Identify Potential Causal Relationships Between Cortical Thickness, Mismatch Negativity, Neurocognition, and Psychosocial Functioning in Drug-Naïve First-Episode Psychosis Patients.

BACKGROUND: Cortical thickness (CT) alterations, mismatch negativity (MMN) reductions, and cognitive deficits are robust findings in first-episode psychosis (FEP). However, most studies focused on medicated patients, leaving gaps in our understanding of the interrelationships between CT, MMN, neurocognition, and psychosocial functioning in unmedicated FEP. This study aimed to employ multiple mediation analysis to investigate potential pathways among these variables in unmedicated drug-naïve FEP. METHODS: We enrolled 28 drug-naïve FEP and 34 age and sex-matched healthy controls. Clinical symptoms, neurocognition, psychosocial functioning, auditory duration MMN, and T1 structural magnetic resonance imaging data were collected. We measured CT in the superior temporal gyrus (STG), a primary MMN-generating region. RESULTS: We found a significant negative correlation between MMN amplitude and bilateral CT of STG (CT_STG) in FEP (left: r = -.709, P < .001; right: r = -.612, P = .008). Multiple mediation models revealed that a thinner left STG cortex affected functioning through both direct (24.66%) and indirect effects (75.34%). In contrast, the effects of the right CT_STG on functioning were mainly mediated through MMN and neurocognitive pathways. CONCLUSIONS: Bilateral CT_STG showed significant association with MMN, and MMN plays a mediating role between CT and cognition. Both MMN alone and its interaction with cognition mediated the effects of structural alterations on psychosocial function. The decline in overall function in FEP may stem from decreased CT_STG, leading to subsequent MMN deficits and neurocognitive dysfunction. These findings underline the crucial role of MMN in elucidating how subtle structural alterations can impact neurocognition and psychosocial function in FEP.

Is auditory processing measured by the N100 an endophenotype for psychosis? A family study and a meta-analysis.

BACKGROUND: The N100, an early auditory event-related potential, has been found to be altered in patients with psychosis. However, it is unclear if the N100 is a psychosis endophenotype that is also altered in the relatives of patients. METHODS: We conducted a family study using the auditory oddball paradigm to compare the N100 amplitude and latency across 243 patients with psychosis, 86 unaffected relatives, and 194 controls. We then conducted a systematic review and a random-effects meta-analysis pooling our results and 14 previously published family studies. We compared data from a total of 999 patients, 1192 relatives, and 1253 controls in order to investigate the evidence and degree of N100 differences. RESULTS: In our family study, patients showed reduced N100 amplitudes and prolonged N100 latencies compared to controls, but no significant differences were found between unaffected relatives and controls. The meta-analysis revealed a significant reduction of the N100 amplitude and delay of the N100 latency in both patients with psychosis (standardized mean difference [s.m.d.] = -0.48 for N100 amplitude and s.m.d. = 0.43 for N100 latency) and their relatives (s.m.d. = - 0.19 for N100 amplitude and s.m.d. = 0.33 for N100 latency). However, only the N100 latency changes in relatives remained significant when excluding studies with affected relatives. CONCLUSIONS: N100 changes, especially prolonged N100 latencies, are present in both patients with psychosis and their relatives, making the N100 a promising endophenotype for psychosis. Such changes in the N100 may reflect changes in early auditory processing underlying the etiology of psychosis.

Psychosis Endophenotypes: A Gene-Set-Specific Polygenic Risk Score Analysis.

BACKGROUND AND HYPOTHESIS: Endophenotypes can help to bridge the gap between psychosis and its genetic predispositions, but their underlying mechanisms remain largely unknown. This study aims to identify biological mechanisms that are relevant to the endophenotypes for psychosis, by partitioning polygenic risk scores into specific gene sets and testing their associations with endophenotypes. STUDY DESIGN: We computed polygenic risk scores for schizophrenia and bipolar disorder restricted to brain-related gene sets retrieved from public databases and previous publications. Three hundred and seventy-eight gene-set-specific polygenic risk scores were generated for 4506 participants. Seven endophenotypes were also measured in the sample. Linear mixed-effects models were fitted to test associations between each endophenotype and each gene-set-specific polygenic risk score. STUDY RESULTS: After correction for multiple testing, we found that a reduced P300 amplitude was associated with a higher schizophrenia polygenic risk score of the forebrain regionalization gene set (mean difference per SD increase in the polygenic risk score: -1.15 µV; 95% CI: -1.70 to -0.59 µV; P = 6 × 10-5). The schizophrenia polygenic risk score of forebrain regionalization also explained more variance of the P300 amplitude (R2 = 0.032) than other polygenic risk scores, including the genome-wide polygenic risk scores. CONCLUSIONS: Our finding on reduced P300 amplitudes suggests that certain genetic variants alter early brain development thereby increasing schizophrenia risk years later. Gene-set-specific polygenic risk scores are a useful tool to elucidate biological mechanisms of psychosis and endophenotypes, offering leads for experimental validation in cellular and animal models.

