Most genetic variants associated with complex traits are hypothesized to regulate gene expression. To understand the genetics underlying gene expression variability, we characterized 14,324 RNA-sequencing samples from the Trans-Omics for Precision Medicine program and performed expression and splicing quantitative trait locus (e/sQTL) analyses in six tissues and cell types, including whole blood (n = 6454) and lung (n = 1291). We detected tens of thousands of secondary cis-e/sQTLs, showing that secondary cis-e/sQTL discovery remains unsaturated. We fine-mapped UK Biobank-derived genome-wide association study (GWAS) signals from 164 traits and identified e/sQTL colocalizations for 10,611 GWAS signals, including 7096 that colocalize with secondary e/sQTLs. Our results suggest that even larger e/sQTL analyses will uncover additional secondary e/sQTLs, further benefiting GWAS interpretation.

Pleiotropic and monotonic effects of gene dosage are central to understanding comorbidities in developmental pediatric and psychiatric disorders, yet the underlying biological processes are not well characterized. Here we develop a functional burden analysis to investigate the association of all protein-coding copy-number variants, genome-wide, with 43 complex traits in approximately 500,000 UK Biobank participants. We test variant associations disrupting 172 tissue or cell-type gene sets, finding associations for all traits, which we replicate in the All of Us cohort. Functional burden pleiotropy, defined as the number of traits significantly associated with a gene set, correlates with genetic constraint and is higher for brain than non-brain functions, even after normalizing for genetic constraint. Levels of pleiotropy, measured by burden correlation, are similar in deletions and loss-of-function single-nucleotide variants, and higher than in common variants and duplications. Most gene dosage responses are non-monotonic, with deletions and duplications showing same-direction effects, and monotonic responses decrease with genetic constraint. We observe associations between functional gene sets and traits for either deletions or duplications, but rarely both, with negatively correlated effect sizes. Together, these results link genetic constraint and brain-specific mechanisms to the whole-body multimorbidity of neurodevelopmental and psychiatric conditions. Gene dosage can help explain comorbidities in developmental pediatric and psychiatric disorders. Here, the authors map how rare copy-number variants disrupting tissue and cell-type gene sets shape 43 human traits.

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.

Structural variants, including copy number variants (CNVs), confer substantial risk for neurodevelopmental and psychiatric disorders (NPDs), yet whether their cortical effects relate to those observed in the psychiatric conditions they predispose to remains unclear. Here, we present the first systematic comparison of cortical phenotypes across 18 NPD-associated CNVs and aneuploidies, disorder-associated common variants, and 8 psychiatric disorders. Rare CNVs preferentially affected total surface area (SA), with 11-fold larger effects than psychiatric diagnoses, while NPDs preferentially affected mean cortical thickness (CT), with most CT effects observed in medicated subgroups, suggesting non-genetic contributions. NPD-associated common variants showed enrichment in SA but not CT associations. Regionally, both rare and common genetic variants showed larger effects in sensorimotor regions, aligning with the sensorimotor-to-association cortical gradient as well as regional heritability estimates. In contrast, psychiatric diagnoses showed larger effects in association regions. Individual NPD-associated variants were evenly split between those increasing and decreasing surface area. This heterogeneity likely explains why aggregating variants using polygenic scores shows only weak associations with SA. Overall, cortical signatures of psychiatric diagnoses diverge from those associated with genetic risk. Genetic variants preferentially impact SA and sensorimotor regions through early developmental mechanisms, while psychiatric diagnoses are associated with CT and association regions likely reflecting medication, illness chronicity, and environmental factors.

Trauma is a risk factor for early-onset (EOP) and adult-onset (AOP) psychosis and is also associated with other psychiatric diagnoses and poorer fputcomes in the general population. We examined (1) whether trauma effects are specific to psychosis and (2) whether these effects differ between EOP and AOP.Linear regression models evaluated trauma exposure in two samples (EOP: 647 cases, 694 controls; AOP: 162 cases, 230 controls) as a function of psychotic and nonpsychotic psychiatric diagnosis (NPD) status. Parallel models assessed associations between trauma and symptom severity, global functioning, and cognition. Relative to individuals without psychiatric disorders, participants with psychosis and comorbid NPDs reported the greatest trauma exposure (EOP: β = 0.95; AOP: β = 1.1), followed by those with psychosis only (EOP: β = 0.67; AOP: β = 0.41) and NPDs only (EOP: β = 0.47; AOP: β = 0.36). Greater numbers of NPDs were associated with higher trauma exposure regardless of psychosis status (EOP: β = 0.15; AOP: β = 0.24). Trauma was associated with greater symptom severity (EOP: β = 0.13; AOP: β = 0.14) and poorer global functioning (EOP: β = -0.21; AOP: β = -0.13), but not cognition. No psychosis-by-trauma interactions were observed.Psychosis-specific effects were limited to greater trauma exposure, while trauma-related impacts on outcomes were similar across diagnostic groups. Findings were consistent across EOP and AOP. Results highlight the need for trauma-informed care in psychiatry given broad effects that influence disease course and prognosis.

