Nature CommunicationsGeneticsPeer-reviewed journal article
Accelerating functional gene discovery in osteoarthritis
Natalie C. ButterfieldiD, Katherine F. Curry, Julia SteinbergiD, Hannah F. DewhurstiD, Davide S. K. Komla-EbriiD, Naila S. Mannan, Anne‐Tounsia Adoum, Victoria D. LeitchiD, John G. LoganiD, Julian A. WaungiD, Elena J. GhirardelloiD, Lorraine SouthamiD, Scott E. YoulteniD, Jeremy Mark WilkinsoniD, Elizabeth A. McAninchiD, Valerie E. VancollieiD, Fiona L. Kussy, Jacqueline K. WhiteiD, Christopher J. LelliottiD, David J. AdamsiD, Richard JacquesiD, Antonio Carlos BiancoiD, ALAN BOYDEiD, Eleftheria ZegginiiD, Peter Ian CroucheriD, , J. H. Duncan BassettiD
Abstract
Osteoarthritis causes debilitating pain and disability, resulting in a huge socioeconomic burden, yet no drugs are available that prevent disease onset or progression. Here, we develop, validate and use rapid-throughput imaging techniques to identify abnormal joint phenotypes in unselected mutant mice generated by the International Knockout Mouse Consortium. We identify 14 genes with functional involvement in osteoarthritis pathogenesis, including the homeobox gene Pitx1, and functionally characterize 6 candidate human osteoarthritis genes in mouse models. We demonstrate sensitivity of the methods by identifying age-related degenerative joint damage in wild-type mice. Finally, we generate mutant mice with an osteoarthritis-associated polymorphism in the Dio2 gene by Crispr/Cas9 genome editing and demonstrate a protective role in disease onset with public health implications. This expanding resource of unselected mutant mice will transform the field by accelerating functional gene discovery in osteoarthritis and offering unanticipated drug discovery opportunities for this common and incapacitating chronic disease.
- Citations
- 61
- FWCI
- 8.09
- Field percentile
- top 1%
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