Genome-wide analyses using UK Biobank data provide insights into the genetic architecture of osteoarthritis

Eleni Zengini, Konstantinos Hatzikotoulas, Ioanna Tachmazidou, Julia Steinberg, Fernando P. Hartwig, Lorraine Southam, Sophie Hackinger, Cindy G. Boer, Unnur Styrkarsdottir, Arthur Gilly, Daniel Suveges, Britt Killian, Thorvaldur Ingvarsson, Helgi Jonsson, George C. Babis, Andrew McCaskie, Andre G. Uitterlinden, Joyce B.J. Van Meurs, Unnur Thorsteinsdottir, Kari StefanssonGeorge Davey Smith, Jeremy M. Wilkinson, Eleftheria Zeggini*

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

72 Citations (Scopus)
364 Downloads (Pure)

Abstract

Osteoarthritis is a common complex disease imposing a large public-health burden. Here, we performed a genome-wide association study for osteoarthritis, using data across 16.5 million variants from the UK Biobank resource. After performing replication and meta-analysis in up to 30,727 cases and 297,191 controls, we identified nine new osteoarthritis loci, in all of which the most likely causal variant was noncoding. For three loci, we detected association with biologically relevant radiographic endophenotypes, and in five signals we identified genes that were differentially expressed in degraded compared with intact articular cartilage from patients with osteoarthritis. We established causal effects on osteoarthritis for higher body mass index but not for triglyceride levels or genetic predisposition to type 2 diabetes.

Original languageEnglish
Pages (from-to)549-558
Number of pages10
JournalNature Genetics
Volume50
Issue number4
Early online date20 Mar 2018
DOIs
Publication statusPublished - 1 Apr 2018

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