Mendelian randomization to evaluate the causal relationship between household income status and the risk of knee osteoarthritis

Abstract Objective To explore the causal relationship between household income status and knee osteoarthritis (KOA) risk using a two-sample Mendelian randomization (MR) approach. Methods In order to assess the causal relationship between household income status and knee osteoarthritis (KOA), we utilized the Genome-wide association studies (GWAS) data. Our selection process involved identifying the single nucleotide polymorphisms (SNPs) as instrumental variables (IVs). Among these SNPs, we specifically chose the significant ones for the MR analysis. To determine the causal relationship, we employed three methods of MR analysis, namely inverse variance weighted (IVW), weighted median (WM), and MR-Egger regression. This analysis allowed us to calculate Odds Ratios (OR) for the relationship between household income status and KOA. Additionally, we also conducted heterogeneity and pleiotropy analyses to further validate the MR results. Results Higher household income tended to reduce the risk of knee osteoarthritis (OR: 0.71, 95% CI: 0.60 to 0.85, p < 0.001), while reverse MR studies showed no causal association between knee osteoarthritis and household income status. The intercept of MR-Egger regression was 0.014 (P = 0.1), indicating that the causal estimation results were unaffected by pleiotropy. Conclusion The findings showed that individuals with higher household incomes had a decreased risk of knee osteoarthritis.