American Journal of Medical Genetics Part B: Neuropsychiatric Genetics

Suicide is an urgent public health crisis that claimed over 48,000 lives in the US in 2022. The importance of genetics in suicide risk has been established by classical twin and family studies, and confirmed with recent large genome-wide association studies (GWAS). While the GWAS are beginning to reveal genetic risk due to common variants each with small effect on liability, these results explain only a fraction of the genetic risk. As with other complex health conditions, some of this unexplained risk is likely due to rarer variants with larger effect on liability. Using whole genome sequencing (WGS) data from 1,054 population-ascertained Utah suicide deaths, we investigated intragenic deletions as a class of genomic variation highly likely to disrupt gene function. To minimize the chance of false positive results, studied deletions were limited to those found in three large publicly-available control datasets (1000 Genomes, GnomAD, and Centers for Common Disease Genomics). Additional internal replication also required deletions to occur at least twice in WGS from an initial cohort of 670 suicide deaths then again in a second cohort of 384 suicide deaths. All results meeting these filters were manually validated. There were 11 validated deletions with at least 2-fold increase in frequency over occurrence in controls (range 2.28 to 4.46). These results implicated genes associated with risk of mental health conditions (MPST, IL4R, CDH13), epilepsy (CLCA4), intellectual disability (ZNF44), neuronal function (OSBPL2), metabolic function (FBOX36), lipid metabolism (TM9SF3), immune related functions (PIPOX, IL4R), and transcriptional repression (ZHX3). SNPs in genes implicated by the deletions have also been associated with mental health conditions, neuronal function, immune response, and other critical biological pathways including neuroinflammation and cellular response to stress. Demographic and clinical associations of suicide deaths with specific genetic deletions, highlight the prevalence of mood, anxiety and bipolar disorders and variations in age at suicide death among affected individuals. This work is the largest genome-wide analyses of WGS variation in suicide deaths to date. Pending replication, results will guide future functional studies with the eventual goals of increased understanding of mechanisms leading to risk.

Genome-wide association studies (GWASs) have identified thousands of risk loci for many psychiatric and substance use phenotypes, however the biological consequences of these loci remain largely unknown. We performed a transcriptome-wide association study of 10 psychiatric disorders and 6 substance use phenotypes (collectively termed "mental health phenotypes") using expression quantitative trait loci data from 532 prefrontal cortex samples. We estimated the correlation due to predicted genetically regulated expression between pairs of mental health phenotypes, and compared the results with the genetic correlations. We identified 1,645 genes with at least one significant trait association, comprising 2,176 significant associations across the 16 mental health phenotypes of which 572 (26%) are novel. Overall, the transcriptomic correlations for phenotype pairs were significantly higher than the respective genetic correlations. For example, attention deficit hyperactivity disorder and autism spectrum disorder, both childhood developmental disorders, showed a much higher transcriptomic correlation (r=0.84) than genetic correlation (r=0.35). Finally, we tested the enrichment of phenotype-associated genes in gene co-expression networks built from prefrontal cortex. Phenotype-associated genes were enriched in multiple gene co-expression modules and the implicated modules contained genes involved in mRNA splicing and glutamatergic receptors, among others. Together, our results highlight the utility of gene expression data in the understanding of functional gene mechanisms underlying psychiatric disorders and substance use phenotypes.

Obsessive compulsive disorder (OCD) is significantly heritable, but only a fraction of the contributory genetic variation has been identified, and the molecular etiology involved remains obscure. Identifying rare contributory variants of large effect would be an important milestone in helping to elucidate the mechanisms involved. Analysis of densely affected pedigrees is a potentially useful strategy to bypass the sample size challenges of standard case-control approaches. Here we performed whole genome sequencing (WGS) of 25 individuals across two multiplex OCD pedigrees. We prioritised rare variants using a Bayesian inference approach which incorporates variant pathogenicity and co-segregation with OCD. In the first pedigree, we identified a highly deleterious missense variant in NPY5R, carried by the majority of affected individuals. This gene is brain-expressed and has previously been implicated in panic disorder and internet addiction GWAS studies. In the second pedigree, we identified a large deletion of DLGAP1 and a missense variant in MAPK8IP3, that perfectly co-segregated in a specific branch of the family: both genes have previously been implicated in OCD and autism. Both genes contribute to a protein interaction network including ERBB4 and RAPGEF1 which we had previously identified in a large Tourette Syndrome pedigree. Our analysis suggests that both energy homeostasis and downstream signalling from the post-synaptic density may both be important avenues for future research.

