DECIPHERING OSTEOARTHRITIS GENETICS ACROSS 826,690 INDIVIDUALS FROM 9 POPULATIONS

Cindy G. Boer, Konstantinos Hatzikotoulas, Lorraine Southam, Lilja Stefansdottir, Yanfei Zhang, Rodrigo Coutinho de Almeida, Tian T. wu, Jie Zhang, April E Hartley, Maris Teder-Laving, Anne Heidi Skogholt, Chikashi Terao, Eleni Zengini, George Alexiadis, Andrei Barysenka, Gyda Bjornsdottir, Maiken Gabrielsen, Arthur Gilly, Thorvaldur Ingvarsson, Marianne B. JohnsenHelgi Jonsson, Margreet Kloppenburg, Almut Luetge, Sigrun H. Lund, Reedik Mägi, Massimo Mangino, Rob Nelissen, Manu Shivakumar, Julia Steinberg, Hiroshi Takuwa, Laurent Thomas, Margo Tuerlings, George C Babis, Jason Pui Yin Cheung, Jae Hee Kang, Peter Kraft, Steven A. Lietman, Dino Samartzis, Eline Slagboom, Kari Stefansson, Unnur Thorsteinsdottir, Jonathan H Tobias, André G Uitterlinden, Bendik S Winsvold, John-Anker Zwart, George Davey Smith, Pak Chung Sham, Gudmar Thorleifsson, Tom R Gaunt, Andrew Morris, Ana M Valdes, Aspasia Tsezou, Kathryn S.E. Cheah, Shiro Ikegawa, Kristian Hveem, Tõnu Esko, J Mark Wilkinson, Ingrid Meulenbelt, Ming Ta Michael Lee, Joyce B.J. van Meurs, Unnur Styrkarsdottir, Eleftheria Zeggini*

*Corresponding author for this work

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

Abstract

Osteoarthritis affects over 300 million people worldwide. Here, we conduct a genome-wide association study meta-analysis across 826,690 individuals (177,517 with osteoarthritis), and identify 100 independently associated risk variants across 11 osteoarthritis phenotypes, 52 of which have not been associated with the disease before. We report thumb and spine osteoarthritis risk variants, and identify differences in genetic effects between weight bearing and non-weight bearing joints. We identify sex-specific and early age-at-onset osteoarthritis risk loci. We integrate functional genomics data from primary patient tissues (including articular cartilage, subchondral bone and osteophytic cartilage), and identify high-confidence effector genes. We provide evidence for genetic correlation with phenotypes related to pain, the main disease symptom, and identify likely causal genes linked to neuronal processes. Our results provide insights into key molecular players in disease processes and highlight attractive drug targets to accelerate translation.
Original languageEnglish
JournalCell
Publication statusAccepted/In press - 2 Aug 2021

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