Expressive

rs10041894 - RNU1-150P - TTC33

Magnitude 2.2 · 2 studies on file

Reported associations

  • Joint analysis of genome-wide cross-trait and multi-omics reveals molecular mechanisms of inflammatory bowel disease and nominates its novel therapeutic genes. - FASEB journal : official publication of the Federation of American Societies for Experimental Biology (2025) · Zhu Z, Wei R, Li H, Wang X, He G, Du M, Tan S, Cheng L · PubMed 39792054

    Inflammatory bowel disease (IBD) with the two predominant endophenotypes-Crohn's disease (CD) and ulcerative colitis (UC)-represents a group of chronic gastrointestinal inflammatory conditions. Since most genetic associations with IBD are often limited to independent subtypes, we reported a genome-wide association study (GWAS) cross-trait analysis combined with CD and UC to enhance statistical power. Initially, we detected 256 association signals at 54 genomic susceptibility loci and further characterized the functionality of variants within these regions. Subsequently, we revealed tissue and cell-specific heritability enrichment, particularly in whole blood, small intestine terminal ileum, spleen, lung, and colon transverse. Leveraging multi-omics datasets, we adopted a two-pronged approa

  • 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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