Sensory gating, neurocognition, social cognition and real-life functioning: a 2-year follow-up of early psychosis.

BACKGROUND: Diminished sensory gating (SG) is a robust finding in psychotic disorders, but studies of early psychosis (EP) are rare. It is unknown whether SG deficit leads to poor neurocognitive, social, and/or real-world functioning. This study aimed to explore the longitudinal relationships between SG and these variables. METHODS: Seventy-nine EP patients and 88 healthy controls (HCs) were recruited at baseline. Thirty-three and 20 EP patients completed 12-month and 24-month follow-up, respectively. SG was measured using the auditory dual-click (S1 & S2) paradigm and quantified as P50 ratio (S2/S1) and difference (S1-S2). Cognition, real-life functioning, and symptoms were assessed using the MATRICS Consensus Cognitive Battery, Global Functioning: Social (GFS) and Role (GFR), Multnomah Community Ability Scale (MCAS), Awareness of Social Inference Test (TASIT), and the Positive and Negative Syndrome Scale (PANSS). Analysis of variance (ANOVA), chi-square, mixed model, correlation and regression analyses were used for group comparisons and relationships among variables controlling for potential confounding variables. RESULTS: In EP patients, P50 ratio (p < 0.05) and difference (p < 0.001) at 24-month showed significant differences compared with that at baseline. At baseline, P50 indices (ratio, S1-S2 difference, S1) were independently associated with GFR in HCs (all p < 0.05); in EP patients, S2 amplitude was independently associated with GFS (p = 0.037). At 12-month and 24-month, P50 indices (ratio, S1, S2) was independently associated with MCAS (all p < 0.05). S1-S2 difference was a trending predictor of future function (GFS or MCAS). CONCLUSIONS: SG showed progressive reduction in EP patients. P50 indices were related to real-life functioning.

Exploring the influence of functional architecture on cortical thickness networks in early psychosis - A longitudinal study.

Cortical thickness reductions differ between individuals with psychotic disorders and comparison subjects even in early stages of illness. Whether these reductions covary as expected by functional network membership or simply by spatial proximity has not been fully elucidated. Through orthonormal projective non-negative matrix factorization, cortical thickness measurements in functionally-annotated regions from MRI scans of early-stage psychosis and matched healthy controls were reduced in dimensionality into features capturing positive covariance. Rather than matching the functional networks, the covarying regions in each feature displayed a more localized spatial organization. With Bayesian belief networks, the covarying regions per feature were arranged into a network topology to visualize the dependency structure and identify key driving regions. The features demonstrated diagnosis-specific differences in cortical thickness distributions per feature, identifying reduction-vulnerable spatial regions. Differences in key cortical thickness features between psychosis and control groups were delineated, as well as those between affective and non-affective psychosis. Clustering of the participants, stratified by diagnosis and clinical variables, characterized the clinical traits that define the cortical thickness patterns. Longitudinal follow-up revealed that in select clusters with low baseline cortical thickness, clinical traits improved over time. Our study represents a novel effort to characterize brain structure in relation to functional networks in healthy and clinical populations and to map patterns of cortical thickness alterations among ESP patients onto clinical variables for a better understanding of brain pathophysiology.

Annotation of Trauma-related Linguistic Features in Psychiatric Electronic Health Records for Machine Learning Applications.