Autism is a heritable neurodevelopmental condition marked by impaired social interaction, repetitive behavior, and co-occurring conditions. Sleep disturbances are common in autism. This study uses low-cost wearable devices to compare sleep, physical activity, and circadian behavior in autistic adults and their non-autistic relatives. We recruited 318 autistic individuals and 130 family members, collecting accelerometer data over 3 weeks (8249 days). Using a data-driven approach, we identified actimetry-derived features associated with autism. We examined 308 traits using the elastic net algorithm and linear mixed effects regressions. We identified 52 actimetry measures associated with autism (area under the curve: 0.812; confidence interval: 0.761-0.862), validated in a test set (area under the curve: 0.756; confidence interval: 0.700-0.813). Both mean and day-to-day variability in several measures (e.g., time spent sedentary, total light physical activity) were associated with autism. In autistic individuals, reduced physical activity during wake was more strongly associated with shorter sleep time than in non-autistic relatives (likelihood ratio: 41.6; p = 1.13e-10). Reduced physical activity in autistic individuals was linked to increased social impairment, as measured by the Social Responsiveness Scale. Long inactivity periods and lower physical activity levels were associated with autism, correlating with less sleep and later sleep onset. Interventional studies are needed to explore if improving sleep and physical activity can improve the quality of life for autistic individuals.Lay AbstractAutistic individuals frequently report problems with their sleep, though what aspects of sleep are most affected is not well understood. In this study, we recruited 318 adult autistic participants without intellectual disability and 130 of their non-autistic family members to measure their sleep, physical activity, and daily routines. Study participants wore accelerometer-based wrist-worn devices over 3 consecutive weeks to record their movement and activity. In total, 154 distinct physical activity, sleep, and behavioral traits were identified from the recordings, 52 of which were found to associate with autism. Many of these traits were related to physical activity, where autistic individuals were more likely to be less active for longer periods and have lower overall physical activity levels. Long periods of inactivity also associated with less sleep, with a stronger association in those with autism. For example, for every hour of inactivity, autistic participants had on average ~23 min less of sleep compared to ~17 min in their family members. Autistic individuals with lower levels of physical activity showed higher social impairment as measured by the Social Responsiveness Scale. Overall, lower physical activity may impair sleep and worsen the core features of autism. Interventional studies aimed to increase physical activity may improve the quality of life of autistic individuals.

The vast majority of trait-associated loci discovered through genome-wide association studies (GWAS) are non-coding, yet most lack statistical alignment with any discovered expression quantitative trait loci (eQTLs). In particular, eQTLs are depleted at gene-distal regions and at "functionally important" genes - those with strong selective constraint and complex regulatory landscapes - likely due to selective depletion of high-effect variants. Here, we investigate the role of variants with weaker effects on expression transmitted through distal regulatory elements, which are detectable as chromatin accessibility QTLs (caQTLs). We aggregated caQTL data from ten studies derived across different tissues, cell-types and lines, representing 104,024 lead caQTLs across 3,457 samples. We found that, across a range of gene properties, caQTLs are discovered at functionally important genes more often than eQTLs. These observations are consistent with a model in which many eQTLs and GWAS hits are mediated through genetic effects on regulatory elements, which may have weak or context-dependent effects on gene expression. Our results suggest that caQTL discovery is more sensitive than eQTL discovery in capturing the molecular consequences of GWAS hits, and can provide complimentary information to eQTLs by implicating functional mechanisms of additional disease-associated loci.

