Complex traits arise from the combined effects of rare and common genetic variation, development and environment, but resolving their joint contributions has been limited by statistical power. Here, we meta-analyze effects of recurrent copy number variants (CNVs), polygenic scores, sex, age and medications on height and body mass index in 1,447,001 individuals across 6 biobanks and clinical cohorts. CNVs show largely mirror dose-dependent effects of deletions and duplications on both traits, but a subset of loci exhibit asymmetric dose-responses on adult height, consistent with buffering of one allele but not the other. Polygenic background and medications combine with CNVs in ways broadly consistent with additivity. However, detailed analyses of loci at 16p11.2 and 22q11.2 reveal context-dependent effects that vary across development, physiology and sex. At 22q11.2, the net effect of a CNV reflects opposing and reinforcing contributions of multiple genes, providing a potential mechanism for buffering of dosage effects. These results indicate that genetic effects follow additive patterns in aggregate, while context-dependent deviations are widespread for specific loci.

Children with autism spectrum disorder (ASD) often experience co-occurring psychiatric conditions, such as anxiety and attention-deficit/hyperactivity disorder (ADHD), which significantly impair daily functioning. However, the underlying mechanisms linking these conditions to core ASD features remain poorly understood. This study examined relationships between anxiety, ADHD symptoms, and multi-domain neurocognitive abilities in a clinic-based sample of 701 Chinese children with ASD (mean age 8 years, 13.4% female), using the Hong Kong version of the Penn Computerized Neurocognitive Battery. Initial correlations revealed negative associations between cognitive performance and ADHD symptoms, but no direct links with anxiety. Ordinal regression demonstrated that poorer executive function (EF) independently predicted greater ADHD severity along a continuum from no ADHD to subclinical features to co-occurring ADHD, in a dose-dependent manner, even after controlling for core autism symptoms, other cognitive domains, and full-scale IQ. Moderation analyses showed that stronger EF specifically buffered the associations between sensory hyper-responsiveness/sensory-seeking and anxiety symptoms-an effect not seen with other cognitive domains or full-scale IQ. These findings indicate that EF plays a unique, compensatory role in modulating the two most common co-occurring psychopathologies in ASD. Systematic assessment of EF could support early risk stratification, while EF-targeted interventions may help mitigate the burden of ADHD and anxiety in children with ASD.

Cannabis use is linked to elevated psychosis risk, yet the neurobiological mechanisms that couple use to symptom expression remain unclear. Because glutamatergic dysregulation has been implicated in both cannabis effects and psychosis vulnerability, we examined whether brain glutamate relates to dimensional psychosis symptoms as a function of cannabis use across the psychosis spectrum. Seventy-nine participants-typically developing controls, clinical high-risk individuals, and patients with psychosis-completed dimensional clinical assessments, detailed cannabis use surveys, urine toxicology, and ultra-high-field 7T magnetic resonance spectroscopy (1HMRS) of the anterior cingulate cortex (ACC). Linear models assessed the main and interactive effects of ACC glutamate and cannabis use on psychopathology symptoms. Self-reported cannabis use showed good concordance with urine toxicology, with strongest agreement among frequent users. Both lower ACC glutamate and higher cannabis use were independently associated with positive and negative psychosis symptoms. Notably, lower glutamate levels were associated with higher positive symptoms in cannabis users but not cannabis non-users. Exploratory analyses suggested interactions for depressive and manic symptoms, indicating that glutamatergic abnormalities may amplify the overall severity of cannabis-related symptoms. Sensitivity analyses revealed lower ACC glutamate in psychosis patients-especially cannabis users-highlighting diagnostic group differences and reinforcing the link between cannabis exposure and glutamatergic dysfunction. These findings implicate ACC glutamatergic dysfunction as a transdiagnostic correlate of symptom burden, particularly in those with psychosis who are cannabis users. Glutamate-targeted interventions and longitudinal designs will be needed to examine causal pathways linking cannabis exposure to psychosis-relevant outcomes.