Psychiatric electronic health records (EHRs) present a distinctive challenge in the domain of ML owing to their unstructured nature, with a high degree of complexity and variability. This study aimed to identify a cohort of patients with diagnoses of a psychotic disorder and posttraumatic stress disorder (PTSD), develop clinically-informed guidelines for annotating these health records for instances of traumatic events to create a gold standard publicly available dataset, and demonstrate that the data gathered using this annotation scheme is suitable for training a machine learning (ML) model to identify these indicators of trauma in unseen health records. We created a representative corpus of 101 EHRs (222,033 tokens) from a centralized database and a detailed annotation scheme for annotating information relevant to traumatic events in the clinical narratives. A team of clinical experts annotated the dataset and updated the annotation guidelines in collaboration with computational linguistic specialists. Inter-annotator agreement was high (0.688 for span tags, 0.589 for relations, and 0.874 for tag attributes). We characterize the major points relating to the annotation process of psychiatric EHRs. Additionally, high-performing baseline span labeling and relation extraction ML models were developed to demonstrate practical viability of the gold standard corpus for ML applications.

Subfield-specific longitudinal changes of hippocampal volumes in patients with early-stage bipolar disorder.

BACKGROUND: The hippocampus is a heterogeneous structure composed of biologically and functionally distinct subfields. Hippocampal aberrations are proposed to play a fundamental role in the etiology of psychotic symptoms. Bipolar disorder (BPD) has substantial overlap in symptomatology and genetic liability with schizophrenia (SZ), and reduced hippocampal volumes, particularly at the chronic illness stages, are documented in both disorders. Studies of hippocampal subfields in the early stage of BPD are limited and cross-sectional findings to date report no reduction in hippocampal volumes. To our knowledge, there have been no longitudinal studies of BPD evaluating hippocampal volumes in the early phase of illness. We investigated the longitudinal changes in hippocampal regions and subfields in BPD mainly and in early stage of psychosis (ESP) patients more broadly and compared them to those in controls (HC). METHODS: Baseline clinical and structural MRI data were acquired from 88 BPD, from a total of 143 ESP patients, and 74 HCs. Of those, 66 participants (23 HC, 43 patients) completed a 12-month follow-up visit. The hippocampus regions and subfields were segmented using Freesurfer automated pipeline. RESULTS: We found general baseline deficits in hippocampal volumes among BPD and ESP cohorts. Both cohorts displayed significant increases in the anterior hippocampal region and dentate gyrus compared with controls. Additionally, antipsychotic medications were positively correlated with the posterior region at baseline. CONCLUSION: These findings highlight brain plasticity in BPD and in ESP patients providing evidence that deviations in hippocampal volumes are adaptive responses to atypical signaling rather than progressive degeneration.

Auditory event-related potentials, neurocognition, and global functioning in drug naïve first-episode schizophrenia and bipolar disorder.

BACKGROUND: Deficits in event-related potential (ERP) including duration mismatch negativity (MMN) and P3a have been demonstrated widely in chronic schizophrenia (SZ) but inconsistent findings were reported in first-episode patients. Psychotropic medications and diagnosis might contribute to different findings on MMN/P3a ERP in first-episode patients. The present study examined MMN and P3a in first episode drug naïve SZ and bipolar disorder (BPD) patients and explored the relationships among ERPs, neurocognition and global functioning. METHODS: Twenty SZ, 24 BPD and 49 age and sex-matched healthy controls were enrolled in this study. Data of clinical symptoms [Positive and Negative Symptoms Scale (PANSS), Young Manic Rating Scale (YMRS), Hamilton Depression Rating Scale (HAMD)], neurocognition [Wechsler Adult Intelligence Scale (WAIS), Cattell's Culture Fair Intelligence Test (CCFT), Delay Matching to Sample (DMS), Rapid Visual Information Processing (RVP)], and functioning [Functioning Assessment Short Test (FAST)] were collected. P3a and MMN were elicited using a passive auditory oddball paradigm. RESULTS: Significant MMN and P3a deficits and impaired neurocognition were found in both SZ and BPD patients. In SZ, MMN was significantly correlated with FAST (r = 0.48) and CCFT (r = -0.31). In BPD, MMN was significantly correlated with DMS (r = -0.54). For P3a, RVP and FAST scores were significant predictors in SZ, whereas RVP, WAIS and FAST were significant predictors in BPD. CONCLUSIONS: The present study found deficits in MMN, P3a, neurocognition in drug naïve SZ and BPD patients. These deficits appeared to link with levels of higher-order cognition and functioning.

A spectrum of altered non-rapid eye movement sleep in schizophrenia.

