rs111262797 - GDI2
Magnitude 2.2 · 1 study on file
Reported associations
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Bayesian Effect Size Ranking to Prioritise Genetic Risk Variants in Common Diseases for Follow‐Up Studies - Unknown journal (n.d.) · Unknown authors · PubMed 39749473
ABSTRACT: ABSTRACT Biological datasets often consist of thousands or millions of variables, e.g. genetic variants or biomarkers, and when sample sizes are large it is common to find many associated with an outcome of interest, for example, disease risk in a GWAS, at high levels of statistical significance, but with very small effects. The False Discovery Rate (FDR) is used to identify effects of interest based on ranking variables according to their statistical significance. Here, we develop a complementary measure to the FDR, the priorityFDR, that ranks variables by a combination of effect size and significance, allowing further prioritisation among a set of variables that pass a significance or FDR threshold. Applying to the largest GWAS of type 1 diabetes to date (15,573 cases and 158,4
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Lifestyle context
Concrete actions anchored to the cited research. We do not prescribe, we describe.
Discuss with your doctor
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Type 1 diabetes genetic risk and family screening strategy Moderate
GDI2 rs111262797 variant confers increased Type 1 diabetes risk; physician assessment of family history and surveillance protocols informs early detection approach
Screening
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Type 1 diabetes autoimmunity screening panel Moderate
Genetic variant rs111262797 associated with increased Type 1 diabetes risk; early autoimmune marker detection enables monitoring and prevention trial participation
Baseline GAD65, IA-2, and ZnT8 autoantibodies; repeat every 1-2 years if negative