCONCLUSION: The patterns of speech deviations in early and established stages of schizophrenia are distinguishable from each other and detectable when lexical, semantic and syntactic aspects are assessed in the pursuit of 'formal thought disorder'.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35644706,

title = {Cortical impoverishment in a stable subgroup of schizophrenia: Validation across various stages of psychosis},

author = {Liangbing Liang and R Walter Heinrichs and Peter F Liddle and Peter Jeon and Jean Théberge and Lena Palaniyappan},

doi = {10.1016/j.schres.2022.05.013},

issn = {1573-2509},

year  = {2024},

date = {2024-02-01},

journal = {Schizophr Res},

volume = {264},

pages = {567--577},

abstract = {BACKGROUND: Cortical thinning is a well-known feature in schizophrenia. The considerable variation in the spatial distribution of thickness changes has been used to parse heterogeneity. A 'cortical impoverishment' subgroup with a generalized reduction in thickness has been reported. However, it is unclear if this subgroup is recoverable irrespective of illness stage, and if it relates to the glutamate hypothesis of schizophrenia.nnMETHODS: We applied hierarchical cluster analysis to cortical thickness data from magnetic resonance imaging scans of three datasets in different stages of psychosis (n = 288; 160 patients; 128 healthy controls) and studied the cognitive and symptom profiles of the observed subgroups. In one of the samples, we also studied the subgroup differences in 7-Tesla magnetic resonance spectroscopy glutamate concentration in the dorsal anterior cingulate cortex.nnRESULTS: Our consensus-based clustering procedure consistently produced 2 subgroups of participants. Patients accounted for 75%-100% of participants in one subgroup that was characterized by significantly lower cortical thickness. Both subgroups were equally symptomatic in clinically unstable stages, but cortical impoverishment indicated a higher symptom burden in a clinically stable sample and higher glutamate levels in the first-episode sample. There were no subgroup differences in cognitive and functional outcome profiles or antipsychotic exposure across all stages.nnCONCLUSIONS: Cortical thinning does not vary with functioning or cognitive impairment, but it is more prevalent among patients, especially those with glutamate excess in early stages and higher residual symptom burden at later stages, providing an important mechanistic clue to one of the several possible pathways to the illness.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid40800408b,

title = {Imaging of the superficial white matter in health and disease},

author = {Peter C Van Dyken and Ali R Khan and Lena Palaniyappan},

doi = {10.1162/imag_a_00221},

issn = {2837-6056},

year  = {2024},

date = {2024-01-01},

journal = {Imaging Neurosci (Camb)},

volume = {2},

abstract = {The superficial white matter, the layer of white matter immediately deep to the cortical grey matter, is a highly complex, heterogeneous tissue region comprising dense meshes of neural fibres, a robust population of interstitial neurons, and ongoing glial activity and myelination. It originates from the histologically distinct, developmentally vital subplate in the foetal brain, maintains thalamo-cortical connections throughout adult life, and is a necessary passage for all axons passing between the grey and white matter. Despite these features, the superficial white matter is among the most poorly understood regions of the brain, in part due to its complex makeup and the resulting difficulty of its study. In this review, we present our current knowledge of superficial white matter (SWM) anatomy, development, and response to disease. We discuss the unique challenges encountered in the neuroimaging of this region, including the lack of standard definition and the non-specificity of neuroimaging markers amplified by the complexity of the tissue. We discuss recent innovations and offer potential pathways forward.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39552391b,

title = {Regional neural functional efficiency across schizophrenia, bipolar disorder, and major depressive disorder: a transdiagnostic resting-state fMRI study},

author = {Jun Yang and Zhening Liu and Yunzhi Pan and Zebin Fan and Yixin Cheng and Feiwen Wang and Fuping Sun and Guowei Wu and Xuan Ouyang and Haojuan Tao and Jie Yang and Lena Palaniyappan},

doi = {10.1017/S0033291724001685},

issn = {1469-8978},

year  = {2024},

date = {2024-11-01},

journal = {Psychol Med},

volume = {54},

number = {15},

pages = {4083--4094},

abstract = {BACKGROUND: Major psychiatric disorders (MPDs) are delineated by distinct clinical features. However, overlapping symptoms and transdiagnostic effectiveness of medications have challenged the traditional diagnostic categorisation. We investigate if there are shared and illness-specific disruptions in the regional functional efficiency (RFE) of the brain across these disorders.nnMETHODS: We included 364 participants (118 schizophrenia [SCZ], 80 bipolar disorder [BD], 91 major depressive disorder [MDD], and 75 healthy controls [HCs]). Resting-state fMRI was used to caclulate the RFE based on the static amplitude of low-frequency fluctuation, regional homogeneity, and degree centrality and corresponding dynamic measures indicating variability over time. We used principal component analysis to obtain static and dynamic RFE values. We conducted functional and genetic annotation and enrichment analysis based on abnormal RFE profiles.nnRESULTS: SCZ showed higher static RFE in the cortico-striatal regions and excessive variability in the cortico-limbic regions. SCZ and MDD shared lower static RFE with higher dynamic RFE in sensorimotor regions than BD and HCs. We observed association between static RFE abnormalities with reward and sensorimotor functions and dynamic RFE abnormalities with sensorimotor functions. Differential spatial expression of genes related to glutamatergic synapse and calcium/cAMP signaling was more likely in the regions with aberrant RFE.nnCONCLUSIONS: SCZ shares more regions with disrupted functional integrity, especially in sensorimotor regions, with MDD rather than BD. The neural patterns of these transdiagnostic changes appear to be potentially driven by gene expression variations relating to glutamatergic synapses and calcium/cAMP signaling. The aberrant sensorimotor, cortico-striatal, and cortico-limbic integrity may collectively underlie neurobiological mechanisms of MPDs.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39542650b,

title = {Glutamate levels and symptom burden in high-risk and first-episode schizophrenia: a dual-voxel study of the anterior cingulate cortex},

author = {Lejia Fan and Zhenmei Zhang and Xiaoqian Ma and Liangbing Liang and Yujue Wang and Liu Yuan and Lijun Ouyang and Zongchang Li and Xiaogang Chen and Ying He and Lena Palaniyappan},

doi = {10.1503/jpn.240094},

issn = {1488-2434},

year  = {2024},

date = {2024-01-01},

journal = {J Psychiatry Neurosci},

volume = {49},

number = {6},

pages = {E367--E376},

abstract = {BACKGROUND: Reduced glutamatergic excitability of the anterior cingulate cortex (ACC) has been long suspected in schizophrenia; recent observations support low glutamatergic tone as the primary pathophysiology contributing to subtle early features of this illness, with a secondary disinhibition (higher glutamate tone) resulting in more prominent clinical symptoms later in its course. We sought to investigate whether people with genetic high risk (GHR) for schizophrenia have lower glutamate levels in the ACC than those at later stages of clinical high risk (CHR) and those with first-episode schizophrenia (FES), among whom symptoms are already prominent.nnMETHODS: We recruited people with CHR, GHR, or FES, as well as healthy controls. Using proton magnetic resonance spectroscopy, we determined glutamate levels in the perigenual ACC (pACC) and dorsal ACC (dACC) using a 3 T scanner.nnRESULTS: We recruited 302 people across multiple stages of psychosis, including 63 with CHR, 76 with GHR, and 96 with FES, as well as 67 healthy controls. Those with GHR had lower glutamate levels in the dACC than those with CHR, while those with CHR had higher glutamate levels in the pACC than those with FES. Higher disorganization, but not any other symptom domain, was associated with lower levels of glutamate in the GHR group (dACC and pACC) and in the CHR group (pACC).nnLIMITATIONS: The cross-sectional design precluded inferences regarding individual clinical trajectory and resolution at 3 T was insufficient to separate spectra of glutamine from glutamate.nnCONCLUSION: Reduced glutamatergic tone among people genetically predisposed to schizophrenia supports diminished excitability as an early feature of schizophrenia, contributing to the subtle symptom of disorganization across high-risk states. Higher glutamate levels become apparent when psychotic symptoms become prominent, possibly as a disinhibitory effect and, at the full-blown stage of psychosis, the relationship between glutamate concentrations and symptoms ceases to be simply linear.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39301700b,

title = {Changes in the structure of spontaneous speech predict the disruption of hierarchical brain organization in first-episode psychosis},

author = {Rui He and Maria Francisca Alonso-Sánchez and Jorge Sepulcre and Lena Palaniyappan and Wolfram Hinzen},

doi = {10.1002/hbm.70030},

issn = {1097-0193},

year  = {2024},

date = {2024-10-01},

journal = {Hum Brain Mapp},

volume = {45},

number = {14},

pages = {e70030},

abstract = {Psychosis implicates changes across a broad range of cognitive functions. These functions are cortically organized in the form of a hierarchy ranging from primary sensorimotor (unimodal) to higher-order association cortices, which involve functions such as language (transmodal). Language has long been documented as undergoing structural changes in psychosis. We hypothesized that these changes as revealed in spontaneous speech patterns may act as readouts of alterations in the configuration of this unimodal-to-transmodal axis of cortical organization in psychosis. Results from 29 patients with first-episodic psychosis (FEP) and 29 controls scanned with 7 T resting-state fMRI confirmed a compression of the cortical hierarchy in FEP, which affected metrics of the hierarchical distance between the sensorimotor and default mode networks, and of the hierarchical organization within the semantic network. These organizational changes were predicted by graphs representing semantic and syntactic associations between meaningful units in speech produced during picture descriptions. These findings unite psychosis, language, and the cortical hierarchy in a single conceptual scheme, which helps to situate language within the neurocognition of psychosis and opens the clinical prospect for mental dysfunction to become computationally measurable in spontaneous speech.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39144115b,

title = {Cortical Network Disruption Is Minimal in Early Stages of Psychosis},

author = {Peter C Van Dyken and Michael MacKinley and Ali R Khan and Lena Palaniyappan},

doi = {10.1093/schizbullopen/sgae010},

issn = {2632-7899},

year  = {2024},

date = {2024-01-01},

journal = {Schizophr Bull Open},

volume = {5},

number = {1},

pages = {sgae010},

abstract = {BACKGROUND AND HYPOTHESIS: Schizophrenia is associated with white matter disruption and topological reorganization of cortical connectivity but the trajectory of these changes, from the first psychotic episode to established illness, is poorly understood. Current studies in first-episode psychosis (FEP) patients using diffusion magnetic resonance imaging (dMRI) suggest such disruption may be detectable at the onset of psychosis, but specific results vary widely, and few reports have contextualized their findings with direct comparison to young adults with established illness.nnSTUDY DESIGN: Diffusion and T1-weighted 7T MR scans were obtained from  = 112 individuals (58 with untreated FEP, 17 with established schizophrenia, 37 healthy controls) recruited from London, Ontario. Voxel- and network-based analyses were used to detect changes in diffusion microstructural parameters. Graph theory metrics were used to probe changes in the cortical network hierarchy and to assess the vulnerability of hub regions to disruption. The analysis was replicated with  = 111 (57 patients, 54 controls) from the Human Connectome Project-Early Psychosis (HCP-EP) dataset.nnSTUDY RESULTS: Widespread microstructural changes were found in people with established illness, but changes in FEP patients were minimal. Unlike the established illness group, no appreciable topological changes in the cortical network were observed in FEP patients. These results were replicated in the early psychosis patients of the HCP-EP datasets, which were indistinguishable from controls in most metrics.nnCONCLUSIONS: The white matter structural changes observed in established schizophrenia are not a prominent feature in the early stages of this illness.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39129270b,

title = {Association of cortical morphology, white matter hyperintensity, and glymphatic function in frontotemporal dementia variants},

author = {Die Xiao and Jianyu Li and Zhanbing Ren and Minghui Dai and Yihan Jiang and Ting Qiu and Huixiong Zhang and Yifan Chen and Youming Zhang and Yuanchao Zhang and Lena Palaniyappan and },

doi = {10.1002/alz.14158},

issn = {1552-5279},

year  = {2024},

date = {2024-09-01},

journal = {Alzheimers Dement},

volume = {20},

number = {9},

pages = {6045--6059},

abstract = {INTRODUCTION: Frontotemporal dementia (FTD) can be phenotypically divided into behavioral variant FTD (bvFTD), nonfluent variant primary progressive aphasia (nfvPPA), and semantic variant PPA (svPPA). However, the neural underpinnings of this phenotypic heterogeneity remain elusive.nnMETHODS: Cortical morphology, white matter hyperintensities (WMH), diffusion tensor image analysis along the perivascular space (DTI-ALPS), and their interrelationships were assessed in subtypes of FTD. Neuroimaging-transcriptional analyses on the regional cortical morphological deviances among subtypes were also performed.nnRESULTS: Changes in cortical thickness, surface area, gyrification, WMH, and DTI-ALPS were subtype-specific in FTD. The three morphologic indices are related to whole-brain WMH volume and cognitive performance, while cortical thickness is related to DTI-ALPS. Neuroimaging-transcriptional analyses identified key biological pathways linked to the formation and/or spread of TDP-43/tau pathologies.nnDISCUSSION: We found subtype-specific changes in cortical morphology, WMH, and glymphatic function in FTD. Our findings have the potential to contribute to the development of personalized predictions and treatment strategies for this disorder.nnHIGHLIGHTS: Cortical morphologic changes, white matter hyperintensities (WMH), and glymphatic dysfunction are subtype-specific. Cortical morphologic changes, WMH, and glymphatic dysfunction are inter-correlated. Cortical morphologic changes and WMH burden contribute to cognitive impairments.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39122409b,

title = {Perplexity of utterances in untreated first-episode psychosis: an ultra-high field MRI dynamic causal modelling study of the semantic network},

author = {Maria Francisca Alonso-Sánchez and Wolfram Hinzen and Rui He and Joseph Gati and Lena Palaniyappan},

doi = {10.1503/jpn.240031},

issn = {1488-2434},

year  = {2024},

date = {2024-01-01},

journal = {J Psychiatry Neurosci},

volume = {49},

number = {4},

pages = {E252--E262},

abstract = {BACKGROUND: Psychosis involves a distortion of thought content, which is partly reflected in anomalous ways in which words are semantically connected into utterances in speech. We sought to explore how these linguistic anomalies are realized through putative circuit-level abnormalities in the brain's semantic network.nnMETHODS: Using a computational large-language model, Bidirectional Encoder Representations from Transformers (BERT), we quantified the contextual expectedness of a given word sequence (perplexity) across 180 samples obtained from descriptions of 3 pictures by patients with first-episode schizophrenia (FES) and controls matched for age, parental social status, and sex, scanned with 7 T ultra-high field functional magnetic resonance imaging (fMRI). Subsequently, perplexity was used to parametrize a spectral dynamic causal model (DCM) of the effective connectivity within (intrinsic) and between (extrinsic) 4 key regions of the semantic network at rest, namely the anterior temporal lobe, the inferior frontal gyrus (IFG), the posterior middle temporal gyrus (MTG), and the angular gyrus.nnRESULTS: We included 60 participants, including 30 patients with FES and 30 controls. We observed higher perplexity in the FES group, indicating that speech was less predictable by the preceding context among patients. Results of Bayesian model comparisons showed that a DCM including the group by perplexity interaction best explained the underlying patterns of neural activity. We observed an increase of self-inhibitory effective connectivity within the IFG, as well as reduced self-inhibitory tone within the pMTG, in the FES group. An increase in self-inhibitory tone in the IFG correlated strongly and positively with inter-regional excitation between the IFG and posterior MTG, while self-inhibition of the posterior MTG was negatively correlated with this interregional excitation.nnLIMITATION: Our design did not address connectivity in the semantic network during tasks that selectively activated the semantic network, which could corroborate findings from this resting-state fMRI study. Furthermore, we do not present a replication study, which would ideally use speech in a different language.nnCONCLUSION: As an explanation for peculiar speech in psychosis, these results index a shift in the excitatory-inhibitory balance regulating information flow across the semantic network, confined to 2 regions that were previously linked specifically to the executive control of meaning. Based on our approach of combining a large language model with causal connectivity estimates, we propose loss in semantic control as a potential neurocognitive mechanism contributing to disorganization in psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39013848b,

