Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated with Psychopathology Across Independent Cohorts.

BACKGROUND: Early Psychosis patients (EP, within 3 years after psychosis onset) show significant variability, making outcome predictions challenging. Currently, little evidence exists for stable relationships between neural microstructural properties and symptom profiles across EP diagnoses, limiting the development of early interventions. METHODS: A data-driven approach, Partial Least Squares (PLS) correlation, was used across two independent datasets to examine multivariate relationships between white matter (WM) properties and symptomatology, to identify stable and generalizable signatures in EP. The primary cohort included EP patients from the Human Connectome Project-Early Psychosis (n=124). The replication cohort included EP patients from the Feinstein Institute for Medical Research (n=78). Both samples included individuals with schizophrenia, schizoaffective disorder, and psychotic mood disorders. RESULTS: In both cohorts, a significant latent component (LC) corresponded to a symptom profile combining negative symptoms, primarily diminished expression, with specific somatic symptoms. Both LCs captured comprehensive features of WM disruption, primarily a combination of subcortical and frontal association fibers. Strikingly, the PLS model trained on the primary cohort accurately predicted microstructural features and symptoms in the replication cohort. Findings were not driven by diagnosis, medication, or substance use. CONCLUSIONS: This data-driven transdiagnostic approach revealed a stable and replicable neurobiological signature of microstructural WM alterations in EP, across diagnoses and datasets, showing a strong covariance of these alterations with a unique profile of negative and somatic symptoms. This finding suggests the clinical utility of applying data-driven approaches to reveal symptom domains that share neurobiological underpinnings.

Decoding Early Psychoses: Unraveling Stable Microstructural Features Associated with Psychopathology Across Independent Cohorts.

Background: Early Psychosis patients (EP, within 3 years after psychosis onset) show significant variability, making outcome predictions challenging. Currently, little evidence exists for stable relationships between neural microstructural properties and symptom profiles across EP diagnoses, limiting the development of early interventions. Methods: A data-driven approach, Partial Least Squares (PLS) correlation, was used across two independent datasets to examine multivariate relationships between white matter (WM) properties and symptomatology, to identify stable and generalizable signatures in EP. The primary cohort included EP patients from the Human Connectome Project-Early Psychosis (n=124). The replication cohort included EP patients from the Feinstein Institute for Medical Research (n=78). Both samples included individuals with schizophrenia, schizoaffective disorder, and psychotic mood disorders. Results: In both cohorts, a significant latent component (LC) corresponded to a symptom profile combining negative symptoms, primarily diminished expression, with specific somatic symptoms. Both LCs captured comprehensive features of WM disruption, primarily a combination of subcortical and frontal association fibers. Strikingly, the PLS model trained on the primary cohort accurately predicted microstructural features and symptoms in the replication cohort. Findings were not driven by diagnosis, medication, or substance use. Conclusions: This data-driven transdiagnostic approach revealed a stable and replicable neurobiological signature of microstructural WM alterations in EP, across diagnoses and datasets, showing a strong covariance of these alterations with a unique profile of negative and somatic symptoms. This finding suggests the clinical utility of applying data-driven approaches to reveal symptom domains that share neurobiological underpinnings.

Childhood trauma moderates schizotypy-related brain morphology: analyses of 1182 healthy individuals from the ENIGMA schizotypy working group.

BACKGROUND: Schizotypy represents an index of psychosis-proneness in the general population, often associated with childhood trauma exposure. Both schizotypy and childhood trauma are linked to structural brain alterations, and it is possible that trauma exposure moderates the extent of brain morphological differences associated with schizotypy. METHODS: We addressed this question using data from a total of 1182 healthy adults (age range: 18-65 years old, 647 females/535 males), pooled from nine sites worldwide, contributing to the Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) Schizotypy working group. All participants completed both the Schizotypal Personality Questionnaire Brief version (SPQ-B), and the Childhood Trauma Questionnaire (CTQ), and underwent a 3D T1-weighted brain MRI scan from which regional indices of subcortical gray matter volume and cortical thickness were determined. RESULTS: A series of multiple linear regressions revealed that differences in cortical thickness in four regions-of-interest were significantly associated with interactions between schizotypy and trauma; subsequent moderation analyses indicated that increasing levels of schizotypy were associated with thicker left caudal anterior cingulate gyrus, right middle temporal gyrus and insula, and thinner left caudal middle frontal gyrus, in people exposed to higher (but not low or average) levels of childhood trauma. This was found in the context of morphological changes directly associated with increasing levels of schizotypy or increasing levels of childhood trauma exposure. CONCLUSIONS: These results suggest that alterations in brain regions critical for higher cognitive and integrative processes that are associated with schizotypy may be enhanced in individuals exposed to high levels of trauma.

