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    Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

    Boer, Cindy G, Hatzikotoulas, Konstantinos, Southam, Lorraine, Stefánsdóttir, Lilja, Zhang, Yanfei, Coutinho de Almeida, Rodrigo, Wu, Tian T, Zheng, Jie, Hartley, April, Teder-Laving, Maris, Skogholt, Anne Heidi, Terao, Chikashi, Zengini, Eleni, Alexiadis, George, Barysenka, Andrei, Bjornsdottir, Gyda, Gabrielsen, Maiken E, Gilly, Arthur, Ingvarsson, Thorvaldur, Johnsen, Marianne B, Jonsson, Helgi, Kloppenburg, Margreet, Luetge, Almut, Lund, Sigrun H, Mägi, Reedik, Mangino, Massimo, Nelissen, Rob RGHH, Shivakumar, Manu, Steinberg, Julia, Takuwa, Hiroshi, Thomas, Laurent F, Tuerlings, Margo, Babis, George C, Cheung, Jason Pui Yin, Kang, Jae Hee, Kraft, Peter, Lietman, Steven A, Samartzis, Dino, Slagboom, P Eline, Stefansson, Kari, Thorsteinsdottir, Unnur, Tobias, Jonathan H, Uitterlinden, André G, Winsvold, Bendik, Zwart, John-Anker, Davey Smith, George, Sham, Pak Chung, Thorleifsson, Gudmar, Gaunt, Tom R, Morris, Andrew P, Valdes, Ana M, Tsezou, Aspasia, Cheah, Kathryn SE, Ikegawa, Shiro, Hveem, Kristian, Esko, Tõnu, Wilkinson, J Mark, Meulenbelt, Ingrid, Lee, Ming Ta Michael, van Meurs, Joyce BJ, Styrkársdóttir, Unnur, Zeggini, Eleftheria, Loughlin, John, Arden, Nigel, Birrell, Fraser, Carr, Andrew, Deloukas, Panos, Doherty, Michael, McCaskie, Andrew W, Ollier, William ER ORCID logoORCID: https://orcid.org/0000-0001-6502-6584, Rai, Ashok, Ralston, Stuart H, Spector, Tim D, Wallis, Gillian A, Martinsen, Amy E, Willer, Cristen, Fors, Egil Andreas, Mundal, Ingunn, Hagen, Knut, Nilsen, Kristian Bernhard, Lie, Marie Udnesseter, Børte, Sigrid, Brumpton, Ben, Nielsen, Jonas Bille, Fritsche, Lars G, Zhou, Wei, Heuch, Ingrid, Storheim, Kjersti, Tyrpenou, Evangelos, Koukakis, Athanasios, Chytas, Dimitrios, Evangelopoulos, Dimitrios Stergios, Efstathios, Chronopoulos, Pneumaticos, Spiros, Nikolaou, Vasileios S, Malizos, Konstantinos, Anastasopoulou, Lydia, Abecasis, Goncalo, Baras, Aris, Cantor, Michael, Coppola, Giovanni, Deubler, Andrew, Economides, Aris, Lotta, Luca A, Overton, John D, Reid, Jeffrey G, Shuldiner, Alan, Karalis, Katia, Siminovitch, Katherine, Beechert, Christina, Forsythe, Caitlin, Fuller, Erin D, Gu, Zhenhua, Lattari, Michael, Lopez, Alexander, Schleicher, Thomas D, Padilla, Maria Sotiropoulos, Widom, Louis, Wolf, Sarah E, Pradhan, Manasi, Manoochehri, Kia, Bai, Xiaodong, Balasubramanian, Suganthi, Boutkov, Boris, Eom, Gisu, Habegger, Lukas, Hawes, Alicia, Krasheninina, Olga, Lanche, Rouel, Mansfield, Adam J, Maxwell, Evan K, Nafde, Mona, O’Keeffe, Sean, Orelus, Max, Panea, Razvan, Polanco, Tommy, Rasool, Ayesha, Salerno, William, Staples, Jeffrey C, Li, Dadong, Sharma, Deepika, Banerjee, Ilanjana, Bovijn, Jonas, Locke, Adam, Verweij, Niek, Haas, Mary, Hindy, George, De, Tanima, Akbari, Parsa, Sosina, Olukayode, Ferreira, Manuel AR, Jones, Marcus B, Mighty, Jason, LeBlanc, Michelle G and Mitnaul, Lyndon J (2021) Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations. Cell, 184 (18). 4784-4818.e17. ISSN 0092-8674

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    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.

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