rs1203979 - LUC7L

Magnitude 2.2 · 2 studies on file

Reported associations

  • Lifestyle Factors and Genetic Variants on 2 Biological Age Measures: Evidence From 94 443 Taiwan Biobank Participants. - The journals of gerontology. Series A, Biological sciences and medical sciences (2022) · Lin WY · PubMed 34427645

    Biological age (BA) can be estimated by phenotypes and is useful for predicting life span and health span. Levine et al. proposed a PhenoAge and a BioAge to measure BA. Although there have been studies investigating the genetic predisposition to BA acceleration in Europeans, little has been known regarding this topic in Asians. I have estimated PhenoAgeAccel (age-adjusted PhenoAge) and BioAgeAccel (age-adjusted BioAge) of 94 443 Taiwan Biobank (TWB) participants, wherein 25 460 TWB1 participants formed a discovery cohort and 68 983 TWB2 individuals constructed a replication cohort. Lifestyle factors and genetic variants associated with PhenoAgeAccel and BioAgeAccel were investigated through regression analysis and a genome-wide association study. A unit (kg/m2) increase of body mass index

  • The contribution of common and rare genetic variants to variation in metabolic traits in 288,137 East Asians - Unknown journal (n.d.) · Unknown authors · PubMed 36333282

    ABSTRACT: Metabolic traits are heritable phenotypes widely-used in assessing the risk of various diseases. We conduct a genome-wide association analysis (GWAS) of nine metabolic traits (including glycemic, lipid, liver enzyme levels) in 125,872 Korean subjects genotyped with the Korea Biobank Array. Following meta-analysis with GWAS from Biobank Japan identify 144 novel signals (MAF ≥ 1%), of which 57.0% are replicated in UK Biobank. Additionally, we discover 66 rare (MAF < 1%) variants, 94.4% of them co-incident to common loci, adding to allelic series. Although rare variants have limited contribution to overall trait variance, these lead, in carriers, substantial loss of predictive accuracy from polygenic predictions of disease risk from common variant alone. We capture groups


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