Elucidating the Causal Impact of Dietary Factors on Rheumatoid Arthritis: Insights From Multivariable Mendelian Randomization Analysis

Rheumatoid arthritis (RA) is a common chronic autoimmune disorder with an incompletely elucidated pathogenesis. Emerging research indicates that dietary factors may significantly influence the onset and progression of RA. Nevertheless, the causal relationship between dietary habits and RA remains ambiguous. This investigation employed a multivariable Mendelian randomization (MVMR) methodology to rigorously assess the potential causal effects of various dietary factors on RA risk. This study utilized genome-wide association study (GWAS) summary-level data, encompassing dietary preferences ( = 113,425-159,579), and RA data ( = 302,614) from the most recent FinnGen database. The primary causal analysis was conducted using inverse-variance weighting (IVW), complemented by MR-Egger, weighted median, Bayesian weighted Mendelian randomization, and Robust Adjusted Profile Score (RAPS) methodologies. Sensitivity analyses incorporated Cochran's test, MR-Egger intercept test, MR-PRESSO, and leave-one-out analysis. Steiger tests were employed to evaluate the identified dietary preferences. MVMR was utilized to assess the direct impact of dietary factors on RA. The study identified significant associations between RA and nine dietary preferences: F-lentils/beans liking (Fle), chips liking (Chips), coffee difference liking (CD), coffee with sugar liking (CWS), milk chocolate liking (MC), coriander liking (Coriander), pollock liking (Pollock), soft cheese liking (SC), and blue cheese liking (BC). The MVMR analysis indicated that genetically predicted coriander and MC have a direct impact on RA, independent of other dietary factors. This study presents novel causal evidence suggesting that dietary preferences may impact the risk of RA. Specifically, a reduction in the consumption of milk chocolate and coriander may contribute to the prevention and alleviation of RA. However, additional research is required to elucidate the underlying mechanisms and to validate these findings across diverse populations.