Abstract Background Small differences between females and males in cognitive abilities have been consistently reported, but the factors underlying these sex differences remain unclear. Social and cultural factors are thought to play a key role, but studies on this topic have been inconclusive. Examination of genetic factors may shed some light on the mechanisms underlying cognitive sex differences. Methods Using data from the Philadelphia Neurodevelopmental Cohort, a large, general population sample of individuals aged 8 to 21 years old (N = 4,694), we tested for sex differences in the genetic factors (i.e., Gene × Sex interactions) underlying cognitive ability. Participants completed the Penn Computerized Neurocognitive Battery, which consists of 14 tests designed to capture accuracy and speed in five domains: 1) executive function (abstraction and mental flexibility, attention, working memory), 2) episodic memory (verbal, facial, spatial), 3) complex cognition (verbal reasoning, nonverbal reasoning, spatial processing), 4) social cognition (emotion identification, emotion differentiation, age differentiation), and 5) speed (motor, sensorimotor). Composite domain scores were derived using confirmatory factor analysis, and general accuracy (g) and speed (gs) using principal component analysis. Results Small sex differences were observed on most cognitive measures (standardized mean difference (SMD) = 0.061–0.182). Males showed significantly higher genetic variance and lower environmental variance in executive (female σ2 g = 0.301 v. male σ2 g = 0.598, p = 0.001, female σ2 e = 0.243 v. male σ2 e = 0.024, p = 0.007), and complex (female σ2 g = 0.291 v. male σ2 g = 0.610, p = 0.001, female σ2 e = 0.259 v. male σ2 e = 0.023, p = 0.006) accuracy. Females showed significantly higher genetic and lower environmental variance on complex (female σ2 g = 0.575 v. male σ2 g = 0.135, p = 0.009, female σ2 e = 0.222 v. male σ2 e = 0.641, p = 0.012) and social (female σ2 g = 0.589 v. male σ2 g = 0.129, p = 0.009, female σ2 e = 0.236 v. male σ2 e = 0.672, p = 0.012) speed. Genetic correlations between females and males were not significantly different from 1 on any cognitive measure. Altogether, our results suggest that while the same genetic factors influence cognition in females and males, the magnitude of effect of these genetic factors differs. Conclusions We observed small differences between females and males on most cognitive measures, as well as sex differences in heritability on some measures. Future studies are needed to delineate how environmental, genetic, and other biological factors jointly influence cognition.

Background Youth at risk for psychosis based on subthreshold positive symptoms (PS) show elevated negative symptoms such as amotivation, associated with disability and increased risk of psychotic transition. Intrinsic motivation (IM), the desire to obtain internal satisfactions such as mastery or curiosity, is more impaired in psychosis than extrinsic motivation (EM), the desire to obtain external rewards. However, the neural mechanisms underlying IM impairment in PS have scarcely been studied, and never with measures designed for this purpose. Methods We applied a novel fMRI fractal memory task that leveraged distinct feedback conditions designed to engage IM and EM processes, along with self-reported IM and EM, in adolescents and young adults with PS (n = 95) and healthy controls (CT, n = 31). Results We hypothesized that IM would generate reinforcement signals in the ventral striatum (VS), a core motivation region, as individuals internally evaluated their performance relative to their expectations. We further hypothesized that reduced VS activation would relate dimensionally to lower self-reported IM across both PS and CT groups. Consistent with these hypotheses, VS and related motivation circuitry preferentially activated to higher confidence task choices and to reward prediction error during performance feedback. VS activation during task choices related selectively to IM but not EM. Conclusions Our findings highlight the role of VS in encoding self-generated reinforcement signals, and demonstrate a selective relationship between VS activation and IM. Understanding the link between VS dysfunction and impaired IM will facilitate therapeutic advances to remediate IM deficits in those at risk for psychosis.

Long-range white matter (WM) tracts support cognition by enabling communication between distant cortical regions, which are organized along a hierarchy defined by the sensorimotor-to-association (S-A) axis. However, it remains unknown how WM tracts are positioned within the cortical hierarchy to support cognition. Here we show that WM tracts are differentially positioned in the cortical hierarchy to support specific cognitive functions, and that tracts spanning the hierarchy connect regions with greater cognitive diversity. Moreover, tracts situated within the same hierarchical level connect biologically similar regions, while those crossing the hierarchy bridge distinct biological milieux to support diverse cognitive functions. The placement of tracts in the cortical hierarchy also reflects developmental variation in tract microstructure and individual differences in cognition. Together, these findings provide a framework that moves beyond conventional categories of association or projection tracts and links WM tract anatomy to cortical organization, cognitive function, cortical neurobiology and neurodevelopment. We anticipate that this cortex-anchored framework for describing WM tracts may aid the interpretation of individual differences in WM structure related to development and behaviour.

