Interview Versus Performance Assessment of Cognition as Predictors of Real-World Outcomes in a Large-Scale Cross-Sectional Study in Schizophrenia.

The Cognitive Assessment Interview (CAI) is an interview-based scale measuring cognitive impairment and its impact on functioning in subjects with schizophrenia (SCZ). It is approved as a coprimary measure of performance-based instruments, such as the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery (MCCB). Recent research highlights negative symptoms, social cognition, and functional capacity as mediators of cognitive impairment's impact on functioning. This study compared mediation analysis outcomes using CAI or MCCB scores, providing insights into the utility of interview-based tools in research and clinical practice. The study included 618 individuals diagnosed with schizophrenia, recruited from 24 Italian psychiatric clinics. Neurocognitive assessments utilized both CAI and MCCB. Mediation analyses explored negative symptoms, social cognition, and functional capacity as mediators of the impact of neurocognition on real-life functioning domains. The study's results extend the validation of the CAI as a coprimary measure that provides valid information on the impact of cognitive impairment on real-life functioning and its possible mediators, complementing the information obtained using the MCCB. Interview-based cognitive assessment might be essential for understanding schizophrenia complexity and its impact on various cognitive and functional domains for clinicians, patients, and caregivers.

Network-wide risk convergence in gene co-expression identifies reproducible genetic hubs of schizophrenia risk.

The omnigenic model posits that genetic risk for traits with complex heritability involves cumulative effects of peripheral genes on mechanistic "core genes," suggesting that in a network of genes, those closer to clusters including core genes should have higher GWAS signals. In gene co-expression networks, we confirmed that GWAS signals accumulate in genes more connected to risk-enriched gene clusters, highlighting across-network risk convergence. This was strongest in adult psychiatric disorders, especially schizophrenia (SCZ), spanning 70% of network genes, suggestive of super-polygenic architecture. In snRNA-seq cell type networks, SCZ risk convergence was strongest in L2/L3 excitatory neurons. We prioritized genes most connected to SCZ-GWAS genes, which showed robust association to a CRISPRa measure of PGC3 regulation and were consistently identified across several brain regions. Several genes, including dopamine-associated ones, were prioritized specifically in the striatum. This strategy thus retrieves current drug targets and can be used to prioritize other potential drug targets.

Abnormal inter-hemispheric effective connectivity from left to right auditory regions during Mismatch Negativity (MMN) tasks in psychosis.

Anomalous Mismatch Negativity (MMN) in psychosis could be a consequence of disturbed neural oscillatory activity at sensory/perceptual stages of stimulus processing. This study investigated effective connectivity within and between the auditory regions during auditory odd-ball deviance tasks. The analyses were performed on two magnetoencephalography (MEG) datasets: one on duration MMN in a cohort with various diagnoses within the psychosis spectrum and neurotypical controls, and one on duration and pitch MMN in first-episode psychosis patients and matched neurotypical controls. We applied spectral Granger causality to MEG source-reconstructed signals to compute effective connectivity within and between the left and right auditory regions. Both experiments showed that duration-deviance detection was associated with early increases of effective connectivity in the beta band followed by increases in the alpha and theta bands, with the connectivity strength linked to the laterality of the MMN amplitude. Compared to controls, people with psychosis had overall smaller effective connectivity, particularly from left to right auditory regions, in the pathway where bilateral information converges toward lateralized processing, often rightward. Blunted MMN in psychosis might reflect a deficit in inter-hemispheric communication between auditory regions, highlighting a "dysconnection" already at preattentive stages of stimulus processing as a model system of widespread pathophysiology.

Genetic determinants of coping, resilience and self-esteem in schizophrenia suggest a primary role for social factors and hippocampal neurogenesis.

