American Journal of Psychiatry

Acute COVID-19 infection can be followed by diverse clinical manifestations referred to as Post Acute Sequelae of SARS-CoV2 Infection (PASC). Studies have shown an increased risk of being diagnosed with new-onset psychiatric disease following a diagnosis of acute COVID-19. However, it was unclear whether non-psychiatric PASC-associated manifestations (PASC-AMs) are associated with an increased risk of new-onset psychiatric disease following COVID-19. A retrospective EHR cohort study of 1,603,767 individuals with acute COVID-19 was performed to evaluate whether non-psychiatric PASC-AMs are associated with new-onset psychiatric disease. Data were obtained from the National COVID Cohort Collaborative (N3C), which has EHR data from 65 clinical organizations. EHR codes were mapped to 151 non-psychiatric PASC-AMs recorded 28-120 days following SARS-CoV-2 diagnosis and before diagnosis of new-onset psychiatric disease. Association of newly diagnosed psychiatric disease with age, sex, race, pre-existing comorbidities, and PASC-AMs in seven categories was assessed by logistic regression. There was a significant association between six categories and newly diagnosed anxiety, mood, and psychotic disorders, with odds ratios highest for cardiovascular (1.35, 1.27-1.42) PASC-AMs. Secondary analysis revealed that the proportions of 95 individual clinical features significantly differed between patients diagnosed with different psychiatric disorders. Our study provides evidence for association between non-psychiatric PASC-AMs and the incidence of newly diagnosed psychiatric disease. Significant associations were found for features related to multiple organ systems. This information could prove useful in understanding risk stratification for new-onset psychiatric disease following COVID-19. Prospective studies are needed to corroborate these findings. FundingNCATS U24 TR002306

ImportanceObsessive-compulsive disorder (OCD) affects 2-3% of the population with often disabling obsessions and compulsions. Despite its high heritability, genetic studies of OCD have lagged other psychiatric disorders, particularly in understanding the role of rare genetic variants. ObjectiveTo identify rare coding genetic variants contributing to OCD risk and examine genetic overlap with chronic tic disorders (CTD) and other psychiatric conditions. DesignFamily-based and case-control whole-exome sequencing (WES) study. SettingsWES data were aggregated from 11 independent cohorts across Sweden, the United States, and the United Kingdom. ParticipantsA total of 47,194 individuals were available, and 44,089 passed quality control for analysis. The final sample included 6,071 individuals with OCD, comprising 1,202 probands from family-based trios and 4,869 cases, and 38,018 controls. ExposuresRare damaging coding variants identified by WES. Main Outcomes and MeasuresIdentification of OCD risk genes through rare variant analyses, meta-analysis with CTD data, gene-set enrichment analyses, and evaluation of cross-disorder genetic overlap using curated gene sets. ResultsThe analysis provided an estimate of approximately 470 autosomal genes contributing to OCD risk through rare genetic variation. CHD8 reached genome-wide significance (q < 0.05). Meta-analysis with CTD data revealed additional risk genes, including CELSR3 (q < 0.05), QRICH1, and WWC1 (q < 0.1). We observed significant genetic overlap between OCD, autism spectrum disorder (ASD), and developmental delay: 33% of ASD genes with FDR < 0.1 showed association with OCD (p < 0.001), and 36% showed possible associations in the shared OCD-CTD genetic architecture (p < 0.001), but minimal rare-variant overlap with bipolar disorder and schizophrenia risk genes. We also found that CHD8-regulated genes were enriched for both rare and common variant associations with OCD. Conclusions and RelevanceIn this largest study to date of rare coding variation in OCD, we confirm CHD8 as the first genome-wide significant rare-variant risk gene, show that genes that are targets of CHD8 can carry rare and common variant risk for OCD, and identify multiple additional genes and pathways contributing to risk. Taken together, the findings show that OCD shares substantially greater genetic overlap with neurodevelopmental conditions than with adult-onset psychiatric disorders, refining the developmental framework of OCD and informing future mechanistic and clinical research. Key PointsO_ST_ABSQuestionC_ST_ABSHow do rare genetic variants contribute to OCD, and how do they overlap with variants linked to chronic tic disorders (CTD) and other neurodevelopmental conditions? FindingsExome sequencing of 6,071 OCD cases demonstrated significant enrichment of rare damaging variants in evolutionarily conserved genes, and CHD8 emerged as the first genome-wide significant OCD risk gene. Rare variant patterns in OCD and CTD aligned with those seen in neurodevelopmental, but not adult-onset psychiatric disorders, indicating shared neurodevelopmental pathways. MeaningThese findings clarify OCDs neurodevelopmental genetic architecture, identify CHD8 as a key risk pathway, and reveal overlap with CTD and other conditions.

