rs1164598 - HS6ST3

Magnitude 2.2 · 7 studies on file

Reported associations

• Leveraging Polygenic Functional Enrichment to Improve GWAS Power. - American journal of human genetics (2019) · Kichaev G, Bhatia G, Loh PR, Gazal S, Burch K, Freund MK, Schoech A, Pasaniuc B, Price AL · PubMed 30595370

  Functional genomics data has the potential to increase GWAS power by identifying SNPs that have a higher prior probability of association. Here, we introduce a method that leverages polygenic functional enrichment to incorporate coding, conserved, regulatory, and LD-related genomic annotations into association analyses. We show via simulations with real genotypes that the method, functionally informed novel discovery of risk loci (FINDOR), correctly controls the false-positive rate at null loci and attains a 9%-38% increase in the number of independent associations detected at causal loci, depending on trait polygenicity and sample size. We applied FINDOR to 27 independent complex traits and diseases from the interim UK Biobank release (average N = 130K). Averaged across traits, we attaine

• Genetic Risk for Smoking: Disentangling Interplay Between Genes and Socioeconomic Status - Unknown journal (n.d.) · Unknown authors · PubMed 34855049

  ABSTRACT: This study aims to disentangle the contribution of genetic liability, educational attainment (EA), and their overlap and interaction in lifetime smoking. We conducted genome-wide association studies (GWASs) in UK Biobank (N = 394,718) to (i) capture variants for lifetime smoking, (ii) variants for EA, and (iii) variants that contribute to lifetime smoking independently from EA ('smoking-without-EA'). Based on the GWASs, three polygenic scores (PGSs) were created for individuals from the Netherlands Twin Register (NTR, N = 17,805) and the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2, N = 3090). We tested gene-environment (G × E) interactions between each PGS, neighborhood socioeconomic status (SES) and EA on lifetime smoking. To assess i

• Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction - Unknown journal (n.d.) · Unknown authors · PubMed 34446935

  ABSTRACT: Behaviors and disorders related to self-regulation, such as substance use, antisocial behavior, and ADHD, are collectively referred to as externalizing and have shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 genetic loci. The loci were enriched for genes expressed in the brain and related to nervous system development. A polygenic score constructed from our results predicts a range of behavioral and medical outcomes that were not part of genome-wide analyses, including traits that until now lacked well-performing polygenic scor

• The Genetic and Neural Substrates of Externalizing Behavior - Unknown journal (n.d.) · Unknown authors · PubMed 36324656

  ABSTRACT: Background To gain more insight into the biological factors that mediate vulnerability to display externalizing behaviors, we leveraged genome-wide association study summary statistics on 13 externalizing phenotypes. Methods After data classification based on genetic resemblance, we performed multivariate genome-wide association meta-analyses and conducted extensive bioinformatic analyses, including genetic correlation assessment with other traits, Mendelian randomization, and gene set and gene expression analyses. Results The genetic data could be categorized into disruptive behavior (DB) and risk-taking behavior (RTB) factors, and subsequent genome-wide association meta-analyses provided association statistics for DB and RTB (Neff = 523,150 and 1,506,537, respectively), yieldi

• Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use - Unknown journal (n.d.) · Unknown authors · PubMed 30643251

  ABSTRACT: Tobacco and alcohol use are leading causes of mortality that influence risk for many complex diseases and disorders. They are heritable and etiologically related behaviors that have been resistant to gene discovery efforts. In sample sizes up to 1.2 million individuals, we discovered 566 genetic variants in 406 loci associated with multiple stages of tobacco use (initiation, cessation, and heaviness) as well as alcohol use, with 150 loci evidencing pleiotropic association. Smoking phenotypes were positively genetically correlated with many health conditions, whereas alcohol use was negatively correlated with these conditions, such that increased genetic risk for alcohol use is associated with lower disease risk. We report evidence for the involvement of many systems in tobacco an

• Genetic diversity fuels gene discovery for tobacco and alcohol use - Unknown journal (n.d.) · Unknown authors · PubMed 36477530

  ABSTRACT: Tobacco and alcohol use are heritable behaviours associated with 15% and 5.3% of worldwide deaths, respectively, due largely to broad increased risk for disease and injury. These substances are used across the globe, yet genome-wide association studies have focused largely on individuals of European ancestries. Here we leveraged global genetic diversity across 3.4 million individuals from four major clines of global ancestry (approximately 21% non-European) to power the discovery and fine-mapping of genomic loci associated with tobacco and alcohol use, to inform function of these loci via ancestry-aware transcriptome-wide association studies, and to evaluate the genetic architecture and predictive power of polygenic risk within and across populations. We found that increases in s

• Genome-wide association analyses of risk tolerance and risky behaviors in over one million individuals identify hundreds of loci and shared genetic influences - Unknown journal (n.d.) · Unknown authors · PubMed 30643258

  ABSTRACT: Humans vary substantially in their willingness to take risks. In a combined sample of over one million individuals, we conducted genome-wide association studies (GWAS) of general risk tolerance, adventurousness, and risky behaviors in the driving, drinking, smoking, and sexual domains. Across all GWAS we identified hundreds of associated loci, including 99 loci associated with general risk tolerance. We report evidence of substantial shared genetic influences across risk tolerance and the risky behaviors: 46 of the 99 general risk tolerance loci contain a lead SNP for at least one of our other GWAS, and general risk tolerance is genetically correlated ( ~ 0.25 to 0.50) with a range of risky behaviors. Bioinformatics analyses imply that genes near general-risk-tolerance-associated

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