Neuropsychiatric disorders, including depression and suicide, are becoming an increasing public health concern. Rising rates of both depression and suicide, exacerbated by the current COVID19 pandemic, have only hastened our need for objective and reliable diagnostic biomarkers. These can aide clinicians treating depressive disorders in both diagnosing and developing treatment plans. While differential gene expression analysis has highlighted the serotonin signaling cascade among other critical neurotransmitter pathways to underly the pathology of depression and suicide, the biological mechanisms remain elusive. Here we propose a novel approach to better understand molecular underpinnings of neuropsychiatric disorders by examining patterns of differential RNA editing by adenosine deaminases acting on RNA (ADARs). We take advantage of publicly available RNA-seq datasets to map ADAR editing landscapes in a global gene-centric view. We use a unique combination of Guttman scaling and random forest classification modeling to create, describe and compare ADAR editing profiles focusing on both spatial and biological sex differences. We use a subset of experimentally confirmed ADAR editing sites located in known protein coding regions, the excitome, to map ADAR editing profiles in Major Depressive Disorder (MDD) and suicide. Using Guttman scaling, we were able to describe significant changes in editing profiles across brain regions in males and females with respect to cause of death (COD) and MDD diagnosis. The spatial distribution of editing sites may provide insight into biological mechanisms under-pinning clinical symptoms associated with MDD and suicidal behavior. Additionally, we use random forest modeling including these differential profiles among other markers of global editing patterns in order to highlight potential biomarkers that offer insights into molecular changes underlying synaptic plasticity. Together, these models identify potential prognostic, diagnostic and therapeutic biomarkers for MDD diagnosis and/or suicide.

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.

A key component of Mendels work is what we now refer to as pleiotropy - when variation in one gene gives rise to variation in multiple phenotypes. This study focuses on aiding genetic discovery in depression by revisiting the depressed phenotype and developing a quantitative trait in a large mixed family and population study, using analyses built upon the theory which underpins Mendels pleiotropic observations - the relationship between phenotypic variation and genetic variation. Measures of genetic covariation were used to evaluate and rank ten measures of mood, personality, and cognitive ability as endophenotypes for depression. The highest-ranking traits were subjected to principal component analysis, and the first principal component used to create multivariate measures of depression. Four traits fulfilled most endophenotype criteria, however, only two traits (neuroticism and the general health questionnaire) consistently ranked highest across all measures of covariation. As such, three composite traits were derived incorporating two, three, or four traits. Composite traits were compared to the binary classification of depression and to their constituent univariate traits in terms of their coheritability, their ability to identify risk loci in a genome-wide association analysis, and phenotypic variance explained by polygenic profile scores for depression. Association analyses of binary depression, univariate traits, and composite traits yielded no genome-wide significant results. However, composite traits were more heritable and more highly correlated with depression than their constituent traits, suggesting that analysing candidate endophenotypes in combination captures more of the heritable component of depression and may in part be limited by sample size in the current study.

Neuropsychiatric and substance use disorders (NPSUD) have a complex etiology that includes environmental and polygenic risk factors with significant cross-trait rG. Genome Wide Association Studies (GWAS) of NPSUD yield numerous association signals. However, for most of these regions, we do not yet have a firm understanding of either the specific risk variants or the effects of these variants. Post-GWAS methods allow researchers to use GWAS summary statistics and functional genomics data to infer the likely molecular mediators (transcript, protein and methylation abundances) for the effect of variants on disorders. One group of post-GWAS approaches is commonly referred to as transcriptome/proteome/methylome wide association studies, which are abbreviated as T/P/MWAS (or collectively as XWAS). Since these approaches use biological mediators, the multiple testing burden is reduced to the number of genes ([~]20,000) instead of millions GWAS SNPs leading to increased signal detection. In this work, our aim is to uncover likely risk genes for NPSUD by performing XWAS analyses in two tissues - blood and brain. Firstly, XWAS using the Summary-data based Mendelian Randomization (SMR), which takes GWAS summary statistics, reference xQTL data and a reference LD panel as inputs, was conducted to identify putative causal risk genes. Second, given the large comorbidities among NPSUD and the shared cis-xQTLs between blood and brain, we improved XWAS signal detection in NPSUD for underpowered analyses by performing joint concordance analyses between XWAS results i) across the two tissues and ii) across NPSUD. All XWAS signals i) were adjusted for HEIDI (non-causality) p-values and ii) used to test for pathway enrichment. The results suggest that there were widely shared gene/protein signals within the Major Histocompatibility (MHC) region on chromosome 6 (BTN3A2 and C4A) and elsewhere in the genome (RERE, FURIN, ZDHHC5 and NEK4). The identification of putative molecular genes and pathways underlying risk may offer new targets for therapeutic development. Some of our analyses more immediate actionable signals might relate to vitamins, i.e., i) in KYAT3 (a part of the kynurenine pathway with vitamin B6 as a cofactor) for post-traumatic stress disorder and ii) omega-3 and vitamin D pathways for bipolar disorder.