Multivariate Associations Among White Matter, Neurocognition, and Social Cognition Across Individuals With Schizophrenia Spectrum Disorders and Healthy Controls.

BACKGROUND AND HYPOTHESIS: Neurocognitive and social cognitive abilities are important contributors to functional outcomes in schizophrenia spectrum disorders (SSDs). An unanswered question of considerable interest is whether neurocognitive and social cognitive deficits arise from overlapping or distinct white matter impairment(s). STUDY DESIGN: We sought to fill this gap, by harnessing a large sample of individuals from the multi-center Social Processes Initiative in the Neurobiology of the Schizophrenia(s) (SPINS) dataset, unique in its collection of advanced diffusion imaging and an extensive battery of cognitive assessments. We applied canonical correlation analysis to estimates of white matter microstructure, and cognitive performance, across people with and without an SSD. STUDY RESULTS: Our results established that white matter circuitry is dimensionally and strongly related to both neurocognition and social cognition, and that microstructure of the uncinate fasciculus and the rostral body of the corpus callosum may assume a "privileged role" subserving both. Further, we found that participant-wise estimates of white matter microstructure, weighted by cognitive performance, were largely consistent with participants' categorical diagnosis, and predictive of (cross-sectional) functional outcomes. CONCLUSIONS: The demonstrated strength of the relationship between white matter circuitry and neurocognition and social cognition underscores the potential for using relationships among these variables to identify biomarkers of functioning, with potential prognostic and therapeutic implications.

Contributions of Parasympathetic Arousal-Related Activity to Cognitive Performance in Patients With First-Episode Psychosis and Control Subjects.

BACKGROUND: Cognitive impairment is integral to the pathophysiology of psychosis. Recent findings implicate autonomic arousal-related activity in both momentary fluctuations and individual differences in cognitive performance. Although altered autonomic arousal is common in patients with first-episode psychosis (FEP), its contribution to cognitive performance is unknown. METHODS: A total of 24 patients with FEP (46% male, age = 24.31 [SD 4.27] years) and 24 control subjects (42% male, age = 27.06 [3.44] years) performed the Multi-Source Interference Task in-scanner with simultaneous pulse oximetry. First-level models included the cardiac-blood oxygen level-dependent regressor, in addition to task (congruent, interference, and error) and nuisance (motion and CompCor physiology) regressors. The cardiac-blood oxygen level-dependent regressor reflected parasympathetic arousal-related activity and was created by convolving the interbeat interval at each heartbeat with the hemodynamic response function. Group models examined the effect of group or cognitive performance (reaction times × error rate) on arousal-related and task activity, while controlling for sex, age, and framewise displacement. RESULTS: Parasympathetic arousal-related activity was robust in both groups but localized to different regions for patients with FEP and healthy control subjects. Within both groups, arousal-related activity was significantly associated with cognitive performance across occipital and temporal cortical regions. Greater arousal-related activity in the bilateral prefrontal cortex (Brodmann area 9) was related to better performance in healthy control subjects but not patients with FEP. CONCLUSIONS: Autonomic arousal circuits contribute to cognitive performance and the pathophysiology of FEP. Arousal-related functional activity is a novel indicator of cognitive ability and should be incorporated into neurobiological models of cognition in psychosis.

Metabolic disturbances, hemoglobin A1c, and social cognition impairment in Schizophrenia spectrum disorders.

Social cognitive impairments are core features of schizophrenia spectrum disorders (SSD) and are associated with greater functional impairment and decreased quality of life. Metabolic disturbances have been related to greater impairment in general neurocognition, but their relationship to social cognition has not been previously reported. In this study, metabolic measures and social cognition were assessed in 245 participants with SSD and 165 healthy comparison subjects (HC), excluding those with hemoglobin A1c (HbA1c) > 6.5%. Tasks assessed emotion processing, theory of mind, and social perception. Functional connectivity within and between social cognitive networks was measured during a naturalistic social task. Among SSD, a significant inverse relationship was found between social cognition and cumulative metabolic burden (ß = -0.38, p < 0.001) and HbA1c (ß = -0.37, p < 0.001). The relationship between social cognition and HbA1c was robust across domains and measures of social cognition and after accounting for age, sex, race, non-social neurocognition, hospitalization, and treatment with different antipsychotic medications. Negative connectivity between affect sharing and motor resonance networks was a partial mediator of this relationship across SSD and HC groups (ß = -0.05, p = 0.008). There was a group x HbA1c effect indicating that SSD participants were more adversely affected by increasing HbA1c. Thus, we provide the first report of a robust relationship in SSD between social cognition and abnormal glucose metabolism. If replicated and found to be causal, insulin sensitivity and blood glucose may present as promising targets for improving social cognition, functional outcomes, and quality of life in SSD.

Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study.

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, pFDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, pspin = 0.024), but not BD (r = 0.166, pspin = 0.205) or MDD (r = -0.274, pspin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, pspin = 0.006), BD (rho = -0.672, pspin = 0.009), and MDD (rho = -0.692, pspin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics.

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. Using our meta-analytic data set (N = 373,617), we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.

Social Cognitive Networks and Social Cognitive Performance Across Individuals With Schizophrenia Spectrum Disorders and Healthy Control Participants.

BACKGROUND: Schizophrenia spectrum disorders (SSDs) feature social cognitive deficits, although their neural basis remains unclear. Social cognitive performance may relate to neural circuit activation patterns more than to diagnosis, which would have important prognostic and therapeutic implications. The current study aimed to determine how functional connectivity within and between social cognitive networks relates to social cognitive performance across individuals with SSDs and healthy control participants. METHODS: Participants with SSDs (n = 164) and healthy control participants (n = 117) completed the Empathic Accuracy task during functional magnetic resonance imaging as well as lower-level (e.g., emotion recognition) and higher-level (e.g., theory of mind) social cognitive measures outside the scanner. Functional connectivity during the Empathic Accuracy task was analyzed using background connectivity and graph theory. Data-driven social cognitive networks were identified across participants. Regression analyses were used to examine network connectivity-performance relationships across individuals. Positive and negative within- and between-network connectivity strengths were also compared in poor versus good social cognitive performers and in SSD versus control groups. RESULTS: Three social cognitive networks were identified: motor resonance, affect sharing, and mentalizing. Regression and group-based analyses demonstrated reduced between-network negative connectivity, or segregation, and greater within- and between-network positive connectivity in worse social cognitive performers. There were no significant effects of diagnostic group on within- or between-network connectivity. CONCLUSIONS: These findings suggest that the neural circuitry of social cognitive performance may exist dimensionally. Across participants, better social cognitive performance was associated with greater segregation between social cognitive networks, whereas poor versus good performers may compensate via hyperconnectivity within and between social cognitive networks.

Overlapping Neurobiological Substrates for Early-Life Stress and Resilience to Psychosis.

Early-life stress, such as childhood maltreatment, is a well-known etiological factor in psychopathology, including psychosis. Exposure to early-life stress disrupts the neurodevelopment of widespread brain systems, including key components of the hypothalamic-pituitary-adrenal axis stress response, such as the amygdala, hippocampus, and medial prefrontal cortex, as well as key components of the brain's reward system, such as the nucleus accumbens and orbitofrontal cortex. These disruptions have a considerable impact on the function of emotion and reward circuitry, which play a central role in the emergence and severity of psychosis. While this overlap may provide insight into the pathophysiology of psychosis, it also provides unique opportunities to elucidate neurobiological substrates that may promote resilience to psychosis. In this review, we discuss the hypothalamic-pituitary-adrenal axis stress response, discuss the disruption in the neurodevelopment of emotion and reward processing associated with early stress exposures, and examine how this circuitry may contribute to resilience to psychotic disorders.

Interaction of Cannabis Use Disorder and Striatal Connectivity in Antipsychotic Treatment Response.

Antipsychotic (AP) medications are the mainstay for the treatment of schizophrenia spectrum disorders (SSD), but their efficacy is unpredictable and widely variable. Substantial efforts have been made to identify prognostic biomarkers that can be used to guide optimal prescription strategies for individual patients. Striatal regions involved in salience and reward processing are disrupted as a result of both SSD and cannabis use, and research demonstrates that striatal circuitry may be integral to response to AP drugs. In the present study, we used functional magnetic resonance imaging (fMRI) to investigate the relationship between a history of cannabis use disorder (CUD) and a striatal connectivity index (SCI), a previously developed neural biomarker for AP treatment response in SSD. Patients were part of a 12-week randomized, double-blind controlled treatment study of AP drugs. A sample of 48 first-episode SSD patients with no more than 2 weeks of lifetime exposure to AP medications, underwent a resting-state fMRI scan pretreatment. Treatment response was defined a priori as a binary (response/nonresponse) variable, and a SCI was calculated in each patient. We examined whether there was an interaction between lifetime CUD history and the SCI in relation to treatment response. We found that CUD history moderated the relationship between SCI and treatment response, such that it had little predictive value in SSD patients with a CUD history. In sum, our findings highlight that biomarker development can be critically impacted by patient behaviors that influence neurobiology, such as a history of CUD.

