Decoding the genomic basis of osteoarthritis
Julia SteinbergiD, Lorraine SouthamiD, Natalie C. ButterfieldiD, Theodoros I. RoumeliotisiD, Andreas FontalisiD, Matthew J. R. ClarkiD, Raveen L. JayasuriyaiD, Diane Swift, Karan Mehul ShahiD, Katherine F. Curry, Roger A. Brooks, Andrew W. McCaskieiD, Christopher J. LelliottiD, Jyoti Sharma ChoudharyiD, J. H. Duncan BassettiD, Graham Richard WilliamsiD, Jeremy Mark WilkinsoniD, Eleftheria ZegginiiD
Abstract
Osteoarthritis causes pain and functional disability for a quarter of a billion people worldwide, with no disease-stratifying tools nor modifying therapy. Here, we use primary cartilage and synovium from osteoarthritis patients to construct a molecular quantitative trait locus map of gene expression and protein abundance. By integrating data across omics levels, we identify likely effector genes for osteoarthritis-associated genetic signals. We detect pronounced molecular differences between macroscopically intact and highly degenerated cartilage. We identify molecularly-defined patient subgroups that correlate with clinical characteristics, stratifying patients on the basis of their molecular profile. We construct and validate a 7-gene classifier that reproducibly distinguishes between these disease subtypes, and identify potentially actionable compounds for disease modification and drug repurposing.
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