Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
Institute of Clinical Pharmacology, Central South University, Changsha, Hunan, China.
Front Endocrinol (Lausanne). 2023 Oct 9;14:1270336. doi: 10.3389/fendo.2023.1270336. eCollection 2023.
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.
The primary aim of our investigation is to establish causality between blood metabolites and three thyroid disorders: TC, GD, and HT.
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.
We found 46 metabolites that showed suggestive associations with thyroid disease risk, especially Aspartate (OR=7.41; 95%CI: 1.51-36.27; P=0.013) and C-glycosyltryptophan (OR=0.04; 95%CI: 0.00-0.29; P=0.001) impacted TC, Kynurenine (OR=2.69; 95%CI: 1.08-6.66; P=0.032) and 4-androsten-3beta,17beta-diol disulfate 2 (OR=0.78; 95%CI: 0.48-0.91; P=0.024) significantly impacted GD, and Alpha-ketoglutarate (OR=46.89; 95%CI: 4.65-473.28; P=0.001) and X-14189-leucylalanine (OR=0.31; 95%CI: 0.15-0.64 P=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.
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.
在观察性研究中，人体血液代谢物与甲状腺疾病之间存在密切关联。然而，确定这些相关性是否意味着因果关系至关重要。孟德尔随机化（Mendelian Randomization，MR）为研究这些模式提供了一种很有前途的方法。
我们研究的主要目的是确定血液代谢物与三种甲状腺疾病（TC、GD 和 HT）之间的因果关系。
我们采用两样本双向 MR 分析方法，评估 452 种血液代谢物与上述三种甲状腺疾病之间的关系。使用 IVW 方法估计因果关系，通过 MR-Egger、加权中位数和 MR-PRESSO 进行敏感性分析。我们使用 MR-Egger 截距和 Cochran's Q 统计量评估潜在的异质性和多效性。此外，我们还进行了途径分析，以确定潜在的代谢途径。
我们发现 46 种代谢物与甲状腺疾病风险呈显著相关性，尤其是天冬氨酸（OR=7.41；95%CI：1.51-36.27；P=0.013）和 C-糖基色氨酸（OR=0.04；95%CI：0.00-0.29；P=0.001）对 TC 有影响，犬尿氨酸（OR=2.69；95%CI：1.08-6.66；P=0.032）和 4-雄烯-3β,17β-二醇二硫酸盐 2（OR=0.78；95%CI：0.48-0.91；P=0.024）对 GD 有影响，α-酮戊二酸（OR=46.89；95%CI：4.65-473.28；P=0.001）和 X-14189-亮氨酸丙氨酸（OR=0.31；95%CI：0.15-0.64；P=0.001）对 HT 有影响。我们还检测到 23 种代谢物受 TC 和 GD 影响。多个代谢途径已被发现与甲状腺疾病有关。
我们的 MR 研究结果表明，所确定的代谢物和途径可以作为临床甲状腺疾病筛查和预防的生物标志物，并为未来的机制探索和药物靶点选择提供新的见解。
