Expressive

rs11665759 - ZNF793 - ZNF571-AS1

Magnitude 2.0 · 2 studies on file

Reported associations

  • Trans-ethnic Meta-analysis of Metabolic Syndrome in a Multi-ethnic Study - Unknown journal (n.d.) · Unknown authors · PubMed 31647587

    ABSTRACT: Genome-wide association studies (GWAS) have been used to establish thousands of genetic associations across numerous phenotypes. To improve the power of GWAS and generalize associations across ethnic groups, trans-ethnic meta-analysis methods are used to combine the results of several GWAS from diverse ancestries. The goal of this study is to identify genetic associations for eight quantitative metabolic syndrome (MetS) traits through a meta-analysis across four ethnic groups. Traits were measured in the GENetics of Non-Insulin dependent Diabetes mellitus (GENNID) Study which consists of African-American (families=73, individuals=288), European-American (families=79, individuals=519), Japanese-American (families=17, individuals=132), and Mexican-American (families=113, individual

  • Genome-wide association analysis of metabolic syndrome quantitative traits in the GENNID multiethnic family study - Unknown journal (n.d.) · Unknown authors · PubMed 34074324

    ABSTRACT: Background To identify genetic associations of quantitative metabolic syndrome (MetS) traits and characterize heterogeneity across ethnic groups. Methods Data was collected from GENetics of Noninsulin dependent Diabetes Mellitus (GENNID), a multiethnic resource of Type 2 diabetic families and included 1520 subjects in 259 African-American, European-American, Japanese-Americans, and Mexican-American families. We focused on eight MetS traits: weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein, triglycerides, fasting glucose, and insulin. Using genotyped and imputed data from Illumina's Multiethnic array, we conducted genome-wide association analyses with linear mixed models for all ethnicities, except for the smaller Japanese-American gro

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