BACKGROUND AND HYPOTHESIS:Convergent evidence shows the presence of brain metabolic abnormalities in psychotic disorders. This study examined brain reductive stress and energy metabolism in people with psychotic disorders with impaired or average range cognition. We hypothesized that global cognitive impairment would be associated with greater brain metabolic dysregulation. STUDY DESIGN:Participants with affective and non-affective psychosis (n = 62) were administered the MATRICS Consensus Cognitive Battery (MCCB) and underwent a 31P-magnetic resonance spectroscopy scan at 4T. We used a cluster-analysis approach to identify 2 clusters of participants with and without cognitive dysfunction. We compared clusters on brain redox balance or reductive stress, measured by the ratio of nicotinamide adenine dinucleotide (NAD+) and its reduced form NADH, in addition to creatine kinase (CK) enzymatic activity and pH. STUDY RESULTS:The mean (SD) age of participants was 25.1 (6.3) years. The mean NAD+/NADH ratio differed between groups, with lower NAD+/NADH ratio, suggesting more reductive stress, in the impaired cognitive cluster (t = -2.60, P = .01). There was also a significant reduction in CK activity in the impaired cognitive cluster (t = -2.19, P = .03). Intracellular pH did not differ between the 2 cluster groups (t = 1.31, P = .19). The clusters did not significantly differ on severity of mood and psychotic symptomatology or other measures of illness severity. CONCLUSIONS:Our results demonstrate that psychotic disorders with greater cognitive impairment have greater brain metabolic dysregulation, with more reductive stress and decrease in energy metabolic rate markers. This provides new evidence for the potential of emerging metabolic therapies to treat cognitive deficits in psychotic disorders.

BACKGROUND AND HYPOTHESIS:Deviated brain folding patterns in psychosis may reflect dysfunctional brain development, more specifically cortical growth and white matter myelination. However, mechanisms that underlie the cortical folding disturbances and their relationship to clinical phenotypes in psychosis remain unknown. STUDY DESIGN:This cross-sectional multimodal neuroimaging study combines structural and diffusion magnetic resonance imaging (MRI) in 203 individuals with early psychosis and 73 healthy individuals. The primary goal is to use local gyrification index (LGI), which quantifies cortical folding, to assess possible cortical abnormalities in subjects with early psychosis. The secondary goal is to combine gyrification measures with advanced diffusion MRI indices, namely, heterogeneity of fractional anisotropy (FA), a proxy for cortical cytoarchitecture, and free-water corrected FA, the latter associated with the tissue-related white matter microstructure. Finally, the relationship between these imaging measures with psychiatric symptoms and cognitive abilities are examined. STUDY RESULTS:Compared to healthy individuals, the early psychosis group exhibited a significant LGI reduction, potentially reflecting sulcal widening and shallowing in the left temporo-parietal region. Local gyrification index was significantly associated with heterogeneity of FA in the corresponding region. Lower LGI was also associated with reduced FA in the white matter tracts connecting this region to the frontal lobe. Finally, lower LGI at the temporo-parietal junction was associated with more severe negative symptoms. CONCLUSIONS:We present the first in vivo evidence that anomalies in cortical folding may be linked to alterations in both the underlying cortical cytoarchitecture and associated microstructure of ipsilateral long-range white matter connections in psychosis.