Background: Multiple facets of sleep neurophysiology, including electroencephalography (EEG) metrics such as non-rapid eye movement (NREM) spindles and slow oscillations (SO), are altered in individuals with schizophrenia (SCZ). However, beyond group-level analyses which treat all patients as a unitary set, the extent to which NREM deficits vary among patients is unclear, as are their relationships to other sources of heterogeneity including clinical factors, illness duration and ageing, cognitive profiles and medication regimens. Using newly collected high density sleep EEG data on 103 individuals with SCZ and 68 controls, we first sought to replicate our previously reported (Kozhemiako et. al, 2022) group-level mean differences between patients and controls (original N=130). Then in the combined sample (N=301 including 175 patients), we characterized patient-to-patient variability in NREM neurophysiology. Results: We replicated all group-level mean differences and confirmed the high accuracy of our predictive model (Area Under the ROC Curve, AUC = 0.93 for diagnosis). Compared to controls, patients showed significantly increased between-individual variability across many (26%) sleep metrics, with patterns only partially recapitulating those for group-level mean differences. Although multiple clinical and cognitive factors were associated with NREM metrics including spindle density, collectively they did not account for much of the general increase in patient-to-patient variability. Medication regimen was a greater (albeit still partial) contributor to variability, although original group mean differences persisted after controlling for medications. Some sleep metrics including fast spindle density showed exaggerated age-related effects in SCZ, and patients exhibited older predicted biological ages based on an independent model of ageing and the sleep EEG. Conclusion: We demonstrated robust and replicable alterations in sleep neurophysiology in individuals with SCZ and highlighted distinct patterns of effects contrasting between-group means versus within-group variances. We further documented and controlled for a major effect of medication use, and pointed to greater age-related change in NREM sleep in patients. That increased NREM heterogeneity was not explained by standard clinical or cognitive patient assessments suggests the sleep EEG provides novel, nonredundant information to support the goals of personalized medicine. Collectively, our results point to a spectrum of NREM sleep deficits among SCZ patients that can be measured objectively and at scale, and that may offer a unique window on the etiological and genetic diversity that underlies SCZ risk, treatment response and prognosis.

Test-retest reliability of the Childhood Trauma Questionnaire in psychotic disorders.

BACKGROUND: Childhood trauma is common and associated with worse psychiatric outcomes. Yet, clinicians may not inquire about childhood trauma due to a misconception that patients cannot provide reliable reports. The goal of this study was to examine the reliability of self-reports of childhood trauma in psychotic disorders. METHODS: We examined the test-retest reliability of the Childhood Trauma Questionnaire (CTQ) in schizophrenia (SZ, n = 19), psychotic bipolar disorder (BD, n = 17), and healthy control (HC, n = 28) participants who completed the CTQ on ≥2 occasions over variable time periods (mean 19.6 months). We calculated the intraclass correlation (ICC) for the total CTQ score, each of the five CTQ domains, and the minimization/denial subscale for the three groups. For any CTQ domains showing low test-retest reliability (ICC < 0.61), we also explored whether positive, negative, depressive, and manic symptom severity were associated with CTQ variability. RESULTS: We found high ICC values for the total CTQ score in all three groups (SZ 0.82, BD 0.85, HC 0.88). The ICC values for CTQ subdomains were also high with the exceptions of scores for sexual abuse in BD (0.40), emotional neglect in SZ (0.60), and physical neglect in BD (0.51) and HC (0.43). In exploratory analyses, self-reports of sexual abuse in BD were associated with greater severity of depressive symptoms (ß = 0.108, p = 0.004). CONCLUSIONS: Patients with SZ and BD can provide reliable self-reports of childhood trauma, especially related to physical and emotional abuse. The presence of psychosis should not deter clinicians from asking patients about childhood trauma.

Rare coding variants in ten genes confer substantial risk for schizophrenia.

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, P < 2.14 × 10-6) and 32 genes at a false discovery rate of <5%. These genes have the greatest expression in central nervous system neurons and have diverse molecular functions that include the formation, structure and function of the synapse. The associations of the NMDA (N-methyl-D-aspartate) receptor subunit GRIN2A and AMPA (α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid) receptor subunit GRIA3 provide support for dysfunction of the glutamatergic system as a mechanistic hypothesis in the pathogenesis of schizophrenia. We observe an overlap of rare variant risk among schizophrenia, autism spectrum disorders1, epilepsy and severe neurodevelopmental disorders2, although different mutation types are implicated in some shared genes. Most genes described here, however, are not implicated in neurodevelopment. We demonstrate that genes prioritized from common variant analyses of schizophrenia are enriched in rare variant risk3, suggesting that common and rare genetic risk factors converge at least partially on the same underlying pathogenic biological processes. Even after excluding significantly associated genes, schizophrenia cases still carry a substantial excess of URVs, which indicates that more risk genes await discovery using this approach.