title = {Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm},

author = {Yuchao Jiang and Cheng Luo and Jijun Wang and Lena Palaniyappan and Xiao Chang and Shitong Xiang and Jie Zhang and Mingjun Duan and Huan Huang and Christian Gaser and Kiyotaka Nemoto and Kenichiro Miura and Ryota Hashimoto and Lars T Westlye and Genevieve Richard and Sara Fernandez-Cabello and Nadine Parker and Ole A Andreassen and Tilo Kircher and Igor Nenadić and Frederike Stein and Florian Thomas-Odenthal and Lea Teutenberg and Paula Usemann and Udo Dannlowski and Tim Hahn and Dominik Grotegerd and Susanne Meinert and Rebekka Lencer and Yingying Tang and Tianhong Zhang and Chunbo Li and Weihua Yue and Yuyanan Zhang and Xin Yu and Enpeng Zhou and Ching-Po Lin and Shih-Jen Tsai and Amanda L Rodrigue and David Glahn and Godfrey Pearlson and John Blangero and Andriana Karuk and Edith Pomarol-Clotet and Raymond Salvador and Paola Fuentes-Claramonte and María Ángeles Garcia-León and Gianfranco Spalletta and Fabrizio Piras and Daniela Vecchio and Nerisa Banaj and Jingliang Cheng and Zhening Liu and Jie Yang and Ali Saffet Gonul and Ozgul Uslu and Birce Begum Burhanoglu and Aslihan Uyar Demir and Kelly Rootes-Murdy and Vince D Calhoun and Kang Sim and Melissa Green and Yann Quidé and Young Chul Chung and Woo-Sung Kim and Scott R Sponheim and Caroline Demro and Ian S Ramsay and Felice Iasevoli and Andrea de Bartolomeis and Annarita Barone and Mariateresa Ciccarelli and Arturo Brunetti and Sirio Cocozza and Giuseppe Pontillo and Mario Tranfa and Min Tae M Park and Matthias Kirschner and Foivos Georgiadis and Stefan Kaiser and Tamsyn E Van Rheenen and Susan L Rossell and Matthew Hughes and William Woods and Sean P Carruthers and Philip Sumner and Elysha Ringin and Filip Spaniel and Antonin Skoch and David Tomecek and Philipp Homan and Stephanie Homan and Wolfgang Omlor and Giacomo Cecere and Dana D Nguyen and Adrian Preda and Sophia I Thomopoulos and Neda Jahanshad and Long-Biao Cui and Dezhong Yao and Paul M Thompson and Jessica A Turner and Theo G M van Erp and Wei Cheng and  and Jianfeng Feng and },

doi = {10.1038/s41467-024-50267-3},

issn = {2041-1723},

year  = {2024},

date = {2024-07-01},

journal = {Nat Commun},

volume = {15},

number = {1},

pages = {5996},

abstract = {Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38865456b,

title = {Neuroimaging epicenters as potential sites of onset of the neuroanatomical pathology in schizophrenia},

author = {Yuchao Jiang and Lena Palaniyappan and Cheng Luo and Xiao Chang and Jie Zhang and Yingying Tang and Tianhong Zhang and Chunbo Li and Enpeng Zhou and Xin Yu and Wei Li and Dongmei An and Dong Zhou and Chu-Chung Huang and Shih-Jen Tsai and Ching-Po Lin and Jingliang Cheng and Jijun Wang and Dezhong Yao and Wei Cheng and Jianfeng Feng and },

doi = {10.1126/sciadv.adk6063},

issn = {2375-2548},

year  = {2024},

date = {2024-06-01},

journal = {Sci Adv},

volume = {10},

number = {24},

pages = {eadk6063},

abstract = {Schizophrenia lacks a clear definition at the neuroanatomical level, capturing the sites of origin and progress of this disorder. Using a network-theory approach called epicenter mapping on cross-sectional magnetic resonance imaging from 1124 individuals with schizophrenia, we identified the most likely "source of origin" of the structural pathology. Our results suggest that the Broca's area and adjacent frontoinsular cortex may be the epicenters of neuroanatomical pathophysiology in schizophrenia. These epicenters can predict an individual's response to treatment for psychosis. In addition, cross-diagnostic similarities based on epicenter mapping over of 4000 individuals diagnosed with neurological, neurodevelopmental, or psychiatric disorders appear to be limited. When present, these similarities are restricted to bipolar disorder, major depressive disorder, and obsessive-compulsive disorder. We provide a comprehensive framework linking schizophrenia-specific epicenters to multiple levels of neurobiology, including cognitive processes, neurotransmitter receptors and transporters, and human brain gene expression. Epicenter mapping may be a reliable tool for identifying the potential onset sites of neural pathophysiology in schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38796480b,

title = {Neuronal activation sequences in lateral prefrontal cortex encode visuospatial working memory during virtual navigation},

author = {Alexandra Busch and Megan Roussy and Rogelio Luna and Matthew L Leavitt and Maryam H Mofrad and Roberto A Gulli and Benjamin Corrigan and Ján Mináč and Adam J Sachs and Lena Palaniyappan and Lyle Muller and Julio C Martinez-Trujillo},

doi = {10.1038/s41467-024-48664-9},

issn = {2041-1723},

year  = {2024},

date = {2024-05-01},

journal = {Nat Commun},

volume = {15},

number = {1},

pages = {4471},

abstract = {Working memory (WM) is the ability to maintain and manipulate information 'in mind'. The neural codes underlying WM have been a matter of debate. We simultaneously recorded the activity of hundreds of neurons in the lateral prefrontal cortex of male macaque monkeys during a visuospatial WM task that required navigation in a virtual 3D environment. Here, we demonstrate distinct neuronal activation sequences (NASs) that encode remembered target locations in the virtual environment. This NAS code outperformed the persistent firing code for remembered locations during the virtual reality task, but not during a classical WM task using stationary stimuli and constraining eye movements. Finally, blocking NMDA receptors using low doses of ketamine deteriorated the NAS code and behavioral performance selectively during the WM task. These results reveal the versatility and adaptability of neural codes supporting working memory function in the primate lateral prefrontal cortex.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38775087b,

title = {Lost in translation? Deciphering the role of language differences in the excess risk of psychosis among migrant groups},

author = {Kelly K Anderson and Jahin Ali Khan and Jordan Edwards and Britney Le and Giuseppe Longobardi and Ivan Witt and María Francisca Alonso-Sánchez and Lena Palaniyappan},

doi = {10.1017/S003329172400117X},

issn = {1469-8978},

year  = {2024},

date = {2024-08-01},

journal = {Psychol Med},

volume = {54},

number = {11},

pages = {3063--3070},

abstract = {BACKGROUND: Migration is a well-established risk factor for psychotic disorders, and migrant language has been proposed as a novel factor that may improve our understanding of this relationship. Our objective was to explore the association between indicators of linguistic distance and the risk of psychotic disorders among first-generation migrant groups.nnMETHODS: Using linked health administrative data, we constructed a retrospective cohort of first-generation migrants to Ontario over a 20-year period (1992-2011). Linguistic distance of the first language was categorized using several approaches, including language family classifications, estimated acquisition time, syntax-based distance scores, and lexical-based distance scores. Incident cases of non-affective psychotic disorder were identified over a 5- to 25-year period. We used Poisson regression to estimate incidence rate ratios (IRR) for each language variable, after adjustment for knowledge of English at arrival and other factors.nnRESULTS: Our cohort included 1 863 803 first-generation migrants. Migrants whose first language was in a different language family than English had higher rates of psychotic disorders (IRR = 1.08, 95% CI 1.01-1.16), relative to those whose first language was English. Similarly, migrants in the highest quintile of linguistic distance based on lexical similarity had an elevated risk of psychotic disorder (IRR = 1.15, 95% CI 1.06-1.24). Adjustment for knowledge of English at arrival had minimal effect on observed estimates.nnCONCLUSION: We found some evidence that linguistic factors that impair comprehension may play a role in the excess risk of psychosis among migrant groups; however, the magnitude of effect is small and unlikely to fully explain the elevated rates of psychotic disorder across migrant groups.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38679324b,

title = {Atypical Brain Aging and Its Association With Working Memory Performance in Major Depressive Disorder},

author = {Natalie C W Ho and Richard A I Bethlehem and Jakob Seidlitz and Nikita Nogovitsyn and Paul Metzak and Pedro L Ballester and Stefanie Hassel and Susan Rotzinger and Jordan Poppenk and Raymond W Lam and Valerie H Taylor and Roumen Milev and  and Edward T Bullmore and Aaron F Alexander-Bloch and Benicio N Frey and Kate L Harkness and Jean Addington and Sidney H Kennedy and Katharine Dunlop},

doi = {10.1016/j.bpsc.2024.04.008},

issn = {2451-9030},

year  = {2024},

date = {2024-08-01},

journal = {Biol Psychiatry Cogn Neurosci Neuroimaging},

volume = {9},

number = {8},

pages = {786--799},

abstract = {BACKGROUND: Patients with major depressive disorder (MDD) can present with altered brain structure and deficits in cognitive function similar to those seen in aging. However, the interaction between age-related brain changes and brain development in MDD remains understudied. In a cohort of adolescents and adults with and without MDD, we assessed brain aging differences and associations through a newly developed tool that quantifies normative neurodevelopmental trajectories.nnMETHODS: A total of 304 participants with MDD and 236 control participants without depression were recruited and scanned from 3 studies under the Canadian Biomarker Integration Network for Depression. Volumetric data were used to generate brain centile scores, which were examined for 1) differences between participants with MDD and control participants; 2) differences between individuals with versus without severe childhood maltreatment; and 3) correlations with depressive symptom severity, neurocognitive assessment domains, and escitalopram treatment response.nnRESULTS: Brain centiles were significantly lower in the MDD group than in the control group. Brain centile was also significantly correlated with working memory in the control group but not the MDD group. No significant associations were observed between depression severity or antidepressant treatment response and brain centiles. Likewise, childhood maltreatment history did not significantly affect brain centiles.nnCONCLUSIONS: Consistent with previous work on machine learning models that predict brain age, brain centile scores differed in people diagnosed with MDD, and MDD was associated with differential relationships between centile scores and working memory. The results support the notion of atypical development and aging in MDD, with implications for neurocognitive deficits associated with aging-related cognitive function.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38678736b,

title = {Neuromelanin levels in individuals with substance use disorders: A systematic review and meta-analysis},

author = {Jessica Ahrens and Farida Zaher and Rachel A Rabin and Clifford M Cassidy and Lena Palaniyappan},

doi = {10.1016/j.neubiorev.2024.105690},

issn = {1873-7528},

year  = {2024},

date = {2024-06-01},

journal = {Neurosci Biobehav Rev},

volume = {161},

pages = {105690},

abstract = {Dopamine's role in addiction has been extensively studied, revealing disruptions in its functioning throughout all addiction stages. Neuromelanin in the substantia nigra (SN) may reflect dopamine auto-oxidation, and can be quantified using neuromelaninsensitive magnetic resonance imaging (neuromelanin-MRI) in a non-invasive manner.In this pre-registered systematic review, we assess the current body of evidence related to neuromelanin levels in substance use disorders, using both post-mortem and MRI examinations. The systematic search identified 10 relevant articles, primarily focusing on the substantia nigra. An early-stage meta-analysis (n = 6) revealed varied observations ranging from standardized mean differences of -3.55 to +0.62, with a pooled estimate of -0.44 (95 % CI = -1.52, 0.65), but there was insufficient power to detect differences in neuromelanin content among individuals with substance use disorders. Our gap analysis highlights the lack of sufficient replication studies, with existing studies lacking the power to detect a true difference, and a complete lack of neuromelanin studies on certain substances of clinical interest. We provide recommendations for future studies of dopaminergic neurobiology in addictions and related psychiatric comorbidities.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38664377b,

title = {Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis},

author = {Mark Sen Dong and Jaroslav Rokicki and Dominic Dwyer and Sergi Papiol and Fabian Streit and Marcella Rietschel and Thomas Wobrock and Bertram Müller-Myhsok and Peter Falkai and Lars Tjelta Westlye and Ole A Andreassen and Lena Palaniyappan and Thomas Schneider-Axmann and Alkomiet Hasan and Emanuel Schwarz and Nikolaos Koutsouleris},

doi = {10.1038/s41398-024-02903-1},

issn = {2158-3188},

year  = {2024},

date = {2024-04-01},

journal = {Transl Psychiatry},

volume = {14},

number = {1},

pages = {196},

abstract = {The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38569724b,

title = {Making use of N-of-1 trials to treat ADHD in people with psychosis: a hypothetical case},

author = {Kathryn Dalton and Ridha Joober and Sherif Karama and Lena Palaniyappan},

doi = {10.1503/jpn.240010},

issn = {1488-2434},

year  = {2024},

date = {2024-01-01},

journal = {J Psychiatry Neurosci},

volume = {49},

number = {2},

pages = {E133--E134},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38494121b,

title = {Antecedents of major depressive, bipolar, and psychotic disorders: A systematic review and meta-analysis of prospective studies},

author = {Rudolf Uher and Barbara Pavlova and Sara Najafi and Nitya Adepalli and Briana Ross and Emily Howes Vallis and Kathryn Freeman and Robin Parker and Lukas Propper and Lena Palaniyappan},

doi = {10.1016/j.neubiorev.2024.105625},

issn = {1873-7528},

year  = {2024},

date = {2024-05-01},

journal = {Neurosci Biobehav Rev},

volume = {160},

pages = {105625},

abstract = {Major depressive, bipolar, or psychotic disorders are preceded by earlier manifestations in behaviours and experiences. We present a synthesis of evidence on associations between person-level antecedents (behaviour, performance, psychopathology) in childhood, adolescence, or early adulthood and later onsets of major depressive disorder, bipolar disorder, or psychotic disorder based on prospective studies published up to September 16, 2022. We screened 11,342 records, identified 460 eligible publications, and extracted 570 risk ratios quantifying the relationships between 52 antecedents and onsets in 198 unique samples with prospective follow-up of 122,766 individuals from a mean age of 12.4 to a mean age of 24.8 for 1522,426 person years of follow-up. We completed meta-analyses of 12 antecedents with adequate data. Psychotic symptoms, depressive symptoms, anxiety, disruptive behaviors, affective lability, and sleep problems were transdiagnostic antecedents associated with onsets of depressive, bipolar, and psychotic disorders. Attention-deficit/hyperactivity and hypomanic symptoms specifically predicted bipolar disorder. While transdiagnostic and diagnosis-specific antecedents inform targeted prevention and help understand pathogenic mechanisms, extensive gaps in evidence indicate potential for improving early risk identification.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38428118b,

title = {Speech markers to predict and prevent recurrent episodes of psychosis: A narrative overview and emerging opportunities},

author = {Farida Zaher and Mariama Diallo and Amélie M Achim and Ridha Joober and Marc-André Roy and Marie-France Demers and Priya Subramanian and Katie M Lavigne and Martin Lepage and Daniela Gonzalez and Irnes Zeljkovic and Kristin Davis and Michael Mackinley and Priyadharshini Sabesan and Shalini Lal and Alban Voppel and Lena Palaniyappan},

doi = {10.1016/j.schres.2024.02.036},

issn = {1573-2509},

year  = {2024},

date = {2024-04-01},

journal = {Schizophr Res},

volume = {266},

pages = {205--215},

abstract = {Preventing relapse in schizophrenia improves long-term health outcomes. Repeated episodes of psychotic symptoms shape the trajectory of this illness and can be a detriment to functional recovery. Despite early intervention programs, high relapse rates persist, calling for alternative approaches in relapse prevention. Predicting imminent relapse at an individual level is critical for effective intervention. While clinical profiles are often used to foresee relapse, they lack the specificity and sensitivity needed for timely prediction. Here, we review the use of speech through Natural Language Processing (NLP) to predict a recurrent psychotic episode. Recent advancements in NLP of speech have shown the ability to detect linguistic markers related to thought disorder and other language disruptions within 2-4 weeks preceding a relapse. This approach has shown to be able to capture individual speech patterns, showing promise in its use as a prediction tool. We outline current developments in remote monitoring for psychotic relapses, discuss the challenges and limitations and present the speech-NLP based approach as an alternative to detect relapses with sufficient accuracy, construct validity and lead time to generate clinical actions towards prevention.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38359932b,

title = {Epigenetic profile of the immune system associated with symptom severity and treatment response in schizophrenia},

author = {Yuanhao Tang and Yunlong Tan and Lena Palaniyappan and Yin Yao and Qiang Luo and Yanli Li},