Objective:Children at familial high risk for psychosis (FHR) are at substantially increased risk for psychotic disorders and other serious mental illnesses. Identifying risk subgroups within FHR youth may enhance prediction models to identify children at greatest risk for potential intervention. This study investigated psychosis-linked symptoms and structural brain patterns in neurocognitive subgroups among FHR children in the Adolescent Brain Cognitive Development (ABCD) Study using baseline, 2-year, and 4-year follow-up data. Methods:Among children with first- and second-degree family history of psychosis, neurocognitive subgroups were defined using NIH Toolbox Cognitive Battery baseline age-corrected total scores: children with low (FHR-LC, 0-33%, n=234), moderate (FHR-MC, 33-66%, n=261), and high (FHR-HC, 66-100%, n=277) cognitive performance. Psychiatric symptoms were assessed using Prodromal Questionnaire-Brief Child Version (PQ-BC) and Childhood Behavior Checklist (CBCL). Regional vulnerability indices (SSD-RVIs), which quantify the similarity of participants' structural brain patterns to the patterns found in adults with schizophrenia spectrum disorders, were calculated using cortical thickness measures following rigorous quality control. Results:At baseline, FHR-LC had significantly higher PQ-BC and CBCL scores, and trend-level higher SSD-RVIs compared to FHR-HC. Longitudinally, PQ-BC and CBCL scores decreased with age across all FHR participants, while SSD-RVIs remained stable. No longitudinal cognitive subgroup-by-age interactions were observed, indicating that subgroup differences persisted over time. Conclusion:Children at FHR who have concurrent poor cognitive performance exhibit elevated and stable clinical and imaging psychosis risk markers. This suggests that they may represent a risk subgroup with elevated vulnerability, presenting an opportunity for early identification and intervention.

Background:This paper presents the recruitment sources of clinical high-risk (CHR) and community controls (CC) from the Accelerating Medicines Partnership Schizophrenia (AMP SCZ) program, which aims to study various clinical variables and biomarkers in 2040 CHR and 652 CC participants. Methods:A total of 1640 CHR and 514 CC had recruitment source data. The Positive Symptoms and Diagnostic Criteria for the Comprehensive Assessment of At-Risk Mental States Harmonized with the SIPS was utilized to assess CHR criteria and severity of attenuated psychotic symptoms (APSs), and the Global Functioning: Social Scale was used for social functioning. Participants were recruited through various methods, including referrals from healthcare providers, schools, and community agencies, and self-referrals via outreach efforts and advertising. Results:Participants were recruited from 13 different sources, with self-referral being the most common for both CHR and CC. Other notable sources included child and youth services and psychiatric hospitals and departments. Regional differences in recruitment patterns were observed across continents. Differences in age, APS, and social functioning for CHR participants were examined in the top 5 recruitment sources. Overall, self-referred individuals were typically older, with less severe APS and higher levels of functioning, whereas those from adult community mental health services had poorer functioning and more severe APS. The remaining recruitment groups fell between these 2 extremes. Conclusion:This paper highlights the diverse recruitment sources for the AMP SCZ program. Self-referral was a significant source, particularly in North America, reflecting changing help-seeking behaviors influenced by the internet and social media. The findings underscore the importance of understanding recruitment sources to optimize future CHR research.

Cognitive impairment occurs at higher rates in individuals at clinical high risk (CHR) for psychosis relative to healthy peers, and it contributes unique variance to multivariate prediction models of transition to psychosis. Such impairment is considered a core biomarker of schizophrenia. Thus, cognition is a key domain measured in the Accelerating Medicines Partnership® program for Schizophrenia (AMP SCZ initiative). The aim of this paper is to describe the rationale, processes, considerations, and final harmonization of the cognitive battery used in AMP SCZ across the two data collection networks. This battery comprises tests of general intellect and specific cognitive domains. We estimate premorbid intelligence at baseline and measure current intelligence at baseline and 2 years. Eight tests from the Penn Computerized Neurocognitive Battery (PennCNB), which measure verbal learning and memory, sensorimotor ability, attention, emotion recognition, working memory, processing speed, verbal memory, visual memory, and motor speed are administered repeatedly at baseline, and four follow-up timepoints over 2 years.