History of childhood maltreatment is associated with reduced fractional anisotropy of the accumbofrontal 'reward' tract in healthy adults.

The deleterious outcomes associated with exposure to childhood maltreatment (CM) are well known and may be at least partially mediated by self-harm behaviors. It has been suggested that these self-harm behaviors serve as a means of decreasing negative mood states but the effects of CM on health outcomes may be much more sinister. A wealth of data suggest that CM may lead to experience-dependent changes in neural circuits underlying reward processes; processes associated with many harmful behaviors. The present study examined the relationship between a history of CM and the microstructure of a white matter tract that may be central to reward processes. Healthy adults (N = 122) were assessed with a diffusion tensor imaging (DTI) exam and the Childhood Trauma Questionnaire (CTQ). Probabilistic tractography was used to delineate the accumbofrontal "reward" tract, connecting the orbitofrontal cortex and nucleus accumbens, and measures of white matter microstructure were extracted. We then examined whether variation in CTQ scores were associated with variation in the microstructure of this tract as measured by fractional anisotropy (FA). After accounting for the effects of age and sex, the CTQ total score accounted for approximately 6% of the variance of FA in the accumbofrontal tract (F(3, 121) = 5.74; p = .001). Post hoc analyses indicated that the overall severity of CM, rather than a specific type of maltreatment, drove this result. These findings indicate that CM influences white matter microstructure in a fiber tract that is likely central to reward processes and adds to a growing literature implicating CM in long-term health-related outcomes.

Parasympathetic arousal-related cortical activity is associated with attention during cognitive task performance.

Parasympathetic arousal is associated with states of heightened attention and well-being. Arousal may affect widespread cortical and subcortical systems across the brain, however, little is known about its influence on cognitive task processing and performance. In the current study, healthy adult participants (n â€‹= â€‹20) underwent multi-band echo-planar imaging (TR â€‹= â€‹0.72 â€‹s) with simultaneous pulse oximetry recordings during performance of the Multi Source Interference Task (MSIT), the Oddball Task (OBT), and during rest. Processing speed on both tasks was robustly related to heart rate (HR). Participants with slower HR responded faster on both the MSIT (33% variance explained) and the OBT (25% variance explained). Within all participants, trial-to-trial fluctuations in processing speed were robustly related to the heartbeat-stimulus interval, a metric that is dependent both on the concurrent HR and the stimulus timing with respect to the heartbeat. Models examining the cardiac-BOLD response revealed that a distributed set of regions showed arousal-related activity that was distinct for different task conditions. Across these cortical regions, activity increased with slower HR. Arousal-related activity was distinct from task-evoked activity and it was robust to the inclusion of additional physiological nuisance regressors into the models. For the MSIT, such arousal-related activity occurred across visual and dorsal attention network regions. For the OBT, this activity occurred within fronto-parietal regions. For rest, arousal-related activity also occurred, but was confined to visual regions. The pulvinar nucleus of the thalamus showed arousal-related activity during all three task conditions. Widespread cortical activity, associated with increased parasympathetic arousal, may be propagated by thalamic circuits and contributes to improved attention. This activity is distinct from task-evoked activity, but affects cognitive performance and therefore should be incorporated into neurobiological models of cognition and clinical disorders.

Pleiotropic Meta-Analysis of Cognition, Education, and Schizophrenia Differentiates Roles of Early Neurodevelopmental and Adult Synaptic Pathways.