doi = {10.1503/jpn.230099},

issn = {1488-2434},

year  = {2024},

date = {2024-01-01},

journal = {J Psychiatry Neurosci},

volume = {49},

number = {1},

pages = {E45--E58},

abstract = {BACKGROUND: Environmental modification of genetic information (epigenetics) is often invoked to explain interindividual differences in the phenotype of schizophrenia. In clinical practice, such variability is most prominent in the symptom profile and the treatment response. Epigenetic regulation of immune function is of particular interest, given the therapeutic relevance of this mechanism in schizophrenia.nnMETHODS: We analyzed the DNA methylation data of immune-relevant genes in patients with schizophrenia whose disease duration was less than 3 years, with previous lifetime antipsychotic treatment of no more than 2 weeks total.nnRESULTS: A total of 441 patients met the inclusion criteria. Core symptoms were consistently associated with 206 methylation positions, many of which had previously been implicated in inflammatory responses. Of these, 24 methylation positions were located either in regulatory regions or near the CpG islands of 20 genes, including the  gene, which is a key player in glutamatergic signalling. These symptom-associated immune genes were enriched in neuronal development functions, such as neuronal migration and glutamatergic synapse. Compared with using only clinical information (including scores on the Positive and Negative Syndrome Scale), integrating methylation data into the model significantly improved the predictive ability (as indicated by area under the curve) for response to 8 weeks of antipsychotic treatment.nnLIMITATIONS: We focused on a small number of methylation probes (immune-centred search) and lacked nutritional data and direct brain-based measures.nnCONCLUSION: Epigenetic modifications of the immune system are associated with symptom severity at onset and subsequent treatment response in schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38280712b,

title = {The 'L-factor': Language as a transdiagnostic dimension in psychopathology},

author = {Wolfram Hinzen and Lena Palaniyappan},

doi = {10.1016/j.pnpbp.2024.110952},

issn = {1878-4216},

year  = {2024},

date = {2024-04-01},

journal = {Prog Neuropsychopharmacol Biol Psychiatry},

volume = {131},

pages = {110952},

abstract = {Thoughts and moods constituting our mental life incessantly change. When the steady flow of this dynamics diverges in clinical directions, the possible pathways involved are captured through discrete diagnostic labels. Yet a single vulnerable neurocognitive system may be causally involved in psychopathological deviations transdiagnostically. We argue that language viewed as integrating cortical functions is the best current candidate, whose forms of breakdown along its different dimensions are then manifest as symptoms - from prosodic abnormalities and rumination in depression to distortions of speech perception in verbal hallucinations, distortions of meaning and content in delusions, or disorganized speech in formal thought disorder. Spontaneous connected speech provides continuous objective readouts generating a highly accessible bio-behavioral marker with the potential of revolutionizing neuropsychological measurement. This argument turns language into a transdiagnostic 'L-factor' providing an analytical and mechanistic substrate for previously proposed latent general factors of psychopathology ('p-factor') and cognitive functioning ('c-factor'). Together with immense practical opportunities afforded by rapidly advancing natural language processing (NLP) technologies and abundantly available data, this suggests a new era of translational clinical psychiatry, in which both psychopathology and language may be rethought together.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38280291b,

title = {Navigating the semantic space: Unraveling the structure of meaning in psychosis using different computational language models},

author = {Rui He and Claudio Palominos and Han Zhang and Maria Francisca Alonso-Sánchez and Lena Palaniyappan and Wolfram Hinzen},

doi = {10.1016/j.psychres.2024.115752},

issn = {1872-7123},

year  = {2024},

date = {2024-03-01},

journal = {Psychiatry Res},

volume = {333},

pages = {115752},

abstract = {Speech in psychosis has long been ascribed as involving 'loosening of associations'. We pursued the aim to elucidate its underlying cognitive mechanisms by analysing picture descriptions from 94 subjects (29 healthy controls, 18 participants at clinical high risk, 29 with first-episode psychosis, and 18 with chronic schizophrenia), using five language models with different computational architectures: FastText, which represents meaning non-contextually/statically; BERT, which represents contextual meaning sensitive to grammar and context; Infersent and SBERT, which provide sentential representations; and CLIP, which evaluates speech relative to a visual stimulus. These models were used to quantify semantic distances crossed between successive tokens/sentences, and semantic perplexity indicating unexpectedness in continuations. Results showed that, among patients, semantic similarity increased when measured with FastText, Infersent, and SBERT, while it decreased with CLIP and BERT. Higher perplexity was observed in first-episode psychosis. Static semantic measures were associated with clinically measured impoverishment of thought and referential semantic measures with disorganization. These patterns indicate a shrinking conceptual semantic space as represented by static language models, which co-occurs with a widening in the referential semantic space as represented by contextual models. This duality underlines the need to separate these two forms of meaning for understanding mechanisms involved in semantic change in psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38268052b,

title = {Using a longitudinal network structure to subgroup depressive symptoms among adolescents},

author = {Sugai Liang and Zejun Huang and Yiquan Wang and Yue Wu and Zhiyu Chen and Yamin Zhang and Wanjun Guo and Zhenqing Zhao and Sabrina D Ford and Lena Palaniyappan and Tao Li},

doi = {10.1186/s40359-024-01537-8},

issn = {2050-7283},

year  = {2024},

date = {2024-01-01},

journal = {BMC Psychol},

volume = {12},

number = {1},

pages = {46},

abstract = {BACKGROUND: Network modeling has been proposed as an effective approach to examine complex associations among antecedents, mediators and symptoms. This study aimed to investigate whether the severity of depressive symptoms affects the multivariate relationships among symptoms and mediating factors over a 2-year longitudinal follow-up.nnMETHODS: We recruited a school-based cohort of 1480 primary and secondary school students over four semesters from January 2020 to December 2021. The participants (n = 1145) were assessed at four time points (ages 10-13 years old at baseline). Based on a cut-off score of 5 on the 9-item Patient Health Questionnaire at each time point, the participants were categorized into the non-depressive symptom (NDS) and depressive symptom (DS) groups. We conducted network analysis to investigate the symptom-to-symptom influences in these two groups over time.nnRESULTS: The global network metrics did not differ statistically between the NDS and DS groups at four time points. However, network connection strength varied with symptom severity. The edge weights between learning anxiety and social anxiety were prominently in the NDS group over time. The central factors for NDS and DS were oversensitivity and impulsivity (3 out of 4 time points), respectively. Moreover, both node strength and closeness were stable over time in both groups.nnCONCLUSIONS: Our study suggests that interrelationships among symptoms and contributing factors are generally stable in adolescents, but a higher severity of depressive symptoms may lead to increased stability in these relationships.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38071933b,

title = {Impact of non-medical cannabis legalization with market restrictions on health service use and incident cases of psychotic disorder in Ontario, Canada},

author = {Kelly K Anderson and Rebecca Rodrigues and Britney Le and Maliha Mamun and Suzanne Archie and Jordan Edwards and Tara Elton-Marshall and Jason Gilliland and Daniel Thomas Myran and Lena Palaniyappan and Christopher M Perlman and Jamie A Seabrook and Robin M Murray and Salimah Z Shariff},

doi = {10.1016/j.drugpo.2023.104285},

issn = {1873-4758},

year  = {2024},

date = {2024-01-01},

journal = {Int J Drug Policy},

volume = {123},

pages = {104285},

abstract = {BACKGROUND: Cannabis is a risk factor in the onset and persistence of psychotic disorders. There is concern that non-medical cannabis legalization in Canada may have population-level impacts on psychotic disorders. We sought to examine changes in health service use and incident cases of psychotic disorder following cannabis legalization, during a period of tight restrictions on retail stores and product types.nnMETHODS: We conducted a cross-sectional interrupted time-series analysis using linked population-based health administrative data from Ontario (Canada) from January 2014 to March 2020. We identified psychosis-related outpatient visits, emergency department visits, hospitalizations, and inpatient length of stay, as well as incident cases of psychotic disorders, among people aged 14 to 60 years.nnRESULTS: We did not find evidence of increases in health service use or incident cases of psychotic disorders over the short-term (17 month) period following cannabis legalization. However, we found clear increasing trends in health service use and incident cases of substance-induced psychotic disorders over the entire observation window (2014-2020).nnCONCLUSION: Our findings suggest that the initial period of tight market restriction following legalization of non-medical cannabis was not associated with an increase in health service use or frequency of psychotic disorders. A longer post-legalization observation period, which includes expansion of the commercial cannabis market, is needed to fully understand the population-level impacts of non-medical cannabis legalization; thus, it would be premature to conclude that the legalization of non-medical cannabis did not lead to increases in health service use and incident cases of psychotic disorder.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38050448b,

title = {Precision of metabolite-selective MRS measurements of glutamate, GABA and glutathione: A review of human brain studies},

author = {Kesavi Kanagasabai and Lena Palaniyappan and Jean Théberge},

doi = {10.1002/nbm.5071},

issn = {1099-1492},

year  = {2024},

date = {2024-03-01},

journal = {NMR Biomed},

volume = {37},

number = {3},

pages = {e5071},

abstract = {Single-voxel proton magnetic resonance spectroscopy (SV  H-MRS) is an in vivo noninvasive imaging technique used to detect neurotransmitters and metabolites. It enables repeated measurements in living participants to build explanatory neurochemical models of psychiatric symptoms and testing of therapeutic approaches. Given the tight link among glutamate, gamma-amino butyric acid (GABA), glutathione and glutamine within the cellular machinery, MRS investigations of neurocognitive and psychiatric disorders must quantify a network of metabolites simultaneously to capture the pathophysiological states of interest. Metabolite-selective sequences typically provide improved metabolite isolation and spectral modelling simplification for a single metabolite at a time. Non-metabolite-selective sequences provide information on all detectable human brain metabolites, but feature many signal overlaps and require complicated spectral modelling. Although there are short-echo time (TE) MRS sequences that do not use spectral editing and are optimised to target either glutamate, GABA or glutathione, these approaches usually imply a precision tradeoff for the remaining two metabolites. Given the interest in assessing psychiatric and neurocognitive diseases that involve excitation-inhibition imbalances along with oxidative stress, there is a need to survey the literature on the quantification precision of current metabolite-selective MRS techniques. In this review, we locate and describe 17 studies that report on the quality of simultaneously acquired MRS metabolite data in the human brain. We note several factors that influence the data quality for single-shot acquisition of multiple metabolites of interest using metabolite-selective MRS: (1) internal in vivo references; (2) brain regions of interests; (3) field strength of scanner; and/or (4) optimised acquisition parameters. We also highlight the strengths and weaknesses of various SV spectroscopy techniques that were able to quantify in vivo glutamate, GABA and glutathione simultaneously. The insights from this review will assist in the development of new MRS pulse sequences for simultaneous, selective measurements of these metabolites and simplified spectral modelling.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38036458b,

title = {Access to a regular primary care physician among young people with early psychosis in Ontario, Canada},

author = {Rebecca Rodrigues and Jennifer N S Reid and Joshua C Wiener and Suzanne Archie and Richard G Booth and Chiachen Cheng and Arlene G MacDougall and Lena Palaniyappan and Bridget L Ryan and Aristotle Voineskos and Paul Kurdyak and Saadia Hameed Jan and Kelly K Anderson and },

doi = {10.1111/eip.13487},

issn = {1751-7893},

year  = {2024},

date = {2024-07-01},

journal = {Early Interv Psychiatry},

volume = {18},

number = {7},

pages = {513--523},

abstract = {AIM: Access to a primary care physician in early psychosis facilitates help-seeking and engagement with psychiatric treatment. We examined access to a regular primary care physician in people with early psychosis, compared to the general population, and explored factors associated with access.nnMETHODS: Using linked health administrative data from Ontario (Canada), we identified people aged 14-35 years with a first diagnosis of nonaffective psychotic disorder (n = 39 449; 2005-2015). We matched cases to four randomly selected general population controls based on age, sex, neighbourhood, and index date (n = 157 796). We used modified Poisson regression to estimate prevalence ratios (PR) for access to a regular primary care physician in the year prior to first diagnosis of psychotic disorder, and the sociodemographic and clinical factors associated with access.nnRESULTS: A larger proportion of people with early psychosis had a regular primary care physician, relative to the general population (89% vs. 68%; PR = 1.30, 95%CI = 1.30-1.31). However, this was accounted for by a higher prevalence of comorbidities among people with psychosis, and this association was no longer present after adjustment (PR = 0.97, 95%CI = 0.97, 0.98). People with early psychosis who were older, male, refugees and those residing in lower income or high residential instability neighbourhoods were less likely to have a regular primary care physician.nnCONCLUSION: Approximately one in ten young people with early psychosis in Ontario lack access to a regular primary care physician. Strategies to improve primary care physician access are needed for management of physical comorbidities and to ensure continuity of care.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37994452b,

title = {Association of cortical gyrification, white matter microstructure, and phenotypic profile in medication-naïve obsessive-compulsive disorder},

author = {Jianyu Li and Jian Cheng and Lei Yang and Qihui Niu and Yuanchao Zhang and Lena Palaniyappan},

doi = {10.1017/S0033291723003422},

issn = {1469-8978},

year  = {2024},

date = {2024-06-01},

journal = {Psychol Med},

volume = {54},

number = {8},

pages = {1573--1579},

abstract = {BACKGROUND: Obsessive-compulsive disorder (OCD) is thought to arise from dysconnectivity among interlinked brain regions resulting in a wide spectrum of clinical manifestations. Cortical gyrification, a key morphological feature of human cerebral cortex, has been considered associated with developmental connectivity in early life. Monitoring cortical gyrification alterations may provide new insights into the developmental pathogenesis of OCD.nnMETHODS: Sixty-two medication-naive patients with OCD and 59 healthy controls (HCs) were included in this study. Local gyrification index (LGI) was extracted from T1-weighted MRI data to identify the gyrification changes in OCD. Total distortion (splay, bend, or twist of fibers) was calculated using diffusion-weighted MRI data to examine the changes in white matter microstructure in patients with OCD.nnRESULTS: Compared with HCs, patients with OCD showed significantly increased LGI in bilateral medial frontal gyrus and the right precuneus, where the mean LGI was positively correlated with anxiety score. Patients with OCD also showed significantly decreased total distortion in the body, genu, and splenium of the corpus callosum (CC), where the average distortion was negatively correlated with anxiety scores. Intriguingly, the mean LGI of the affected cortical regions was significantly correlated with the mean distortion of the affected white matter tracts in patients with OCD.nnCONCLUSIONS: We demonstrated associations among increased LGI, aberrant white matter geometry, and higher anxiety in patients with OCD. Our findings indicate that developmental dysconnectivity-driven alterations in cortical folding are one of the neural substrates underlying the clinical manifestations of OCD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37886802b,

title = {The effect of non-medical cannabis retailer proximity on use of mental health services for psychotic disorders in Ontario, Canada},

author = {Jared C Wootten and Rebecca Rodrigues and Jason Gilliland and Brooke Carter and Salimah Z Shariff and Shiran Zhong and Suzanne Archie and Jordan Edwards and Tara Elton-Marshall and Daniel Thomas Myran and Lena Palaniyappan and Christopher M Perlman and Jamie A Seabrook and Robin M Murray and Kelly K Anderson},

doi = {10.1177/00207640231206053},

issn = {1741-2854},

year  = {2024},

date = {2024-03-01},

journal = {Int J Soc Psychiatry},

volume = {70},

number = {2},

pages = {308--318},

abstract = {BACKGROUND: Cannabis is associated with the onset and persistence of psychotic disorders. Evidence suggests that accessibility of substances is associated with an increased risk of use-related harms. We sought to examine the effect of residing in proximity to non-medical cannabis retailers on the prevalence of health service use for psychosis.nnMETHODS: We conducted a cross-sectional study using linked health administrative data, and used geospatial analyses to determine whether people in Ontario, Canada (aged 14-60 years) resided within walking (1.6 km) or driving (5.0 km) distance of non-medical cannabis retailers (open as of February-2020). We identified outpatient visits, emergency department (ED) visits, and hospitalizations for psychotic disorders between 01-April-2019 and 17-March-2020. We used zero-inflated Poisson regression models and gamma generalized linear models to estimate the association between cannabis retailer proximity and indicators of health service use.nnRESULTS: Non-medical cannabis retailers were differentially located in areas with high levels of marginalization and pre-existing health service use for psychosis. People residing within walking or driving distance of a cannabis retailer had a higher rate of psychosis-related outpatient visits, ED visits, and hospitalizations, compared to people living outside these areas. This effect was stronger among those with no prior service use for psychosis.nnCONCLUSIONS: Proximity to a non-medical cannabis retailer was associated with higher health service use for psychosis, even after adjustment for prior health service use. These findings suggest that opening of non-medical cannabis retailers could worsen the burden of psychosis on mental health services in areas with high-risk populations.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37752221b,

title = {Glutamatergic basis of antipsychotic response in first-episode psychosis: a dual voxel study of the anterior cingulate cortex},

author = {Lejia Fan and Liangbing Liang and Yujue Wang and Xiaoqian Ma and Liu Yuan and Lijun Ouyang and Ying He and Zongchang Li and Chunwang Li and Xiaogang Chen and Lena Palaniyappan},