Schizophrenia is a severe psychiatric disorder, associated with a reduction in life expectancy of 15-20 years. Available treatments are at least partially effective in most affected individuals, and personal resources such as resilience (successful adaptation despite adversity) and coping abilities (strategies used to deal with stressful or threatening situations), are important determinants of disease outcomes and long-term sustained recovery. Published findings support the existence of a genetic background underlying resilience and coping, with variable heritability estimates. However, genome-wide analyses concerning the genetic determinants of these personal resources, especially in the context of schizophrenia, are lacking. Here, we performed a genome-wide association study coupled with accessory analyses to investigate potential genetic determinants of resilience, coping and self-esteem in 490 schizophrenia patients. Results revealed a complex genetic background partly overlapping with that of neuroticism, worry and schizophrenia itself and support the importance of social aspects in shapingthese psychological constructs. Hippocampal neurogenesis and lipid metabolism appear to be potentially relevant biological underpinnings, and specific miRNAs such as miR-124 and miR-137 may warrant further studies as potential biomarkers. In conclusion, this study represents an important first step in the identification of genetic and biological correlates shaping resilience, coping resources and self-esteem in schizophrenia.

MEG Microstates: An Investigation of Underlying Brain Sources and Potential Neurophysiological Processes.

Microstates are transient scalp configurations of brain activity measured by electroencephalography (EEG). The application of microstate analysis in magnetoencephalography (MEG) data remains challenging. In one MEG dataset (N = 113), we aimed to identify MEG microstates at rest, explore their brain sources, and relate them to changes in brain activity during open-eyes (ROE) or closed-eyes resting state (RCE) and an auditory Mismatch Negativity (MMN) task. In another dataset of simultaneously recorded EEG-MEG data (N = 21), we investigated the association between MEG and EEG microstates. Six MEG microstates (mMS) provided the best clustering of resting-state activity, each linked to different brain sources: mMS 1-2: left/right occipito-parietal; mMS 3: fronto-temporal; mMS 4: centro-medial; mMS 5-6: left/right fronto-parietal. Increases in occipital alpha power in RCE relative to ROE correlated with greater mMS 1-2 time coverage (τbs < 0.20, ps > .002), while the lateralization of deviance detection in MMN was associated with mMS 5-6 time coverage (τbs < 0.16, ps > .012). No temporal correlation was found between EEG and MEG microstates (ps > .05), despite some overlap in brain sources and global explained variance between mMS 2-3 and EEG microstates B-C (rs > 0.60, ps < .002). Hence, the MEG signal can be decomposed into microstates, but mMS brain activity clustering captures phenomena different from EEG microstates. Source reconstruction and task-related modulations link mMS to large-scale networks and localized activities. Thus, mMSs offer insights into brain dynamics and task-specific processes, complementing EEG microstates in studying physiological and dysfunctional brain activity.

Illness-related variables and abnormalities of resting-state brain activity in schizophrenia.

Background: The development of neuroimaging biomarkers in patients with schizophrenia (SCZ) requires a refined clinical characterization. A limitation of the neuroimaging literature is the partial uptake of progress in characterizing disease-related features, particularly negative symptoms (NS) and cognitive impairment (CI). In the present study, we assessed NS and CI using up-to-date instruments and investigated the associations of abnormalities in brain resting-state (rs)-activity with disease-related features. Methods: Sixty-two community-dwelling SCZ subjects participated in the study. Multiple regression analyses were performed with the rs-activity of nine regions of interest as dependent variables and disease-related features as explanatory variables. Results: Attention/vigilance deficits were negatively associated with dorsal anterior cingulate rs-activity and, together with depression, were positively associated with right dorsolateral prefrontal cortex rs-activity. These deficits and impairment of Reasoning/problem-solving, together with conceptual disorganization, were associated with right inferior parietal lobule and temporal parietal junction rs-activity. Independent of other features, the NS Expressive Deficit domain was associated with the left ventral caudate, while the Motivational Deficit was associated with the dorsal caudate rs-activity. Conclusion: Neurocognitive deficits and the two negative symptom domains are associated with different neural markers. Replications of these findings could foster the identification of clinically actionable biomarkers of poor functional outcomes.

