Expressive

rs12139120 - COL11A1

Magnitude 2.2 · 2 studies on file

Reported associations

  • Translational genomics of osteoarthritis in 1,962,069 individuals - Unknown journal (n.d.) · Unknown authors · PubMed 40205036

    ABSTRACT: Osteoarthritis is the third most rapidly growing health condition associated with disability, after dementia and diabetes. By 2050, the total number of patients with osteoarthritis is estimated to reach 1 billion worldwide. As no disease-modifying treatments exist for osteoarthritis, a better understanding of disease aetiopathology is urgently needed. Here we perform a genome-wide association study meta-analyses across up to 489,975 cases and 1,472,094 controls, establishing 962 independent associations, 513 of which have not been previously reported. Using single-cell multiomics data, we identify signal enrichment in embryonic skeletal development pathways. We integrate orthogonal lines of evidence, including transcriptome, proteome and epigenome profiles of primary joint tiss

  • GWAS of allometric body-shape indices in UK Biobank identifies loci suggesting associations with morphogenesis, organogenesis, adrenal cell renewal and cancer - Unknown journal (n.d.) · Unknown authors · PubMed 34021172

    ABSTRACT: Genetic studies have examined body-shape measures adjusted for body mass index (BMI), while allometric indices are additionally adjusted for height. We performed the first genome-wide association study of A Body Shape Index (ABSI), Hip Index (HI) and the new Waist-to-Hip Index and compared these with traditional indices, using data from the UK Biobank Resource for 219,872 women and 186,825 men with white British ancestry and Bayesian linear mixed-models (BOLT-LMM). One to two thirds of the loci identified for allometric body-shape indices were novel. Most prominent was rs72959041 variant in RSPO3 gene, expressed in visceral adipose tissue and regulating adrenal cell renewal. Highly ranked were genes related to morphogenesis and organogenesis, previously additionally linked to can

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