ArticleOrthopedic research and reviews2026
Protective Causal Effects of CCL19, CCL23, and IL17A on Achilles Tendinitis: Insights from Bidirectional Mendelian Randomization and Metabolite-Mediated Pathway Analysis.
Article in Orthopedic research and reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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8 authors.
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Abstract
Background: Achilles tendinitis (AT) is a prevalent musculoskeletal disorder with unclear etiology. This study aimed to investigate the causal relationships between circulating inflammatory cytokines (ICs), metabolites, and AT risk using bidirectional Mendelian randomization (MR), and to identify potential metabolite-mediated pathways. Methods: A bidirectional MR design was implemented, integrating genetic instruments for 91 ICs and 1400 metabolites with GWAS summary statistics from the FinnGen consortium. Causal inferences were drawn using inverse variance weighting (IVW), MR-Egger regression, and weighted median approaches, accompanied by sensitivity and mediated analyses. Results: CCL19, CCL23, and IL17A were identified as protective factors for AT, with CCL23 demonstrating consistent associations across multiple MR methods. 65 metabolite traits were significantly associated with disease risk. Glycochenodeoxycholate glucuronide showed a protective effect (P = 0.002), whereas the alpha-tocopherol to glycerol ratio increased risk (P = 0.011). Mediation analysis indicated six pathways: CCL19 - pantothenate - AT; CCL19 - Picolinate - AT; CCL19 - X-21845- AT; CCL23 - X-12822 - AT; CCL23 - X-18921 - AT; IL17A - cysteinylglycine disulfide - AT. Conclusion: This is the first MR study to systematically assess the causal roles of ICs and metabolites in AT, identifying CCL19, CCL23, and IL17A as protective factors and highlighting multiple metabolite signatures linked to disease risk, offering novel insights for mechanistic research and targeted intervention.
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