Susceptibility to schizophrenia is inversely correlated with general cognitive ability at both the phenotypic and the genetic level. Paradoxically, a modest but consistent positive genetic correlation has been reported between schizophrenia and educational attainment, despite the strong positive genetic correlation between cognitive ability and educational attainment. Here we leverage published genome-wide association studies (GWASs) in cognitive ability, education, and schizophrenia to parse biological mechanisms underlying these results. Association analysis based on subsets (ASSET), a pleiotropic meta-analytic technique, allowed jointly associated loci to be identified and characterized. Specifically, we identified subsets of variants associated in the expected ("concordant") direction across all three phenotypes (i.e., greater risk for schizophrenia, lower cognitive ability, and lower educational attainment); these were contrasted with variants that demonstrated the counterintuitive ("discordant") relationship between education and schizophrenia (i.e., greater risk for schizophrenia and higher educational attainment). ASSET analysis revealed 235 independent loci associated with cognitive ability, education, and/or schizophrenia at p < 5 × 10-8. Pleiotropic analysis successfully identified more than 100 loci that were not significant in the input GWASs. Many of these have been validated by larger, more recent single-phenotype GWASs. Leveraging the joint genetic correlations of cognitive ability, education, and schizophrenia, we were able to dissociate two distinct biological mechanisms-early neurodevelopmental pathways that characterize concordant allelic variation and adulthood synaptic pruning pathways-that were linked to the paradoxical positive genetic association between education and schizophrenia. Furthermore, genetic correlation analyses revealed that these mechanisms contribute not only to the etiopathogenesis of schizophrenia but also to the broader biological dimensions implicated in both general health outcomes and psychiatric illness.

Striatal volume and functional connectivity correlate with weight gain in early-phase psychosis.

Second-generation antipsychotic drugs (SGAs) are essential in the treatment of psychotic disorders, but are well-known for inducing substantial weight gain and obesity. Critically, weight gain may reduce life expectancy for up to 20-30 years in patients with psychotic disorders, and prognostic biomarkers are generally lacking. Even though other receptors are also implicated, the dorsal striatum, rich in dopamine D2 receptors, which are antagonized by antipsychotic medications, plays a key role in the human reward system and in appetite regulation, suggesting that altered dopamine activity in the striatal reward circuitry may be responsible for increased food craving and weight gain. Here, we measured striatal volume and striatal resting-state functional connectivity at baseline, and weight gain over the course of 12 weeks of antipsychotic treatment in 81 patients with early-phase psychosis. We also included a sample of 58 healthy controls. Weight measurements were completed at baseline, and then weekly for 4 weeks, and every 2 weeks until week 12. We used linear mixed models to compute individual weight gain trajectories. Striatal volume and whole-brain striatal connectivity were then calculated for each subject, and used to assess the relationship between striatal structure and function and individual weight gain in multiple regression models. Patients had similar baseline weights and body mass indices (BMI) compared with healthy controls. There was no evidence that prior drug exposure or duration of untreated psychosis correlated with baseline BMI. Higher left putamen volume and lower sensory motor connectivity correlated with the magnitude of weight gain in patients, and these effects multiplied when the structure-function interaction was considered in an additional exploratory analysis. In conclusion, these results provide evidence for a correlation of striatal structure and function with antipsychotic-induced weight gain. Lower striatal connectivity was associated with more weight gain, and this relationship was stronger for higher compared with lower left putamen volumes.

Deconstructing Avolition: Initiation vs persistence of reward-directed effort.

Avolition, a decrease in the initiation and persistence of goal-directed behavior, is a critical determinant of disability in patients with schizophrenia. Recent studies have demonstrated that avolition can be modeled using reward-based, behavioral paradigms. These studies suggest that avolition represents a motivational deficit, accounted for by a diminished ability to anticipate pleasurable experiences. Notably, although data suggest that "initiation" and "persistence" of goal-directed behavior may depend on different processes, few studies have sought to distinguish between these two components of avolitional symptoms. Such distinctions could have real consequences for the development and evaluation of interventions designed to ameliorate avolitional symptoms. Thus, the present study examined the relationship between anticipatory pleasure, a key driver of avolition, and both the initiation and persistence of reward-directed, effortful responding during the Effort Expenditures for Rewards Task in 103 healthy participants. We found that anticipatory pleasure was not significantly predictive of the initiation of effortful responding but was significantly predictive of the persistence of effortful responding; most notably when the probabilities of reward and non-reward were equivalent. These data suggest that although deficits in reward processes contribute to the likelihood of persisting in reward-driven behavior, they contribute little to the initiation of such behavior.

Author Correction: Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

Christina M. Lill, who contributed to analysis of data, was inadvertently omitted from the author list in the originally published version of this article. This has now been corrected in both the PDF and HTML versions of the article.

Structural similarity networks predict clinical outcome in early-phase psychosis.