Background:Adolescent mental health is influenced by family history. Experiences of trauma also convey substantial risk for mental health challenges. Mediation of the association of family history with adolescent mental health by trauma experiences could be actionable and warrants evaluation. We sought to interrogate the mediating role of trauma in the association of family history of psychiatric disorders (FH) with adolescent general psychopathology, accounting for shared environment and genetics. Methods:The Philadelphia Neurodevelopmental Cohort was a cross-sectional study of participants ages 8 to 21 years with English fluency and in good medical health with characterization from November 2009 to December 2011. The analysis reported here was completed from March 2023 to February 2025. Among 7840 participants, we tested associations of first-degree FH (category count [0-4]: psychosis, mood, suicide attempt, substance use), youth exposure to trauma, neighborhood environment (block-level geocoded socioeconomic indices), and genomic factor of polygenic scores for psychopathologies (depression, posttraumatic stress disorder, schizophrenia, bipolar, cross-disorder) with adolescent general psychopathology modeled as p-factor. Association of FH with general psychopathology was assessed with structural equation modeling, querying for an indirect pathway via trauma, with stepwise accounting of genomics and shared environment, controlling for age and sex. Results:Of 7840 participants, 31% had FH and 44% of youths reported trauma exposure. Trauma had substantial direct association with general psychopathology and consistently mediated more than 20% of variance from FH to psychopathology, accounting for neighborhood and genomic predisposition. Conclusions:Trauma exposures mediate a substantial portion of association between FH and adolescent psychopathology, an opportunity for transgenerational intervention.

Background Despite schizophrenia’s high heritability, the effects of its genetic risk on the brain remain poorly understood. Prior studies on this topic have usually employed either nuclear family designs, which are especially sensitive to possible shared environmental effects, or polygenic risk scores, which index a small portion of total genetic risk. These studies have also typically examined the brain using MRI at the relatively gross level of the volume, thickness, or surface area of particular anatomical structures or regions of interest. As techniques for examining abnormalities of gene expression in neurons now allow post-mortem studies at the single cell level, more precise information about where schizophrenia genetic risk affects the brain is needed. Methods We employed a multiplex (two schizophrenia probands per family), extended pedigree (first to fourth degree relatives of probands) design that boosts genetic effects and allows the estimation of genetic correlations between schizophrenia and brain measures. A total of 1304 participants, including 789 relatives from 52 multiplex extended-pedigree families of 123 schizophrenia patients along with 517 unrelated controls were assessed for diagnoses and 506 participants provided quality MRI scans (230 relatives, 30 with schizophrenia, from 32 pedigrees and 276 unrelated controls). Here we present data from 3-T structural MRI scans to examine where in the brain schizophrenia genetic risk affects gray matter concentration at voxel-wise resolution (1 mm3). FSL and the Harvard Oxford Structural Atlas were used for MRI analyses and genetic analyses employed the SOLAR-Eclipse program with False Discovery Rate (FDR) correction, p < .05. Results Of the 1,433,823 voxels in the total brain (including cerebellum and brain stem), 210,152 (14.7%) were significantly heritable. Although present throughout the brain, heritable voxels were primarily in subcortical structures (30% - 60% voxels of subcortical structures). 24,101 voxels (11.5% of significantly heritable voxels, 1.7% of total voxels) were significantly genetically correlated with schizophrenia, indicating the location of schizophrenia genetic risk effects on gray matter concentration. Forty-five clusters of 50 or more voxels that were significantly genetically correlated with schizophrenia were identified (603 to 50 voxels in volume). Although distributed throughout the brain, the largest clusters of voxels significantly genetically correlated with schizophrenia were concentrated in subcortical structures (cerebellum, brain stem, caudate, 603 to 211 voxels) as well as some in the frontal cortex (frontal orbital cortex, 179 voxels). Most (70%) of genetic correlations with schizophrenia were negative (Rg = -.84 to -.48), indicating lower gray matter concentration with increasing schizophrenia genetic risk. Discussion These results provide a view of the effects of schizophrenia genetic risk on gray matter concentration at voxel-wise (1 mm3) resolution that should be helpful in better targeting post-mortem studies of abnormal neuronal gene-expression in schizophrenia. These findings also highlight subcortical structures as being especially sensitive to schizophrenia genetic risk effects – more so than frontal cortex regions. They also emphasize the importance of further study of the cerebellum and brain stem in schizophrenia, which are often omitted in sMRI studies.

