Exploring blood metabolites and thyroid disorders: a bidirectional mendelian randomization study - Zhang, Xuan; Zhou, Jiating; Xie, Zilan; Li, Xi; Hu, Jiaqing; He, Hengzheng; Li, Zhi (Frontiers in Endocrinology, 2023)
Background Human blood metabolites have demonstrated close associations with thyroid disorders in observational studies. However, it’s essential to determine whether these correlations imply causation. Mendelian Randomization (MR) offers a promising approach to investigate these patterns. Aims The primary aim of our investigation is to establish causality between blood metabolites and three thyroid disorders: TC, GD, and HT. Methods We employed a two-sample bidirectional MR analysis approach to assess the relationships between 452 blood metabolites and the three aforementioned thyroid disorders. Causal links were estimated using the IVW method, with sensitivity analyses conducted via MR-Egger, Weighted Median, and MR-PRESSO. We assessed potential heterogeneity and pleiotropy using MR-Egger intercept and Cochran’s Q statistic. Additionally, we conducted pathway analysis to identify potential metabolic pathways. Results We found 46 metabolites that showed suggestive associations with thyroid disease risk, especially Aspartate (ORIVW=7.41; 95%CI: 1.51-36.27; PIVW=0.013) and C-glycosyltryptophan (ORIVW=0.04; 95%CI: 0.00–0.29; PIVW=0.001) impacted TC, Kynurenine (ORIVW=2.69; 95%CI: 1.08–6.66; PIVW=0.032) and 4-androsten-3beta,17beta-diol disulfate 2 (ORIVW=0.78; 95%CI: 0.48–0.91; PIVW=0.024) significantly impacted GD, and Alpha-ketoglutarate (ORIVW=46.89; 95%CI: 4.65–473.28; PIVW=0.001) and X-14189–leucylalanine (ORIVW=0.31; 95%CI: 0.15–0.64 PIVW=0.001) significantly impacted HT. We also detected 23 metabolites influenced by TC and GD. Multiple metabolic pathways have been found to be involved in thyroid disease. Conclusion Our MR findings suggest that the identified metabolites and pathways can serve as biomarkers for clinical thyroid disorder screening and prevention, while also providing new insights for future mechanistic exploration and drug target selection.