In epidemiological studies, obsessive-compulsive disorder (OCD) is robustly associated with increased risk of cardiometabolic disorders, including cardiovascular diseases, type 2 diabetes, and obesity. However, the mechanisms behind these associations are unclear. We conducted genetic correlation analyses to explore shared genetic etiology and bi-directional summary-level Mendelian randomization (MR) to explore potential causal effects between genetic liability to OCD and 14 cardiometabolic phenotypes (e.g., coronary artery disease, blood pressure, body mass index [BMI]). If causal effects were observed, we planned to conduct multivariable-MR to explore indirect effects via health behaviors. We found no evidence for genetic correlations between OCD and any of the cardiometabolic phenotypes under study, except for a negative correlation with BMI (rG=-0.123, SE=0.029, p<0.001). Summary-level MR showed no evidence for causal effects. Therefore, multivariable-MR was not conducted. We found limited evidence for shared genetic etiology or causal effects. However, we were only powered to detect medium effects in the direction of OCD to cardiometabolic traits, leaving the possibility of smaller causal effects existing. Future studies with larger, more representative samples will help to further interpret findings.

BackgroundCopy Number Variations (CNVs) are structural variation in the genome, which may impact complex human traits and diseases. The investigation of rare CNVs is impeded by low sample size. To understand the mechanisms through which CNVs influence human health, common variation in the genomic region of the CNV from large samples could be used as a proxy. MethodsUtilising genome-wide association study (GWAS) summary statistics of 20 traits, we assessed the cumulative effect of common genetic variants in eight genomic regions containing pathogenic CNVs, using MAGMA gene-based analysis. We used GSA-MiXeR to estimate the fold enrichment of these CNV regions for the specific phenotypes. ResultsThe distal and proximal regions of the 16p11.2 CNV exhibited the highest number of significant associations and were enriched for the highest number of traits: 12 of 27 significant MAGMA associations (44%) were enriched. These CNV regions also had the highest number of phenotype-associated genes related to ion transport, signalling, transcriptional regulation, development, and protein metabolism. We compared the significance of all the genomic regions and the genes in these regions and found two opposing patterns: 1) cumulative value of separate genes, resulting in the higher significance of the whole region than of the particular genes; 2) higher significance of the specific genes that drive the association of the whole region. ConclusionsCharting the features of genomic regions encompassing CNVs might aid in clarifying CNVs role in human disease, especially pinpointing candidate genes within these regions that are associated with complex traits.

Large disparities in the prevalence of cannabis use disorder (CUD) exist across ethnic groups in the U.S. Despite large GWAS meta-analyses identifying numerous genome-wide significant loci for CUD in European descents, little is known about other ethnic groups. While most GWAS and SNP-heritability studies focus on common genomic variants, rare and low-frequency variants, particularly those altering proteins, are known to be enriched for the heritability of complex traits and may contribute to disease in different ways across populations, either through converging or alternative pathways. In this study, we examined three populations including European Americans (EA) and two understudied populations: American Indians (AI) and Mexican Americans (MA). We focused on rare and low frequency functional variants in genes and pathways, and performed association analysis with CUD severity. We identified 10 significant loci in AI, the ARSA gene in MA, three significant pathways in MA, and one in EA associated with CUD severity. Notably, pathways related to arylsulfatases activation and heparan sulfate degradation were supported by both EA and MA, with additional evidence from AI. The integrin beta-1 cell surface interaction pathway, involved in cell adhesion, was uniquely significant in MA. Several immune-related pathways were also found, including an autoimmune condition significant in MA with evidence from EA as well, and a p38-gamma/delta mediated signaling pathway supported across all three cohorts. Although each population displayed distinct pathways linked to CUD, overlapping genes in top pathways suggested shared genetic factors, further highlighting the importance of considering diverse populations in genetic research on cannabis use disorder.

