Expressive

rs11115162 - LINC02426 - CCDC59

Magnitude 2.2 · 2 studies on file

Reported associations

  • 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

  • Genome-wide association studies and heritability analysis reveal the involvement of host genetics in the Japanese gut microbiota - Unknown journal (n.d.) · Unknown authors · PubMed 33208821

    ABSTRACT: Numerous host extrinsic and intrinsic factors affect the gut microbiota composition, but their cumulative effects do not sufficiently explain the variation in the microbiota, suggesting contributions of missing factors. The Japanese population possesses homogeneous genetic features suitable for genome-wide association study (GWAS). Here, we performed GWASs for human gut microbiota using 1068 healthy Japanese adults. To precisely evaluate genetic effects, we corrected for the impacts of numerous host extrinsic and demographic factors by introducing them as covariates, enabling us to discover five loci significantly associated with microbiome diversity measures: HS3ST4, C2CD2, 2p16.1, 10p15.1, and 18q12.2. Nevertheless, these five variants explain only a small fraction of the varia

Auto-generated from study metadata. AI-synthesised commentary is added when this entry is regenerated through content-service's LLM mode.