A Genome-Wide Association Study (GWAS) meta-analysis of post-traumatic osteoarthritis of the knee (GO-PTOA): Protocol for Analysis Plan

Post Traumatic Osteoarthritis (PTOA) of the knee is osteoarthritis (OA) occurring specifically after a significant acute injury to the joint. Approximately 50% of people with significant knee joint injuries, such as anterior cruciate ligament (ACL) rupture, develop symptomatic radiographic OA within 10 years. Although impacts of the disease are well-described, there is little known about the genetic risk of developing OA after a knee injury relative to idiopathic OA. There is an unmet clinical need to understand the aetiology of PTOA, which will help us to understand, predict and prevent PTOA. In this Analysis Plan, we describe our methodological approach to performing a Genome Wide Association Study (GWAS) meta-analysis, developed by the Genetics of Osteoarthritis consortium (GO)-PTOA working group. We aim to determine if genetic variants associate with PTOA following a knee joint injury and understand whether these variants are similar to or different from those associated with idiopathic knee OA (iOA). Summary statistics from six international cohorts and biobanks will be included in the meta-analysis. We have harmonized an approach to identify cases of acute knee injury, knee PTOA cases as well as controls. Our three main objectives are to identify genetic variation associated with: O_LIknee PTOA independent of knee iOA C_LIO_LIknee PTOA compared with knee injured controls without OA C_LIO_LIknee PTOA compared with controls over 40 years of age without injury or OA Although not part of our primary analysis, we also plan to identify genetic variation associated with the onset of knee PTOA in a time-to-event analysis in the future. C_LI Where resources allow, sensitivity analyses for all aims will be carried out, adjusting for body mass index (BMI). For case-control analyses, either a logistic regression or linear mixed model (LMM) will be used. For later time-to-event analysis, a matched case-control Cox Proportion Hazards (PH) regression model will be applied. Cohorts will share their summary statistics with the central analysis site conducting the single meta-analysis for each GWAS, which is likely to be carried out in either METAL or GWAMA. Findings from this work will potentially improve our understanding of PTOA pathogenesis and aetiology. Better understanding of genetic determinants could contribute to more accurate prognostic modelling and precision medicine in the future.