Background Although previous metabolomics studies have identified metabolic alterations in ankylosing spondylitis (AS), the causal relationship between circulating serum metabolites and disease risk remains unclear. To address this knowledge gap, we aimed to investigate these causal associations using a two-sample Mendelian randomization approach. Objective To investigate the causal effects of serum metabolites on the risk of ankylosing spondylitis. Methods Inverse variance weighting (IVW) and Wald ratio tests were adopted to assess causal associations between 1,400 serum metabolites and AS risk. We performed FDR correction for multiple testing and a comprehensive suite of complementary MR robustness analyses, including weighted median regression, MR-Egger regression, MR-PRESSO outlier correction and Cochran’s Q heterogeneity test to evaluate pleiotropy and result stability. Metabolic pathway enrichment analysis was conducted on all FDR-significant metabolites. Results In the discovery analysis, 89 metabolites were associated with the risk of AS, including 15 metabolite ratios and 74 individual metabolites. External validation confirmed directionally consistent associations for 20 metabolites. Among lipid metabolites, 2-aminoheptanoate showed the strongest protective association with ankylosing spondylitis risk (OR = 0.399, 95% CI: 0.210–0.760), whereas 3-carboxy-4-methyl-5-propyl-2-furanpropanoate showed the strongest risk association (OR = 2.071, 95% CI: 1.257–3.414). Among the xenobiotics, 4-allylphenol sulfate was positively associated with ankylosing spondylitis risk (OR = 1.856, 95% CI: 1.112–3.098), whereas hippurate showed a protective association (OR = 0.342, 95% CI: 0.176–0.663). Pathway enrichment analyses highlighted porphyrin metabolism, phenylalanine metabolism, tryptophan-related biosynthesis, and carbohydrate metabolism. Conclusion This Mendelian randomization study suggests that several serum metabolites may be causally associated with the risk of developing ankylosing spondylitis. These findings provide potential metabolic biomarkers and mechanistic clues for future studies, although experimental and prospective clinical validation is still required before clinical application.
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Li et al. (2026) studied this question.
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