rs116279971 - HORMAD1
Magnitude 2.2 · 4 studies on file
Reported associations
-
Cross-ancestry Genome-wide Association Studies of Sex Hormone Concentrations in Pre- and Postmenopausal Women. - Endocrinology (2022) · Haas CB, Hsu L, Lampe JW, Wernli KJ, Lindström S · PubMed 35192695
Concentrations of circulating sex hormones have been associated with a variety of diseases in women and are strongly influenced by menopausal status. We investigated the genetic architectures of circulating concentrations of estradiol, testosterone, and SHBG by menopausal status in women of European and African ancestry. Using data on 229 966 women from the UK Biobank, we conducted genome-wide association studies (GWASs) of circulating concentrations of estradiol, testosterone, and SHBG in premenopausal and postmenopausal women. We tested for evidence of heterogeneity of genetic effects by menopausal status and genetic ancestry. We conducted gene-based enrichment analyses to identify tissues in which genes with GWAS-enriched signals were expressed. We identified 4 loci (5q35.2, 12q14.3, 19
-
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
-
A scalable variational inference approach for increased mixed-model association power - Unknown journal (n.d.) · Unknown authors · PubMed 39789286
ABSTRACT: The rapid growth of modern biobanks is creating new opportunities for large-scale genome-wide association studies (GWASs) and the analysis of complex traits. However, performing GWASs on millions of samples often leads to trade-offs between computational efficiency and statistical power, reducing the benefits of large-scale data collection efforts. We developed Quickdraws, a method that increases association power in quantitative and binary traits without sacrificing computational efficiency, leveraging a spike-and-slab prior on variant effects, stochastic variational inference and graphics processing unit acceleration. We applied Quickdraws to 79 quantitative and 50 binary traits in 405,088 UK Biobank samples, identifying 4.97% and 3.25% more associations than REGENIE and 22.71%
-
Using human genetics to understand the disease impacts of testosterone in men and women - Unknown journal (n.d.) · Unknown authors · PubMed 32042192
ABSTRACT: Testosterone supplementation is commonly used for its effects on sexual function, bone health and body composition, yet its effects on disease outcomes are unknown. To better understand this, we identified genetic determinants of testosterone levels and related sex hormone traits in 425,097 UK Biobank study participants. Using 2,571 genome-wide significant associations, we demonstrate the genetic determinants of testosterone levels are substantially different between sexes, and that genetically higher testosterone is harmful for metabolic diseases in women but beneficial in men. For example, a genetically determined 1-standard deviation higher testosterone increases the risks of Type 2 diabetes (T2D) (OR=1.37 [1.22-1.53]) and polycystic ovary syndrome (OR=1.51 [1.33-1.72]) in
Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.