rs10259649 - GCK

Magnitude 2.2 · 3 studies on file

Reported associations

• 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

• The genetics of a "femaleness/maleness" score in cardiometabolic traits in the UK biobank - Unknown journal (n.d.) · Unknown authors · PubMed 37277458

  ABSTRACT: We recently devised continuous "sex-scores" that sum up multiple quantitative traits, weighted by their respective sex-difference effect sizes, as an approach to estimating polyphenotypic "maleness/femaleness" within each binary sex. To identify the genetic architecture underlying these sex-scores, we conducted sex-specific genome-wide association studies (GWASs) in the UK Biobank cohort (females: n = 161,906; males: n = 141,980). As a control, we also conducted GWASs of sex-specific "sum-scores", simply aggregating the same traits, without weighting by sex differences. Among GWAS-identified genes, while sum-score genes were enriched for genes differentially expressed in the liver in both sexes, sex-score genes were enriched for genes differentially expressed

• Genetic risk and polygenic risk score assessment of prediabetes and progression to type 2 diabetes - Unknown journal (n.d.) · Unknown authors · PubMed 40468860

  ABSTRACT: Abstract Aims To identify susceptibility loci to prediabetes and evaluate the performance of existing polygenic risk scores (PGS) for type 2 diabetes (T2D) in predicting prevalent prediabetes and progression to diabetes. Materials and Methods We conducted a case-control Genome‐Wide Association Study (GWAS) on Qatar Biobank (QBB) participants with prediabetes (n = 2267) and normoglycaemia (n = 8665). We further evaluated the performance of 140 existing PGS for T2D in predicting prediabetes using logistic regression in the baseline QBB cohort (n = 10 932) and progression to T2D using Cox regression in the follow‐up cohort (n = 2143). Results GWAS identified two loci associated with prediabetes (p < 5 × 10−8), mapped near GCK and HK1 genes. Among 1

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