Schizophrenia is often conceptualized as a brain network disorder, yet the organizational principles and heterogeneity underlying widespread cortical abnormalities remain poorly understood. Leveraging multisite MRI data from 3,958 individuals diagnosed with schizophrenia and 5,489 neurotypical individuals, we studied the cortical organization and its subtyping by analyzing individualized cortical network similarity. We used eigenvector decompositions to study spatial patterning of the gradients and graph theory to study small-world topology. Individuals with schizophrenia showed widespread alterations of gradient loadings, which followed inferior-superior and frontal-temporal axes. Alterations in small-world topology were localized in key network hubs, including the insula and anterior cingulate cortex. Brain-symptom association analyses identified a latent dimension linking disorganization symptoms to topological alterations. Finally, clustering cortical alterations identified two robust subtypes, characterized by divergent anterior cingulate (S1) versus temporoparietal (S2) thickness differences aligned with the intrinsic gradient-topology patterns. Both subtypes were present early in the illness and stable across disease stages and age groups. These findings reveal systematic disruptions of cortical organization in schizophrenia, providing a network-level framework for macroscale brain organization and inter-individual heterogeneity.

The COVID-19 pandemic was disruptive to birthing individuals’ peripartum experiences. This study examined associations between interpersonal racism experiences, pandemic worries, and mental health of Asian and Non-Hispanic white birthing individuals receiving prenatal care in a large northeastern healthcare system. The sample (N=122; Age, M = 33.6, SD = 3.73) was n=61 Asian and n=61 white individuals who were propensity matched on age at childbirth, gestational age, relationship status, income, and educational attainment. Participants completed self-report surveys on discrimination experiences, pandemic worries, and general mental health at 10–15 weeks postpartum. Asian individuals reported experiencing significantly more interpersonal racism compared to matched white individuals. Pandemic worries were associated with anxiety and depressive symptoms in the entire sample. Among Asian individuals, the association between pandemic worries and anxiety was stronger among those who reported more interpersonal racism. While postpartum birthing individuals experienced heightened worry during the pandemic, which may have increased risk for anxiety, this association was pronounced among Asian individuals who experienced interpersonal racism. Peripartum individuals had increased rates of mental disorders during the pandemic (Yan et al., 2020). Few studies have examined the pandemic’s negative effects on racially diverse peripartum individuals (Goyal et al., 2023), including Asians who experienced anti-Asian hate. This study investigated the pandemic’s impact on mental health, interpersonal racism, and pandemic worries among Asian postpartum individuals in the U.S.

Abstract Elucidating the neurobiological basis of neurodevelopmental and psychiatric conditions (NDPCs) remains challenging because brain alterations vary within diagnoses and overlap across them. Whether diverse alterations follow a systematic organization that may reflect shared vulnerabilities remains unknown. Here, we assembled 10,135 individuals with schizophrenia, autism, bipolar, obsessive-compulsive, generalized anxiety, and major depressive disorders, and 11,998 reference participants across six continents through the ENIGMA consortium. Using normative modeling, we quantified individual deviations in cortical thickness, surface area, and subcortical volumes relative to lifespan reference trajectories (5 to 80 years). We show that structural deviations converged along cortical axes reflecting connectome organization, maturation, and cytoarchitectonic diversity. These axes mirrored typical population variation, but their expression differed across diagnoses and partly scaled with symptom severity. Even rare and highly individualized extreme deviations followed this organization, concentrating in densely connected regions. Finally, brain structural deviations overlapped substantially across diagnoses, while differences between them increased toward the association cortex. Together, we provide large-scale evidence that structural deviations across NDPCs are systematically constrained by the brain’s intrinsic architecture. This shared organization provides a framework for reconciling individual variability with transdiagnostic similarities and motivates an integrative, systems-level understanding of mental health.