INTRODUCTION:Major depressive disorder (MDD) and bipolar disorder (BD) are often associated with persistent cognitive deficits that impair psychosocial functioning. While pro-cognitive interventions show promise, trial findings are inconsistent, potentially due to baseline factors influencing treatment response. This systematic review summarizes evidence on pre-treatment characteristics associated with cognitive improvement and offers methodological recommendations. METHODS:A systematic search was conducted in PubMed/MEDLINE, EMBASE, PsycINFO, and Cochrane Library from inception to February 28, 2025. Eligible studies included primary or secondary analyses of randomized controlled trials (RCTs) investigating predictors of cognitive response to pro-cognitive interventions in MDD and/or BD. Two researchers independently conducted study selection and risk of bias assessments. Findings were synthesized qualitatively. RESULTS:Forty studies (N = 3864) were identified, covering pharmacological treatments (k = 20; N = 2299), psychological therapies (k = 16; N = 1165), brain stimulation (k = 2; N = 168), and physical activity (k = 2; N = 232). Poorer baseline cognitive performance was the most consistent predictor of greater cognitive improvement, though the direction of the effect was not entirely uniform across all studies. Baseline depression severity showed no significant association with cognitive outcomes. Age, education, sex, IQ, diagnosis, and medication status were similarly non-predictive. Risk of bias was high in 77% of studies, mainly due to deviations from specified outcomes, poor randomization processes, and inconsistent handling of missing data. Considerable heterogeneity in interventions, outcome measures, and sample characteristics limited replicability and precluded meta-analysis. CONCLUSION:Poorer baseline cognition emerged as the most reliable predictor of greater cognitive improvement across interventions. More rigorous, well-powered studies are needed to replicate these findings and identify robust predictors to guide personalized pro-cognitive treatment approaches in mood disorders.

Introduction Negative symptoms are associated with poorer cognitive functioning in psychosis, and both negative symptoms and cognition are associated with poorer community functioning, even in the early course of illness. Current conceptualizations of negative symptoms in psychosis have identified separate subdomains, not all of which may be affected in every patient; however, few studies have examined associations between specific negative symptom subdomains and cognition and functioning in early psychosis. Methods Participants with schizophrenia spectrum disorders (SSD; n = 26) or mood disorders with psychosis (MDP; n = 41) within the first 6.5 years of illness were assessed at two timepoints on negative symptoms (BNSS and CAINS), cognition, and functioning. Group comparisons and correlations among measures were conducted, and linear regression predicting functioning at follow-up by baseline negative symptoms and cognition were run. Results Groups did not differ on negative symptoms or cognition at either timepoint. The SSD group had more impaired functioning at both timepoints. BNSS and CAINS total scores and several subscales correlated with cognition at both timepoints transdiagnostically. At baseline, BNSS Anhedonia, Asociality, and total score and CAINS Motivation and Pleasure and total score significantly predicted MIRECC GAF symptoms at follow-up and BNSS Asociality, Avolition, and BNSS and CAINS total scores predicted MIRECC GAF social functioning at follow-up. Cognition did not predict functioning at follow-up. Conclusion Baseline negative symptoms of amotivation and anhedonia, but not cognition, predicted measures of functioning at follow-up. These findings suggest that interventions targeting motivation and hedonic capacity early in treatment may improve future functioning.

Research on the intersection between eating disorders and schizophrenia (SCZ) has mainly focused on binge eating, since increased appetite and metabolic side effects are common during antipsychotic use. However, the prevalence of restrictive eating and anorexia nervosa may be higher in people with SCZ than in the general population, and evidence suggests shared genetic liability for SCZ and anorexia nervosa (AN). The aim of this systematic review was to examine the prevalence, psychological and biological mechanisms, and theoretical underpinnings underlying the co-occurrence of AN and SCZ. We identified 40 articles that met inclusion criteria. Evidence suggested that the prevalence of AN in patients with SCZ is higher than would be expected in the general population; conversely, evidence regarding the prevalence of SCZ in AN was mixed. Psychological mechanisms underlying AN in people with SCZ fell into three categories: positive symptoms, negative symptoms, and atypical pathways. A limited literature generally supports the hypothesis of higher prevalence of AN in patients with SCZ, but there are few studies in this area. Studies of the prevalence of SCZ in AN yield more mixed findings, although these studies are also relatively small and few. Further, studies of both types tend to include only clinically ascertained samples, which limits the generalizability of findings beyond patients. Larger, better-designed studies may improve identification and treatment of people with co-occurring SCZ and AN.