ObjectivePersons with substance use disorders (SUD) often suffer from additional comorbidities. Researchers have explored this overlap via phenome wide association studies (PheWAS). However, PheWAS are largely cross-sectional, limiting our understanding of whether diagnoses predate development of an SUD. We characterize whether polygenic scores (PGS) are associated with time to comorbid diagnoses in electronic health records (EHR) after the first documented SUD diagnosis. MethodsUsing data from All of Us (N = 393,596), we explored: 1) whether social determinants of health (SDoH) are associated with lifetime risk of SUD (N cases = 42,568) and 2) within a subset those with a diagnosed SUD and available genetic data SUD (N = 21,357), whether PGS for alcohol use disorders, cannabis use disorders, depression, externalizing, post-traumatic stress disorder, and schizophrenia were associated with subsequent diagnoses via a phenome-wide survival analysis. ResultsMultiple SDoH were associated with lifetime SUD diagnosis, with annual household income having the largest overall associations (e.g., <$10K annually vs $100K-$150K annually: OR = 3.89, 95% CI = 3.66, 4.13). There were 101 phenome-wide significant PGS associations with subsequent diagnoses across various bodily systems. PGSs for alcohol use disorders, post-traumatic stress disorder, and schizophrenia were each associated with time to their respective diagnoses. ConclusionsSocial determinants, especially those related to income, have profound associations with lifetime SUD risk. Additionally, PGS for psychiatric conditions are associated with multiple post-SUD diagnoses within those with a SUD, suggesting PGS may capture information beyond lifetime risk, including timing and severity of comorbidities related to SUD.

Evidence indicates a great degree of genetic overlap between psychiatric diagnoses. Accounting for these transdiagnostic effects can sharpen research on disorder-specific genetic architecture. Here we isolate genetic effects that are shared across 11 major psychiatric disorders (p factor) to gain further insight into genetic specificity and comorbidity over and above that contributed by the p factor, unique to each psychiatric disorder. After adjusting for transdiagnostic genetic effects, we examined genetic correlations among psychiatric traits as well as relationships with other biobehavioural traits. The landscape of genetic associations between pairs of psychiatric disorders changed substantially, and their genetic correlations with biobehavioural traits showed greater specificity. Isolating transdiagnostic genetic effects across major psychiatric disorders provides a nuanced understanding of disorder-specific genetic architecture and genetic comorbidity, and may help guide diagnostic nomenclature and treatment research.

Trichotillomania and excoriation disorder are obsessive-compulsive related disorders that are often subclassified together as body-focused repetitive behavior (BFRB) disorders. While previous research suggests shared genetic factors, the genetic architecture of these BFRBs remains incompletely understood. Probands with trichotillomania and/or excoriation disorder and both of their biological parents were recruited for an ongoing genetic study of parent-offspring trios with BFRBs. Genome-wide array data were generated in 110 families (334 individuals total) to investigate the role of both common single-nucleotide polymorphisms and rare copy-number variants (CNVs). Polygenic risk scores were calculated using summary statistics from genome-wide association studies of related psychiatric conditions, including obsessive-compulsive disorder (OCD), depression, anxiety, and attention deficit/hyperactivity disorder. Using the polygenic transmission disequilibrium test, we observed a significant over-transmission of polygenic risk for OCD in probands of European ancestry from their parents (mean pTDT = 0.36, p = 0.01, n = 92), and a non-significant enrichment for the other conditions. Our results suggest that common variants associated with OCD may contribute to risk for BFRBs, consistent with their current classification as obsessive-compulsive related disorders. We also identified several rare CNVs in probands that overlapped genes intolerant to loss-of-function (LoF) mutations and those previously associated with neurodevelopmental disorders. The LoF-intolerant genes were enriched in biological processes relevant to synapse organization and neurodevelopment. This work provides new insight into the genetic underpinnings of these BFRB disorders, paving the way for larger genomic studies of these understudied conditions.

