rs1209523 - FOXA2 - LNCNEF

Magnitude 2.0 · 2 studies on file

Reported associations

  • A weighted false discovery rate control procedure reveals alleles at FOXA2 that influence fasting glucose levels. - American journal of human genetics (2010) · Xing C, Cohen JC, Boerwinkle E · PubMed 20152958

    Association signals in GWAS are usually prioritized solely by p values. Here, we attempt to improve the power of GWAS by using a weighted false discovery rate control procedure to detect associations of low-frequency variants with effect sizes similar to or even larger than those of common variants. We used the Affymetrix Genome-Wide Human SNP Array 6.0 to test for association with fasting glucose levels in the Atherosclerosis Risk in Communities Study (ARIC) population. In addition to finding several previously identified sequence variations, we identified a low-frequency variant (rs1209523; minor allele frequency = 0.043) near FOXA2 that was associated with fasting glucose levels in European Americans (EAs) (n = 7428, p value = 1.3 x 10(-5)). The association between rs1209523 and glucose

  • Genetic analyses of diverse populations improves discovery for complex traits - Unknown journal (n.d.) · Unknown authors · PubMed 31217584

    ABSTRACT: Genome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development and clinical guidelines. However, the majority of discovery efforts are based on data from populations of European ancestry. In light of the differential genetic architecture that is known to exist between populations, bias in representation can exacerbate existing disease and healthcare disparities. Critical variants may be missed if they have a low frequency or are completely absent in European populations, especially as the field shifts its attention towards rare variants, which are more likely to be population-specific. Additionally, effect sizes and their derived risk prediction scores derived in one population may not accurately extrapolate


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