SummaryOsteoarthritis (OA) is the most common musculoskeletal disorder, affecting more than 240 million people worldwide. It imposes a substantial burden on individuals, healthcare systems, and economies, and its prevalence is expected to rise further with ageing populations and increasing obesity rates—two major risk factors. We request access to musculoskeletal related questionnaire and survey data as well as the genetic data when they become available. Using predefined inclusion and exclusion criteria, we will identify individuals with OA and an appropriately matched control group and perform a genome-wide association study (GWAS) to try to understand the inherited predisposition to disease, the relevant biological pathways involved and build predictive risk scores. This work will contribute to the global Genetics of Osteoarthritis (GO) Consortium (https://www.genetics-osteoarthritis.com/), which we lead. The consortium recently published the largest OA GWAS to date, involving ~2 million individuals (Hatzikotoulas K. et al., Nature, PMID: 40205036). Inclusion of NAKO’s well-characterised cohort will strengthen both the diversity and statistical power of this global effort, ensuring more robust insights into OA risk and biology. The longitudinal nature of NAKO will increase our ability to track progression of disease and improve early diagnosis.

Keywords GWAS Genetik Muskuloskelettale-Erkrankungen Osteoarthritis Polygenic-risk-score Predictive-risk-modeling chronic-pain disease-heterogeneity disease-stratification disease-trajectories multi-omics

InstitutionsHelmholtz Munich, Helmholtz Zentrum München GmbH, Helmholtz Zentrum Munich, Helmholtz Zentrum München