To date, four genome-wide association studies (GWAS) of obsessive-compulsive disorder (OCD) have been published, reporting a high single-nucleotide polymorphism (SNP)-heritability of 28% but finding only one significant SNP. A sub-stantial increase in sample size will likely lead to further identification of SNPs, genes, and biological pathways mediating the susceptibility to OCD. We conducted a GWAS meta-analysis with a 2-3-fold increase in case sample size (OCD cases: N = 37,015, controls: N = 948,616) compared to the last OCD GWAS, including six previously published cohorts (OCGAS, IOCDF-GC, IOCDF-GC-trio, NORDiC-nor, NORDiC-swe, and iPSYCH) and unpublished self-report data from 23andMe Inc. We explored the genetic architecture of OCD by conducting gene-based tests, tissue and celltype enrichment analyses, and estimating heritability and genetic correlations with 74 pheno-types. To examine a potential heterogeneity in our data, we conducted multivariable GWASs with MTAG. We found support for 15 independent genome-wide significant loci (14 new) and 79 protein-coding genes. Tissue enrichment analyses implicate multiple cortical regions, the amygdala, and hypothalamus, while cell type analyses yielded 12 cell types linked to OCD (all neurons). The SNP-based heritability of OCD was estimated to be 0.08. Using MTAG we found evidence for specific genetic underpinnings characteristic of different cohort-ascertainment and identified additional significant SNPs. OCD was genetically correlated with 40 disorders or traits-positively with all psychiatric disorders and negatively with BMI, age at first birth and multiple autoimmune diseases. The GWAS meta-analysis identified several biologically informative genes as important contributors to the aetiology of OCD. Overall, we have begun laying the groundwork through which the biology of OCD will be understood and described.

Obsessive-compulsive disorder (OCD) is a chronic, serious psychiatric disorder that affects 2-3% of the population and is associated with high personal and societal costs. Genetic factors are estimated to explain roughly half the risk of developing OCD, and genomic studies are just beginning to identify common and rare genetic variants mediating this risk. A major goal of genomic studies is to yield insights into the etiology of OCD and identify molecular targets for the development of novel therapeutics. However, the overwhelming majority of subjects in existing genetic studies are of European ancestry, limiting the generalizability of these findings. To address this gap in understanding, we established the Black EquaLity in OCD NeuroGenomics (BELONG) study (https://belongocd.com/). BELONG aims to collect DNA and clinical data from 1,250 richly phenotyped OCD cases of African ancestry in a culturally sensitive manner. In addition, BELONG includes the collection of parental DNA samples for trio-based analyses and unrelated matched controls for case-control analysis. DNA samples will be sequenced using optimized approaches that will allow us to examine both rare and common genome-wide variation to identify OCD risk genes. We will also meta-analyze these data with other existing OCD genomic data. Overall, BELONG will increase the representation of Black Americans in OCD genetic research, which is necessary to generalize precision medicine discoveries in psychiatric genetics.

This scoping review examines sex and gender differences in obsessive-compulsive disorder (OCD) to generate hypotheses about sources of heterogeneity. A PubMed search (2009-2025) using terms related to sex, gender, and OCD identified 7,497 records. Records were screened by two reviewers, and 1,446 articles were assessed at the full-text level by four co-authors. Of these, 855 studies were included: 61 meta-analyses, 13 systematic reviews, 39 narrative reviews, and 742 original reports. Original studies were grouped by focus--symptoms (96), epidemiology (217), comorbidities (187), human genetics (89), neurocognitive and neurobiological functioning (56), treatment (66), animal models (55)--and evaluated using CASP checklists. Across domains, sex- and gender-related patterns in OCD have been reported, but findings remain fragmented and rarely synthesized. Methodological limitations include inconsistent assessment of sex and gender, variability in symptom measurement, limited consideration of menstrual and reproductive factors, and few genome-wide or whole-brain imaging studies. Biases may also arise from gender differences in insight, help-seeking behavior, and comorbidity. Synthesizing these findings, we hypothesize that two OCD subtypes may contribute to observed sex and gender patterns. One subtype (OCD-I) is characterized by earlier onset and stronger familial or neurodevelopmental loading and shows a male preponderance that may reflect a female protective effect. A second subtype (OCD-II) is more often stress-precipitated, emerges later, and may be more common in women due to greater exposure to interpersonal, reproductive, and traumatic stressors rather than greater innate susceptibility. Appreciating sex and gender effects may clarify OCD heterogeneity and inform research, prevention, and treatment.

