Expressive

rs10779835 - GALNT2

Magnitude 2.2 · 7 studies on file

Reported associations

  • Comprehensive genetic study of the insulin resistance marker TG:HDL-C in the UK Biobank. - Nature genetics (2024) · Oliveri A, Rebernick RJ, Kuppa A, Pant A, Chen Y, Du X, Cushing KC, Bell HN, Raut C, Prabhu P, Chen VL, Halligan BD, Speliotes EK · PubMed 38200128

    Insulin resistance (IR) is a well-established risk factor for metabolic disease. The ratio of triglycerides to high-density lipoprotein cholesterol (TG:HDL-C) is a surrogate marker of IR. We conducted a genome-wide association study of the TG:HDL-C ratio in 402,398 Europeans within the UK Biobank. We identified 369 independent SNPs, of which 114 had a false discovery rate-adjusted P value < 0.05 in other genome-wide studies of IR making them high-confidence IR-associated loci. Seventy-two of these 114 loci have not been previously associated with IR. These 114 loci cluster into five groups upon phenome-wide analysis and are enriched for candidate genes important in insulin signaling, adipocyte physiology and protein metabolism. We created a polygenic-risk score from the high-confidence

  • Multi-ancestry genome-wide association analyses incorporating SNP-by-psychosocial interactions identify novel loci for serum lipids - Unknown journal (n.d.) · Unknown authors · PubMed 40537477

    ABSTRACT: Serum lipid levels, which are influenced by both genetic and environmental factors, are key determinants of cardiometabolic health and are influenced by both genetic and environmental factors. Improving our understanding of their underlying biological mechanisms can have important public health and therapeutic implications. Although psychosocial factors, including depression, anxiety, and perceived social support, are associated with serum lipid levels, it is unknown if they modify the effect of genetic loci that influence lipids. We conducted a genome-wide gene-by-psychosocial factor interaction (G×Psy) study in up to 133,157 individuals to evaluate if G×Psy influences serum lipid levels. We conducted a two-stage meta-analysis of G×Psy using both a one-degree of freedom (1df)

  • Use of genetic variation to separate the effects of early and later life adiposity on disease risk: mendelian randomisation study - Unknown journal (n.d.) · Unknown authors · PubMed 32376654

    ABSTRACT: Abstract Objective To evaluate whether body size in early life has an independent effect on risk of disease in later life or whether its influence is mediated by body size in adulthood. Design Two sample univariable and multivariable mendelian randomisation. Setting The UK Biobank prospective cohort study and four large scale genome-wide association studies (GWAS) consortiums. Participants 453 169 participants enrolled in UK Biobank and a combined total of more than 700 000 people from different GWAS consortiums. Exposures Measured body mass index during adulthood (mean age 56.5) and self-reported perceived body size at age 10. Main outcome measures Coronary artery disease, type 2 diabetes, breast cancer, and prostate cancer. Results Having a larger genetically predicted body

  • 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

  • A comprehensive study of metabolite genetics reveals strong pleiotropy and heterogeneity across time and context - Unknown journal (n.d.) · Unknown authors · PubMed 31636271

    ABSTRACT: Genetic studies of metabolites have identified thousands of variants, many of which are associated with downstream metabolic and obesogenic disorders. However, these studies have relied on univariate analyses, reducing power and limiting context-specific understanding. Here we aim to provide an integrated perspective of the genetic basis of metabolites by leveraging the Finnish Metabolic Syndrome In Men (METSIM) cohort, a unique genetic resource which contains metabolic measurements, mostly lipids, across distinct time points as well as information on statin usage. We increase effective sample size by an average of two-fold by applying the Covariates for Multi-phenotype Studies (CMS) approach, identifying 588 significant SNP-metabolite associations, including 228 new associations

  • 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

  • A genetic map of human metabolism across the allele frequency spectrum - Unknown journal (n.d.) · Unknown authors · PubMed 41044249

    ABSTRACT: Genetic studies of human metabolism have been limited in scale and allelic breadth. Here we provide a data-driven map of the genetic regulation of circulating small molecules and lipoprotein characteristics (249 traits) measured using proton nuclear magnetic resonance spectroscopy across the allele frequency spectrum in ~450,000 individuals. Trans-ancestral meta-analyses identify 29,824 locus-metabolite associations mapping to 753 regions with effects largely consistent between men and women and large ancestral groups represented in UK Biobank. We observe and classify extreme genetic pleiotropy, identify regulators of lipid metabolism, and assign effector genes at >100 loci through rare-to-common allelic series. We propose roles for genes less established in metabolic control (

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