Global burden and genetic pathways of knee osteoarthritis: An integrated analysis of GBD data, Mendelian randomization, and multi-omics approaches

Osteoarthritis is one of the leading causes of chronic pain and disability among adults, and it poses a significant global public health burden. This study aimed to analyze global trends in the incidence, prevalence and disability-adjusted life years (DALYs) of knee osteoarthritis (KOA) across countries/regions using data from the Global Burden of Disease (GBD) database. To further explore the underlying factors, we combined Socio-demographic Index (SDI) index with decomposition analysis, frontier analysis and health inequality assessment. We also investigated potential genetic contributors to KOA by integrating disease risk factors from the GBD database with obesity related gene expression datasets from the GEO database to identify key genes. The intersection of differentially expressed genes with those from expression quantitative trait loci analysis was further refined using least absolute shrinkage and selection operator regression to identify characteristic genes most strongly associated with KOA risk factors. Finally, mediation analysis was conducted to establish potential causal pathways linking genes, risk factors, and KOA. Our findings indicate that the global burden of KOA is continuing to increase across most regions. Notably, the SVBP gene appears to promote disease progression, potentially through pathways associated with body mass index (BMI). These findings highlight the importance of addressing modifiable risk factors, such as BMI, and provide new insights into the genetic mechanisms underlying KOA.