rs10842708 - SSPN-AS1, ITPR2-AS2

Magnitude 4.5 · 5 studies on file

Reported associations

• 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

• Genome-wide physical activity interactions in adiposity ― A meta-analysis of 200,452 adults - Unknown journal (n.d.) · Unknown authors · PubMed 28448500

  ABSTRACT: Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive t

• Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation - Unknown journal (n.d.) · Unknown authors · PubMed 35551307

  ABSTRACT: We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 cases and 1,159,055 controls (48.9% non-European descent) through the DIAMANTE (DIAbetes Meta-ANalysis of Trans-Ethnic association studies) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 x 10−9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular me

• 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

• Genetics of Blood Lipids Among ~300,000 Multi-Ethnic Participants of the Million Veteran Program - Unknown journal (n.d.) · Unknown authors · PubMed 30275531

  ABSTRACT: The Million Veteran Program (MVP) was established in 2011 as a national research initiative to determine how genetic variation influences the health of U.S. military veterans. We genotyped 312,571 MVP participants using a custom biobank array and linked the genetic data to laboratory and clinical phenotypes extracted from electronic health records covering a median of 10.0 years of follow-up. Among 297,626 veterans with at least 1 blood lipid measurement including 57,332 blacks and 24,743 Hispanics, we tested up to ~32 million variants for association with lipid levels and identified 118 novel genome-wide significant loci after meta-analysis with data from the Global Lipids Genetics Consortium (total N > 600,000). Through a focus on mutations predicted to result in a loss of gene

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