doi = {10.1038/s41386-023-01741-x},

issn = {1740-634X},

year  = {2024},

date = {2024-04-01},

journal = {Neuropsychopharmacology},

volume = {49},

number = {5},

pages = {845--853},

abstract = {A subgroup of patients with schizophrenia is believed to have aberrant excess of glutamate in the frontal cortex; this subgroup is thought to show poor response to first-line antipsychotic treatments that focus on dopamine blockade. If we can identify this subgroup early in the course of illness, we can reduce the repeated use of first-line antipsychotics and potentially stratify first-episode patients to intervene early with second-line treatments such as clozapine. The use of proton magnetic resonance spectroscopy (1H-MRS) to measure glutamate and Glx (glutamate plus glutamine) may provide a means for such a stratification. We must first establish if there is robust evidence linking elevations in anterior cingulate cortex (ACC) glutamate metabolites to poor response, and determine if the use of antipsychotics worsens the glutamatergic excess in eventual nonresponders. In this study, we estimated glutamate levels at baseline in 42 drug-naive patients with schizophrenia. We then treated them all with risperidone at a standard dose range of 2-6 mg/day and followed them up for 3 months to categorize their response status. We expected to see baseline "hyperglutamatergia" in nonresponders, and expected this to worsen over time at the follow-up. In line with our predictions, nonresponders had higher glutamate than responders, but patients as a group did not differ in glutamate and Glx from the healthy control (HC) group before treatment-onset (F = 3.20, p = 0.046, partial η2 = 0.075). Glutamatergic metabolites did not change significantly over time in both nonresponders and responders over the 3 months of antipsychotic exposure (F = 1.26, p = 0.270, partial η2 = 0.039). We conclude that the use of antipsychotics without prior knowledge of later response delays symptom relief in a subgroup of first-episode patients, but does not worsen the glutamatergic excess seen at the baseline. Given the current practice of nonstratified use of antipsychotics, longer-time follow-up MRS studies are required to see if improvement in symptoms accompanies a dynamic shift in glutamate profile.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37735237b,

title = {Frontostriatal circuitry and the tryptophan kynurenine pathway in major psychiatric disorders},

author = {Sugai Liang and Liansheng Zhao and Peiyan Ni and Qiang Wang and Wanjun Guo and Yan Xu and Jia Cai and Shiwan Tao and Xiaojing Li and Wei Deng and Lena Palaniyappan and Tao Li},

doi = {10.1007/s00213-023-06466-9},

issn = {1432-2072},

year  = {2024},

date = {2024-01-01},

journal = {Psychopharmacology (Berl)},

volume = {241},

number = {1},

pages = {97--107},

abstract = {RATIONALE: An imbalance of the tryptophan kynurenine pathway (KP) commonly occurs in psychiatric disorders, though the neurocognitive and network-level effects of this aberration are unclear.nnOBJECTIVES: In this study, we examined the connection between dysfunction in the frontostriatal brain circuits, imbalances in the tryptophan kynurenine pathway (KP), and neurocognition in major psychiatric disorders.nnMETHODS: Forty first-episode medication-naive patients with schizophrenia (SCZ), fifty patients with bipolar disorder (BD), fifty patients with major depressive disorder (MDD), and forty-two healthy controls underwent resting-state functional magnetic resonance imaging. Plasma levels of KP metabolites were measured, and neurocognitive function was evaluated. Frontostriatal connectivity and KP metabolites were compared between groups while controlling for demographic and clinical characteristics. Canonical correlation analyses were conducted to explore multidimensional relationships between frontostriatal circuits-KP and KP-cognitive features.nnRESULTS: Patient groups shared hypoconnectivity between bilateral ventrolateral prefrontal cortex (vlPFC) and left insula, with disorder-specific dysconnectivity in SCZ related to PFC, left dorsal striatum hypoconnectivity. The BD group had higher anthranilic acid and lower xanthurenic acid levels than the other groups. KP metabolites and ratios related to disrupted frontostriatal dysconnectivity in a transdiagnostic manner. The SCZ group and MDD group separately had high-dimensional associations between KP metabolites and cognitive measures.nnCONCLUSIONS: The findings suggest that KP may influence cognitive performance across psychiatric conditions via frontostriatal dysfunction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37018464b,

title = {Aberrant Brain Dynamics in Schizophrenia During Working Memory Task: Evidence From a Replication Functional MRI Study},

author = {Feiwen Wang and Zhening Liu and Sabrina D Ford and Mengjie Deng and Wen Zhang and Jie Yang and Lena Palaniyappan},

doi = {10.1093/schbul/sbad032},

issn = {1745-1701},

year  = {2024},

date = {2024-01-01},

journal = {Schizophr Bull},

volume = {50},

number = {1},

pages = {96--106},

abstract = {BACKGROUND AND HYPOTHESIS: The integration of information that typifies working memory (WM) operation requires a flexible, dynamic functional relationship among brain regions. In schizophrenia, though WM capacity is prominently impaired at higher loads, the mechanistic underpinnings are unclear. As a result, we lack convincing cognitive remediation of load-dependent deficits. We hypothesize that reduced WM capacity arises from a disruption in dynamic functional connectivity when patients face cognitive demands.nnSTUDY DESIGN: We calculate the dynamic voxel-wise degree centrality (dDC) across the functional connectome in 142 patients with schizophrenia and 88 healthy controls (HCs) facing different WM loads during an n-back task. We tested associations of the altered variability in dDC and clinical symptoms and identified intermediate connectivity configurations (clustered states) across time during WM operation. These analyses were repeated in another independent dataset of 169 subjects (102 with schizophrenia).nnSTUDY RESULTS: Compared with HCs, patients showed an increased dDC variability of supplementary motor area (SMA) for the "2back vs. 0back" contrast. This instability at the SMA seen in patients correlated with increased positive symptoms and followed a limited "U-shape" pattern at rest-condition and 2 loads. In the clustering analysis, patients showed reduced centrality in the SMA, superior temporal gyrus, and putamen. These results were replicated in a constrained search in the second independent dataset.nnCONCLUSIONS: Schizophrenia is characterized by a load-dependent reduction of stable centrality in SMA; this relates to the severity of positive symptoms, especially disorganized behaviour. Restoring SMA stability in the presence of cognitive demands may have a therapeutic effect in schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35752547,

title = {Syntactic complexity of spoken language in the diagnosis of schizophrenia: A probabilistic Bayes network model},

author = {Angelica M Silva and Roberto Limongi and Michael MacKinley and Sabrina D Ford and Maria Francisca Alonso-Sánchez and Lena Palaniyappan},

doi = {10.1016/j.schres.2022.06.011},

issn = {1573-2509},

year  = {2023},

date = {2023-09-01},

journal = {Schizophr Res},

volume = {259},

pages = {88--96},

abstract = {In the clinical linguistics of schizophrenia, syntactic complexity has received much attention. In this study, we address whether syntactic complexity deteriorates within the six months following the first episode of psychosis in those who develop a diagnosis of schizophrenia. We collected data from a cohort of twenty-six first-episode psychosis and 12 healthy control subjects using the Thought and Language Index interview in response to three pictures from the Thematic Apperception Test at first assessment and after six months (the time of consensus diagnosis). An automated labeling (part-of-speech tagging) for specific syntactic elements calculated large and granular syntactic complexity indices with a focus on clause complexity as a particular case from this spoken language data. Probabilistic reasoning leveraging the conditional independence properties of Bayes networks revealed that consensus diagnosis of schizophrenia predicted a decrease in nominal subjects per clause among individuals with first episode psychosis. From the entire sample, we estimate a 95.4 % probability that a 50 % decrease in mean nominal subjects per clause after six months is explained by the presence of first episode psychosis. Among those with psychosis, a 30 % decrease in this clause-complexity index after six months of experiencing the first episode predicted with 95 % probability a consensus diagnosis of schizophrenia, representing a conditional relationship between a longitudinal decrease in syntactic complexity and a diagnosis of schizophrenia. We conclude that an early drift towards linguistic disorganization/impoverishment of clause complexity-at the granular level of nominal subject per clause-is a distinctive feature of schizophrenia that decreases longitudinally, thus differentiating schizophrenia from other psychotic illnesses with shared phenomenology.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35568676,

title = {Language network self-inhibition and semantic similarity in first-episode schizophrenia: A computational-linguistic and effective connectivity approach},

author = {María Francisca Alonso-Sánchez and Roberto Limongi and Joseph Gati and Lena Palaniyappan},

doi = {10.1016/j.schres.2022.04.007},

issn = {1573-2509},

year  = {2023},

date = {2023-09-01},

journal = {Schizophr Res},

volume = {259},

pages = {97--103},

abstract = {INTRODUCTION: A central feature of schizophrenia is the disorganization and impoverishment of language. Recently, we observed higher semantic similarity in first-episode-schizophrenia (FES) patients. In this study, we investigate if this aberrant similarity relates to the 'causal' connectivity between two key nodes of the word production system: inferior frontal gyrus (IFG) and the semantic-hub at the ventral anterior temporal lobe (vATL).nnMETHODS: Resting-state fMRI scans were collected from 60 participants (30 untreated FES and 30 healthy controls). The semantic distance was measured with the CoVec semantic tool based on GloVe. A spectral dynamic causal model with Parametrical Empirical Bayes was constructed modelling the intrinsic self-inhibitory and extrinsic-excitatory connections within the brain regions. We estimated the parameters of a fully connected model with the semantic distance as a covariate.nnRESULTS: FES patients chose words with higher semantic similarity when describing the pictures compared to the HC group. Among patients, an increased semantic similarity was related with an increase in intrinsic connections within both the vATL and IFG, suggesting that reduced 'synaptic gain' in these regions likely contribute to aberrant sampling of the semantic space during discourse in schizophrenia.nnCONCLUSIONS: Lexical impoverishment relates to increased self-inhibition in both the IFG and vATL. The associated reduction in synaptic gain may relate to reduced precision of locally generated neural activity, forcing the choice of words that are already 'activated' in a lexical network. One approach to improve word sampling may be via promoting synaptic gain via supra-physiological stimulation within the Broca's-vATL network; this proposal needs verification.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35244484,

title = {The centrality of working memory networks in differentiating bipolar type I depression from unipolar depression: A task-fMRI study},

author = {Chang Xi and Zhening Liu and Can Zeng and Wenjian Tan and Fuping Sun and Jie Yang and Lena Palaniyappan},

doi = {10.1177/07067437221078646},

issn = {1497-0015},

year  = {2023},

date = {2023-01-01},

journal = {Can J Psychiatry},

volume = {68},

number = {1},

pages = {22--32},

abstract = {OBJECTIVES: Up to 70%-80% of patients with bipolar disorder are misdiagnosed as having major depressive disorder (MDD), leading to both delayed intervention and worsening disability. Differences in the cognitive neurophysiology may serve to distinguish between the depressive phase of type 1 bipolar disorder (BDD-I) from MDD, though this remains to be demonstrated. To this end, we investigate the discriminatory signal in the topological organization of the functional connectome during a working memory (WM) task in BDD-I and MDD, as a candidate identification approach.nnMETHODS: We calculated and compared the degree centrality (DC) at the whole-brain voxel-wise level in 31 patients with BDD-I, 35 patients with MDD, and 80 healthy controls (HCs) during an n-back task. We further extracted the distinct DC patterns in the two patient groups under different WM loads and used machine learning approaches to determine the distinguishing ability of the DC map.nnRESULTS: Patients with BDD-I had lower accuracy and longer reaction time (RT) than HCs at high WM loads. BDD-I is characterized by decreased DC in the default mode network (DMN) and the sensorimotor network (SMN) when facing high WM load. In contrast, MDD is characterized by increased DC in the DMN during high WM load. Higher WM load resulted in better classification performance, with the distinct aberrant DC maps under 2-back load discriminating the two disorders with 90.91% accuracy.nnCONCLUSIONS: The distributed brain connectivity during high WM load provides novel insights into the neurophysiological mechanisms underlying cognitive impairment of depression. This could potentially distinguish BDD-I from MDD if replicated in future large-scale evaluations of first-episode depression with longitudinal confirmation of diagnostic transition.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid35164887,

title = {Ameliorative patterns of grey matter in patients with first-episode and treatment-naïve schizophrenia},

author = {Mingli Li and Wei Deng and Yinfei Li and Liansheng Zhao and Xiaohong Ma and Hua Yu and Xiaojing Li and Yajing Meng and Qiang Wang and Xiangdong Du and Pak Chung Sham and Lena Palaniyappan and Tao Li},

doi = {10.1017/S0033291722000058},

issn = {1469-8978},

year  = {2023},

date = {2023-06-01},

journal = {Psychol Med},

volume = {53},

number = {8},

pages = {3500--3510},

abstract = {BACKGROUND: Grey matter (GM) reduction is a consistent observation in established late stages of schizophrenia, but patients in the untreated early stages of illness display an increase as well as a decrease in GM distribution relative to healthy controls (HC). The relative excess of GM may indicate putative compensatory responses, though to date its relevance is unclear.nnMETHODS: 343 first-episode treatment-naïve patients with schizophrenia (FES) and 342 HC were recruited. Multivariate source-based morphometry was performed to identify covarying 'networks' of grey matter concentration (GMC). Neurocognitive scores using the Cambridge Neuropsychological Test Automated Battery (CANTAB) and symptom burden using the Positive and Negative Symptoms Scale (PANSS) were obtained. Bivariate linear relationships between GMC and cognition/symptoms were studied.nnRESULTS: Compared to healthy subjects, FES had prominently lower GMC in two components; the first consists of the anterior insula, inferior frontal gyrus, anterior cingulate and the second component with the superior temporal gyrus, precuneus, inferior/superior parietal lobule, cuneus, and lingual gyrus. Higher GMC was seen in adjacent areas of the middle and superior temporal gyrus, middle frontal gyrus, inferior parietal cortex and putamen. Greater GMC of this component was associated with lower duration of untreated psychosis, less severe positive symptoms and better performance on cognitive tests.nnCONCLUSIONS: In untreated stages of schizophrenia, both a distributed lower and higher GMC is observable. While the higher GMC is relatively modest, it occurs across frontoparietal, temporal and subcortical regions in association with reduced illness burden suggesting a compensatory role for higher GMC in the early stages of schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid38441079b,

title = {Studying Psychosis Using Natural Language Generation: A Review of Emerging Opportunities},

author = {Lena Palaniyappan and David Benrimoh and Alban Voppel and Roberta Rocca},

doi = {10.1016/j.bpsc.2023.04.009},

issn = {2451-9030},

year  = {2023},

date = {2023-10-01},

journal = {Biol Psychiatry Cogn Neurosci Neuroimaging},

volume = {8},

number = {10},

pages = {994--1004},

abstract = {Disrupted language in psychotic disorders, such as schizophrenia, can manifest as false contents and formal deviations, often described as thought disorder. These features play a critical role in the social dysfunction associated with psychosis, but we continue to lack insights regarding how and why these symptoms develop. Natural language generation (NLG) is a field of computer science that focuses on generating human-like language for various applications. The theory that psychosis is related to the evolution of language in humans suggests that NLG systems that are sufficiently evolved to generate human-like language may also exhibit psychosis-like features. In this conceptual review, we propose using NLG systems that are at various stages of development as in silico tools to study linguistic features of psychosis. We argue that a program of in silico experimental research on the network architecture, function, learning rules, and training of NLG systems can help us understand better why thought disorder occurs in patients. This will allow us to gain a better understanding of the relationship between language and psychosis and potentially pave the way for new therapeutic approaches to address this vexing challenge.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37873296b,