Psychiatric disorders exhibit substantial genetic overlap, raising questions about the utility of transdiagnostic genetic risk models. Using data from the All of Us Research Program (N=102,091), we evaluated common psychiatric genetic (CPG) factor-based polygenic risk scores (PRSs) compared to standard disorder-specific PRSs. The CPG PRS consistently outperformed disorder-specific scores in predicting individual disorder risk, explaining 1.07 to 24.6 times more phenotypic variance across 11 psychiatric conditions. Meanwhile, many disorder-specific PRSs retained independent but smaller contributions, highlighting the complementary nature of shared and disorder-specific genetic risk. While alternative multi-factor models improved model fit, the CPG PRS provided comparable or superior predictive performance across most disorders, including overall comorbidity burden. Cross-ancestry analyses however revealed notable limitations of European-centric GWAS datasets for other populations due to ancestral differences in genetic architecture. These findings underscore the potential value of transdiagnostic PRSs for psychiatric genetics while highlighting the need for more equitable genetic risk models.

BackgroundRisk for Tourettes and related tic disorders (CTD) derives from a combination of genetic and environmental factors. While multiple studies have demonstrated the importance of direct additive genetic variation for CTD, little is known about the role of cross-generational transmission of genetic risks, such as maternal effects. Here, we partition sources of variation on CTD risk into direct additive genetic effect and maternal effects. MethodsThe study population consists of 2,522,677 individuals from the Swedish Medical Birth Register, born in Sweden between January 1, 1982, to December 31, 1990, and followed for a diagnosis of CTD through December 31, 2013. ResultsWe identified 6,227 (0.25%) individuals in the birth cohort diagnosed with CTD. Using generalized linear mixed models, we estimated 4.7% (95% CrI, 4.4%-4.8%) genetic maternal effects, 0.5% (95% CrI, 0.2%-7%) environmental maternal effects, and 61% (95% CrI, 59%-63%) direct additive genetic effects. Around 1% of genetic maternal effects were due to maternal effects from the individual with comorbid obsessive-compulsive disorder. ConclusionsOur results demonstrate genetic maternal effects contributing to the risk of CTD in offspring and also highlight new sources of overlapping risk between CTD and obsessive-compulsive disorder.

Many personality traits are influenced by genetic factors. Rodents models provide an efficient system for analyzing genetic contribution to these traits. Using 1,246 adolescent heterogeneous stock (HS) male and female rats, we conducted a genome-wide association study (GWAS) of behaviors measured in an open field, including locomotion, novel object interaction, and social interaction. We identified 30 genome-wide significant quantitative trait loci (QTL). Using multiple criteria, including the presence of high impact genomic variants and co-localization of cis-eQTL, we identified 13 candidate genes (Adarb2, Ankrd26, Cacna1c, Clock, Crhr1, Ctu2, Cyp26b1, Eva1a, Fam114a1, Kcnj9, Mlf2, Rab27b, Sec11a) for these traits. Most of these genes have been implicated by human GWAS of various psychiatric traits. For example, Cacna1c, a gene known to be critical for social behavior in rodents and implicated in human schizophrenia and bipolar disorder, is a candidate gene for distance to the social zone. In addition, the QTL region for total distance to the novel object zone, on Chr1 at 144 Mb, is syntenic to a hotspot on human Chr15 (82.5-90.8 Mb) that contains 14 genes associated with psychiatric or substance abuse traits. Although some of the genes identified by this study appear to replicate findings from prior human GWAS, others likely represent novel findings that can be the catalyst for future molecular and genetic insights into human psychiatric diseases. Together, these findings provide strong support for the use of the HS population to study psychiatric disorders.