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.

Psychiatric disorders frequently co-occur with insulin resistance (IR)-related conditions, including obesity, type 2 diabetes mellitus (T2DM), and metabolic syndrome (MetS). Although pairwise genetic correlations have been observed, the shared genetics underlying this multimorbidity remains underexplored. Here, we investigate the joint genetic architecture of psychiatric-IR multimorbidity, explore tissue-specific gene expression associations, and identify potential underlying biological mechanisms and repurposable drugs. We applied genomic structural equation modeling (SEM) to genome-wide association study (GWAS) data (N=9,725-933,970) from five psychiatric disorders (attention-deficit/hyperactivity disorder, anorexia nervosa, major depressive disorder, obsessive-compulsive disorder, and schizophrenia) and three IR-related conditions (MetS, obesity, T2DM). Factor analyses revealed a 2-factor solution, where one of the factors was composed by all psychiatric disorders (excluding schizophrenia) and IR-related conditions (the Psych-IR factor), representing the shared genetics of these psychiatric and IR-conditions. This factor showed genetic correlations with the inferior temporal, lateral occipital, and total cortical brain surface areas. A multivariate GWAS of the Psych-IR factor identified 150 risk loci and 366 associated genes (128 novel). The significant gene-set associations included the insulin binding and the Notch signaling pathways, while the gene-property tissue expression implicated the cerebellum, brain cortex, and pituitary gland, particularly involving the brain during prenatal development stages. Transcriptome-wide SEM (T-SEM) assessed tissue-specific gene expression associations and identified 499 genes (191 novel), including MHC-related genes. Drug repurposing analysis using PharmOmics suggested six potential candidates, including memantine and rosiglitazone. Associated genes derived from the Psych-IR factor multivariate GWAS and T-SEM results were combined for enrichment analyses, which highlighted the involvement of the chr16p11.2 region, BDNF signaling, and lipid metabolism. The identified Psych-IR factor offers novel insights into the shared genetic and biological mechanisms underlying psychiatric-IR multimorbidity, providing a foundation for future research on precision medicine and prevention approaches.

Self-domestication could play an important role in contributing to shape the biology of human brain and the predisposition to neurodevelopmental disorders. Leveraging genome-wide data from the Psychiatric Genomics Consortium, we tested the enrichment of self-domestication and neural crest function loci with respect to the heritability of autism spectrum disorder, schizophrenia (SCZ in East Asian and European ancestries, EAS and EUR, respectively), attention-deficit/hyperactivity disorder, obsessive-compulsive disorder, and Tourettes syndrome (TS). Considering only self-domestication and neural-crest-function annotations in the linkage disequilibrium score regression (LDSC) model, our partitioned heritability analysis revealed statistically significant enrichments across all disorders investigated. The estimates of the heritability enrichments for self-domestication loci were similar across neurodevelopmental disorders, ranging from 0.902 (EAS SCZ, p=4.55x10-20) to 1.577 (TS, p=5.85x10-5). Conversely, a wider spectrum of heritability enrichment estimates was present for neural crest function with the highest enrichment observed for TS (enrichment=3.453, p=2.88x10-3) and the lowest for EAS SCZ (enrichment=1.971, p=3.8lx10-3). Although these estimates appear to be strong, the enrichments for self-domestication and neural crest function were null once we included additional annotations related to different genomic features. This indicates that the effect of self-domestication on the polygenic architecture of neurodevelopmental disorders is not independent of other functions of human genome.

Suicide attempts (SA) and suicidal ideation (SI) are major public health concerns with incompletely defined biology. We investigated shared genetic architecture between SA or SI and thirteen correlated phenotypes using genome-wide association study summary statistics from 46,350 to 975,353 individuals. Local Analysis of [co]Variant Association (LAVA) identified locus-specific genetic covariance, while conjunctional false discovery rate (conjFDR) analyses detected single-nucleotide polymorphysms jointly associated with suicide phenotypes and external traits. Functional annotation and enrichment analyses characterised pathways and tissue-specific expression. LAVA identified sixteen loci with significant local correlations, mapping to 493 genes. After conditioning on major depressive disorder and post-traumatic stress disorder, several locus-trait-pair correlations remained significant, including SI-ADHD, whose mapped genes were differentially expressed in hypothalamus, cortical regions, and peripheral tissues. Correlated loci implicated ion transport and transcriptional regulation. ConjFDR identified shared loci mapping 798 genes. These genes showed enrichment for pathways related to cell adhesion, neurogenesis, signal transduction, chromatin regulation, immune processes, and protein secretion. Stratified analyses showed SA-based pairs enriched for gene sets related to brain morphology, cognition, and sleep regulation, whereas SI-based pairs for neuroticism, body mass index, and gastrointestinal traits. Across pairs, shared loci displayed both concordant and discordant effect directions. Both SA and SI were enriched for gene sets involving glycine, serine, and threonine metabolism, systemic lupus erythematosus, and DNA damage- and telomere stress-induced senescence. Recurrently mapped genes exhibited region- and developmental stage-specific brain expression. These findings refine the genetic architecture of suicide and implicate neurodevelopmental, immune, metabolic, and chromatin-related mechanisms in suicidal thoughts and behaviours.