Anhedonia as a Potential Transdiagnostic Phenotype With Immune-Related Changes in Recent-Onset Mental Health Disorders.

BACKGROUND: Chronic low-grade inflammation is observed across mental disorders and is associated with difficult-to-treat-symptoms of anhedonia and functional brain changes, reflecting a potential transdiagnostic dimension. Previous investigations have focused on distinct illness categories in people with enduring illness, but few have explored inflammatory changes. We sought to identify an inflammatory signal and the associated brain function underlying anhedonia among young people with recent-onset psychosis and recent-onset depression. METHODS: Resting-state functional magnetic resonance imaging, inflammatory markers, and anhedonia symptoms were collected from 108 (mean [SD] age = 26.2 [6.2] years; female = 50) participants with recent-onset psychosis (n = 53) and recent-onset depression (n = 55) from the European Union/Seventh Framework Programme-funded PRONIA (Personalised Prognostic Tools for Early Psychosis Management) study. Time series were extracted using the Schaefer atlas, defining 100 cortical regions of interest. Using advanced multimodal machine learning, an inflammatory marker model and a functional connectivity model were developed to classify participants into an anhedonic group or a normal hedonic group. RESULTS: A repeated nested cross-validation model using inflammatory markers classified normal hedonic and anhedonic recent-onset psychosis/recent-onset depression groups with a balanced accuracy of 63.9% and an area under the curve of 0.61. The functional connectivity model produced a balanced accuracy of 55.2% and an area under the curve of 0.57. Anhedonic group assignment was driven by higher levels of interleukin 6, S100B, and interleukin 1 receptor antagonist and lower levels of interferon gamma, in addition to connectivity within the precuneus and posterior cingulate. CONCLUSIONS: We identified a potential transdiagnostic anhedonic subtype that was accounted for by an inflammatory profile and functional connectivity. Results have implications for anhedonia as an emerging transdiagnostic target across emerging mental disorders.

Distinct multimodal biological and functional profiles of symptom-based subgroups in recent-onset psychosis.

Symptom heterogeneity characterizes psychotic disorders and hinders the delineation of underlying biomarkers. Here, we identify symptom-based subtypes of recent-onset psychosis (ROP) patients from the multi-center PRONIA (Personalized Prognostic Tools for Early Psychosis Management) database and explore their multimodal biological and functional signatures. We clustered N = 328 ROP patients based on their maximum factor scores in an exploratory factor analysis on the Positive and Negative Syndrome Scale items. We assessed inter-subgroup differences and compared to N = 464 healthy control (HC) individuals regarding gray matter volume (GMV), neurocognition, polygenic risk scores, and longitudinal functioning trajectories. Finally, we evaluated factor stability at 9- and 18-month follow-ups. A 4-factor solution optimally explained symptom heterogeneity, showing moderate longitudinal stability. The ROP-MOTCOG (Motor/Cognition) subgroup was characterized by GMV reductions within salience, control and default mode networks, predominantly throughout cingulate regions, relative to HC individuals, had the most impaired neurocognition and the highest genetic liability for schizophrenia. ROP-SOCWD (Social Withdrawal) patients showed GMV reductions within medial fronto-temporal regions of the control, default mode, and salience networks, and had the lowest social functioning across time points. ROP-POS (Positive) evidenced GMV decreases in salience, limbic and frontal regions of the control and default mode networks. The ROP-AFF (Affective) subgroup showed GMV reductions in the salience, limbic, and posterior default-mode and control networks, thalamus and cerebellum. GMV reductions in fronto-temporal regions of the salience and control networks were shared across subgroups. Our results highlight the existence of behavioral subgroups with distinct neurobiological and functional profiles in early psychosis, emphasizing the need for refined symptom-based diagnosis and prognosis frameworks.

The relationship between the resting state functional connectivity and social cognition in schizophrenia: Results from the Italian Network for Research on Psychoses.

