Translational genomics of osteoarthritis in 1,962,069 individuals

作者信息Konstantinos Hatzikotoulas, Lorraine Southam, Lilja Stefansdottir, Cindy G Boer, Merry-Lynn McDonald, J Patrick Pett, Young-Chan Park, Margo Tuerlings, Rick Mulders, Andrei Barysenka, Ana Luiza Arruda, Vinicius Tragante, Alison Rocco, Norbert Bittner, Shibo Chen, Susanne Horn, Vinodh Srinivasasainagendra, Ken To, Georgia Katsoula, Peter Kreitmaier, Amabel M M Tenghe, Arthur Gilly, Liubov Arbeeva, Lane G Chen, Agathe M de Pins, Daniel Dochtermann, Cecilie Henkel, Jonas Höijer, Shuji Ito, Penelope A Lind, Bitota Lukusa-Sawalena, Aye Ko Ko Minn, Marina Mola-Caminal, Akira Narita, Chelsea Nguyen, Ene Reimann, Micah D Silberstein, Anne-Heidi Skogholt, Hemant K Tiwari, Michelle S Yau, Ming Yue, Wei Zhao, Jin J Zhou, George Alexiadis, Karina Banasik, Søren Brunak, Archie Campbell, Jackson T S Cheung, Joseph Dowsett, Tariq Faquih, Jessica D Faul, Lijiang Fei, Anne Marie Fenstad, Takamitsu Funayama, Maiken E Gabrielsen, Chinatsu Gocho, Kirill Gromov, Thomas Hansen, Georgi Hudjashov, Thorvaldur Ingvarsson, Jessica S Johnson, Helgi Jonsson, Saori Kakehi, Juh
PMID40205036
期刊Nature
发布时间2025-05
DOI10.1038/s41586-025-08771-z

摘要

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.

实验方法