title = {Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia},

author = {Yuchao Jiang and Cheng Luo and Jijun Wang and Lena Palaniyappan and Xiao Chang and Shitong Xiang and Jie Zhang and Mingjun Duan and Huan Huang and Christian Gaser and Kiyotaka Nemoto and Kenichiro Miura and Ryota Hashimoto and Lars T Westlye and Genevieve Richard and Sara Fernandez-Cabello and Nadine Parker and Ole A Andreassen and Tilo Kircher and Igor Nenadić and Frederike Stein and Florian Thomas-Odenthal and Lea Teutenberg and Paula Usemann and Udo Dannlowski and Tim Hahn and Dominik Grotegerd and Susanne Meinert and Rebekka Lencer and Yingying Tang and Tianhong Zhang and Chunbo Li and Weihua Yue and Yuyanan Zhang and Xin Yu and Enpeng Zhou and Ching-Po Lin and Shih-Jen Tsai and Amanda L Rodrigue and David Glahn and Godfrey Pearlson and John Blangero and Andriana Karuk and Edith Pomarol-Clotet and Raymond Salvador and Paola Fuentes-Claramonte and María Ángeles Garcia-León and Gianfranco Spalletta and Fabrizio Piras and Daniela Vecchio and Nerisa Banaj and Jingliang Cheng and Zhening Liu and Jie Yang and Ali Saffet Gonul and Ozgul Uslu and Birce Begum Burhanoglu and Aslihan Uyar Demir and Kelly Rootes-Murdy and Vince D Calhoun and Kang Sim and Melissa Green and Yann Quidé and Young Chul Chung and Woo-Sung Kim and Scott R Sponheim and Caroline Demro and Ian S Ramsay and Felice Iasevoli and Andrea de Bartolomeis and Annarita Barone and Mariateresa Ciccarelli and Arturo Brunetti and Sirio Cocozza and Giuseppe Pontillo and Mario Tranfa and Min Tae M Park and Matthias Kirschner and Foivos Georgiadis and Stefan Kaiser and Tamsyn E Van Rheenen and Susan L Rossell and Matthew Hughes and William Woods and Sean P Carruthers and Philip Sumner and Elysha Ringin and Filip Spaniel and Antonin Skoch and David Tomecek and Philipp Homan and Stephanie Homan and Wolfgang Omlor and Giacomo Cecere and Dana D Nguyen and Adrian Preda and Sophia Thomopoulos and Neda Jahanshad and Long-Biao Cui and Dezhong Yao and Paul M Thompson and Jessica A Turner and Theo G M van Erp and Wei Cheng and  and  and Jianfeng Feng},

doi = {10.1101/2023.10.11.23296862},

year  = {2023},

date = {2023-10-01},

journal = {medRxiv},

abstract = {Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37804598b,

title = {Risk stratification for treating people at ultra-high risk for psychosis: A cost-effectiveness analysis},

author = {Olajumoke M Ologundudu and Lena Palaniyappan and Lauren E Cipriano and Ben F M Wijnen and Kelly K Anderson and Shehzad Ali},

doi = {10.1016/j.schres.2023.09.015},

issn = {1573-2509},

year  = {2023},

date = {2023-11-01},

journal = {Schizophr Res},

volume = {261},

pages = {225--233},

abstract = {People who are at ultra-high risk (UHR) for psychosis receive clinical care with the aim to prevent first-episode psychosis (FEP), regardless of the risk of conversion to psychosis. An economic model from the Canadian health system perspective was developed to evaluate the cost-effectiveness of treating all with UHR compared to risk stratification over a 15-year time horizon, based on conversion probability, expected quality-of-life and costs. The analysis used a decision tree followed by a Markov model. Health states included: Not UHR, UHR with <20 % risk of conversion to FEP (based on the North American Prodrome Longitudinal Study risk calculator), UHR with ≥20 % risk, FEP, Remission, Post-FEP, and Death. The analysis found that: risk stratification (i.e., only treating those with ≥20 % risk) had lower costs ($1398) and quality-adjusted life-years (0.055 QALYs) per person compared to treating all. The incremental cost-effectiveness ratio for 'treat all' was $25,448/QALY, and suggests treating all may be cost-effective. The model was sensitive to changes to the probability of conversion.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37740852b,

title = {Disorganized Communication and Social Dysfunction in Schizophrenia: Emerging Concepts and Methods},

author = {Emmanuel Olarewaju and Guillaume Dumas and Lena Palaniyappan},

doi = {10.1007/s11920-023-01462-4},

issn = {1535-1645},

year  = {2023},

date = {2023-11-01},

journal = {Curr Psychiatry Rep},

volume = {25},

number = {11},

pages = {671--681},

abstract = {PURPOSE OF REVIEW: In this review, we embrace the emerging field of second-person neuroscience to address disorganization in schizophrenia. We argue that the focus of interest for disorganization is the interpersonal space where shared mental processes ('social mind') occur based on the bio-behavioural synchrony between two (or more) interacting people. We lay out several bio-behavioural measures that can capture the component parts of this process. In particular, we highlight the real-time imaging technology of hyperscanning that enables multi-person analysis of naturalistic social interaction. We illustrate how these measures can be used in empirical studies by posing disorganization as a problem of interpersonal processing.nnRECENT FINDINGS: Traditionally, disorganized speech and behaviour have been studied as the product of hidden cognitive processes ('private mind'). A dysfunction in these processes was attributed to the brain afflicted by the illness ('brain-bound mechanisms'). But this approach has contributed to challenges in measuring and quantifying disorganization. Consequently, the single-brain focus has not provided satisfactory clarity or led to effective treatments for persistent social dysfunction in schizophrenia. Social dysfunction is a core feature of schizophrenia. This dysfunction arises from disorganized interpersonal interaction that typifies the social profile of affected individuals. We outline challenges in employing several emerging concepts and methods and how they can be addressed to investigate the mechanisms of social dysfunction in schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37713573b,

title = {Transdiagnostic risk of mental disorders in offspring of affected parents: a meta-analysis of family high-risk and registry studies},

author = {Rudolf Uher and Barbara Pavlova and Joaquim Radua and Umberto Provenzani and Sara Najafi and Lydia Fortea and Maria Ortuño and Anna Nazarova and Nader Perroud and Lena Palaniyappan and Katharina Domschke and Samuele Cortese and Paul D Arnold and Jehannine C Austin and Michael M Vanyukov and Myrna M Weissman and Allan H Young and Manon H J Hillegers and Andrea Danese and Merete Nordentoft and Robin M Murray and Paolo Fusar-Poli},

doi = {10.1002/wps.21147},

issn = {1723-8617},

year  = {2023},

date = {2023-10-01},

journal = {World Psychiatry},

volume = {22},

number = {3},

pages = {433--448},

abstract = {The offspring of parents with mental disorders are at increased risk for developing mental disorders themselves. The risk to offspring may extend transdiagnostically to disorders other than those present in the parents. The literature on this topic is vast but mixed. To inform targeted prevention and genetic counseling, we performed a comprehensive, PRISMA 2020-compliant meta-analysis. We systematically searched the literature published up to September 2022 to retrieve original family high-risk and registry studies reporting on the risk of mental disorders in offspring of parents with any type of mental disorder. We performed random-effects meta-analyses of the relative risk (risk ratio, RR) and absolute risk (lifetime, up to the age at assessment) of mental disorders, defined according to the ICD or DSM. Cumulative incidence by offspring age was determined using meta-analytic Kaplan-Meier curves. We measured heterogeneity with the I statistic, and risk of bias with the Quality In Prognosis Studies (QUIPS) tool. Sensitivity analyses addressed the impact of study design (family high-risk vs. registry) and specific vs. transdiagnostic risks. Transdiagnosticity was appraised with the TRANSD criteria. We identified 211 independent studies that reported data on 3,172,115 offspring of parents with psychotic, bipolar, depressive, disruptive, attention-deficit/hyperactivity, anxiety, substance use, eating, obsessive-compulsive, and borderline personality disorders, and 20,428,575 control offspring. The RR and lifetime risk of developing any mental disorder were 3.0 and 55% in offspring of parents with anxiety disorders; 2.6 and 17% in offspring of those with psychosis; 2.1 and 55% in offspring of those with bipolar disorder; 1.9 and 51% in offspring of those with depressive disorders; and 1.5 and 38% in offspring of those with substance use disorders. The offspring's RR and lifetime risk of developing the same mental disorder diagnosed in their parent were 8.4 and 32% for attention-deficit/hyperactivity disorder; 5.8 and 8% for psychosis; 5.1 and 5% for bipolar disorder; 2.8 and 9% for substance use disorders; 2.3 and 14% for depressive disorders; 2.3 and 1% for eating disorders; and 2.2 and 31% for anxiety disorders. There were 37 significant transdiagnostic associations between parental mental disorders and the RR of developing a different mental disorder in the offspring. In offspring of parents with psychosis, bipolar and depressive disorder, the risk of the same disorder onset emerged at 16, 5 and 6 years, and cumulated to 3%, 19% and 24% by age 18; and to 8%, 36% and 46% by age 28. Heterogeneity ranged from 0 to 0.98, and 96% of studies were at high risk of bias. Sensitivity analyses restricted to prospective family high-risk studies confirmed the pattern of findings with similar RR, but with greater absolute risks compared to analyses of all study types. This study demonstrates at a global, meta-analytic level that offspring of affected parents have strongly elevated RR and lifetime risk of developing any mental disorder as well as the same mental disorder diagnosed in the parent. The transdiagnostic risks suggest that offspring of parents with a range of mental disorders should be considered as candidates for targeted primary prevention.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37673436b,

title = {Common and disorder-specific cortical thickness alterations in internalizing, externalizing and thought disorders during early adolescence: an Adolescent Brain and Cognitive Development study},

author = {Gechang Yu and Zhaowen Liu and Xinran Wu and Benjamin Becker and Kai Zhang and Huaxin Fan and Songjun Peng and Nanyu Kuang and Jujiao Kang and Guiying Dong and Xing-Ming Zhao and Gunter Schumann and Jianfeng Feng and Barbara J Sahakian and Trevor W Robbins and Lena Palaniyappan and Jie Zhang},

doi = {10.1503/jpn.220202},

issn = {1488-2434},

year  = {2023},

date = {2023-01-01},

journal = {J Psychiatry Neurosci},

volume = {48},

number = {5},

pages = {E345--E356},

abstract = {BACKGROUND: A growing body of neuroimaging studies has reported common neural abnormalities among mental disorders in adults. However, it is unclear whether the distinct disorder-specific mechanisms operate during adolescence despite the overlap among disorders.nnMETHODS: We studied a large cohort of more than 11 000 preadolescent (age 9-10 yr) children from the Adolescent Brain and Cognitive Development cohort. We adopted a regrouping approach to compare cortical thickness (CT) alterations and longitudinal changes between healthy controls ( = 4041) and externalizing ( = 1182), internalizing ( = 1959) and thought disorder ( = 347) groups. Genome-wide association study (GWAS) was performed on regional CT across 4468 unrelated European youth.nnRESULTS: Youth with externalizing or internalizing disorders exhibited increased regional CT compared with controls. Externalizing ( = 8 × 10, Cohen  = 0.10) and internalizing disorders ( = 2 × 10, Cohen  = 0.08) shared thicker CT in the left pars opercularis. The somatosensory and the primary auditory cortex were uniquely affected in externalizing disorders, whereas the primary motor cortex and higher-order visual association areas were uniquely affected in internalizing disorders. Only youth with externalizing disorders showed decelerated cortical thinning from age 10-12 years. The GWAS found 59 genome-wide significant associated genetic variants across these regions. Cortical thickness in common regions was associated with glutamatergic neurons, while internalizing-specific regional CT was associated with astrocytes, oligodendrocyte progenitor cells and GABAergic neurons.nnLIMITATIONS: The sample size of the GWAS was relatively small.nnCONCLUSION: Our study provides strong evidence for the presence of specificity in CT, developmental trajectories and underlying genetic underpinnings among externalizing and internalizing disorders during early adolescence. Our results support the neurobiological validity of the regrouping approach that could supplement the use of a dimensional approach in future clinical practice.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37667020b,

title = {Brain health in ethnically minority youth at risk for psychosis},

author = {Rachel A Rabin and Lena Palaniyappan},

doi = {10.1038/s41386-023-01719-9},

issn = {1740-634X},

year  = {2023},

date = {2023-11-01},

journal = {Neuropsychopharmacology},

volume = {48},

number = {12},

pages = {1701--1702},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37604823b,

title = {A longitudinal resource for population neuroscience of school-age children and adolescents in China},

author = {Xue-Ru Fan and Yin-Shan Wang and Da Chang and Ning Yang and Meng-Jie Rong and Zhe Zhang and Ye He and Xiaohui Hou and Quan Zhou and Zhu-Qing Gong and Li-Zhi Cao and Hao-Ming Dong and Jing-Jing Nie and Li-Zhen Chen and Qing Zhang and Jia-Xin Zhang and Lei Zhang and Hui-Jie Li and Min Bao and Antao Chen and Jing Chen and Xu Chen and Jinfeng Ding and Xue Dong and Yi Du and Chen Feng and Tingyong Feng and Xiaolan Fu and Li-Kun Ge and Bao Hong and Xiaomeng Hu and Wenjun Huang and Chao Jiang and Li Li and Qi Li and Su Li and Xun Liu and Fan Mo and Jiang Qiu and Xue-Quan Su and Gao-Xia Wei and Yiyang Wu and Haishuo Xia and Chao-Gan Yan and Zhi-Xiong Yan and Xiaohong Yang and Wenfang Zhang and Ke Zhao and Liqi Zhu and  and  and Xi-Nian Zuo},

doi = {10.1038/s41597-023-02377-8},

issn = {2052-4463},

year  = {2023},

date = {2023-08-01},

journal = {Sci Data},

volume = {10},

number = {1},

pages = {545},

abstract = {During the past decade, cognitive neuroscience has been calling for population diversity to address the challenge of validity and generalizability, ushering in a new era of population neuroscience. The developing Chinese Color Nest Project (devCCNP, 2013-2022), the first ten-year stage of the lifespan CCNP (2013-2032), is a two-stages project focusing on brain-mind development. The project aims to create and share a large-scale, longitudinal and multimodal dataset of typically developing children and adolescents (ages 6.0-17.9 at enrolment) in the Chinese population. The devCCNP houses not only phenotypes measured by demographic, biophysical, psychological and behavioural, cognitive, affective, and ocular-tracking assessments but also neurotypes measured with magnetic resonance imaging (MRI) of brain morphometry, resting-state function, naturalistic viewing function and diffusion structure. This Data Descriptor introduces the first data release of devCCNP including a total of 864 visits from 479 participants. Herein, we provided details of the experimental design, sampling strategies, and technical validation of the devCCNP resource. We demonstrate and discuss the potential of a multicohort longitudinal design to depict normative brain growth curves from the perspective of developmental population neuroscience. The devCCNP resource is shared as part of the "Chinese Data-sharing Warehouse for In-vivo Imaging Brain" in the Chinese Color Nest Project (CCNP) - Lifespan Brain-Mind Development Data Community ( https://ccnp.scidb.cn ) at the Science Data Bank.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37542243b,

title = {Neurodevelopmental risk and adaptation as a model for comorbidity among internalizing and externalizing disorders: genomics and cell-specific expression enriched morphometric study},

author = {Nanyu Kuang and Zhaowen Liu and Gechang Yu and Xinran Wu and Benjamin Becker and Huaxin Fan and Songjun Peng and Kai Zhang and Jiajia Zhao and Jujiao Kang and Guiying Dong and Xingming Zhao and Barbara J Sahakian and Trevor W Robbins and Wei Cheng and Jianfeng Feng and Gunter Schumann and Lena Palaniyappan and Jie Zhang},

doi = {10.1186/s12916-023-02920-9},

issn = {1741-7015},

year  = {2023},

date = {2023-08-01},

journal = {BMC Med},

volume = {21},

number = {1},

pages = {291},

abstract = {BACKGROUND: Comorbidity is the rule rather than the exception for childhood and adolescent onset mental disorders, but we cannot predict its occurrence and do not know the neural mechanisms underlying comorbidity. We investigate if the effects of comorbid internalizing and externalizing disorders on anatomical differences represent a simple aggregate of the effects on each disorder and if these comorbidity-associated cortical surface differences relate to a distinct genetic underpinning.nnMETHODS: We studied the cortical surface area (SA) and thickness (CT) of 11,878 preadolescents (9-10 years) from the Adolescent Brain and Cognitive Development Study. Linear mixed models were implemented in comparative and association analyses among internalizing (dysthymia, major depressive disorder, disruptive mood dysregulation disorder, agoraphobia, panic disorder, specific phobia, separation anxiety disorder, social anxiety disorder, generalized anxiety disorder, post-traumatic stress disorder), externalizing (attention-deficit/hyperactivity disorder, oppositional defiant disorder, conduct disorder) diagnostic groups, a group with comorbidity of the two and a healthy control group. Genome-wide association analysis (GWAS) and cell type specificity analysis were performed on 4468 unrelated European participants from this cohort.nnRESULTS: Smaller cortical surface area but higher thickness was noted across patient groups when compared to controls. Children with comorbid internalizing and externalizing disorders had more pronounced areal reduction than those without comorbidity, indicating an additive burden. In contrast, cortical thickness had a non-linear effect with comorbidity: the comorbid group had no significant CT differences, while those patient groups without comorbidity had significantly higher thickness compare to healthy controls. Distinct biological pathways were implicated in regional SA and CT differences. Specifically, CT differences were associated with immune-related processes implicating astrocytes and oligodendrocytes, while SA-related differences related mainly to inhibitory neurons.nnCONCLUSION: The emergence of comorbidity across distinct clusters of psychopathology is unlikely to be due to a simple additive neurobiological effect alone. Distinct developmental risk moderated by immune-related adaptation processes, with unique genetic and cell-specific factors, may contribute to underlying SA and CT differences. Children with the highest risk but lowest resilience, both captured in their developmental morphometry, may develop a comorbid illness pattern.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37480668b,

