Exploring blood metabolites and thyroid disorders: a bidirectional mendelian randomization study

Xuan Zhang; Jiating Zhou; Zilan Xie; Xi Li; Jiaqing Hu; Hengzheng He; Zhi Li

doi:10.3389/fendo.2023.1270336

Exploring blood metabolites and thyroid disorders: a bidirectional mendelian randomization study

Front Endocrinol (Lausanne). 2023 Oct 9:14:1270336. doi: 10.3389/fendo.2023.1270336. eCollection 2023.

Authors

Xuan Zhang^{1

2

3

4

5}, Jiating Zhou^{1

2

3

4}, Zilan Xie^{1

2

3

4}, Xi Li^{1

2

3

4}, Jiaqing Hu⁶, Hengzheng He⁵, Zhi Li^{1

2

3

4}

Affiliations

¹ Department of Clinical Pharmacology, Xiangya Hospital, Central South University, Changsha, Hunan, China.
² Institute of Clinical Pharmacology, Central South University, Changsha, Hunan, China.
³ Engineering Research Center of Applied Technology of Pharmacogenomics, Ministry of Education, Changsha, Hunan, China.
⁴ National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan, China.
⁵ Department of General Surgery, The Second People's Hospital of Hunan, Changsha, Hunan, China.
⁶ Department of Emergency Medicine, Trauma Center, The Second People's Hospital of Hunan, Changsha, Hunan, China.

Abstract

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 (OR_IVW=7.41; 95%CI: 1.51-36.27; P_IVW=0.013) and C-glycosyltryptophan (OR_IVW=0.04; 95%CI: 0.00-0.29; P_IVW=0.001) impacted TC, Kynurenine (OR_IVW=2.69; 95%CI: 1.08-6.66; P_IVW=0.032) and 4-androsten-3beta,17beta-diol disulfate 2 (OR_IVW=0.78; 95%CI: 0.48-0.91; P_IVW=0.024) significantly impacted GD, and Alpha-ketoglutarate (OR_IVW=46.89; 95%CI: 4.65-473.28; P_IVW=0.001) and X-14189-leucylalanine (OR_IVW=0.31; 95%CI: 0.15-0.64 P_IVW=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.

Keywords: Mendelian randomization; autoimmune thyroid disease; bidirectional; metabolites; thyroid cancer.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Aspartic Acid
Humans
Mendelian Randomization Analysis*
Thyroid Diseases* / epidemiology
Thyroid Diseases* / genetics

Substances

C-glycosyltryptophan
Aspartic Acid

Grants and funding

The authors declare financial support was received for the research, authorship, and/or publication of this article. This work was financially supported by the Natural Science Foundation of Hunan Province, China Grant [No. 2020JJ4888].