Deficits in social cognition (SC) interfere with recovery in schizophrenia (SZ) and may be related to resting state brain connectivity. This study aimed at assessing the alterations in the relationship between resting state functional connectivity and the social-cognitive abilities of patients with SZ compared to healthy subjects. We divided the brain into 246 regions of interest (ROI) following the Human Healthy Volunteers Brainnetome Atlas. For each participant, we calculated the resting-state functional connectivity (rsFC) in terms of degree centrality (DC), which evaluates the total strength of the most powerful coactivations of every ROI with all other ROIs during rest. The rs-DC of the ROIs was correlated with five measures of SC assessing emotion processing and mentalizing in 45 healthy volunteers (HVs) chosen as a normative sample. Then, controlling for symptoms severity, we verified whether these significant associations were altered, i.e., absent or of opposite sign, in 55 patients with SZ. We found five significant differences between SZ patients and HVs: in the patients' group, the correlations between emotion recognition tasks and rsFC of the right entorhinal cortex (R-EC), left superior parietal lobule (L-SPL), right caudal hippocampus (R-c-Hipp), and the right caudal (R-c) and left rostral (L-r) middle temporal gyri (MTG) were lost. An altered resting state functional connectivity of the L-SPL, R-EC, R-c-Hipp, and bilateral MTG in patients with SZ may be associated with impaired emotion recognition. If confirmed, these results may enhance the development of non-invasive brain stimulation interventions targeting those cerebral regions to reduce SC deficit in SZ.

Dopamine signaling enriched striatal gene set predicts striatal dopamine synthesis and physiological activity in vivo.

The polygenic architecture of schizophrenia implicates several molecular pathways involved in synaptic function. However, it is unclear how polygenic risk funnels through these pathways to translate into syndromic illness. Using tensor decomposition, we analyze gene co-expression in the caudate nucleus, hippocampus, and dorsolateral prefrontal cortex of post-mortem brain samples from 358 individuals. We identify a set of genes predominantly expressed in the caudate nucleus and associated with both clinical state and genetic risk for schizophrenia that shows dopaminergic selectivity. A higher polygenic risk score for schizophrenia parsed by this set of genes predicts greater dopamine synthesis in the striatum and greater striatal activation during reward anticipation. These results translate dopamine-linked genetic risk variation into in vivo neurochemical and hemodynamic phenotypes in the striatum that have long been implicated in the pathophysiology of schizophrenia.

Sex dimorphism controls dysbindin-related cognitive dysfunctions in mice and humans with the contribution of COMT.

Cognitive dysfunctions are core-enduring symptoms of schizophrenia, with important sex-related differences. Genetic variants of the DTBPN1 gene associated with reduced dysbindin-1 protein (Dys) expression negatively impact cognitive functions in schizophrenia through a functional epistatic interaction with Catechol-O-methyltransferase (COMT). Dys is involved in the trafficking of dopaminergic receptors, crucial for prefrontal cortex (PFC) signaling regulation. Moreover, dopamine signaling is modulated by estrogens via inhibition of COMT expression. We hypothesized a sex dimorphism in Dys-related cognitive functions dependent on COMT and estrogen levels. Our multidisciplinary approach combined behavioral-molecular findings on genetically modified mice, human postmortem Dys expression data, and in vivo fMRI during a working memory task performance. We found cognitive impairments in male mice related to genetic variants characterized by reduced Dys protein expression (pBonferroni = 0.0001), as well as in male humans through a COMT/Dys functional epistatic interaction involving PFC brain activity during working memory (t(23) = -3.21; pFDR = 0.004). Dorsolateral PFC activity was associated with lower working memory performance in males only (p = 0.04). Also, male humans showed decreased Dys expression in dorsolateral PFC during adulthood (pFDR = 0.05). Female Dys mice showed preserved cognitive performances with deficits only with a lack of estrogen tested in an ovariectomy model (pBonferroni = 0.0001), suggesting that genetic variants reducing Dys protein expression could probably become functional in females when the protective effect of estrogens is attenuated, i.e., during menopause. Overall, our results show the differential impact of functional variants of the DTBPN1 gene interacting with COMT on cognitive functions across sexes in mice and humans, underlying the importance of considering sex as a target for patient stratification and precision medicine in schizophrenia.