OBJECTIVE:Psychomotor function is a critical marker of risk and outcome of psychosis. Grip strength is one aspect of psychomotor function that is known to be linked to structural neural integrity and well-being. This study sought to determine whether grip strength is a marker of alterations in resting-state connectivity and well-being in psychotic disorders in order to further clarify the mechanisms by which psychosis phenomenology is related to psychomotor processes. METHODS:The authors analyzed resting-state functional MRI and grip strength in 89 individuals with early psychosis and 51 control subjects without psychiatric disorders from the Human Connectome Project for Early Psychosis. Participants ranged in age from 16 to 35 years. Using multivariate pattern analysis of whole-connectome data, the authors identified brain correlates of grip strength and then replicated this analysis using the NIH Toolbox well-being measures and the Global Assessment of Functioning Scale (GAF). RESULTS:The psychosis group exhibited reduced grip strength, well-being, and GAF scores compared to the control group. Grip strength was linked to resting-state connectivity in the sensorimotor cortex, anterior cingulate cortex, and cerebellum. Connectivity correlated with the default mode network (DMN) (rsensorimotor=0.22, rcingulate=0.30, rcerebellum=0.24). When the analysis was repeated for GAF and well-being, overlapping regions in the sensorimotor cortex and cerebellum were connected to the DMN and related to GAF (rsensorimotor=0.17, rcerebellum=0.28) and well-being (rsensorimotor=0.16, rcerebellum=0.16). Relationships were driven by the psychosis group for cerebellum and cingulate nodes. CONCLUSIONS:Data-driven, connectome-wide analysis identified shared brain correlates of grip strength, overall function, and well-being in a sample of young adults with psychosis and healthy control subjects. This suggests that grip strength may be a marker of DMN connectivity, which may in turn be an important marker of overall health, even in young adult populations.

The Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ) project assesses a large sample of individuals at clinical high-risk for developing psychosis (CHR) and community controls. Subjects are enrolled in 43 sites across 5 continents. The assessments include domains similar to those acquired in previous CHR studies along with novel domains that are collected longitudinally across a period of 2 years. In parallel with the data acquisition, multidisciplinary teams of experts have been working to formulate the data analysis strategy for the AMP SCZ project. Here, we describe the key principles for the data analysis. The primary AMP SCZ analysis aim is to use baseline clinical assessments and multimodal biomarkers to predict clinical endpoints of CHR individuals. These endpoints are defined for the AMP SCZ study as transition to psychosis (i.e., conversion), remission from CHR syndrome, and persistent CHR syndrome (non-conversion/non-remission) obtained at one year and two years after baseline assessment. The secondary aim is to use longitudinal clinical assessments and multimodal biomarkers from all time points to identify clinical trajectories that differentiate subgroups of CHR individuals. The design of the analysis plan is informed by reviewing legacy data and the analytic approaches from similar international CHR studies. In addition, we consider properties of the newly acquired data that are distinct from the available legacy data. Legacy data are used to assist analysis pipeline building, perform benchmark experiments, quantify clinical concepts and to make design decisions meant to overcome the challenges encountered in previous studies. We present the analytic design of the AMP SCZ project, mitigation strategies to address challenges related to the analysis plan, provide rationales for key decisions, and present examples of how the legacy data have been used to support design decisions for the analysis of the multimodal and longitudinal data. Watch Prof. Ofer Pasternak discuss his work and this article: https://vimeo.com/1023394132?share=copy#t=0 .