ObjectivesObsessive-compulsive disorder (OCD) is a common psychiatric disorder, with two-thirds of affected individuals reporting severe impairment. Despite its substantial burden and moderate heritability, its etiology remains poorly understood, and treatments are often suboptimal. While recent genome-wide association studies (GWAS) have identified some risk loci, yet OCD remains in the linear phase of sample collection to variant association, with many more OCD-associated variants left to discover. This study aimed to develop and validate an electronic health record (EHR)-based algorithm to identify OCD cases and facilitate large-scale genetic studies. MethodsWe leveraged EHR-linked biobank data from two large hospital systems, namely Vanderbilt University Medical Center (VUMC) and Mass General Brigham (MGB), to develop a high-throughput phenotyping algorithm integrating diagnostic codes, medication records, and natural language processing (NLP) of clinical notes. Algorithm performance was evaluated through expert chart review, and genetic validation was performed using OCD polygenic risk scores (PRS). ResultsExpert chart reviews found that our algorithm combining both ICD codes and NLP achieved higher positive predictive values (PPV) for OCD cases (0.84 at VUMC and 0.91 at MGB) compared to using either ICD codes or NLP alone, albeit with a lower case yield. Furthermore, at both sites, algorithm-determined cases exhibited significantly elevated PRS derived from the latest OCD GWAS, providing genetic validation of our phenotyping approach. ConclusionOur study demonstrates a scalable and cost-efficient approach for EHR-based ascertainment of OCD cases, facilitating large-scale genetic studies and advancing understanding of the disorders complex etiology.

Current phenotype classifiers for large biobanks with coupled electronic health records EHR and multi-omic data rely on ICD-10 codes for definition. However, ICD-10 codes are primarily designed for billing purposes, and may be insufficient for research. Nuanced phenotypes composed of a patients experience in the EHR will allow us to create precision psychiatry to predict disease risk, severity, and trajectories in EHR and clinical populations. Here, we create a phenotype risk score (PheRS) for major depressive disorder (MDD) using 2,086 cases and 31,000 individuals from Mount Sinais biobank BioMe . Rather than classifying individuals as cases and controls, PheRS provide a whole-phenome estimate of each individuals likelihood of having a given complex trait. These quantitative scores substantially increase power in EHR analyses and may identify individuals with likely missing diagnoses (for example, those with large numbers of comorbid diagnoses and risk factors, but who lack explicit MDD diagnoses). Our approach applied ten-fold cross validation and elastic net regression to select comorbid ICD-10 codes for inclusion in our PheRS. We identified 158 ICD-10 codes significantly associated with Moderate MDD (F33.1). Phenotype Risk Score were significantly higher among individuals with ICD-10 MDD diagnoses compared to the rest of the population (Kolgorov-Smirnov p<2.2e-16), and were significantly correlated with MDD polygenic risk scores (R2>0.182). Accurate classifiers are imperative for identification of genetic associations with psychiatric disease; therefore, moving forward research should focus on algorithms that can better encompass a patients phenome.

Obsessive-compulsive disorder (OCD) is a prevalent neuropsychiatric disorder with an incompletely understood genetic basis, limiting targeted therapeutic options. Although previous rare variant studies have primarily focused on protein-coding genes, the contribution of rare regulatory non-coding variants remains largely unexplored. We analyzed whole-genome sequencing data from 2,561 OCD cases and 12,974 controls from the All of Us Research Program to investigate rare, conserved variants (minor allele count [&le;] 5, GERP++ > 0) within antisense long non-coding RNA (lncRNA) and protein-coding gene overlap regions. A burden analysis identified a significant association with OCD in the KNCN/MKNK1-AS1 overlap region (odds ratio: 5.1, FDR < 0.05). Expression analysis revealed strong co-expression of these genes in striatal brain regions implicated in OCD pathophysiology. Genes co-expressed with KNCN/MKNK1-AS1 were enriched for synaptic vesicle dynamics, calcium signaling, and established OCD risk genes, highlighting the importance of non-coding regulatory variation in psychiatric genetics.

