4.8 Article

Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations

Journal

CELL
Volume 184, Issue 18, Pages 4784-+

Publisher

CELL PRESS
DOI: 10.1016/j.cell.2021.07.038

Keywords

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Funding

  1. UK Biobank Resource [9979, 23359]
  2. Medical Research Council Integrative Epidemiology Unit at the University of Bristol [MC_UU_00011/14]
  3. NIHR Nottingham BRC
  4. University of Bristol
  5. UK Medical Research Council Integrative Epidemiology Unit [MC_UU_00011/4]
  6. MRC [MC_UU_00011/4] Funding Source: UKRI

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The study identified risk variants for osteoarthritis through a genome-wide association study, revealing genetic effects related to factors such as sex, age, and weight-bearing joints. By integrating functional genomics data from patient tissues, high-confidence effector genes were confirmed, and likely causal genes linked to neuronal processes were identified.
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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