Oxidative Balance Score and Osteoarthritis: A Multi-Omics Study Based on NHANES, RNA-seq, and Mendelian Randomization

This study employs a multi-omics approach to investigate the association between the Oxidative Balance Score (OBS) and Osteoarthritis (OA), aiming to uncover molecular mechanisms and identify therapeutic targets. Analyzing baseline characteristics of 42,883 participants from the NHANES dataset, the study reveals that the OA group has a significantly lower OBS than the non-OA group (16.03{+/-}8.60 vs. 17.57{+/-}9.27, p<0.001), with notable differences in age, gender, race, and socioeconomic status. Multivariate logistic regression indicates an inverse relationship between OBS and OA risk (OR = 0.99, 95% CI: 0.99 - 1.00, p = 0.007), while Restricted Cubic Spline analysis shows a nonlinear association, with a more pronounced decline in OR when OBS exceeds 17.37. RNA-seq technology identifies 2,304 differentially expressed genes (946 upregulated, 1,358 downregulated) between OA patients and controls, and Mendelian Randomization analysis, supported by sensitivity tests, highlights PTGS2 and NR4A2 as protective factors and HFE as a risk factor for OA, findings further validated by expression data. The study concludes that oxidative stress is significantly linked to OA risk, with higher OBS potentially offering protective effects, and identifies PTGS2, NR4A2, and HFE as promising intervention targets, providing new directions for OAs mechanistic research and precision treatment.