Anxiety disorders (ANX) are a prevalent public health burden that significantly impair daily functioning and decrease quality of life. A growing body of research suggests that DNA methylation (DNAm), an epigenetic modification that can impact gene expression, may be altered in ANX. The current review used a systematic approach to identify and synthesize the literature regarding methylome-wide association studies (MWASs) of ANX in humans. We screened 804 articles returned by a search in PubMed in May 2025 and identified 12 studies for inclusion. All included studies examined ANX-associated DNAm in blood. In total, 2,023 DNAm sites corresponding to 985 genes were significantly associated with ANX. No DNAm sites significantly replicated across studies and four nominally replicated. This is likely a result of a lack of replication attempts, small sample sizes, and differences in data analysis choices. Findings suggest that ANX-associated DNAm may promote dysregulation of immune and inflammatory processes, some possibly sex-dependent. Collectively, the findings from studies included in this review provide preliminary evidence of ANX-related alterations to DNAm in whole blood and multiple blood cell-types. Future MWASs of ANX could benefit from larger sample sizes, a standardized analytic pipeline, longitudinal study designs, and the examination of DNAm in additional cell-types and tissues.

Difficulties with sociability include a tendency to avoid social contacts and activities, and to prefer being alone rather than being with others. While sociability is a continuously distributed trait in the population, decreased sociability represent a common early manifestation of multiple neuropsychiatric disorders such as Schizophrenia (SCZ), Bipolar Disorder (BP), Major Depressive Disorder (MDD), Autism Spectrum Disorders (ASDs), and Alzheimers disease (AD). We aimed to investigate the genetic underpinnings of sociability as a continuous trait in the general population. In this respect, we performed a genome-wide association study (GWAS) using a sociability score based on 4 social functioning-related self-report questions in the UK Biobank sample (n=342,461) to test the effect of individual genetic variants. This was followed by LD score analyses to investigate the genetic correlation with psychiatric disorders (SCZ, BP, MDD, ASDs) and a neurological disorder (AD) as well as related phenotypes (Loneliness and Social Anxiety). The phenotypic data indeed showed that the sociability score was decreased in individuals with ASD, (probable) MDD, BP and SCZ, but not in individuals with AD. Our GWAS showed 604 genome-wide significant SNPs, coming from 18 independent loci (SNP-based h2=0.06). Genetic correlation analyses showed significant correlations with SCZ (rg=0.15, p=9.8e-23), MDD (rg=0.68, p=6.6e-248) and ASDs (rg=0.27, p=4.5e-28), but no correlation with BP (rg=0.01, p=0.45) or AD (rg=0.04, p=0.55). Our sociability trait was also genetically correlated with Loneliness (rg=0.45, p=2.4e-8) and Social Anxiety (rg=0.48, p=0.002). Our study shows that there is a significant genetic component to variation in population levels of sociability, which is relevant to some psychiatric disorders (SCZ, MDD, ASDs), but not to BP and AD.