This chapter explores ongoing research in schizophrenia, focusing on the prodromal phase and the early course of the disorder. It emphasizes the importance of identifying neurocognitive and neuroimaging biomarkers that predict the onset of psychosis before full-blown symptoms emerge. The chapter highlights the need for studies on clinical characteristics, pathways to care, and neurodevelopmental processes that underlie psychosis. It also discusses the role of social cognition and brain imaging in understanding early psychosis and the influence of genetic factors, particularly in high-risk populations like those with the 22q11.2 deletion syndrome. Finally, the chapter stresses the potential of future precision medicine approaches, including multimodal interventions targeting non-dopaminergic pathways, to improve outcomes for individuals at risk of schizophrenia.

Importance:22q11.2 deletion syndrome (22q11DS) is among the strongest genetic risk factors for neuropsychiatric disorders and has marked effects on brain structure. Yet, it remains unclear which neuroanatomical features reflect uniform effects of the deletion versus inter-individual biological processes relevant to psychiatric outcomes. Identifying these features is critical for developing targeted treatments and interventions. Objective:To identify brain regions where 22q11DS exerts its most consistent and most variable impacts, and to test whether these patterns align with normative neurotransmitter receptor distributions and cortical growth trajectories. Design:Multisite cross-sectional case-control study. Setting:T1-weighted brain MRI data were obtained across 15 scanners. MRI data underwent standardized processing, quality control procedures and statistical site-adjustment using ComBat. Participants:A total of N = 438 individuals with 22q11DS (5-54 years, 48% females) and 380 typically developing controls (6-58 years, 48% females). Main Outcomes and Measures:Primary outcomes were global and regional cortical thickness and surface area. Mean and dispersion estimates were calculated using double generalized linear models, correcting for age, age2, sex (and intracranial volume for surface area). Quantile shift functions characterized fine-scale distributional differences. Sensitivity analyses adjustedt for co-occurring neuropsychiatric disorders, antipsychotic use and deletion subtype. Secondary outcomes included spatial correspondence between regional structural alterations and normative maps of neurotransmitter receptor density and cortical expansion. Results:Compared with controls, individuals with 22q11DS showed widespread mean differences in cortical thickness and surface area. Notably, 22q11DS was associated with greater regional heterogeneity in both measures, except for reduced dispersion in the anterior cingulate. Effects were attenuated after covariate adjustment. Cortical thickness differences spatially overlapped with regions enriched for glutamatergic and GABAergic receptors. There was partial evidence linking surface area dispersion patterns to normative cortical growth trajectories. Conclusions and Relevance:22q11DS exerts broad effects on cortical structure consistent with a global developmental mechanism, reflected in widespread mean shifts. Beyond these, region-specific variability, particularly in cortical thickness, suggests individualized neurobiological processes. The anterior cingulate emerges as a region of consistent structural deviation. Overall, structural variability in 22q11DS aligns with normative patterns of excitatory-inhibitory signaling and cortical development, implicating these pathways as potential targets for intervention.

This chapter discusses the prevention of schizophrenia, emphasizing early intervention strategies to identify individuals at risk during childhood and adolescence. It introduces a classification system for prevention, which includes primary, secondary, and tertiary approaches, and distinguishes between universal, selective, and indicated prevention strategies. The chapter explains that while risk factors such as family history and birth complications are well-established, recent research focuses on identifying clinical high-risk signs that may emerge during the prodromal phase. Researchers identify several neurodevelopmental and behavioral precursors of schizophrenia, including motor dysfunctions, attention deficits, and social withdrawal, which often begin in infancy. Finally, the chapter stresses the need to refine screening tools and interventions, as current methods have limitations in predicting who will develop schizophrenia.

This chapter defines schizophrenia as a severe neurodevelopmental disorder with onset typically in adolescence or early adulthood and examines its diagnostic criteria, phenomenology, and links to neurobiology. It compares DSM and ICD diagnostic systems, highlights challenges in adolescent diagnosis due to comorbidities and substance use, and emphasizes the importance of developmental context in symptom assessment. The chapter explores early signs of psychosis in clinical high-risk youth, describes neural and cognitive impairments, and connects symptoms to brain circuitry through neuroimaging, electrophysiology, and genetics. It underscores adolescence as a critical period due to hormonal changes, stress sensitivity, and ongoing brain maturation that influence psychosis risk. Finally, the chapter emphasizes integrating neurodevelopmental, genetic, and environmental models to understand the pathophysiology of schizophrenia and guide early detection, intervention, and prevention strategies.