Impact of Substance Use Disorder on Between-Network Brain Connectivity in Early Psychosis.

The Triple Network Model of psychopathology identifies the salience network (SN), central executive network (CEN), and default mode network (DMN) as key networks underlying the pathophysiology of psychiatric disorders. In particular, abnormal SN-initiated network switching impacts the engagement and disengagement of the CEN and DMN, and is proposed to lead to the generation of psychosis symptoms. Between-network connectivity has been shown to be abnormal in both substance use disorders (SUD) and psychosis. However, none have studied how SUD affects connectivity between sub-networks of the DMN, SN, and CEN in early stage psychosis (ESP) patients. In this study, we collected data from 113 ESP patients and 50 healthy controls to investigate the effect of SUD on between-network connectivity. In addition, we performed sub-group analysis by exploring whether past SUD vs current SUD co-morbidity, or diagnosis (affective vs non-affective psychosis) had a modulatory effect. Connectivity between four network-pairs, consisting of sub-networks of the SN, CEN, and DMN, was significantly different between ESP patients and controls. Two patterns of connectivity were observed when patients were divided into sub-groups with current vs past SUD. In particular, connectivity between right CEN and the cingulo-opercular salience sub-network (rCEN-CON) showed a gradient effect where the severity of abnormalities increased from no history of SUD to past+ to current+. We also observed diagnosis-specific effects, suggesting non-affective psychosis patients were particularly vulnerable to effects of substance use on rCEN-CON connectivity. Our findings reveal insights into how comorbid SUD affects between-network connectivity and symptom severity in ESP.

Dynamic and progressive changes in thalamic functional connectivity over the first five years of psychosis.

The early stage of psychosis (ESP) is a critical period where effective intervention has the most favorable impact on outcomes. Thalamic connectivity abnormalities have been consistently found in psychosis, and are associated with clinical symptoms and cognitive deficits. However, most studies consider ESP patients as a homogeneous population and fail to take the duration of illness into account. In this study, we aimed to capture the progression of thalamic connectivity changes over the first five years of psychosis. Resting-state functional MRI scans were collected from 156 ESP patients (44 with longitudinal data) and 82 healthy controls (24 with longitudinal data). We first performed a case-control analysis comparing thalamic connectivity with 13 networks in the cortex and cerebellum. Next, we modelled the shape (flat, linear, curvilinear) of thalamic connectivity trajectories by comparing flexible non-linear versus linear models. We then tested the significance of the duration of illness and diagnosis in trajectories that changed over time. Connectivity changed over the ESP period between the thalamus and default mode network (DMN) and fronto-parietal network (FPN) nodes in both the cortex and cerebellum. Three models followed a curvilinear trajectory (early increase followed by a subsequent decrease), while thalamo-cerebellar FPN connectivity followed a linear trajectory of steady reductions over time, indicating different rates of change. Finally, diagnosis significantly predicted thalamic connectivity. Thalamo-cortical and thalamo-cerebellar connectivity change in a dynamic fashion during the ESP period. A better understanding of these changes may provide insights into the compensatory and progressive changes in functional connectivity in the early stages of illness.

Smoking as a Common Modulator of Sensory Gating and Reward Learning in Individuals with Psychotic Disorders.

Motivational and perceptual disturbances co-occur in psychosis and have been linked to aberrations in reward learning and sensory gating, respectively. Although traditionally studied independently, when viewed through a predictive coding framework, these processes can both be linked to dysfunction in striatal dopaminergic prediction error signaling. This study examined whether reward learning and sensory gating are correlated in individuals with psychotic disorders, and whether nicotine-a psychostimulant that amplifies phasic striatal dopamine firing-is a common modulator of these two processes. We recruited 183 patients with psychotic disorders (79 schizophrenia, 104 psychotic bipolar disorder) and 129 controls and assessed reward learning (behavioral probabilistic reward task), sensory gating (P50 event-related potential), and smoking history. Reward learning and sensory gating were correlated across the sample. Smoking influenced reward learning and sensory gating in both patient groups; however, the effects were in opposite directions. Specifically, smoking was associated with improved performance in individuals with schizophrenia but impaired performance in individuals with psychotic bipolar disorder. These findings suggest that reward learning and sensory gating are linked and modulated by smoking. However, disorder-specific associations with smoking suggest that nicotine may expose pathophysiological differences in the architecture and function of prediction error circuitry in these overlapping yet distinct psychotic disorders.

