Expressive

rs10734398 - METTL15 - LINC02758

Magnitude 2.0 · 2 studies on file

Reported associations

  • Tissue-specific genetic variation suggests distinct molecular pathways between body shape phenotypes and colorectal cancer - Science advances (2024) · Peruchet-Noray L, Sedlmeier AM, Dimou N, Baurecht H, Fervers B, Fontvieille E, Konzok J, Tsilidis KK, Christakoudi S, Jansana A, Cordova R, Bohmann P, Stein MJ, Weber A, Bézieau S, Brenner H, Chan AT, Cheng I, Figueiredo JC, Garcia-Etxebarria K, Moreno V, Newton CC, Schmit SL, Song M, Ulrich CM, Ferrari P, Viallon V, Carreras-Torres R, Gunter MJ, Freisling H · PubMed 38640244

    ABSTRACT: It remains unknown whether adiposity subtypes are differentially associated with colorectal cancer (CRC). To move beyond single-trait anthropometric indicators, we derived four multi-trait body shape phenotypes reflecting adiposity subtypes from principal components analysis on body mass index, height, weight, waist-to-hip ratio, and waist and hip circumference. A generally obese (PC1) and a tall, centrally obese (PC3) body shape were both positively associated with CRC risk in observational analyses in 329,828 UK Biobank participants (3728 cases). In genome-wide association studies in 460,198 UK Biobank participants, we identified 3414 genetic variants across four body shapes and Mendelian randomization analyses confirmed positive associations of PC1 and PC3 with CRC risk (52,77

  • Principled distillation of UK Biobank phenotype data reveals underlying structure in human variation - Nature human behaviour (2024) · Carey CE, Shafee R, Wedow R, Elliott A, Palmer DS, Compitello J, Kanai M, Abbott L, Schultz P, Karczewski KJ, Bryant SC, Cusick CM, Churchhouse C, Howrigan DP, King D, Davey Smith G, Neale BM, Walters RK, Robinson EB · PubMed 38965376

    ABSTRACT: Data within biobanks capture broad yet detailed indices of human variation, but biobank-wide insights can be difficult to extract due to complexity and scale. Here, using large-scale factor analysis, we distill hundreds of variables (diagnoses, assessments and survey items) into 35 latent constructs, using data from unrelated individuals with predominantly estimated European genetic ancestry in UK Biobank. These factors recapitulate known disease classifications, disentangle elements of socioeconomic status, highlight the relevance of psychiatric constructs to health and improve measurement of pro-health behaviours. We go on to demonstrate the power of this approach to clarify genetic signal, enhance discovery and identify associations between underlying phenotypic structure and

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