Browse/search for people

Publication - Dr Valeriia Haberland

    Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank data

    Citation

    Tachmazidou, I, Hatzikotoulas, K, Southam, L, Esparza-Gordillo, J, Haberland, V, Zheng, J, Johnson, T, Koprulu, M, Zengini, E, Steinberg, J, Wilkinson, JM, Bhatnagar, S, Hoffman, JD, Buchan, N, Süveges, D, Yerges-Armstrong, L, Smith, GD, Gaunt, TR, Scott, RA, McCarthy, LC, Zeggini, E & , 2019, ‘Identification of new therapeutic targets for osteoarthritis through genome-wide analyses of UK Biobank data’. Nature Genetics, vol 51., pp. 230-236

    Abstract

    Osteoarthritis is the most common musculoskeletal disease and the leading cause of disability globally. Here, we performed a genome-wide association study for osteoarthritis (77,052 cases and 378,169 controls), analyzing four phenotypes: knee osteoarthritis, hip osteoarthritis, knee and/or hip osteoarthritis, and any osteoarthritis. We discovered 64 signals, 52 of them novel, more than doubling the number of established disease loci. Six signals fine-mapped to a single variant. We identified putative effector genes by integrating expression quantitative trait loci (eQTL) colocalization, fine-mapping, and human rare-disease, animal-model, and osteoarthritis tissue expression data. We found enrichment for genes underlying monogenic forms of bone development diseases, and for the collagen formation and extracellular matrix organization biological pathways. Ten of the likely effector genes, including TGFB1 (transforming growth factor beta 1), FGF18 (fibroblast growth factor 18), CTSK (cathepsin K), and IL11 (interleukin 11), have therapeutics approved or in clinical trials, with mechanisms of action supportive of evaluation for efficacy in osteoarthritis.

    Full details in the University publications repository