Hatzikotoulas, K. orcid.org/0000-0002-4699-3672, Southam, L., Stefansdottir, L. et al. (174 more authors) (2025) Translational genomics of osteoarthritis in 1,962,069 individuals. Nature. ISSN 0028-0836
Abstract
Osteoarthritis is the third most rapidly growing health condition associated with disability, after dementia and diabetes1. By 2050, the total number of patients with osteoarthritis is estimated to reach 1 billion worldwide2. 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 tissues, and implicate 700 effector genes. Within these, we find rare coding-variant burden associations with effect sizes that are consistently higher than common frequency variant associations. We highlight eight biological processes in which we find convergent involvement of multiple effector genes, including the circadian clock, glial-cell-related processes and pathways with an established role in osteoarthritis (TGFβ, FGF, WNT, BMP and retinoic acid signalling, and extracellular matrix organization). We find that 10% of the effector genes express a protein that is the target of approved drugs, offering repurposing opportunities, which can accelerate translation.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © The Author(s) 2025. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
Keywords: | arcOGEN Consortium; ARGO Consortium; DBDS Genomic Consortium; Estonian Biobank Research Team; FinnGen; Genes & Health Research Team; HUNT All-In Pain; Million Veteran Program; Regeneron Genetics Center |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Medicine, Dentistry and Health (Sheffield) > School of Medicine and Population Health |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 11 Apr 2025 15:31 |
Last Modified: | 11 Apr 2025 15:31 |
Status: | Published online |
Publisher: | Springer Science and Business Media LLC |
Refereed: | Yes |
Identification Number: | 10.1038/s41586-025-08771-z |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:225424 |