Hoarding Disorder (HD) is a mental disorder characterized by persistent difficulties discarding or parting with possessions, often resulting in cluttered living spaces, distress, and impairment. Its etiology is largely unknown, but twin studies suggest that it is moderately heritable. In this study, we pooled phenotypic and genomic data from seven international cohorts (N = 27 537 individuals) and conducted a genome wide association study (GWAS) meta-analysis of parent- or self-reported hoarding symptoms (HS). We followed up the results with gene-based and gene-set analyses, as well as leave-one-out HS polygenic risk score (PRS) analyses. To examine a possible genetic association between hoarding symptoms and other phenotypes we conducted cross-trait PRS analyses. Though we did not report any genome-wide significant SNPs, we found a significant contribution of common genetic factors to HS, as indicated by substantial SNP-based twin-heritability estimates ranging between 26% and 48% and a SNP-heritability of 11% for one sub-cohort. Cross-trait PRS analyses showed that the genetic risk for schizophrenia and autism spectrum disorder were significantly associated with hoarding symptoms. We also found suggestive evidence for an association with educational attainment. There were no significant associations with other phenotypes previously linked to HD, such as obsessive-compulsive disorder, depression, anxiety, or attention-deficit hyperactivity disorder. To conclude, we found that HS are heritable, confirming and extending previous twin studies but we had limited power to detect any genome-wide significant loci. Much larger samples will be needed to further extend these findings and reach a "gene discovery zone". To move the field forward, future research should not only include genetic analyses of quantitative hoarding traits in larger samples, but also in samples of individuals meeting strict diagnostic criteria for HD, and more ethnically diverse samples.

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.

Attention-deficit/hyperactivity disorder (ADHD) is a heritable neurodevelopmental disorder for which genetic factors explain up to 75% of the variance. In this study, we performed a genome-wide association meta-analysis (GWAMA) of ADHD symptom measures, with an effective sample size of 120,092 (71,733 unique individuals from 28 population-based cohorts, with 288,887 quantitative ADHD symptom measures). Next, we meta-analyzed the results with a genome-wide association study (GWAS) of ADHD diagnosis. The GWAMA of ADHD symptoms returned no genome-wide significant variants. However, we estimated strong genetic correlations between our study of quantitative ADHD symptoms and the earlier study of ADHD diagnosis (rg= 1.00, SE= 0.06). Moderate negative genetic correlations (rg< -0.40) were observed with several cognitive traits. Genetic correlations between ADHD and aggressive behavior and antisocial behavior were around 1. This provides further evidence of the wide pleiotropic effects of genetic variants and the role that genetic variants play in the co-occurrence with (mental) health traits. The GWAMAs of ADHD symptoms and diagnosis identified 2,039 genome-wide significant variants, representing 39 independent loci, of which 17 were new. Using a novel fine-mapping and functional annotation method, we identified 22 potential effector genes which implicate several new potential biological processes and pathways that may play a role in ADHD. Our findings support the notion that clinical ADHD is at the extreme end of a continuous liability that is indexed by ADHD symptoms. We show that including ADHD symptom counts in large-scale GWAS can be useful to identify novel genes implicated in ADHD and related symptoms.

BackgroundWhile COVID-19 outcomes are associated with increased anxiety, individuals affected by anxiety disorders are more likely to develop severe COVID-19 outcomes. MethodsWe used genome-wide data from UK Biobank (up to 420,531 participants), FinnGen Project (up to 329,077 participants), Million Veteran Program (175,163 participants), and COVID-19 Host Genetics Initiative (up to 122,616 cases and 2,475,240 controls) to investigate possible causal effects and shared genetic mechanisms linking COVID-19 outcomes to anxiety disorders and symptoms. ResultsWe observed a strong genetic correlation of anxiety disorder with COVID-19 positive status (rg=0.35, p=2 x 10-4) and COVID-19 hospitalization (rg=0.31, p=7.2 x 10-4). Among anxiety symptoms, "Tense, sore, or aching muscles during worst period of anxiety" was genetically correlated with COVID-19 positive status (rg=0.33, p=0.001), while "Frequent trouble falling or staying asleep during worst period of anxiety" was genetically correlated with COVID-19 hospitalization (rg=0.24, p=0.004). Through a latent causal variable analysis, we observed that COVID-19 outcomes have statistically significant genetic causality proportion (gcp) on anxiety symptoms (e.g., COVID-19 positive status[-&gt;]"Recent easy annoyance or irritability" [boxv]gcp[boxv]=0.18, p=6.72 x 10-17). Conversely, anxiety disorders appear to have a possible causal effect on COVID-19 ([boxv]gcp[boxv]=0.38, p=3.17 x 10-9). Additionally, we also identified multiple loci with evidence of local genetic correlation between anxiety and COVID-19. These appear to be related to genetic effects shared with lung function, brain morphology, alcohol and tobacco use, and hematologic parameters. ConclusionsThis study provided important insights into the relationship between COVID-19 and mental health, differentiating the dynamics linking anxiety disorders to COVID-19 from the effect of COVID-19 on anxiety symptoms.