Alterations of Functional Connectivity Dynamics in Affective and Psychotic Disorders.

BACKGROUND: Patients with psychosis and patients with depression exhibit widespread neurobiological abnormalities. The analysis of dynamic functional connectivity (dFC) allows for the detection of changes in complex brain activity patterns, providing insights into common and unique processes underlying these disorders. METHODS: We report the analysis of dFC in a large sample including 127 patients at clinical high risk for psychosis, 142 patients with recent-onset psychosis, 134 patients with recent-onset depression, and 256 healthy control participants. A sliding window-based technique was used to calculate the time-dependent FC in resting-state magnetic resonance imaging data, followed by clustering to reveal recurrent FC states in each diagnostic group. RESULTS: We identified 5 unique FC states, which could be identified in all groups with high consistency (mean r = 0.889 [SD = 0.116]). Analysis of dynamic parameters of these states showed a characteristic increase in the lifetime and frequency of a weakly connected FC state in patients with recent-onset depression (p < .0005) compared with the other groups and a common increase in the lifetime of an FC state characterized by high sensorimotor and cingulo-opercular connectivities in all patient groups compared with the healthy control group (p < .0002). Canonical correlation analysis revealed a mode that exhibited significant correlations between dFC parameters and clinical variables (r = 0.617, p < .0029), which was associated with positive psychosis symptom severity and several dFC parameters. CONCLUSIONS: Our findings indicate diagnosis-specific alterations of dFC and underline the potential of dynamic analysis to characterize disorders such as depression and psychosis and clinical risk states.

The interaction between early life complications and a polygenic risk score for schizophrenia is associated with brain activity during emotion processing in healthy participants.

BACKGROUND: Previous evidence suggests that early life complications (ELCs) interact with polygenic risk for schizophrenia (SCZ) in increasing risk for the disease. However, no studies have investigated this interaction on neurobiological phenotypes. Among those, anomalous emotion-related brain activity has been reported in SCZ, even if evidence of its link with SCZ-related genetic risk is not solid. Indeed, it is possible this relationship is influenced by non-genetic risk factors. Thus, this study investigated the interaction between SCZ-related polygenic risk and ELCs on emotion-related brain activity. METHODS: 169 healthy participants (HP) in a discovery and 113 HP in a replication sample underwent functional magnetic resonance imaging (fMRI) during emotion processing, were categorized for history of ELCs and genome-wide genotyped. Polygenic risk scores (PRSs) were computed using SCZ-associated variants considering the most recent genome-wide association study. Furthermore, 75 patients with SCZ also underwent fMRI during emotion processing to verify consistency of their brain activity patterns with those associated with risk factors for SCZ in HP. RESULTS: Results in the discovery and replication samples indicated no effect of PRSs, but an interaction between PRS and ELCs in left ventrolateral prefrontal cortex (VLPFC), where the greater the activity, the greater PRS only in presence of ELCs. Moreover, SCZ had greater VLPFC response than HP. CONCLUSIONS: These results suggest that emotion-related VLPFC response lies in the path from genetic and non-genetic risk factors to the clinical presentation of SCZ, and may implicate an updated concept of intermediate phenotype considering early non-genetic factors of risk for SCZ.

A miR-137-Related Biological Pathway of Risk for Schizophrenia Is Associated With Human Brain Emotion Processing.