OBJECTIVE:Late childhood is a crucial period for individuals with psychiatric disorders. While common single-nucleotide polymorphisms explain a large proportion of inherited risk, structural variations including copy number variants (CNVs) play a significant role in the genetic architecture of neurodevelopmental disorders. The relevance of CNVs to child psychopathology and cognitive function in the general population remains underexplored. The authors conducted a comprehensive exploration of the CNV architecture underlying dimensions of psychopathology and cognitive phenotypes within the Adolescent Brain Cognitive Development (ABCD) Study. METHODS:Using two algorithms for CNV detection, the authors identified duplications and deletions across 11,876 individuals from the ABCD Study. Quality control procedures considered array log R ratio and B allele frequency profiles, CNV size, agreement between the two algorithms, and genomic location of CNVs. CNVs that passed quality control were used to identify regions associated with quantitative measures of broad psychiatric symptom domains and cognitive functioning. Additionally, CNV risk scores, reflecting the aggregated burden of genetic intolerance to inactivation and dosage sensitivity, were calculated to assess cumulative impact on overall and dimensional psychiatric and cognitive phenotypes. RESULTS:Across 8,564 individuals whose data passed quality control, 4,111 carried 5,760 autosomal CNVs. Although no CNV regions reached significance after strict multiple testing correction was applied, 16 regions were associated with psychopathology and cognitive development at an uncorrected genome-wide significance level. A duplication at 14q11.2 showed the strongest association with attentional psychopathology. Moreover, individuals carrying CNVs previously associated with neurodevelopmental disorders exhibited greater impairment in social functioning and cognitive performance across fluid intelligence, working memory, and processing speed. Notably, higher CNV risk scores were significantly correlated with greater attention problems and cognitive impairment across multiple domains (fluid intelligence, attention, working memory, flexible thinking, and processing speed). CONCLUSIONS:These findings shed light on the contributions of CNVs to interindividual variability in complex traits related to neurocognitive development and child psychopathology.

While pleiotropic effects of gene dosage are of particular relevance for comorbidities observed in the developmental pediatric and psychiatric clinic, the biological processes underlying such pleiotropy remain unknown. We developed a new functional burden analysis (FunBurd) to investigate all CNVs, genome-wide, beyond well-studied recurrent CNVs. In ~500,000 UK-Biobank participants, we tested the association between 43 traits and CNVs disrupting 172 tissue or cell-type gene-sets. CNVs affected all traits. Pleiotropy was correlated with genetic constraint and was higher in the brain compared to non-brain functions, even after normalizing for genetic constraint. The levels of pleiotropy, measured by burden correlation, were similar in deletions and loss-of-function SNVs and higher compared to common variants and duplications. Gene sets under high genetic constraint showed less monotonic gene dosage responses across traits. Even in the absence of a monotonic response, we observed a negative correlation between deletion and duplication effect sizes across most traits. Overall, functional gene sets are preferentially associated with a given trait when either deleted or duplicated, but rarely both.

BACKGROUND:von Willebrand disease (VWD) is a common inherited bleeding disorder caused by low levels or activity of circulating von Willebrand factor (VWF). Genetic susceptibility to VWF antigen (VWF:Ag) below normal (≤ 50 IU/dL) in the general population is underexplored. OBJECTIVES:To identify genetic variants influencing VWF:Ag levels ≤ 50 IU/dL. METHODS:We performed a genome-wide association study in 926 cases with VWF:Ag levels ≤ 50 IU/dL and 12 846 controls from 7 studies from the Trans-Omics for Precision Medicine program. We then examined whether significant genome-wide findings were also associated with clinical diagnosis of VWD in 5 biobanks with 708 VWD cases and 1 286 069 controls, and with 6 bleeding and thrombotic disorders in FinnGen. RESULTS:Variants at 2 loci were associated (P < 5 × 10-9) with VWF:Ag levels ≤ 50 IU/dL: ABO and VWF. The VWF index variant, p.Tyr1584Cys, is a rare (0.22%) missense variant with odds ratio (OR) of 78.58, while the ABO index variant is a common intronic variant with a smaller effect (OR = 2.52). Notably, both VWF (OR = 7.16) and ABO (OR = 1.57) variants were also associated (P < .025) with diagnosed VWD. Among p.Tyr1584Cys heterozygotes, the penetrance of VWF:Ag levels ≤ 50 IU/dL was 24.2% and the penetrance of diagnosed VWD was 0.3%. p.Tyr1584Cys was associated (P < .0042) with increased odds of heavy menstrual bleeding (OR = 1.27), iron deficiency anemia (OR = 1.55), and intrapartum hemorrhage (OR = 2.20), but decreased odds of deep vein thrombosis (OR = 0.54). CONCLUSIONS:Although there are currently conflicting interpretations of pathogenicity p.Tyr1584Cys, our results suggest that it is a low penetrance pathogenic variant that contributes to VWF:Ag levels ≤ 50 IU/dL, bleeding, and VWD.