title = {Short communication: Prevalence of long-acting injectable antipsychotic use in Canadian early intervention services for psychosis},

author = {Kyle A McKee and Candice E Crocker and Katerina Dikaios and Nicola Otter and Andrea Bardell and Marc-André Roy and Amal Abdel-Baki and Lena Palaniyappan and Ashok Malla and Philip G Tibbo},

doi = {10.1016/j.jpsychires.2023.07.005},

issn = {1879-1379},

year  = {2023},

date = {2023-09-01},

journal = {J Psychiatr Res},

volume = {165},

pages = {77--82},

abstract = {The use of long-acting injectable (LAI) antipsychotic drugs for psychotic disorders in Canada has been historically low compared to other jurisdictions despite advantages of LAIs in improving medication adherence and preventing relapse. In response, treatment recommendations were developed in 2013 by the Canadian Consortium for Early Intervention in Psychosis and other Canadian provincial expert groups. The impact of these guidelines needed to be assessed. To document practices in LAI use in early intervention services (EIS) for psychosis, Canadian EIS were surveyed in 2016 (n = 18) and 2020 (n = 12). Trends and descriptive information were examined using repeated cross-sectional survey data. Eight EIS responded to surveys at both time points allowing for longitudinal comparisons. Outcomes of interest included i) LAI use frequency, ii) timing of LAI starts, and iii) factors influencing LAI use. Cross-sectional analysis identified a significant increase in overall LAI usage (24.7% in 2016; 35.1% in 2020). Longitudinal analysis indicated that patients in the second program year saw the greatest increase in LAI use between 2016 and 2020 (25.6% vs. 36.1%), especially among patients under community treatment orders (65.5% vs. 81.5%). Results support increases in LAI use over time, accessibility, awareness, and increasing comfortability among Canadian clinicians.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37443193b,

title = {Neural variability in three major psychiatric disorders},

author = {Wei Wei and Lihong Deng and Chunxia Qiao and Yubing Yin and Yamin Zhang and Xiaojing Li and Hua Yu and Lingqi Jian and Mingli Li and Wanjun Guo and Qiang Wang and Wei Deng and Xiaohong Ma and Liansheng Zhao and Pak C Sham and Lena Palaniyappan and Tao Li},

doi = {10.1038/s41380-023-02164-2},

issn = {1476-5578},

year  = {2023},

date = {2023-12-01},

journal = {Mol Psychiatry},

volume = {28},

number = {12},

pages = {5217--5227},

abstract = {Across the major psychiatric disorders (MPDs), a shared disruption in brain physiology is suspected. Here we investigate the neural variability at rest, a well-established behavior-relevant marker of brain function, and probe its basis in gene expression and neurotransmitter receptor profiles across the MPDs. We recruited 219 healthy controls and 279 patients with schizophrenia, major depressive disorder, or bipolar disorders (manic or depressive state). The standard deviation of blood oxygenation level-dependent signal (SD) obtained from resting-state fMRI was used to characterize neural variability. Transdiagnostic disruptions in SD patterns and their relationships with clinical symptoms and cognitive functions were tested by partial least-squares correlation. Moving beyond the clinical sample, spatial correlations between the observed patterns of SD disruption and postmortem gene expressions, Neurosynth meta-analytic cognitive functions, and neurotransmitter receptor profiles were estimated. Two transdiagnostic patterns of disrupted SD were discovered. Pattern 1 is exhibited in all diagnostic groups and is most pronounced in schizophrenia, characterized by higher SD in the language/auditory networks but lower SD in the default mode/sensorimotor networks. In comparison, pattern 2 is only exhibited in unipolar and bipolar depression, characterized by higher SD in the default mode/salience networks but lower SD in the sensorimotor network. The expression of pattern 1 related to the severity of clinical symptoms and cognitive deficits across MPDs. The two disrupted patterns had distinct spatial correlations with gene expressions (e.g., neuronal projections/cellular processes), meta-analytic cognitive functions (e.g., language/memory), and neurotransmitter receptor expression profiles (e.g., D2/serotonin/opioid receptors). In conclusion, neural variability is a potential transdiagnostic biomarker of MPDs with a substantial amount of its spatial distribution explained by gene expressions and neurotransmitter receptor profiles. The pathophysiology of MPDs can be traced through the measures of neural variability at rest, with varying clinical-cognitive profiles arising from differential spatial patterns of aberrant variability.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37402580b,

title = {Collaborative discontinuation of antipsychotics after the first episode of psychosis},

author = {Theo Korchia and Hani Abdelhafez and Alice Bretelle and Ridha Joober and Lena Palaniyappan},

doi = {10.1503/220223},

issn = {1488-2434},

year  = {2023},

date = {2023-01-01},

journal = {J Psychiatry Neurosci},

volume = {48},

number = {4},

pages = {E265--E266},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37352748b,

title = {Polygenic risk for schizophrenia and the language network: Putative compensatory reorganization in unaffected siblings},

author = {Xudong Chen and Wenjian Tan and Yixin Cheng and Danqing Huang and Dayi Liu and Jiamei Zhang and Jinyue Li and Zhening Liu and Yunzhi Pan and Lena Palaniyappan},

doi = {10.1016/j.psychres.2023.115319},

issn = {1872-7123},

year  = {2023},

date = {2023-08-01},

journal = {Psychiatry Res},

volume = {326},

pages = {115319},

abstract = {Language-related symptoms, such as disorganized, impoverished speech and communicative behaviors, are one of the core features of schizophrenia. These features most strongly correlate with cognitive deficits and polygenic risk among various symptom dimensions of schizophrenia. Nevertheless, unaffected siblings with genetic high-risk fail to show consistent deficits in language network (LN), indicating that either (1) polygenic risk has no notable effect on LN and/or (2) siblings show compensatory changes in opposing direction to patients. To answer this question, we related polygenic risk scores (PRS) to the region-level, tract-level, and systems-level structure (cortical thickness and fiber connectivity) of LN in 182 patients, 48 unaffected siblings and 135 healthy controls. We also studied the relationships between symptoms, language-related cognition, social functioning and LN structure. We observed a significantly lower thickness in LN (especially the Broca's, Wernicke's area and their right homologues) in patients. Siblings had a distinctly higher thickness in parts of the LN and a more pronounced small-world-like structural integration within the LN. Patients with reduced LN thickness had higher PRS, more disorganization and impoverished speech with lower language-related cognition and social functioning. We conclude that the genetic susceptibility and putative compensatory changes for schizophrenia operate, in part, via key regions in the Language Network.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37268433b,

title = {Association of Cortical Gyrification With Imaging and Serum Biomarkers in Patients With Parkinson Disease},

author = {Yuanchao Zhang and Yu Zhang and Chengjie Mao and Zhen Jiang and Guohua Fan and Erlei Wang and Yifan Chen and Lena Palaniyappan},

doi = {10.1212/WNL.0000000000207410},

issn = {1526-632X},

year  = {2023},

date = {2023-07-01},

journal = {Neurology},

volume = {101},

number = {3},

pages = {e311--e323},

abstract = {BACKGROUND AND OBJECTIVES: Pathologic progression across the cortex is a key feature of Parkinson disease (PD). Cortical gyrification is a morphologic feature of human cerebral cortex that is tightly linked to the integrity of underlying axonal connectivity. Monitoring cortical gyrification reductions may provide a sensitive marker of progression through structural connectivity, preceding the progressive stages of PD pathology. We aimed to examine the progressive cortical gyrification reductions and their associations with overlying cortical thickness, white matter (WM) integrity, striatum dopamine availability, serum neurofilament light (NfL) chain, and CSF α-synuclein levels in PD.nnMETHODS: This study included a longitudinal dataset with baseline (T0), 1-year (T1), and 4-year (T4) follow-ups and 2 cross-sectional datasets. Local gyrification index (LGI) was computed from T1-weighted MRI data to measure cortical gyrification. Fractional anisotropy (FA) was computed from diffusion-weighted MRI data to measure WM integrity. Striatal binding ratio (SBR) was measured from Ioflupane SPECT scans. Serum NfL and CSF α-synuclein levels were also measured.nnRESULTS: The longitudinal dataset included 113 patients with de novo PD and 55 healthy controls (HCs). The cross-sectional datasets included 116 patients with relatively more advanced PD and 85 HCs. Compared with HCs, patients with de novo PD showed accelerated LGI and FA reductions over 1-year period and a further decline at 4-year follow-up. Across the 3 time points, the LGI paralleled and correlated with FA ( = 0.002 at T0,  = 0.0214 at T1, and  = 0.0037 at T4) and SBR ( = 0.0095 at T0,  = 0.0035 at T1, and  = 0.0096 at T4) but not with overlying cortical thickness in patients with PD. Both LGI and FA correlated with serum NfL level (LGI:  < 0.0001 at T0,  = 0.0043 at T1; FA:  < 0.0001 at T0,  = 0.0001 at T1) but not with CSF α-synuclein level in patients with PD. In the 2 cross-sectional datasets, we revealed similar patterns of LGI and FA reductions and associations between LGI and FA in patients with more advanced PD.nnDISCUSSION: We demonstrated progressive reductions in cortical gyrification that were robustly associated with WM microstructure, striatum dopamine availability, and serum NfL level in PD. Our findings may contribute biomarkers for PD progression and potential pathways for early interventions of PD.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37266694b,

title = {Sex differences in the clinical presentation of early psychosis in a primary care setting},

author = {Brooke Carter and Rebecca Rodrigues and Jennifer Reid and Suzanne Archie and Amanda L Terry and Lena Palaniyappan and Arlene G MacDougall and Aristotle Voineskos and Saadia Hameed Jan and Liisa Jaakkimainen and Branson Chen and Neo Sawh and Kelly K Anderson},

doi = {10.1007/s00737-023-01329-w},

issn = {1435-1102},

year  = {2023},

date = {2023-08-01},

journal = {Arch Womens Ment Health},

volume = {26},

number = {4},

pages = {485--493},

abstract = {Primary care is an important part of the help-seeking pathway for young people experiencing early psychosis, but sex differences in clinical presentation in these settings are unexplored. We aimed to identify sex differences in clinical presentation to primary care services in the 1-year period prior to a first diagnosis of psychotic disorder. We identified first-onset cases of non-affective psychotic disorder over a 10-year period (2005-2015) using health administrative data linked with electronic medical records (EMRs) from primary care (n = 465). Detailed information on encounters in the year prior to first diagnosis was abstracted, including psychiatric symptoms, other relevant behaviours, and diagnoses recorded by the family physician (FP). We used modified Poisson regression models to examine sex differences in the signs, symptoms, and diagnoses recorded by the FP, adjusting for various clinical and sociodemographic factors. Positive symptoms (PR = 0.76, 95%CI: 0.58, 0.98) and substance use (PR = 0.54, 95%CI: 0.40, 0.72) were less prevalent in the medical records of women. Visits by women were more likely to be assigned a diagnosis of depression or anxiety (PR = 1.18, 95%CI: 1.00, 1.38), personality disorder (PR = 5.49, 95%CI: 1.22, 24.62), psychological distress (PR = 11.29, 95%CI: 1.23, 103.91), and other mental or behavioral disorders (PR = 3.49, 95%CI: 1.14, 10.66) and less likely to be assigned a diagnosis of addiction (PR = 0.33, 95%CI: 0.13, 0.87). We identified evidence of sex differences in the clinical presentation of early psychosis and recorded diagnoses in the primary care EMR. Further research is needed to better understand sex differences in clinical presentation in the primary care context, which can facilitate better understanding, detection, and intervention for first-episode psychotic disorders.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37253483b,

title = {Opening up mental health research},

author = {Isabel O L Bacellar and Geneviève Morin and Sylvanne Daniels and Gustavo Turecki and Lena Palaniyappan and Martin Lepage},

doi = {10.1503/jpn.220199},

issn = {1488-2434},

year  = {2023},

date = {2023-01-01},

journal = {J Psychiatry Neurosci},

volume = {48},

number = {3},

pages = {E209--E216},

abstract = {Open science provides a compelling framework for accelerating global collaborations and enabling discoveries to understand and treat mental health disorders. Herein, we discuss the advantages and obstacles to adopting open science in mental health research, considering the particularities of sensitive and diverse data types, the potential of co-designing projects with research participants and the opportunity of amplifying open science by integration with mental health care. We present a practical example of how this landscape may be navigated to adopt open science across an entire research centre, in 5 steps, namely leadership committing to open science; finding models, resources and allies; identifying needs; defining open science principles; and putting principles into practice. We derive lessons learned that can be built upon by researchers and research organizations joining the open science movement in mental health.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37158213b,

title = {Cortical morphological heterogeneity of schizophrenia and its relationship with glutamatergic receptor variations},

author = {Xuan Ouyang and Yunzhi Pan and Xudong Chen and Guowei Wu and Yixin Cheng and Wenjian Tan and Manqi Zhang and Mengjie Deng and Zhening Liu and Lena Palaniyappan},

doi = {10.1192/j.eurpsy.2023.2408},

issn = {1778-3585},

year  = {2023},

date = {2023-05-01},

journal = {Eur Psychiatry},

volume = {66},

number = {1},

pages = {e38},

abstract = {BACKGROUND: Recent genetic evidence implicates glutamatergic-receptor variations in schizophrenia. Glutamatergic excess during early life in people with schizophrenia may cause excitotoxicity and produce structural deficits in the brain. Cortical thickness and gyrification are reduced in schizophrenia, but only a subgroup of patients exhibits such structural deficits. We delineate the structural variations among unaffected siblings and patients with schizophrenia and study the role of key glutamate-receptor polymorphisms on these variations.nnMETHODS: Gaussian Mixture Model clustering was applied to the cortical thickness and gyrification data of 114 patients, 112 healthy controls, and 42 unaffected siblings to identify subgroups. The distribution of glutamate-receptor (GRM3, GRIN2A, and GRIA1) and voltage-gated calcium channel (CACNA1C) variations across the MRI-based subgroups was studied. The comparisons in clinical symptoms and cognition between patient subgroups were conducted.nnRESULTS: We observed a "hypogyric," "impoverished-thickness," and "supra-normal" subgroups of patients, with higher negative symptom burden and poorer verbal fluency in the hypogyric subgroup and notable functional deterioration in the impoverished-thickness subgroup. Compared to healthy subjects, the hypogyric subgroup had significant GRIN2A and GRM3 variations, the impoverished-thickness subgroup had CACNA1C variations while the supra-normal group had no differences.nnCONCLUSIONS: Disrupted gyrification and thickness can be traced to the glutamatergic receptor and voltage-gated calcium channel dysfunction respectively in schizophrenia. This raises the question of whether MRI-based multimetric subtyping may be relevant for clinical trials of agents affecting the glutamatergic system.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37124249b,

title = {More than words: Speech production in first-episode psychosis predicts later social and vocational functioning},

author = {Michael Mackinley and Roberto Limongi and Angélica María Silva and Julie Richard and Priya Subramanian and Hooman Ganjavi and Lena Palaniyappan},

doi = {10.3389/fpsyt.2023.1144281},

issn = {1664-0640},

year  = {2023},

date = {2023-01-01},

journal = {Front Psychiatry},

volume = {14},

pages = {1144281},

abstract = {BACKGROUND: Several disturbances in speech are present in psychosis; however, the relationship between these disturbances during the first-episode of psychosis (FEP) and later vocational functioning is unclear. Demonstrating this relationship is critical if we expect speech and communication deficits to emerge as targets for early intervention.nnMETHOD: We analyzed three 1-min speech samples using automated speech analysis and Bayes networks in an antipsychotic-naive sample of 39 FEP patients and followed them longitudinally to determine their vocational status (engaged or not engaged in employment education or training-EET vs. NEET) after 6-12 months of treatment. Five baseline linguistic variables with prior evidence of clinical relevance (total and acausal connectives use, pronoun use, analytic thinking, and total words uttered in a limited period) were included in a Bayes network along with follow-up NEET status and Social and Occupational Functioning Assessment Scale (SOFAS) scores to determine dependencies among these variables. We also included clinical (Positive and Negative Syndrome Scale 8-item version (PANSS-8)), social (parental socioeconomic status), and cognitive features (processing speed) at the time of presentation as covariates.nnRESULTS: The Bayes network revealed that only total words spoken at the baseline assessment were directly associated with later NEET status and had an indirect association with SOFAS, with a second set of dependencies emerging among the remaining linguistic variables. The primary (speech-only) model outperformed models including parental socioeconomic status, processing speed or both as latent variables.nnCONCLUSION: Impoverished speech, even at subclinical levels, may hold prognostic value for functional outcomes and warrant consideration when providing measurement based care for first-episode psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37121089b,

