The Causal Relationship Between Genetically Determined Plasma Metabolites and Rheumatoid Arthritis

Abstract

Background

Presently, research examining the impact of plasma metabolites on rheumatoid arthritis (RA) is scarce. We utilized a bidirectional two-sample Mendelian randomization (MR) analysis to explore the potential causal link between 1400 plasma metabolites and RA.

Methods

We performed a two-sample MR analysis to assess the causal association between 1400 plasma metabolites and RA. The primary method of two-sample MR Analysis was the Inverse Variance Weighted (IVW) model, and the secondary methods were the Weighted Median (WM) and MR Egger methods. We conducted sensitivity analyses using Cochran's Q test, MR-Egger intercept test, MR-PRESSO, and Leave-One-Out analyses. Steiger test was used for validation of the metabolites. The main results were validated in the UK Biobank.

Results

In the discovery dataset, 60 metabolites were identified as significantly associated with the onset of RA. A notable finding was the strong correlation between Valve levels and RA risk, showing the highest positive correlation (OR [95% CI]: 1.361 (1.112, 1.667), p = 0.0028). Subsequent analysis of the validation dataset revealed 46 metabolites linked to RA, with X-22771 levels displaying the strongest positive association (OR [95% CI]: 1.002 (1.00, 1.004), p = 0.037). Notably, Glycohydrocolate levels exhibited a protective effect on RA in both datasets. Specifically, the effect size in the initial dataset was (OR [95% CI]:0.867 (0.753, 1.000), p = 0.050), whereas in the validation dataset, the effect was weaker (OR [95% CI]: 0.999 (0.997, 1.000), p = 0.048). These findings were further validated through a series of sensitivity analyses, affirming their robustness and reliability.

Conclusions

This study highlights a strong correlation between elevated Valine levels and an increased risk of RA, as well as potential protective effects of Glycohydrohorate in independent datasets.