Transcriptome-wide association study reveals two genes that influence mismatch negativity.

Mismatch negativity (MMN) is a differential electrophysiological response measuring cortical adaptability to unpredictable stimuli. MMN is consistently attenuated in patients with psychosis. However, the genetics of MMN are uncharted, limiting the validation of MMN as a psychosis endophenotype. Here, we perform a transcriptome-wide association study of 728 individuals, which reveals 2 genes (FAM89A and ENGASE) whose expression in cortical tissues is associated with MMN. Enrichment analyses of neurodevelopmental expression signatures show that genes associated with MMN tend to be overexpressed in the frontal cortex during prenatal development but are significantly downregulated in adulthood. Endophenotype ranking value calculations comparing MMN and three other candidate psychosis endophenotypes (lateral ventricular volume and two auditory-verbal learning measures) find MMN to be considerably superior. These results yield promising insights into sensory processing in the cortex and endorse the notion of MMN as a psychosis endophenotype.

Longitudinal relationships between mismatch negativity, cognitive performance, and real-world functioning in early psychosis.

BACKGROUND: Reduced mismatch negativity (MMN) is observed in early psychosis (EP) and correlated with cognition and functioning, but few studies have examined their longitudinal relationships and diagnostic specificity. We examined MMN, neuro- and social-cognition, and functional measures in EP patients with schizophrenia-spectrum (SZ) or bipolar disorder (BD) over a 1-year follow-up. METHODS: 54 EP patients (SZ: n = 24; BD: n = 30) and 42 healthy controls completed baseline measures: MMN, neuro- and social-cognition, and functional assessments. 30 EP patients completed 12-month follow-up assessments. Patients and controls were compared on MMN at baseline and follow-up, and diagnostic subgroup analyses were performed. Associations amongst MMN, neuro- and social cognition, and clinical measures were examined and predictive models of follow-up outcomes were conducted. RESULTS: EP patients showed significantly reduced MMN compared to controls at baseline (p = 0.023). MMN was impaired in SZ patients at baseline (p = 0.017) and follow-up (p = 0.003); BD patients did not differ from controls at either timepoint. MMN was associated with symptom severity and functioning at baseline, and with social cognition and functioning at follow up, but was not predictive of functional outcomes at follow-up. CONCLUSIONS: MMN abnormalities were evident in EP SZ-spectrum disorders at both timepoints, but not in BD at either timepoint. MMN was associated with functioning cross-sectionally, but did not predict future functional outcomes. However, deficits in MMN were associated with social cognition, which may have downstream effects on community functioning. Implications for targeted interventions to improve social processing and community outcomes are discussed.

Genetic copy number variants, cognition and psychosis: a meta-analysis and a family study.

The burden of large and rare copy number genetic variants (CNVs) as well as certain specific CNVs increase the risk of developing schizophrenia. Several cognitive measures are purported schizophrenia endophenotypes and may represent an intermediate point between genetics and the illness. This paper investigates the influence of CNVs on cognition. We conducted a systematic review and meta-analysis of the literature exploring the effect of CNV burden on general intelligence. We included ten primary studies with a total of 18,847 participants and found no evidence of association. In a new psychosis family study, we investigated the effects of CNVs on specific cognitive abilities. We examined the burden of large and rare CNVs (>200 kb, <1% MAF) as well as known schizophrenia-associated CNVs in patients with psychotic disorders, their unaffected relatives and controls (N = 3428) from the Psychosis Endophenotypes International Consortium (PEIC). The carriers of specific schizophrenia-associated CNVs showed poorer performance than non-carriers in immediate (P = 0.0036) and delayed (P = 0.0115) verbal recall. We found suggestive evidence that carriers of schizophrenia-associated CNVs had poorer block design performance (P = 0.0307). We do not find any association between CNV burden and cognition. Our findings show that the known high-risk CNVs are not only associated with schizophrenia and other neurodevelopmental disorders, but are also a contributing factor to impairment in cognitive domains such as memory and perceptual reasoning, and act as intermediate biomarkers of disease risk.

Heterogeneity of Outcomes and Network Connectivity in Early-Stage Psychosis: A Longitudinal Study.