Cognitive deficits are common across many neurodevelopmental and psychiatric conditions, including those studied in the current set of PGC-CNV papers. How changes in regional gene expression across the cerebral cortex influence cognitive ability remains unknown. Population variation in gene dosage-which significantly impacts gene expression-represents a unique paradigm to address this question. We developed a cerebral-cortex gene-set burden analysis (CC-GSBA) to associate a trait with genomic deletions and duplications that disrupt genes with similar expression profiles across 180 cortical regions. We performed CC-GSBA across 180 cortical regions to test associations with cognitive ability in 260,000 individuals from general population cohorts. Most cortical gene sets were associated with a decrease in cognitive ability when deleted or duplicated, and this novel approach revealed opposing cortical patterns for the effect sizes of deletions and duplications. These cortical patterns of effect sizes followed the cortical gradient previously characterized at the molecular, cellular, and functional levels. We show that genes with preferential expression in sensorimotor regions demonstrated the largest effect on cognition when deleted. At the opposing end of the cortical gradient, genes with preferential expression in multimodal association regions affected cognition the most when duplicated. These two gene dosage cortical patterns could not be explained by particular cell types, developmental epochs, or genetic constraints, highlighting the fact that the macroscopic network organization of the cerebral cortex is key to understanding the effects of gene dosage on cognitive traits.

BACKGROUND:There has been little examination of the stability and validity of polygenic risk scores (PRSs), i.e., whether individuals identified as high risk for a disorder with one PRS are identified as high risk with another PRS and whether high-risk individuals have the disorder. METHODS:The UK Biobank recruited 502,534 individuals ages 37 to 73 years in the United Kingdom between 2006 and 2010. PRSs were calculated for 408,853 White British individuals. PRS continuous shrinkage (CS), which uses single nucleotide polymorphism effect sizes under CS, was used to calculate 3 different PRSs for major depressive disorder (MDD), alcohol use disorder (AUD), and type 2 diabetes (T2D) and 2 different PRSs for schizophrenia (SCZ). PRS stability was measured using correlations between different PRSs for the same disorder and the percentage of individuals consistently identified as high risk (top 5% PRS). Sensitivity and specificity were used to measure PRS validity. RESULTS:Correlations between PRSs ranged from low to high (SCZ: r = 0.78; MDD: rs = 0.16-0.78; AUD: rs = 0.13-0.90; T2D rs = 0.29-0.77). The percentage of individuals consistently identified as high risk (top 5% PRS) for SCZ with a different SCZ PRS was 47.7%, i.e., less than half of individuals identified as high risk with one PRS were identified as high risk with another PRS. Percentages of individuals consistently identified as high risk were 9.5% to 47.0% for MDD, 8.3% to 63.5% for AUD, and 14.1% to 45.2% for T2D. PRS sensitivity was moderate for MDD (66.1%-74.4%) and AUD (72.3%-74.2%), moderate/good for T2D (77.3%-96.3%), and good for SCZ (90.2%-93.3%). Specificity was low for all PRSs (50.7%-56.4%). CONCLUSIONS:Limited stability and specificity of PRSs highlight their current lack of clinical utility in psychiatry.

Copy number variants (CNVs) have large effects on complex traits, but they are rare and remain challenging to study. As a result, our understanding of biological functions linking gene dosage to complex traits remains limited, and whether these functions sensitive to gene dosage are similar to those underlying the effects of rare single nucleotide variants (SNVs) and common variants remains unknown. Methods:We developed FunBurd, a functional burden analysis, to test the association of CNVs aggregated within functional gene sets. We applied this approach in 500,000 individuals from the UK Biobank to associate 43 complex traits with CNVs disrupting 172 gene sets across tissues and cell types. We compared CNV findings with those from common variants and LoF (Loss of Function) SNVs in the same cohort using the same functional gene sets. Results:All 43 traits showed FDR significant associations with CNVs. Brain tissue and neuronal cell-types showed the highest levels of pleiotropy. Most of the functional gene set associations could, in part, be explained by genetic constraint, except for brain related processes. Shared genetic contributions between pairs of traits were concordant across types of variants, but on average 2-fold higher, for rare CNVs and SNVs compared to common variants.Functional enrichment across traits found limited overlap between CNVs and common variants. Moreover, the effects of deletions and duplications were negatively correlated for most traits.In conclusion, we present new methods to separate the contributions of genetic constraint and gene function to the associations of CNVs with complex traits. Overall, the functional convergence between different types of variants -even between deletions and duplications-remains limited.