rs116272812 - CARMIL1
Magnitude 2.0 · 4 studies on file
Reported associations
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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
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An expanded set of genome-wide association studies of brain imaging phenotypes in UK Biobank - Unknown journal (n.d.) · Unknown authors · PubMed 33875891
ABSTRACT: UK Biobank is a major prospective epidemiological study, including multimodal brain imaging, genetics and ongoing health outcomes. Previously, we published genome-wide associations of 3,144 brain imaging-derived phenotypes, with a discovery sample of 8,428 subjects. Here we present a new open resource of GWAS summary statistics, using the 2020 data release, almost tripling the discovery sample size. We now include the X chromosome, and new classes of image derived phenotypes (subcortical volumes and tissue contrast). Previously we had found 148 replicated clusters of associations between genetic variants and imaging phenotypes; here we find 692, including 12 on the X chromosome. We describe some of the newly found associations, focussing on the X chromosome and autosomal associat
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The power of genetic diversity in genome-wide association studies of lipids - Unknown journal (n.d.) · Unknown authors · PubMed 34887591
ABSTRACT: Elevated blood lipid levels are heritable risk factors of cardiovascular disease with varying prevalence worldwide due to differing dietary patterns and medication use. Despite advances in prevention and treatment, particularly through the lowering of low-density lipoprotein cholesterol levels, heart disease remains the leading cause of death worldwide. Genome-wide association studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS have been conducted in European ancestry populations and may have missed genetic variants contributing to lipid level variation in other ancestry groups due to differences in allele frequencies, effect sizes, and linkage-disequilibr
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Participation bias in the UK Biobank distorts genetic associations and downstream analyses - Unknown journal (n.d.) · Unknown authors · PubMed 37106081
ABSTRACT: While volunteer-based studies such as the UK Biobank have become the cornerstone of genetic epidemiology, the participating individuals are rarely representative of their target population. To evaluate the impact of selective participation, here we derived UK Biobank participation probabilities on the basis of 14 variables harmonized across the UK Biobank and a representative sample. We then conducted weighted genome-wide association analyses on 19 traits. Comparing the output from weighted genome-wide association analyses (neffective = 94,643 to 102,215) with that from standard genome-wide association analyses (n = 263,464 to 283,749), we found that increasing representativeness led to changes in SNP effect sizes and identified novel SNP associations for 12 traits. While
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