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Cell · 2021

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations.

СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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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 R G H H, Shivakumar Manu, Steinberg Julia, Takuwa Hiroshi, Thomas Laurent F, Tuerlings Margo, arcOGEN Consortium, HUNT All-In Pain, ARGO Consortium, Regeneron Genetics Center, 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 S E, Ikegawa Shiro, Hveem Kristian, Esko Tõnu, Wilkinson J Mark, Meulenbelt Ingrid, Lee Ming Ta Michael, van Meurs Joyce B J, Styrkársdóttir Unnur, Zeggini Eleftheria

Аннотация

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.

Предметные рубрики MeSH

FemaleGenetic Predisposition to DiseaseGenetics, PopulationGenome-Wide Association StudyHumansOsteoarthritisPhenotypePolymorphism, Single NucleotideRisk FactorsSex CharacteristicsSignal Transduction