BACKGROUND:The time following a recent onset of psychosis is a critical period during which intervention may be maximally effective. Studying individuals in this period also offers an opportunity to investigate putative brain biomarkers of illness prior to the long-term effects of chronicity and medication. The Human Connectome Project for Early Psychosis (HCP-EP) was funded by the National Institutes of Mental Health (NIMH) as an extension of the original Human Connectome Project's approach to understanding the human brain and its structural and functional connections. DESIGN:The HCP-EP data were collected at 3 sites in Massachusetts (Beth Israel Deaconess Medical Center, McLean Hospital, and Massachusetts General Hospital), and one site in Indiana (Indiana University). Brigham and Women's Hospital served as the data coordination center and as an imaging site. RESULTS:The HCP-EP dataset includes high-quality clinical, cognitive, functional, neuroimaging, and blood specimen data acquired from 303 individuals between the ages of 16-35 years old with affective psychosis (n = 75), non-affective psychosis (n = 148), and healthy controls (n = 80). Participants with early psychosis were within 5 years of illness onset (mean duration = 1.9 years, standard deviation = 1.4 years). All data and novel or modified analytic tools developed as part of the study are publicly available to the research community through the NIMH Data Archive (NDA) or GitHub (https://github.com/pnlbwh). CONCLUSIONS:This paper provides an overview of the specific HCP-EP procedures, assessments, and protocols, as well as a brief characterization of the study participants to make it easier for researchers to use this rich dataset. Although we focus here on discussing and comparing affective and non-affective psychosis groups, the HCP-EP dataset also provides sufficient information for investigators to group participants differently.

Background:This paper focuses on the baseline clinical characterization of the participants in the Accelerating Medicines Partnership Schizophrenia (AMP SCZ) program. The AMP SCZ program is designed to investigate a wide array of clinical variables and biomarkers in a total of 2040 clinical high-risk (CHR) participants and 652 community control (CC) participants. Methods:The dataset analyzed includes 1642 individuals at clinical high risk for psychosis and 519 CCs. Key measures include the Positive Symptoms and Diagnostic Criteria for the Comprehensive Assessment of At-Risk Mental States Harmonized with the Structured Interview for Psychosis-Risk Syndromes, which determined CHR criteria and the severity of attenuated psychotic symptoms (APS). Other measures included the Structured Clinical Interview for DSM-5, scales to assess negative symptoms, depression, suicidal ideation, substance use, social and role functioning, and a selection of patient-reported outcomes. Results:CHR participants presented with more severe ratings on all clinical measures and poorer functioning relative to the CC. There were a few significant small associations between measures of APS and other clinical measures. Conclusion:The results from this study support previous research indicating that CHR individuals face serious clinical challenges beyond the risk of developing psychosis. Findings indicate significant associations among various clinical measures, underscoring the complex nature of the CHR population. Limitations are acknowledged, including the preliminary nature of the data and the need for more in-depth analyses from AMP SCZ papers already in progress. Future work will focus on longitudinal data and further exploration of clinical variables and their relationship with biomarkers.

Cognitive dysfunction is a core dimension in psychotic disorders and among the strongest predictors of disability and poor quality of life. Cognitive impairments are highly heterogeneous, and cross-sectional studies have consistently found evidence of distinct cognitive profiles both within diagnoses and transdiagnostically. Findings regarding the course of cognitive impairments over time have been mixed. We hypothesized that subgroups of patients in the early course of psychosis show distinct cognitive trajectories that can be identified using data-driven methods, and that these subgroups differ on clinical and functional outcomes over time. Persons with schizophrenia-spectrum disorders or mood disorders with psychosis in the early course of illness (N=127) were assessed using clinical, functional and cognitive measures at three timepoints: baseline, 8 and 16 months. Group-based trajectory modeling was used to identify cognitive subgroups, which were then compared on clinical and functional measures using multilevel models. We identified three distinct cognitive subgroups: an Impaired group, an Average group, and a High-Functioning group. Cognition was stable over the follow-up period in the Impaired and High-Functioning groups, whereas the Average group showed cognitive improvement. Groups did not differ in terms of diagnostic distribution, baseline clinical symptoms, and most baseline functional and demographic measures. However, over the follow-up, group membership predicted changes in negative symptoms, social functioning, and patient-reported outcomes, with the Impaired group showing the most severe illness course. We conclude that patients in the early course of psychosis show distinct cognitive trajectories that predict future symptoms and social functioning, despite presenting no clinical differences at baseline. These findings have implications for understanding biology-cognition associations, which may be related to heterogeneity; developing predictive models for clinical and functional outcomes; and personalizing treatment to support patients' cognitive, clinical and functional needs towards improving illness course.