30 research outputs found

    Genome-wide association study of problematic opioid prescription use in 132,113 23andMe research participants of European ancestry

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    The growing prevalence of opioid use disorder (OUD) constitutes an urgent health crisis. Ample evidence indicates that risk for OUD is heritable. As a surrogate (or proxy) for OUD, we explored the genetic basis of using prescription opioids \u27not as prescribed\u27. We hypothesized that misuse of opiates might be a heritable risk factor for OUD. To test this hypothesis, we performed a genome-wide association study (GWAS) of problematic opioid use (POU) in 23andMe research participants of European ancestry (N = 132,113; 21% cases). We identified two genome-wide significant loci (rs3791033, an intronic variant of KDM4A; rs640561, an intergenic variant near LRRIQ3). POU showed positive genetic correlations with the two largest available GWAS of OUD and opioid dependence (

    Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits

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    Problematic alcohol use (PAU) is a leading cause of death and disability worldwide. Although genome-wide association studies have identified PAU risk genes, the genetic architecture of this trait is not fully understood. We conducted a proxy-phenotype meta-analysis of PAU, combining alcohol use disorder and problematic drinking, in 435,563 European-ancestry individuals. We identified 29 independent risk variants, 19 of them novel. PAU was genetically correlated with 138 phenotypes, including substance use and psychiatric traits. Phenome-wide polygenic risk score analysis in an independent biobank sample (BioVU, n = 67,589) confirmed the genetic correlations between PAU and substance use and psychiatric disorders. Genetic heritability of PAU was enriched in brain and in conserved and regulatory genomic regions. Mendelian randomization suggested causal effects on liability to PAU of substance use, psychiatric status, risk-taking behavior and cognitive performance. In summary, this large PAU meta-analysis identified novel risk loci and revealed genetic relationships with numerous other traits

    Meta-analyses of genome-wide association studies for postpartum depression

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    Objective: Postpartum depression (PPD) is a common subtype of major depressive disorder (MDD) that is more heritable, yet is understudied in psychiatric genetics. The authors conducted meta-analyses of genome-wide association studies (GWASs) to investigate the genetic architecture of PPD. Method: Meta-analyses were conducted on 18 cohorts of European ancestry (17,339 PPD cases and 53,426 controls), one cohort of East Asian ancestry (975 cases and 3,780 controls), and one cohort of African ancestry (456 cases and 1,255 controls), totaling 18,770 PPD cases and 58,461 controls. Post-GWAS analyses included 1) single-nucleotide polymorphism (SNP)–based heritability (), 2) genetic correlations between PPD and other phenotypes, and 3) enrichment of the PPD GWAS findings in 27 human tissues and 265 cell types from the mouse central and peripheral nervous system. Results: No SNP achieved genome-wide significance in the European or the trans-ancestry meta-analyses. The of PPD was 0.14 (SE=0.02). Significant genetic correlations were estimated for PPD with MDD, bipolar disorder, anxiety disorders, posttraumatic stress disorder, insomnia, age at menarche, and polycystic ovary syndrome. Cell-type enrichment analyses implicate inhibitory neurons in the thalamus and cholinergic neurons within septal nuclei of the hypothalamus, a pattern that differs from MDD. Conclusions: While more samples are needed to reach genome-wide levels of significance, the results presented confirm PPD as a polygenic and heritable phenotype. There is also evidence that despite a high correlation with MDD, PPD may have unique genetic components. Cell enrichment results suggest GABAergic neurons, which converge on a common mechanism with the only medication approved by the U.S. Food and Drug Administration for PPD (brexanolone)

    A phenome‐wide association study of polygenic scores for attention deficit hyperactivity disorder across two genetic ancestries in electronic health record data

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    Testing the association between genetic scores for Attention Deficit Hyperactivity Disorder (ADHD) and health conditions, can help us better understand its complex etiology. Electronic health records linked to genetic data provide an opportunity to test whether genetic scores for ADHD correlate with ADHD and additional health outcomes in a health care context across different age groups. We generated polygenic scores (ADHD-PGS) trained on summary statistics from the latest genome-wide association study of ADHD (N = 55,374) and applied them to genome-wide data from 12,383 unrelated individuals of African-American ancestry and 66,378 unrelated individuals of European ancestry from the Vanderbilt Biobank. Overall, only Tobacco use disorder (TUD) was associated with ADHD-PGS in the African-American ancestry group (Odds ratio [95% confidence intervals] = 1.23[1.16-1.31], p = 9.3 × 10-09 ). Eighty-six phenotypes were associated with ADHD-PGS in the European ancestry individuals, including ADHD (OR[95%CIs] = 1.22[1.16-1.29], p = 3.6 × 10-10 ), and TUD (OR[95%CIs] = 1.22[1.19-1.25], p = 2.8 × 10-46 ). We then stratified outcomes by age (ages 0-11, 12-18, 19-25, 26-40, 41-60, and 61-100). Our results suggest that ADHD polygenic scores are associated with ADHD diagnoses early in life and with an increasing number of health conditions throughout the lifespan (even in the absence of ADHD diagnosis). This study reinforces the utility of applying trait-specific PGSs to biobank data, and performing exploratory sensitivity analyses, to probe relationships among clinical conditions

    A blended genome and exome sequencing method captures genetic variation in an unbiased, high-quality, and cost-effective manner

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    We deployed the Blended Genome Exome (BGE), a DNA library blending approach that generates low pass whole genome (1-4x mean depth) and deep whole exome (30-40x mean depth) data in a single sequencing run. This technology is cost-effective, empowers most genomic discoveries possible with deep whole genome sequencing, and provides an unbiased method to capture the diversity of common SNP variation across the globe. To evaluate this new technology at scale, we applied BGE to sequence \u3e53,000 samples from the Populations Underrepresented in Mental Illness Associations Studies (PUMAS) Project, which included participants across African, African American, and Latin American populations. We evaluated the accuracy of BGE imputed genotypes against raw genotype calls from the Illumina Global Screening Array. All PUMAS cohorts had R2 concordance ≥95% among SNPs with MAF≥1%, and never fell below ≥90% R2 for SNPs with MA
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