Brain development during adolescence and early adulthood coincides with shifts in emotion regulation and sleep. Despite this, few existing datasets simultaneously characterize affective dynamics, sleep variation, and multimodal measures of brain development. Here, we describe the study protocol and initial release (n = 10) of an open data resource of neuroimaging paired with densely sampled behavioral measures in adolescents and young adults. All participants complete multi-echo functional MRI, compressed-sensing diffusion MRI, and advanced arterial spin-labeled MRI. Behavioral measures include ecological momentary assessment, actigraphy, extensive cognitive assessments, and detailed clinical phenotyping focused on emotion regulation. Raw and processed data are openly available without a data use agreement and will be regularly updated as accrual continues. Together, this resource will accelerate research on the links between mood, sleep, and brain development.

Autism spectrum disorder (ASD) diagnosis is more common in males than females. To understand sex differences in psychopathology and neurocognitive performance, research systematically comparing males and females with autism spectrum disorder to non-autistic peers is critically needed. We examined sex differences in psychopathology and neurocognitive performance profiles in ASD and typically developing youths from the Philadelphia Neurodevelopment Cohort (PNC), a U.S. community sample ascertained through pediatric (non-mental-health) network. We studied 218 youths with ASD diagnosis (IQ> 70, 171 males, 47 females, mean age 12.3 years), age and sex matched to 872 Non-ASD controls. We compared psychopathology in multiple domains including mood-anxiety, fear (phobias), externalizing and psychosis spectrum symptoms as well as neurocognitive function comparing Social and Non-Social cognitive domains. Repeated-measures mixed models were applied with ASD, sex, and their interaction as fixed factors, and psychopathology and neurocognitive domains as within-group factors. All models controlled for age, socioeconomic status, IQ, and ADHD. Findings indicated sex differences in the associations between ASD and co-occurring psychopathology. Among adolescents with ASD, males exhibited more pronounced fear and mood symptoms than females. Analyses also revealed ASD-related sex differences across neurocognitive domains: performance in Social Cognition was lower in adolescents with ASD compared to non-ASD peers for both sexes, while males with ASD showed greater difficulties in Non-Social Cognition relative to females with ASD. In conclusion, ASD diagnosis is associated with sex differences in psychopathology and neurocognition in early adolescence in a large community sample. Results add to the understanding of sex-specific manifestations of ASD in youth.

Neuroanatomical findings on panic disorder (PD) are typically difficult to replicate, with inconsistent effects. These concerns prompted a paradigm shift towards large-scale collaborations, focused on harmonized data extraction and processing for robust examination of PD brain correlates. Hence, leveraging the largest-ever multi-site neuroimaging database on PD (Age: 10–66 years; global sites: 28), compiled by the ENIGMA-Anxiety Working Group, we report on cortical and subcortical differences in individuals with PD (N = 1146) versus healthy controls (HC: N = 3778). The analyses revealed lower thickness and smaller cortical surface area within fronto-temporo-parietal regions in PD (Cohen’s ds: −0.08–0.13), along with lower thalamic and caudate volumes (Cohen’s ds: −0.07–0.12). Diagnosis-by-age2 interactions (Cohen’s ds: 0.07–0.12) revealed lower thickness in individuals with PD compared to HC in certain regions during adulthood (25–55 years), with relative absence of such differences during youth (<25 years) or late adulthood (>55 years). Finally, patient subgroup analyses showed that early disease onset (≤21 years) in PD was associated with larger lateral ventricles (Cohen’s ds: 0.31–0.38), whilst no medication, comorbidity, or severity effects were found. These findings lend support to neurocircuitry models of PD, which postulate differences within fronto-striato-limbic circuits and temporo-parietal regions. Moreover, findings highlight the potential importance of abnormal development and aging in neuroanatomical differences related to PD. Given its unprecedented scale, the current study is an important milestone towards identifying the structural brain correlates of PD.