Objective: Autistic individuals may face elevated risk for PTSD, yet the degree to which this risk differs by sex remains unknown. We examined the association between autism and incident PTSD, characterized sex differences in risk, identified high-risk subgroups, and described post-diagnosis clinical trajectories. Method: We conducted a population-based matched cohort study using Swedish national registers. Individuals born 1990 through 2010 were followed from age 6 years through December 31, 2017. Autistic individuals (N=42,862) were matched 1:10 to controls (N=412,251) on sex and birth year. Cox proportional hazards regression estimated hazard ratios (HRs) for incident PTSD. Among those who developed PTSD, we compared care utilization, hospitalization rates, and persistence of care contacts. Results: During mean follow-up of 5.1 years, 401 autistic individuals (0.9%) and 903 controls (0.2%) developed PTSD (incidence rates: 18.3 vs 4.2 per 10,000 person-years). Autism was associated with 4.4-fold increased PTSD risk (HR=4.37; 95% CI, 3.93-4.86). Risk was higher among females (HR=4.79) than males (HR=3.39; P interaction=.006). Among autistic individuals, comorbid ADHD conferred additional risk (HR=1.38; 95% CI, 1.14-1.68). Ten-year cumulative incidence reached 6.0% among autistic females with ADHD. Autistic individuals with PTSD had higher care utilization (mean visits: 5.0 vs 3.9; P<.001), more psychiatric hospitalizations (27.9% vs 19.8%; P=.002), and more persistent courses (24.8% vs 12.3% with contacts in all 3 post-diagnosis years; P=.001). Conclusion: Autism is associated with substantially elevated PTSD risk, particularly among females with comorbid ADHD. When PTSD occurs, autistic individuals experience more severe and persistent clinical courses, supporting targeted screening and sustained follow-up.

BackgroundAnxiety disorders are prevalent and anxiety symptoms co-occur with many psychiatric disorders. We aimed to identify genomic risk loci associated with anxiety, characterize its genetic architecture, and genetic overlap with psychiatric disorders. MethodsWe used the GWAS of anxiety symptoms, schizophrenia, bipolar disorder, major depression, and attention deficit hyperactivity disorder (ADHD). We employed MiXeR and LAVA to characterize the genetic architecture and genetic overlap between the phenotypes. Conditional and conjunctional false discovery rate analyses were performed to boost the identification of genomic loci associated with anxiety and those shared with psychiatric disorders. Gene annotation and gene set analyses were conducted using OpenTargets and FUMA, respectively. ResultsAnxiety was polygenic with 12.9k estimated genetic risk variants and overlapped extensively with psychiatric disorders (4.1-11.4k variants). MiXeR and LAVA revealed predominantly positive genetic correlations between anxiety and psychiatric disorders. We identified 114 novel loci for anxiety by conditioning on the psychiatric disorders. We also identified loci shared between anxiety and major depression (n = 47), bipolar disorder (n = 33), schizophrenia (n = 71), and ADHD (n = 20). Genes annotated to anxiety loci exhibit enrichment for a broader range of biological pathways and differential tissue expression in more diverse tissues than those annotated to the shared loci. ConclusionsAnxiety is a highly polygenic phenotype with extensive genetic overlap with psychiatric disorders. These genetic overlaps enabled the identification of novel loci for anxiety. The shared genetic architecture may underlie the extensive cross-disorder comorbidity of anxiety, and the identified genetic loci implicate molecular pathways that may lead to potential drug targets.

BackgroundTransdiagnostic genetic factor models organize shared liability across psychiatric disorders, but they may leave systematic pairwise genetic overlap unexplained. MethodsUsing publicly available PGC cross-disorder LD score regression genetic correlations and published five-factor genomic SEM parameters, we computed model-implied disorder correlations and derived edge-level residual genetic correlations (observed minus model-implied) for all disorder pairs. We summarized residual misfit by ranking the largest residual edges and by aggregating residual edges into disorder-level hub indices. As a parsimonious comparison, we constructed a p-factor-augmented baseline and repeated the residual mapping. Uncertainty was propagated via Monte Carlo sampling using reported standard errors. ResultsResidual structure was concentrated in a subset of disorders rather than being uniformly distributed. The largest positive residual edge was OCD-anxiety ([~]0.35), followed by prominent residual links including OCD-Tourette syndrome, ADHD-cannabis use disorder, and ASD-ADHD. At the node level, OCD emerged as the most consistent residual hub, with ADHD typically second. Under the p-factor baseline, the overall residual pattern persisted. Hub rankings did not map one-to-one onto disorder uniqueness, indicating complementary information captured by node-level and edge-level residuals. ConclusionsHigher-order genetic factors explain broad shared liability but leave meaningful, structured residual links between specific disorder pairs. OCD and ADHD are robust residual hubs, highlighting candidate cross-disorder connections for targeted phenotypic harmonization, cross-phenotype GWAS, and theory-guided model refinements.