Despite recent advances, there is still a major need for prediction of treatment success in schizophrenia, a condition long considered a disorder of dysconnectivity in the brain. Graph theory provides a means to characterize the connectivity in both healthy and abnormal brains. We calculated structural similarity networks in each participant and hypothesized that the "hubness", i.e., the number of edges connecting a node to the rest of the network, would be associated with clinical outcome. This prospective controlled study took place at an academic research center and included 82 early-phase psychosis patients (23 females; mean age [SD] = 21.6 [5.5] years) and 58 healthy controls. Medications were administered in a double-blind randomized manner, and patients were scanned at baseline prior to treatment with second-generation antipsychotics. Symptoms were assessed with the Brief Psychiatric Rating Scale at baseline and over the course of 12 weeks. Nodal degree of structural similarity networks was computed for each subject and entered as a predictor of individual treatment response into a partial least squares (PLS) regression. The model fit was significant in a permutation test with 1000 permutations (P = 0.006), and the first two PLS regression components explained 29% (95% CI: 27; 30) of the variance in treatment response after cross-validation. Nodes loading strongly on the first PLS component were primarily located in the orbito- and prefrontal cortex, whereas nodes loading strongly on the second PLS component were primarily located in the superior temporal, precentral, and middle cingulate cortex. These data suggest a link between brain network morphology and clinical outcome in early-phase psychosis.

Separable and Replicable Neural Strategies During Social Brain Function in People With and Without Severe Mental Illness.

OBJECTIVE: Case-control study design and disease heterogeneity may impede biomarker discovery in brain disorders, including serious mental illnesses. To identify biologically and/or behaviorally driven as opposed to diagnostically driven subgroups of individuals, the authors used hierarchical clustering to identify individuals with similar patterns of brain activity during a facial imitate/observe functional MRI task. METHODS: Participants in the Social Processes Initiative in Neurobiology of the Schizophrenia(s) study (N=179; 109 with a schizophrenia spectrum disorder and 70 healthy control participants) underwent MRI scanning at three sites. Hierarchical clustering was used to identify new data-driven groups of participants; differences on social and neurocognitive tests completed outside the scanner were compared among the new groups. RESULTS: Three clusters with distinct patterns of neural activity were found. Cluster membership was not related to diagnosis or scan site. The largest cluster consisted of "typical activators," with activity in the canonical "simulation" circuit. The other clusters represented a "hyperactivating" group and a "deactivating" group. Between-participants Euclidean distances were smaller within clusters than within site or diagnostics groups. The deactivating group had the highest social cognitive and neurocognitive test scores. The hierarchical clustering analysis was repeated on a replication sample (N=108; 32 schizophrenia spectrum disorder, 37 euthymic bipolar disorder, and 39 healthy control participants), which exhibited the same three cluster patterns. CONCLUSIONS: The study findings demonstrate replicable differing patterns of neural activity among individuals during a socio-emotional task, independent of DSM diagnosis or scan site. The findings may provide objective neuroimaging endpoints (biomarkers) for subgroups of individuals in target engagement research aimed at enhancing cognitive performance independent of diagnostic category.

Frontal lobe functioning during a simple response conflict task in first-episode psychosis and its relationship to treatment response.

Prior functional magnetic resonance imaging (fMRI) studies have investigated the neural mechanisms underlying cognitive control in patients with psychosis with findings of both hypo- and hyperfrontality. One factor that may contribute to inconsistent findings is the use of complex and polyfactorial tasks to investigate frontal lobe functioning. In the current study we employed a simple response conflict task during fMRI to examine differences in brain activation between patients experiencing their first-episode of psychosis (n = 33) and age- and sex-matched healthy volunteers (n = 33). We further investigated whether baseline brain activation among patients predicted changes in symptom severity and treatment response following 12 weeks of controlled antipsychotic treatment. During the task subjects were instructed to press a response button on the same side or opposite side of a circle that appeared on either side of a central fixation point. Imaging data revealed that for the contrast of opposite-side vs. same-side, patients showed significantly greater activation compared with healthy volunteers in the anterior cingulate cortex and intraparietal sulcus. Among patients, greater baseline anterior cingulate cortex, temporal-parietal junction, and superior temporal cortex activation predicted greater symptom reduction and therapeutic response following treatment. All findings remained significant after covarying for task performance. Intact performance on this relatively parsimonious task was associated with frontal hyperactivity suggesting the need for patients to utilize greater neural resources to achieve task performance comparable to healthy individuals. Moreover, frontal hyperactivity observed using a simple fMRI task may provide a biomarker for predicting treatment response in first-episode psychosis.