Expressive

rs11925835 - ARHGEF3

Magnitude 2.2 · 3 studies on file

Reported associations

  • Genome-Wide Association Study for Alcohol-Related Cirrhosis Identifies Risk Loci in MARC1 and HNRNPUL1. - Gastroenterology (2021) · Innes H, Buch S, Hutchinson S, Guha IN, Morling JR, Barnes E, Irving W, Forrest E, Pedergnana V, Goldberg D, Aspinall E, Barclay S, Hayes PC, Dillon J, Nischalke HD, Lutz P, Spengler U, Fischer J, Berg T, Brosch M, Eyer F, Datz C, Mueller S, Peccerella T, Deltenre P, Marot A, Soyka M, McQuillin A, Morgan MY, Hampe J, Stickel F · PubMed 32561361

    Little is known about genetic factors that affect development of alcohol-related cirrhosis. We performed a genome-wide association study (GWAS) of samples from the United Kingdom Biobank (UKB) to identify polymorphisms associated with risk of alcohol-related liver disease. We performed a GWAS of 35,839 participants in the UKB with high intake of alcohol against markers of hepatic fibrosis (FIB-4, APRI, and Forns index scores) and hepatocellular injury (levels of aminotransferases). Loci identified in the discovery analysis were tested for their association with alcohol-related cirrhosis in 3 separate European cohorts (phase 1 validation cohort; n=2545). Variants associated with alcohol-related cirrhosis in the validation at a false discovery rate of less than 20% were then directly genotyp

  • Mapping the proteo-genomic convergence of human diseases - Unknown journal (n.d.) · Unknown authors · PubMed 34648354

    ABSTRACT: Characterization of the genetic regulation of proteins is essential for understanding disease etiology and developing therapies. We identified 10,674 genetic associations for 3,892 plasma proteins to create a cis-anchored gene-protein-disease map of 1,859 connections that highlights strong cross-disease biological convergence. This proteo-genomic map provides a framework to 1) connect etiologically related diseases, 2) provide biological context for new or emerging disorders, and 3) integrate different biological domains to establish mechanisms for known gene-disease links. Our results identify proteo-genomic connections within and between diseases and establish the value of cis-protein variants for annotation of likely causal disease genes at GWAS loci, addressing a major barrie

  • Genome-wide analyses of variance in blood cell phenotypes provide new insights into complex trait biology and prediction - Unknown journal (n.d.) · Unknown authors · PubMed 40335489

    ABSTRACT: Blood cell phenotypes are routinely tested in healthcare to inform clinical decisions. Genetic variants influencing mean blood cell phenotypes have been used to understand disease aetiology and improve prediction; however, additional information may be captured by genetic effects on observed variance. Here, we mapped variance quantitative trait loci (vQTL), i.e. genetic loci associated with trait variance, for 29 blood cell phenotypes from the UK Biobank (N ~ 408,111). We discovered 176 independent blood cell vQTLs, of which 147 were not found by additive QTL mapping. vQTLs displayed on average 1.8-fold stronger negative selection than additive QTL, highlighting that selection acts to reduce extreme blood cell phenotypes. Variance polygenic scores (vPGSs) were constructed to

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