Imaging studies in psychotic disorders typically examine cross-sectional relationships between magnetic resonance imaging (MRI) signals and diagnosis or symptoms. We sought to examine changes in network connectivity identified using resting-state functional MRI (fMRI) corresponding to divergent functional recovery trajectories and relapse in early-stage psychosis (ESP). Prior studies have linked schizophrenia to hyperconnectivity in the default mode network (DMN). Given the correlations between the DMN and behavioral impairments in psychosis, we hypothesized that dynamic changes in DMN connectivity reflect the heterogeneity of outcomes in ESP. Longitudinal data were collected from 66 ESP patients and 20 healthy controls. Longitudinal cluster analysis identified subgroups of patients with similar trajectories in terms of symptom severity and functional outcomes. DMN connectivity was measured in a subset of patients (n = 36) longitudinally over 2 scans separated by a mean of 12 months. We then compared connectivity between patients and controls, and among the different outcome trajectory subgroups. Among ESP participants, 4 subgroups were empirically identified corresponding to: "Poor," "Middle," "Catch-up," and "Good" trajectory outcomes in the complete dataset (n = 36), and an independent replication (n = 30). DMN connectivity changes differed significantly between functional subgroups (F3,32 = 6.06, P-FDR corrected = .01); DMN connectivity increased over time in the "Poor" outcome cluster (ß = +0.145) but decreased over time in the "Catch-up" cluster (ß = -0.212). DMN connectivity is dynamic and correlates with a change in functional status over time in ESP. This approach identifies a brain-based marker that reflects important neurobiological processes required to sustain functional recovery.

Incorporating Risk Factor Embeddings in Pre-trained Transformers Improves Sentiment Prediction in Psychiatric Discharge Summaries.

Reducing rates of early hospital readmission has been recognized and identified as a key to improve quality of care and reduce costs. There are a number of risk factors that have been hypothesized to be important for understanding re-admission risk, including such factors as problems with substance abuse, ability to maintain work, relations with family. In this work, we develop RoBERTa-based models to predict the sentiment of sentences describing readmission risk factors in discharge summaries of patients with psychosis. We improve substantially on previous results by a scheme that shares information across risk factors while also allowing the model to learn risk factor-specific information.

Identifying Clinically and Functionally Distinct Groups Among Healthy Controls and First Episode Psychosis Patients by Clustering on EEG Patterns.

OBJECTIVE: The mismatch negativity (MMN) is considered as a promising biomarker that can inform future therapeutic studies. However, there is a large variability among patients with first episode psychosis (FEP). Also, most studies report a single electrode site and on comparing case-control group differences. Few have taken advantage of the full wealth of multi-channel EEG signals to examine observable patterns. None, to our knowledge, have used machine learning (ML) approaches to investigate neurophysiological derived subgroups with distinct cognitive and functional outcome characteristics. In this study, we applied ML to empirically stratify individuals into homogeneous subgroups based on multi-channel MMN data. We then characterized the functional, cognitive, and clinical profiles of these neurobiologically derived subgroups. We also explored the underlying low frequency range responses (delta, theta, alpha) during MMN. METHODS: Clinical, neurocognitive, functioning data of 33 healthy controls and 20 FEP patients were collected. 90% of the patients had 6-month follow-up data. Neurocognition, social cognition, and functioning measures were assessed using the NCCB Cognitive Battery, the Awareness of Social Inference Test, UCSD Performance-Based Skills Assessment, and Multnomah Community Ability Scale. Symptom severity was collected using the PANSS. MMN amplitude and single-trial derived low frequency activity across 24 frontocentral channels were used as main variables in the ML k-means clustering analyses. RESULTS: We found a consistent pattern of two distinctive subgroups. We labeled them as "better functioning" and "poorer functioning" clusters, respectively. Each subgroup can be mapped onto either better or poorer clinical, cognitive, and functioning profiles. Also, we identified two subgroups of patients: one showed improved MMN and one showed worsening of MMN over time. Patients with improved MMN had better follow-up clinical, cognitive, and functioning profile than those with worsening MMN. Among the low frequency bands, delta frequency appeared to be the most relevant to the observed MMN responses in all individuals. However, higher delta responses were not necessarily associated with a better functioning profile, suggesting that delta frequency alone may not be useful in clinical characterization. CONCLUSIONS: The ML approach could be a robust tool to explore heterogeneity and facilitate the identification of neurobiological homogeneous subgroups in FEP.