rs10096191 - EYA1
Magnitude 4.5 · 5 studies on file
Reported associations
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Genetic drivers of heterogeneity in type 2 diabetes pathophysiology - Unknown journal (n.d.) · Unknown authors · PubMed 38374256
ABSTRACT: Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes and molecular mechanisms that are often specific to cell type. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10−8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-sp
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Testosterone and socioeconomic position: Mendelian randomization in 306,248 men and women in UK Biobank - Unknown journal (n.d.) · Unknown authors · PubMed 34321204
ABSTRACT: Mendelian randomization suggests circulating testosterone does not meaningfully affect men's socioeconomic position. Men with more advantaged socioeconomic position (SEP) have been observed to have higher levels of testosterone. It is unclear whether these associations arise because testosterone has a causal impact on SEP. In 306,248 participants of UK Biobank, we performed sex-stratified genome-wide association analysis to identify genetic variants associated with testosterone. Using the identified variants, we performed Mendelian randomization analysis of the influence of testosterone on socioeconomic position, including income, employment status, neighborhood-level deprivation, and educational qualifications; on health, including self-rated health and body mass index; and on
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Genome-wide association study of serum liver enzymes implicates diverse metabolic and liver pathology - Unknown journal (n.d.) · Unknown authors · PubMed 33547301
ABSTRACT: Serum liver enzyme concentrations are the most frequently-used laboratory markers of liver disease, a major cause of mortality. We conduct a meta-analysis of genome-wide association studies of liver enzymes from UK BioBank and BioBank Japan. We identified 160 previously-unreported independent alanine aminotransferase, 190 aspartate aminotransferase, and 199 alkaline phosphatase genome-wide significant associations, with some affecting multiple different enzymes. Associated variants implicate genes that demonstrate diverse liver cell type expression and promote a range of metabolic and liver diseases. These findings provide insight into the pathophysiology of liver and other metabolic diseases that are associated with serum liver enzyme concentrations. Serum liver enzymes are used
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Shared Genetic and Experimental Links between Obesity-Related Traits and Asthma Subtypes in UK Biobank - Unknown journal (n.d.) · Unknown authors · PubMed 31669095
ABSTRACT: Background: Clinical and epidemiological studies have shown that obesity is associated with asthma and that these associations differ by asthma subtypes. Little is known about the shared genetic components between obesity and asthma. Objective: To identify shared genetic associations between obesity-related traits and asthma subtypes in adults. Methods: A cross-trait genome-wide association study (GWAS) was performed using 457,822 individuals of European ancestry from the UK Biobank. Experimental evidence to support the role of genes significantly associated with both obesity-related traits and asthma via GWAS was sought using results from obese vs. lean mouse RNA-seq and RT-PCR experiments. Results: We found a substantial positive genetic correlation between BMI and later-onset
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Multivariate genomic analysis of 5 million people elucidates the genetic architecture of shared components of the metabolic syndrome - Unknown journal (n.d.) · Unknown authors · PubMed 39349817
ABSTRACT: Metabolic syndrome (MetS) is a complex hereditary condition comprising various metabolic traits as risk factors. Although the genetics of individual MetS components have been investigated actively through large-scale genome-wide association studies, the conjoint genetic architecture has not been fully elucidated. Here, we performed the largest multivariate genome-wide association study of MetS in Europe (nobserved = 4,947,860) by leveraging genetic correlation between MetS components. We identified 1,307 genetic loci associated with MetS that were enriched primarily in brain tissues. Using transcriptomic data, we identified 11 genes associated strongly with MetS. Our phenome-wide association and Mendelian randomization analyses highlighted associations of MetS with diverse di
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