title = {Non-linear variations in glutamate dynamics during a cognitive task engagement in schizophrenia},

author = {James W C Graham and Peter Jeon and Jean Théberge and Lena Palaniyappan},

doi = {10.1016/j.pscychresns.2023.111640},

issn = {1872-7506},

year  = {2023},

date = {2023-07-01},

journal = {Psychiatry Res Neuroimaging},

volume = {332},

pages = {111640},

abstract = {To investigate the role of glutamate in psychosis, we employ functional magnetic resonance spectroscopy at an ultra-high magnetic field (7T) and employ fuzzy-approximate entropy (F-ApEn) and Hurst Exponent (HE) to capture time-varying nature of glutamate signaling during a cognitive task. We recruited thirty first-episode psychosis patients (FEP) with age- and gender-matched healthy controls (HC) and administered the Color-Word Stroop paradigm, providing 128 raw MRS time-points per subject over a period of 16 min. We then performed metabolite quantification of glutamate in the dorsal anterior cingulate cortex, a region reliably activated during the Stroop task. Symptoms/cognitive functioning was measured using Positive and Negative Syndrome Scale-8 score, Social and Occupational Functioning (SOFAS) score, digit symbol) coding score, and Stroop accuracy. These scores were related to the Entropy/HE data from the overall glutamate time-series. Patients with FEP had significantly higher HE compared to HC, with individuals displaying significantly higher HE having lower functional performance (SOFAS) in both HC and FEP groups. Among healthy individuals, higher HE also indicated significantly lower cognitive function through Stroop accuracy and DSST scores. F-ApEn had an inverse Pearson correlation with HE, and tracked diagnosis, cognition and function as expected, but with lower effect sizes not reaching statistical significance. We demonstrate notable diagnostic differences in the temporal course of glutamate signaling during a cognitive task in psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid37014101b,

title = {Atypical hemispheric lateralization of brain function and structure in autism: a comprehensive meta-analysis study},

author = {Qingqing Li and Wei Zhao and Lena Palaniyappan and Shuixia Guo},

doi = {10.1017/S0033291723000181},

issn = {1469-8978},

year  = {2023},

date = {2023-10-01},

journal = {Psychol Med},

volume = {53},

number = {14},

pages = {6702--6713},

abstract = {BACKGROUND: Characteristic changes in the asymmetric nature of the human brain are associated with neurodevelopmental differences related to autism. In people with autism, these differences are thought to affect brain structure and function, although the structural and functional bases of these defects are yet to be fully characterized.nnMETHODS: We applied a comprehensive meta-analysis to resting-state functional and structural magnetic resonance imaging datasets from 370 people with autism and 498 non-autistic controls using seven datasets of the Autism Brain Imaging Data Exchange Project. We studied the meta-effect sizes based on standardized mean differences and standard deviations (s.d.) for lateralization of gray matter volume (GMV), fractional amplitude of low-frequency fluctuation (fALFF), and regional homogeneity (ReHo). We examined the functional correlates of atypical laterality through an indirect annotation approach followed by a direct correlation analysis with symptom scores.nnRESULTS: In people with autism, 85, 51, and 51% of brain regions showed a significant diagnostic effect for lateralization in GMV, fALFF, and ReHo, respectively. Among these regions, 35.7% showed overlapping differences in lateralization in GMV, fALFF, and ReHo, particularly in regions with functional annotations for language, motor, and perceptual functions. These differences were associated with clinical measures of reciprocal social interaction, communication, and repetitive behaviors. A meta-analysis based on s.d. showed that people with autism had lower variability in structural lateralization but higher variability in functional lateralization.nnCONCLUSION: These findings highlight that atypical hemispheric lateralization is a consistent feature in autism across different sites and may be used as a neurobiological marker for autism.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36959745b,

title = {Competencies for Repetitive Transcranial Magnetic Stimulation in Postgraduate Medical Education: Expert Consensus Using a Modified Delphi Process},

author = {Ka Sing Paris Lai and Robyn Waxman and Daniel M Blumberger and Peter Giacobbe and Gary Hasey and Lisa McMurray and Roumen Milev and Lena Palaniyappan and Rajamannar Ramasubbu and Yuri E Rybak and Tegan Sacevich and Fidel Vila-Rodriguez and Amer M Burhan},

doi = {10.1177/07067437231164571},

issn = {1497-0015},

year  = {2023},

date = {2023-12-01},

journal = {Can J Psychiatry},

volume = {68},

number = {12},

pages = {916--924},

abstract = {BACKGROUND: Repetitive transcranial magnetic stimulation (rTMS) is recommended in Canadian guidelines as a first-line treatment for major depressive disorder. With the shift towards competency-based medical education, it remains unclear how to determine when a resident is considered competent in applying knowledge of rTMS to patient care. Given inconsistencies between postgraduate training programmes with regards to training requirements, defining competencies will improve the standard of care in rTMS delivery.nnOBJECTIVE: The goal of this study was to develop competencies for rTMS that can be implemented into a competency-based training curriculum in postgraduate training programmes.nnMETHODS: A working group drafted competencies for postgraduate psychiatry trainees. Fourteen rTMS experts from across Canada were invited to participate in the modified Delphi process.nnRESULTS: Ten experts participated in all three rounds of the modified Delphi process. A total of 20 items reached a consensus. There was improvement in the Cronbach's alpha over the rounds of modified Delphi process (Cronbach's alpha increased from 0.554 to 0.824) suggesting improvement in internal consistency. The intraclass correlation coefficient (ICC) increased from 0.543 to 0.805 suggesting improved interrater agreement.nnCONCLUSIONS: This modified Delphi process resulted in expert consensus on competencies to be acquired during postgraduate medical education programmes where a learner is training to become competent as a consultant and/or practitioner in rTMS treatment. This is a field that still requires development, and it is expected that as more evidence emerges the competencies will be further refined. These results will help the development of other curricula in interventional psychiatry.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36946528b,

title = {Active Inference, Epistemic Value, and Uncertainty in Conceptual Disorganization in First-Episode Schizophrenia},

author = {Roberto Limongi and Angelica M Silva and Michael Mackinley and Sabrina D Ford and Lena Palaniyappan},

doi = {10.1093/schbul/sbac125},

issn = {1745-1701},

year  = {2023},

date = {2023-03-01},

journal = {Schizophr Bull},

volume = {49},

number = {Suppl_2},

pages = {S115--S124},

abstract = {BACKGROUND AND HYPOTHESIS: Active inference has become an influential concept in psychopathology. We apply active inference to investigate conceptual disorganization in first-episode schizophrenia. We conceptualize speech production as a decision-making process affected by the latent "conceptual organization"-as a special case of uncertainty about the causes of sensory information. Uncertainty is both minimized via speech production-in which function words index conceptual organization in terms of analytic thinking-and tracked by a domain-general salience network. We hypothesize that analytic thinking depends on conceptual organization. Therefore, conceptual disorganization in schizophrenia would be both indexed by low conceptual organization and reflected in the effective connectivity within the salience network.nnSTUDY DESIGN: With 1-minute speech samples from a picture description task and resting state fMRI from 30 patients and 30 healthy subjects, we employed dynamic causal and probabilistic graphical models to investigate if the effective connectivity of the salience network underwrites conceptual organization.nnSTUDY RESULTS: Low analytic thinking scores index low conceptual organization which affects diagnostic status. The influence of the anterior insula on the anterior cingulate cortex and the self-inhibition within the anterior cingulate cortex are elevated given low conceptual organization (ie, conceptual disorganization).nnCONCLUSIONS: Conceptual organization, a construct that explains formal thought disorder, can be modeled in an active inference framework and studied in relation to putative neural substrates of disrupted language in schizophrenia. This provides a critical advance to move away from rating-scale scores to deeper constructs in the pursuit of the pathophysiology of formal thought disorder.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36946526b,

title = {Natural Language Processing Markers for Psychosis and Other Psychiatric Disorders: Emerging Themes and Research Agenda From a Cross-Linguistic Workshop},

author = {Hugo Corona Hernández and Cheryl Corcoran and Amélie M Achim and Janna N de Boer and Tessel Boerma and Sanne G Brederoo and Guillermo A Cecchi and Silvia Ciampelli and Brita Elvevåg and Riccardo Fusaroli and Silvia Giordano and Mathias Hauglid and Arjan van Hessen and Wolfram Hinzen and Philipp Homan and Sybren F de Kloet and Sanne Koops and Gina R Kuperberg and Kritika Maheshwari and Natalia B Mota and Alberto Parola and Roberta Rocca and Iris E C Sommer and Khiet Truong and Alban E Voppel and Marieke van Vugt and Frank Wijnen and Lena Palaniyappan},

doi = {10.1093/schbul/sbac215},

issn = {1745-1701},

year  = {2023},

date = {2023-03-01},

journal = {Schizophr Bull},

volume = {49},

number = {Suppl_2},

pages = {S86--S92},

abstract = {This workshop summary on natural language processing (NLP) markers for psychosis and other psychiatric disorders presents some of the clinical and research issues that NLP markers might address and some of the activities needed to move in that direction. We propose that the optimal development of NLP markers would occur in the context of research efforts to map out the underlying mechanisms of psychosis and other disorders. In this workshop, we identified some of the challenges to be addressed in developing and implementing NLP markers-based Clinical Decision Support Systems (CDSSs) in psychiatric practice, especially with respect to psychosis. Of note, a CDSS is meant to enhance decision-making by clinicians by providing additional relevant information primarily through software (although CDSSs are not without risks). In psychiatry, a field that relies on subjective clinical ratings that condense rich temporal behavioral information, the inclusion of computational quantitative NLP markers can plausibly lead to operationalized decision models in place of idiosyncratic ones, although ethical issues must always be paramount.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36946524b,

title = {Language and Psychosis: Tightening the Association},

author = {Eric J Tan and Iris E C Sommer and Lena Palaniyappan},

doi = {10.1093/schbul/sbac211},

issn = {1745-1701},

year  = {2023},

date = {2023-03-01},

journal = {Schizophr Bull},

volume = {49},

number = {Suppl_2},

pages = {S83--S85},

abstract = {This special issue of DISCOURSE in Psychosis focuses on the role of language in psychosis, including the relationships between formal thought disorder and conceptual disorganization, with speech and language markers and the neural mechanisms underlying these features in psychosis. It also covers the application of computational techniques in the study of language in psychosis, as well as the potential for using speech and language data for digital phenotyping in psychiatry.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36913907b,

title = {Aberrant frontal lobe "U"-shaped association fibers in first-episode schizophrenia: A 7-Tesla Diffusion Imaging Study},

author = {Jason Kai and Michael Mackinley and Ali R Khan and Lena Palaniyappan},

doi = {10.1016/j.nicl.2023.103367},

issn = {2213-1582},

year  = {2023},

date = {2023-01-01},

journal = {Neuroimage Clin},

volume = {38},

pages = {103367},

abstract = {Schizophrenia is believed to be a developmental disorder with one hypothesis suggesting that symptoms arise due to abnormal interactions (or disconnectivity) between different brain regions. While some major deep white matter pathways have been extensively studied (e.g. arcuate fasciculus), studies of short-ranged, "U"-shaped tracts have been limited in patients with schizophrenia, in part due to the sheer abundance of tracts present and due to the spatial variations across individuals that defy probabilistic characterization in the absence of reliable templates. In this study, we use diffusion magnetic resonance imaging (dMRI) to investigate frontal lobe superficial white matter that are present in the majority of study participants, comparing healthy controls and minimally treated patients with first-episode schizophrenia (<3 median days of lifetime treatment). Through group comparisons, 3 out of 63 frontal lobe "U"-shaped tracts were found to demonstrate localized aberrations affecting the microstructural tissue properties (via diffusion tensor metrics) in this early stage of disease. No associations were found in patients between aberrant segments of affected tracts and clinical or cognitive variables. Aberrations in the frontal lobe "U"-shaped tracts in early untreated stages of psychosis occur irrespective of symptom burden, and are distributed across critical functional networks associated with executive function and salience processing. While we limited the investigation to the frontal lobe, a framework has been developed to study such connections in other brain regions, enabling further extensive investigations jointly with the major deep white matter pathways.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36806762b,

title = {Variability and magnitude of brain glutamate levels in schizophrenia: a meta and mega-analysis},

author = {Kate Merritt and Robert A McCutcheon and André Aleman and Sarah Ashley and Katherine Beck and Wolfgang Block and Oswald J N Bloemen and Faith Borgan and Christiana Boules and Juan R Bustillo and Aristides A Capizzano and Jennifer M Coughlin and Anthony David and Camilo de la Fuente-Sandoval and Arsime Demjaha and Kara Dempster and Kim Q Do and Fei Du and Peter Falkai and Beata Galińska-Skok and Jürgen Gallinat and Charles Gasparovic and Cedric E Ginestet and Naoki Goto and Ariel Graff-Guerrero and Beng-Choon Ho and Oliver Howes and Sameer Jauhar and Peter Jeon and Tadafumi Kato and Charles A Kaufmann and Lawrence S Kegeles and Matcheri S Keshavan and Sang-Young Kim and Bridget King and Hiroshi Kunugi and J Lauriello and Pablo León-Ortiz and Edith Liemburg and Meghan E Mcilwain and Gemma Modinos and Elias Mouchlianitis and Jun Nakamura and Igor Nenadic and Dost Öngür and Miho Ota and Lena Palaniyappan and Christos Pantelis and Tulsi Patel and Eric Plitman and Sotirios Posporelis and Scot E Purdon and Jürgen R Reichenbach and Perry F Renshaw and Francisco Reyes-Madrigal and Bruce R Russell and Akira Sawa and Martin Schaefer and Dikoma C Shungu and Stefan Smesny and Jeffrey A Stanley and James Stone and Agata Szulc and Reggie Taylor and Katharine N Thakkar and Jean Théberge and Philip G Tibbo and Thérèse van Amelsvoort and Jerzy Walecki and Peter C Williamson and Stephen J Wood and Lijing Xin and Hidenori Yamasue and Philip McGuire and Alice Egerton and },

doi = {10.1038/s41380-023-01991-7},

issn = {1476-5578},

year  = {2023},

date = {2023-05-01},

journal = {Mol Psychiatry},

volume = {28},

number = {5},

pages = {2039--2048},

abstract = {Glutamatergic dysfunction is implicated in schizophrenia pathoaetiology, but this may vary in extent between patients. It is unclear whether inter-individual variability in glutamate is greater in schizophrenia than the general population. We conducted meta-analyses to assess (1) variability of glutamate measures in patients relative to controls (log coefficient of variation ratio: CVR); (2) standardised mean differences (SMD) using Hedges g; (3) modal distribution of individual-level glutamate data (Hartigan's unimodality dip test). MEDLINE and EMBASE databases were searched from inception to September 2022 for proton magnetic resonance spectroscopy (1H-MRS) studies reporting glutamate, glutamine or Glx in schizophrenia. 123 studies reporting on 8256 patients and 7532 controls were included. Compared with controls, patients demonstrated greater variability in glutamatergic metabolites in the medial frontal cortex (MFC, glutamate: CVR = 0.15, p < 0.001; glutamine: CVR = 0.15, p = 0.003; Glx: CVR = 0.11, p = 0.002), dorsolateral prefrontal cortex (glutamine: CVR = 0.14, p = 0.05; Glx: CVR = 0.25, p < 0.001) and thalamus (glutamate: CVR = 0.16, p = 0.008; Glx: CVR = 0.19, p = 0.008). Studies in younger, more symptomatic patients were associated with greater variability in the basal ganglia (BG glutamate with age: z = -0.03, p = 0.003, symptoms: z = 0.007, p = 0.02) and temporal lobe (glutamate with age: z = -0.03, p = 0.02), while studies with older, more symptomatic patients associated with greater variability in MFC (glutamate with age: z = 0.01, p = 0.02, glutamine with symptoms: z = 0.01, p = 0.02). For individual patient data, most studies showed a unimodal distribution of glutamatergic metabolites. Meta-analysis of mean differences found lower MFC glutamate (g = -0.15, p = 0.03), higher thalamic glutamine (g = 0.53, p < 0.001) and higher BG Glx in patients relative to controls (g = 0.28, p < 0.001). Proportion of males was negatively associated with MFC glutamate (z = -0.02, p < 0.001) and frontal white matter Glx (z = -0.03, p = 0.02) in patients relative to controls. Patient PANSS total score was positively associated with glutamate SMD in BG (z = 0.01, p = 0.01) and temporal lobe (z = 0.05, p = 0.008). Further research into the mechanisms underlying greater glutamatergic metabolite variability in schizophrenia and their clinical consequences may inform the identification of patient subgroups for future treatment strategies.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36732587b,

