Summary
This large-scale translational genomics study integrated GWAS data from nearly 2 million participants to establish 962 genetic associations with osteoarthritis, identifying 513 previously unreported loci. By incorporating single-cell multiomics and multi-omics profiles of joint tissues, the research implicated 700 effector genes and converged on eight biological processes, including circadian regulation and multiple developmental signalling pathways. The findings suggest that rare coding variants have stronger effects than common variants and identify potential drug-repurposing candidates, offering translational pathways toward disease-modifying treatments for this rapidly growing health burden.
Regional applicability
These genomic findings are relevant to the United Kingdom's biomedical research infrastructure and NHS clinical practice, as osteoarthritis affects a substantial proportion of the UK population. The identification of drug-repurposing targets and biological pathways may inform future therapeutic development and personalised medicine approaches applicable to UK patient populations.
Key measures
Genome-wide association study signals; transcriptome, proteome and epigenome profiles of primary joint tissues; rare coding-variant burden associations; drug-repurposing opportunities (10% of effector genes targeted by approved drugs)
Outcomes reported
The study identified 962 independent genetic associations with osteoarthritis across nearly 2 million individuals, of which 513 were novel. The research implicated 700 effector genes and highlighted eight biological processes involved in disease pathogenesis, including circadian clock regulation, glial-cell processes, and multiple signalling pathways.
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