BACKGROUND: miR-137 is a microRNA involved in brain development, regulating neurogenesis and neuronal maturation. Genome-wide association studies have implicated miR-137 in schizophrenia risk but do not explain its involvement in brain function and underlying biology. Polygenic risk for schizophrenia mediated by miR-137 targets is associated with working memory, although other evidence points to emotion processing. We characterized the functional brain correlates of miR-137 target genes associated with schizophrenia while disentangling previously reported associations of miR-137 targets with working memory and emotion processing. METHODS: Using RNA sequencing data from postmortem prefrontal cortex (N = 522), we identified a coexpression gene set enriched for miR-137 targets and schizophrenia risk genes. We validated the relationship of this set to miR-137 in vitro by manipulating miR-137 expression in neuroblastoma cells. We translated this gene set into polygenic scores of coexpression prediction and associated them with functional magnetic resonance imaging activation in healthy volunteers (n1 = 214; n2 = 136; n3 = 2075; n4 = 1800) and with short-term treatment response in patients with schizophrenia (N = 427). RESULTS: In 4652 human participants, we found that 1) schizophrenia risk genes were coexpressed in a biologically validated set enriched for miR-137 targets; 2) increased expression of miR-137 target risk genes was mediated by low prefrontal miR-137 expression; 3) alleles that predict greater gene set coexpression were associated with greater prefrontal activation during emotion processing in 3 independent healthy cohorts (n1, n2, n3) in interaction with age (n4); and 4) these alleles predicted less improvement in negative symptoms following antipsychotic treatment in patients with schizophrenia. CONCLUSIONS: The functional translation of miR-137 target gene expression linked with schizophrenia involves the neural substrates of emotion processing.

Transdiagnostic subgroups of cognitive impairment in early affective and psychotic illness.

Cognitively impaired and spared patient subgroups were identified in psychosis and depression, and in clinical high-risk for psychosis (CHR). Studies suggest differences in underlying brain structural and functional characteristics. It is unclear whether cognitive subgroups are transdiagnostic phenomena in early stages of psychotic and affective disorder which can be validated on the neural level. Patients with recent-onset psychosis (ROP; N = 140; female = 54), recent-onset depression (ROD; N = 130; female = 73), CHR (N = 128; female = 61) and healthy controls (HC; N = 270; female = 165) were recruited through the multi-site study PRONIA. The transdiagnostic sample and individual study groups were clustered into subgroups based on their performance in eight cognitive domains and characterized by gray matter volume (sMRI) and resting-state functional connectivity (rsFC) using support vector machine (SVM) classification. We identified an impaired subgroup (NROP = 79, NROD = 30, NCHR = 37) showing cognitive impairment in executive functioning, working memory, processing speed and verbal learning (all p < 0.001). A spared subgroup (NROP = 61, NROD = 100, NCHR = 91) performed comparable to HC. Single-disease subgroups indicated that cognitive impairment is stronger pronounced in impaired ROP compared to impaired ROD and CHR. Subgroups in ROP and ROD showed specific symptom- and functioning-patterns. rsFC showed superior accuracy compared to sMRI in differentiating transdiagnostic subgroups from HC (BACimpaired = 58.5%; BACspared = 61.7%, both: p < 0.01). Cognitive findings were validated in the PRONIA replication sample (N = 409). Individual cognitive subgroups in ROP, ROD and CHR are more informative than transdiagnostic subgroups as they map onto individual cognitive impairment and specific functioning- and symptom-patterns which show limited overlap in sMRI and rsFC. CLINICAL TRIAL REGISTRY NAME: German Clinical Trials Register (DRKS). Clinical trial registry URL: https://www.drks.de/drks_web/ . Clinical trial registry number: DRKS00005042.

Algorithmic fairness in precision psychiatry: analysis of prediction models in individuals at clinical high risk for psychosis.