title = {Longitudinal changes in brain metabolites in healthy controls and patients with first episode psychosis: a 7-Tesla MRS study},

author = {Min Wang and Peter B Barker and Nicola G Cascella and Jennifer M Coughlin and Gerald Nestadt and Frederick C Nucifora and Thomas W Sedlak and Alexandra Kelly and Laurent Younes and Donald Geman and Lena Palaniyappan and Akira Sawa and Kun Yang},

doi = {10.1038/s41380-023-01969-5},

issn = {1476-5578},

year  = {2023},

date = {2023-05-01},

journal = {Mol Psychiatry},

volume = {28},

number = {5},

pages = {2018--2029},

abstract = {Seven Tesla magnetic resonance spectroscopy (7T MRS) offers a precise measurement of metabolic levels in the human brain via a non-invasive approach. Studying longitudinal changes in brain metabolites could help evaluate the characteristics of disease over time. This approach may also shed light on how the age of study participants and duration of illness may influence these metabolites. This study used 7T MRS to investigate longitudinal patterns of brain metabolites in young adulthood in both healthy controls and patients. A four-year longitudinal cohort with 38 patients with first episode psychosis (onset within 2 years) and 48 healthy controls was used to examine 10 brain metabolites in 5 brain regions associated with the pathophysiology of psychosis in a comprehensive manner. Both patients and controls were found to have significant longitudinal reductions in glutamate in the anterior cingulate cortex (ACC). Only patients were found to have a significant decrease over time in γ-aminobutyric acid, N-acetyl aspartate, myo-inositol, total choline, and total creatine in the ACC. Together we highlight the ACC with dynamic changes in several metabolites in early-stage psychosis, in contrast to the other 4 brain regions that also are known to play roles in psychosis. Meanwhile, glutathione was uniquely found to have a near zero annual percentage change in both patients and controls in all 5 brain regions during a four-year follow-up in young adulthood. Given that a reduction of the glutathione in the ACC has been reported as a feature of treatment-refractory psychosis, this observation further supports the potential of glutathione as a biomarker for this subset of patients with psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36712574b,

title = {Subcortical Origin of Salience Processing Deficits in Schizophrenia},

author = {Lena Palaniyappan},

doi = {10.1016/j.bpsgos.2021.12.008},

issn = {2667-1743},

year  = {2023},

date = {2023-01-01},

journal = {Biol Psychiatry Glob Open Sci},

volume = {3},

number = {1},

pages = {6--7},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36702660b,

title = {Integrative Brain Network and Salience Models of Psychopathology and Cognitive Dysfunction in Schizophrenia},

author = {Vinod Menon and Lena Palaniyappan and Kaustubh Supekar},

doi = {10.1016/j.biopsych.2022.09.029},

issn = {1873-2402},

year  = {2023},

date = {2023-07-01},

journal = {Biol Psychiatry},

volume = {94},

number = {2},

pages = {108--120},

abstract = {Brain network models of cognitive control are central to advancing our understanding of psychopathology and cognitive dysfunction in schizophrenia. This review examines the role of large-scale brain organization in schizophrenia, with a particular focus on a triple-network model of cognitive control and its role in aberrant salience processing. First, we provide an overview of the triple network involving the salience, frontoparietal, and default mode networks and highlight the central role of the insula-anchored salience network in the aberrant mapping of salient external and internal events in schizophrenia. We summarize the extensive evidence that has emerged from structural, neurochemical, and functional brain imaging studies for aberrancies in these networks and their dynamic temporal interactions in schizophrenia. Next, we consider the hypothesis that atypical striatal dopamine release results in misattribution of salience to irrelevant external stimuli and self-referential mental events. We propose an integrated triple-network salience-based model incorporating striatal dysfunction and sensitivity to perceptual and cognitive prediction errors in the insula node of the salience network and postulate that dysregulated dopamine modulation of salience network-centered processes contributes to the core clinical phenotype of schizophrenia. Thus, a powerful paradigm to characterize the neurobiology of schizophrenia emerges when we combine conceptual models of salience with large-scale cognitive control networks in a unified manner. We conclude by discussing potential therapeutic leads on restoring brain network dysfunction in schizophrenia.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36637216b,

title = {Evaluating test-retest reliability and sex-/age-related effects on temporal clustering coefficient of dynamic functional brain networks},

author = {Yicheng Long and Xuan Ouyang and Chaogan Yan and Zhipeng Wu and Xiaojun Huang and Weidan Pu and Hengyi Cao and Zhening Liu and Lena Palaniyappan},

doi = {10.1002/hbm.26202},

issn = {1097-0193},

year  = {2023},

date = {2023-04-01},

journal = {Hum Brain Mapp},

volume = {44},

number = {6},

pages = {2191--2208},

abstract = {The multilayer dynamic network model has been proposed as an effective method to understand the brain function. In particular, derived from the definition of clustering coefficient in static networks, the temporal clustering coefficient provides a direct measure of the topological stability of dynamic brain networks and shows potential in predicting altered brain functions. However, test-retest reliability and demographic-related effects on this measure remain to be evaluated. Using a data set from the Human Connectome Project (157 male and 180 female healthy adults; 22-37 years old), the present study investigated: (1) the test-retest reliability of temporal clustering coefficient across four repeated resting-state functional magnetic resonance imaging scans as measured by intraclass correlation coefficient (ICC); and (2) sex- and age-related effects on temporal clustering coefficient. The results showed that (1) the temporal clustering coefficient had overall moderate test-retest reliability (ICC > 0.40 over a wide range of densities) at both global and subnetwork levels, (2) female subjects showed significantly higher temporal clustering coefficient than males at both global and subnetwork levels, particularly within the default-mode and subcortical regions, and (3) temporal clustering coefficient of the subcortical subnetwork was positively correlated with age in young adults. The results of sex effects were robustly replicated in an independent REST-meta-MDD data set, while the results of age effects were not. Our findings suggest that the temporal clustering coefficient is a relatively reliable and reproducible approach for identifying individual differences in brain function, and provide evidence for demographically related effects on the human brain dynamic connectomes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36624107b,

title = {Gray matter volume drives the brain age gap in schizophrenia: a SHAP study},

author = {Pedro L Ballester and Jee Su Suh and Natalie C W Ho and Liangbing Liang and Stefanie Hassel and Stephen C Strother and Stephen R Arnott and Luciano Minuzzi and Roberto B Sassi and Raymond W Lam and Roumen Milev and Daniel J Müller and Valerie H Taylor and Sidney H Kennedy and James P Reilly and Lena Palaniyappan and Katharine Dunlop and Benicio N Frey},

doi = {10.1038/s41537-022-00330-z},

issn = {2754-6993},

year  = {2023},

date = {2023-01-01},

journal = {Schizophrenia (Heidelb)},

volume = {9},

number = {1},

pages = {3},

abstract = {Neuroimaging-based brain age is a biomarker that is generated by machine learning (ML) predictions. The brain age gap (BAG) is typically defined as the difference between the predicted brain age and chronological age. Studies have consistently reported a positive BAG in individuals with schizophrenia (SCZ). However, there is little understanding of which specific factors drive the ML-based brain age predictions, leading to limited biological interpretations of the BAG. We gathered data from three publicly available databases - COBRE, MCIC, and UCLA - and an additional dataset (TOPSY) of early-stage schizophrenia (82.5% untreated first-episode sample) and calculated brain age with pre-trained gradient-boosted trees. Then, we applied SHapley Additive Explanations (SHAP) to identify which brain features influence brain age predictions. We investigated the interaction between the SHAP score for each feature and group as a function of the BAG. These analyses identified total gray matter volume (group × SHAP interaction term β = 1.71 [0.53; 3.23]; p < 0.03) as the feature that influences the BAG observed in SCZ among the brain features that are most predictive of brain age. Other brain features also presented differences in SHAP values between SCZ and HC, but they were not significantly associated with the BAG. We compared the findings with a non-psychotic depression dataset (CAN-BIND), where the interaction was not significant. This study has important implications for the understanding of brain age prediction models and the BAG in SCZ and, potentially, in other psychiatric disorders.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36596590b,

title = {Utilizing pharmacogenetics when treating first episode psychosis},

author = {Theo Korchia and Ridha Joober and Raphaelle Richieri and Priyadharshini Sabesan and Lena Palaniyappan},

doi = {10.1503/jpn.220154},

issn = {1488-2434},

year  = {2023},

date = {2023-01-01},

journal = {J Psychiatry Neurosci},

volume = {48},

number = {1},

pages = {E11--E12},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36473996b,

title = {Morphometric dis-similarity between cortical and subcortical areas underlies cognitive function and psychiatric symptomatology: a preadolescence study from ABCD},

author = {Xinran Wu and Lena Palaniyappan and Gechang Yu and Kai Zhang and Jakob Seidlitz and Zhaowen Liu and Xiangzhen Kong and Gunter Schumann and Jianfeng Feng and Barbara J Sahakian and Trevor W Robbins and Edward Bullmore and Jie Zhang},

doi = {10.1038/s41380-022-01896-x},

issn = {1476-5578},

year  = {2023},

date = {2023-03-01},

journal = {Mol Psychiatry},

volume = {28},

number = {3},

pages = {1146--1158},

abstract = {Preadolescence is a critical period characterized by dramatic morphological changes and accelerated cortico-subcortical development. Moreover, the coordinated development of cortical and subcortical regions underlies the emerging cognitive functions during this period. Deviations in this maturational coordination may underlie various psychiatric disorders that begin during preadolescence, but to date these deviations remain largely uncharted. We constructed a comprehensive whole-brain morphometric similarity network (MSN) from 17 neuroimaging modalities in a large preadolescence sample (N = 8908) from Adolescent Brain Cognitive Development (ABCD) study and investigated its association with 10 cognitive subscales and 27 psychiatric subscales or diagnoses. Based on the MSNs, each brain was clustered into five modules with distinct cytoarchitecture and evolutionary relevance. While morphometric correlation was positive within modules, it was negative between modules, especially between isocortical and paralimbic/subcortical modules; this developmental dissimilarity was genetically linked to synapse and neurogenesis. The cortico-subcortical dissimilarity becomes more pronounced longitudinally in healthy children, reflecting developmental differentiation of segregated cytoarchitectonic areas. Higher cortico-subcortical dissimilarity (between the isocortical and paralimbic/subcortical modules) were related to better cognitive performance. In comparison, children with poor modular differentiation between cortex and subcortex displayed higher burden of externalizing and internalizing symptoms. These results highlighted cortical-subcortical morphometric dissimilarity as a dynamic maturational marker of cognitive and psychiatric status during the preadolescent stage and provided insights into brain development.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36403173b,

title = {Patient and Physician Factors Associated with First Diagnosis of Non-affective Psychotic Disorder in Primary Care},

author = {Joshua C Wiener and Rebecca Rodrigues and Jennifer N S Reid and Suzanne Archie and Richard G Booth and Chiachen Cheng and Saadia Hameed Jan and Paul Kurdyak and Arlene G MacDougall and Lena Palaniyappan and Bridget L Ryan and Kelly K Anderson and },

doi = {10.1007/s10488-022-01233-y},

issn = {1573-3289},

year  = {2023},

date = {2023-03-01},

journal = {Adm Policy Ment Health},

volume = {50},

number = {2},

pages = {212--224},

abstract = {Primary care physicians play a central role in pathways to care for first-episode psychosis, and their increased involvement in early detection could improve service-related outcomes. The aim of this study was to estimate the proportion of psychosis first diagnosed in primary care, and identify associated patient and physician factors. We used linked health administrative data to construct a retrospective cohort of people aged 14-35 years with a first diagnosis of non-affective psychosis in Ontario, Canada between 2005-2015. We restricted the sample to patients with help-seeking contacts for mental health reasons in primary care in the six months prior to first diagnosis of psychotic disorder. We used modified Poisson regression models to examine patient and physician factors associated with a first diagnosis of psychosis in primary care. Among people with early psychosis (n = 39,449), 63% had help-seeking contacts in primary care within six months prior to first diagnosis. Of those patients, 47% were diagnosed in primary care and 53% in secondary/tertiary care. Patients factors associated with lower likelihood of diagnosis in primary care included male sex, younger age, immigrant status, and comorbid psychosocial conditions. Physician factors associated with lower likelihood of diagnosis in primary care included solo practice model, urban practice setting, international medical education, and longer time since graduation. Our findings indicate that primary care is an important contact for help-seeking and diagnosis for a large proportion of people with early psychosis. For physicians less likely to diagnose psychosis in primary care, targeted resources and interventions could be provided to support them in caring for patients with early psychosis.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36376466b,

title = {Working memory processing deficit associated with a nonlinear response pattern of the anterior cingulate cortex in first-episode and drug-naïve schizophrenia},

author = {Nana Feng and Lena Palaniyappan and Trevor W Robbins and Luolong Cao and Shuanfeng Fang and Xingwei Luo and Xiang Wang and Qiang Luo},

doi = {10.1038/s41386-022-01499-8},

issn = {1740-634X},

year  = {2023},

date = {2023-02-01},

journal = {Neuropsychopharmacology},

volume = {48},

number = {3},

pages = {552--559},

abstract = {Impaired working memory (WM) is a core neuropsychological dysfunction of schizophrenia, however complex interactions among the information storage, information processing and attentional aspects of WM tasks make it difficult to uncover the psychophysiological mechanisms of this deficit. Thirty-six first-episode and drug-naïve schizophrenia and 29 healthy controls (HCs) were enrolled in this study. Here, we modified a WM task to isolate components of WM storage and WM processing, while also varying the difficulty level (load) of the task to study regional differences in load-specific activation using mixed effects models, and its relationship to distributed gene expression. Comparing patients with HCs, we found both attentional deficits and WM deficits, with WM processing being more impaired than WM storage in patients. In patients, but not controls, a linear modulation of brain activation was observed mainly in the frontoparietal and dorsal attention networks. In controls, an inverted U-shaped response pattern was identified in the left anterior cingulate cortex. The vertex of this inverted U-shape was lower in patients than controls, and a left-shifting axis of symmetry was associated with better WM performance in patients. Both the above linear and U-shaped modulation effects were associated with the expressions of the genes enriched in the dopamine neurotransmitter system across all cortical brain regions. These findings indicate that a WM processing deficit is evident in schizophrenia from an early stage before antipsychotic treatment, and associated with a dopamine pathway related aberration in nonlinear response pattern at the cingulate cortex when processing WM load.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid36305160b,

title = {Language Network Dysfunction and Formal Thought Disorder in Schizophrenia},

author = {Lena Palaniyappan and Philipp Homan and Maria F Alonso-Sanchez},

doi = {10.1093/schbul/sbac159},

issn = {1745-1701},

year  = {2023},

date = {2023-03-01},

journal = {Schizophr Bull},

volume = {49},

number = {2},

pages = {486--497},

abstract = {BACKGROUND: Pathophysiological inquiries into schizophrenia require a consideration of one of its most defining features: disorganization and impoverishment in verbal behavior. This feature, often captured using the term Formal Thought Disorder (FTD), still remains to be one of the most poorly understood and understudied dimensions of schizophrenia. In particular, the large-scale network level dysfunction that contributes to FTD remains obscure to date.nnSTUDY DESIGN: In this narrative review, we consider the various challenges that need to be addressed for us to move towards mapping FTD (construct) to a brain network level account (circuit).nnSTUDY RESULTS: The construct-to-circuit mapping goal is now becoming more plausible than it ever was, given the parallel advent of brain stimulation and the tools providing objective readouts of human speech. Notwithstanding this, several challenges remain to be overcome before we can decisively map the neural basis of FTD. We highlight the need for phenotype refinement, robust experimental designs, informed analytical choices, and present plausible targets in and beyond the Language Network for brain stimulation studies in FTD.nnCONCLUSIONS: Developing a therapeutically beneficial pathophysiological model of FTD is a challenging endeavor, but holds the promise of improving interpersonal communication and reducing social disability in schizophrenia. Addressing the issues raised in this review will be a decisive step in this direction.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}