While 1-2% of individuals meet the criteria for a clinical diagnosis of obsessive-compulsive disorder (OCD), many more ([~]15-40%) experience subclinical obsessive-compulsive symptoms (OCS) during their life. To characterize the genetic underpinnings of OCS and its genetic relationship to OCD, we conducted the largest genome-wide association study (GWAS) meta-analysis of parent- or self-reported OCS to date (N = 33,943 with complete phenotypic and genome-wide data), combining the results from seven large-scale population-based cohorts from Sweden, the Netherlands, England, and Canada (including six twin cohorts and one cohort of unrelated individuals). We found no genome-wide significant associations on the SNP or gene-level, but a polygenic risk score (PRS) based on the OCD GWAS previously published by the Psychiatric Genetics Consortium (PGC-OCD) was significantly associated with OCS (Pfixed = 3.06 x10-5). Also, one curated gene set (Mootha Gluconeogenesis) reached Bonferroni-corrected significance (Ngenes = 28, Beta = 0.79, SE = 0.16, Pbon = 0.008). Expression of genes in this set is high at sites of insulin-mediated glucose disposal. Dysregulated insulin signaling in the etiology of OCS has been suggested by a previous study describing a genetic overlap of OCS with insulin signaling-related traits in children and adolescents. We report a SNP heritability of 4.1% (P = 0.0044) in the meta-analyzed GWAS, and heritability estimates based on the twin cohorts of 33% - 43%. Genetic correlation analysis showed that OCS were most strongly associated with OCD (rG = 0.72, p = 0.0007) among all tested psychiatric disorders (N = 11). Of all 97 tested phenotypes, 24 showed a significant genetic correlation with OCS, and 66 traits showed concordant directions of effect with OCS and OCD. OCS have a significant polygenic contribution and share genetic risk with diagnosed OCD, supporting the hypothesis that OCD represents the extreme end of widely distributed OCS in the population.

Obsessive-compulsive disorder (OCD) is a heritable disorder, but no definitive, replicated OCD susceptibility loci have yet been identified by any genome-wide association study (GWAS). Here, we report results from a GWAS in the largest OCD case-control sample (N = 14,140 OCD cases and N = 562,117 controls) to date. We explored the genetic architecture of OCD, including its genetic relationships to other psychiatric and non-psychiatric phenotypes. In the GWAS analysis, we identified one SNP associated with OCD at a genome-wide significant level. Subsequent gene-based analyses identified additional two genes as potentially implicated in OCD pathogenesis. All SNPs combined explained 16% of the heritability of OCD. We show sub-stantial positive genetic correlations between OCD and a range of psychiatric disorders, including anxiety disorders, anorexia nervosa, and major depression. We thus for the first time provide evidence of a genome-wide locus implicated in OCD and strengthen previous literature suggesting a polygenic nature of this disorder.

Individuals vary in their liability to develop Posttraumatic Stress Disorder (PTSD), the symptoms of which are highly heterogeneous, following exposure to life-threatening trauma. Understanding genetic factors that contribute to the biology of PTSD is critical for refining diagnosis and developing new treatments. Using genetic data from more than 250,000 participants in the Million Veteran Program, genomewide association analyses were conducted using a validated electronic health record-based algorithmically-defined PTSD diagnosis phenotype (48,221 cases and 217,223 controls), and PTSD quantitative symptom phenotypes (212,007 individuals). We identified several genome-wide significant loci in the case-control analyses, and numerous such loci in the quantitative trait analyses, including some (e.g., MAD1L1; TCF4; CRHR1) that were associated with multiple symptom sub-domains and total symptom score, and others that were more specific to certain symptom sub-domains (e.g., CAMKV to re-experiencing; SOX6 to hyperarousal). Genetic correlations between all pairs of symptom sub-domains and their total were very high (rg 0.93 - 0.98) supporting validity of the PTSD diagnostic construct. We also demonstrate strong shared heritability with a range of traits, show that heritability persists when conditioned on other major psychiatric disorders, present independent replication results, provide support for one of the implicated genes in postmortem brain of individuals with PTSD, and use this information to identify potential drug repositioning candidates. These results point to the utility of genetics to inform and validate the biological coherence of the PTSD syndrome despite considerable heterogeneity at the symptom level, and to provide new directions for treatment development.