BACKGROUND: Computational models offer promising potential for personalised treatment of psychiatric diseases. For their clinical deployment, fairness must be evaluated alongside accuracy. Fairness requires predictive models to not unfairly disadvantage specific demographic groups. Failure to assess model fairness prior to use risks perpetuating healthcare inequalities. Despite its importance, empirical investigation of fairness in predictive models for psychiatry remains scarce. AIMS: To evaluate fairness in prediction models for development of psychosis and functional outcome. METHOD: Using data from the PRONIA study, we examined fairness in 13 published models for prediction of transition to psychosis (n = 11) and functional outcome (n = 2) in people at clinical high risk for psychosis or with recent-onset depression. Using accuracy equality, predictive parity, false-positive error rate balance and false-negative error rate balance, we evaluated relevant fairness aspects for the demographic attributes 'gender' and 'educational attainment' and compared them with the fairness of clinicians' judgements. RESULTS: Our findings indicate systematic bias towards assigning less favourable outcomes to individuals with lower educational attainment in both prediction models and clinicians' judgements, resulting in higher false-positive rates in 7 of 11 models for transition to psychosis. Interestingly, the bias patterns observed in algorithmic predictions were not significantly more pronounced than those in clinicians' predictions. CONCLUSIONS: Educational bias was present in algorithmic and clinicians' predictions, assuming more favourable outcomes for individuals with higher educational level (years of education). This bias might lead to increased stigma and psychosocial burden in patients with lower educational attainment and suboptimal psychosis prevention in those with higher educational attainment.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).

External validation of the five domains of negative symptoms: Focus on cognition, functional capacity, and real-world functioning.

BACKGROUND: The conceptualization of negative symptoms (NS) in schizophrenia is still controversial. Recent confirmatory factor-analytic studies suggested that the bi-dimensional model (motivational deficit [MAP] and expressive deficit [EXP]) may not capture the complexity of NS structure, which could be better defined by a five-factor (five NS domains) or a hierarchical model (five NS domains as first-order factors, and MAP and EXP, as second-order factors). A validation of these models is needed to define the structure of NS. To evaluate the validity and temporal stability of the five-factor or the hierarchical structure of the brief negative symptom scale (BNSS) in individuals with schizophrenia (SCZ), exploring associations between these models with cognition, social cognition, functional capacity, and functioning at baseline and at 4 years follow-up. METHODS: Clinical variables were assessed using state-of-the-art tools in 612 SCZ at two-time points. The validity of the five-factor and the hierarchical models was analyzed through structural equation models. RESULTS: The two models had both a good fit and showed a similar pattern of associations with external validators at the two-time points, with minor variations. The five-factor solution had a slightly better fit. The associations with external validators favored the five-factor structure. CONCLUSIONS: Our findings suggest that both five-factor and hierarchical models provide a valid conceptualization of NS in relation to external variables and that five-factor solution provides the best balance between parsimony and granularity to summarize the BNSS structure. This finding has important implications for the study of pathophysiological mechanisms and the development of new treatments.

Dopamine and schizophrenia from bench to bedside: Discovery of a striatal co-expression risk gene set that predicts in vivo measures of striatal function.

Schizophrenia (SCZ) is characterized by a polygenic risk architecture implicating diverse molecular pathways important for synaptic function. However, how polygenic risk funnels through these pathways to translate into syndromic illness is unanswered. To evaluate biologically meaningful pathways of risk, we used tensor decomposition to characterize gene co-expression in post-mortem brain (of neurotypicals: N=154; patients with SCZ: N=84; and GTEX samples N=120) from caudate nucleus (CN), hippocampus (HP), and dorsolateral prefrontal cortex (DLPFC). We identified a CN-predominant gene set showing dopaminergic selectivity that was enriched for genes associated with clinical state and for genes associated with SCZ risk. Parsing polygenic risk score for SCZ based on this specific gene set (parsed-PRS), we found that greater pathway-specific SCZ risk predicted greater in vivo striatal dopamine synthesis capacity measured by [ 18 F]-FDOPA PET in three independent cohorts of neurotypicals and patients (total N=235) and greater fMRI striatal activation during reward anticipation in two additional independent neurotypical cohorts (total N=141). These results reveal a 'bench to bedside' translation of dopamine-linked genetic risk variation in driving in vivo striatal neurochemical and hemodynamic phenotypes that have long been implicated in the pathophysiology of SCZ.