Expressive

rs11646732 - TMC5

Magnitude 2.2 · 2 studies on file

Reported associations

  • Genome-wide associations of human gut microbiome variation and implications for causal inference analyses - Unknown journal (n.d.) · Unknown authors · PubMed 32572223

    ABSTRACT: Recent population-based and clinical studies have identified a range of factors associated with human gut microbiome variation. Murine quantitative trait loci, human twin studies and microbiome genome-wide association studies (mGWAS) have provided evidence for genetic contributions to microbiome composition. Despite this, there is still poor overlap in genetic association across human studies. Using appropriate taxon-specific models along with support from independent cohorts, we show association between human host genotype and gut microbiome variation. We also suggest that interpretation of applied analyses using genetic associations is complicated by the likely overlap between genetic contributions and heritable components of host environment. Using fecal derived 16S rRNA gene

  • Genome-Wide Association Study of Nicotine Dependence in American Populations: Identification of Novel Risk Loci in Both African-Americans and European-Americans - Unknown journal (n.d.) · Unknown authors · PubMed 25555482

    ABSTRACT: BACKGROUND We report a genome-wide association study (GWAS) of nicotine dependence defined on the basis of scores on the Fagerström Test for Nicotine Dependence in European-American (EA) and African-American (AA) populations. METHODS Our sample, from the one used in our previous GWAS, included only subjects who had smoked >100 cigarettes lifetime (2114 EA and 2602 AA subjects) and an additional 927 AA and 2003 EA subjects from the Study of Addiction: Genetics and Environment project [via the database of Genotypes and Phenotypes (dbGAP)]. GWAS analysis considered Fagerström Test for Nicotine Dependence score as an ordinal trait, separately in each population and sample and by combining the results in meta-analysis. We also conducted analyses that were adjusted for other substanc

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