Application of Mendelian randomization in thyroid diseases: a review

Front Endocrinol (Lausanne). 2024 Dec 19:15:1472009. doi: 10.3389/fendo.2024.1472009. eCollection 2024.

Abstract

Thyroid diseases are increasingly prevalent, posing significant challenges to patients' quality of life and placing substantial financial burdens on families and society. Despite these impacts, the underlying pathophysiology of many thyroid conditions remains poorly understood, complicating efforts in treatment, management, and prevention. Observational studies can identify associations between exposure variables and disease; however, they often struggle to account for confounding factors and reverse causation. Understanding disease occurrence, epidemiological trends, and clinical diagnosis, prevention, and treatment relies heavily on robust etiological research. Mendelian randomization, a method grounded in genetics and epidemiology, has been widely employed in studying the etiology of thyroid diseases, offering a solution to some of these challenges. This paper categorizes thyroid diseases into thyroid dysfunction and thyroid cancer, reviewing related Mendelian randomization studies. It further provides novel perspectives and approaches for investigating the mechanisms underlying thyroid diseases and designing intervention strategies.

Keywords: Mendelian randomization; casual relationship; etiological research; risk factors; thyroid diseases.

Publication types

  • Review

MeSH terms

  • Genetic Predisposition to Disease
  • Humans
  • Mendelian Randomization Analysis*
  • Thyroid Diseases* / epidemiology
  • Thyroid Diseases* / genetics
  • Thyroid Neoplasms / epidemiology
  • Thyroid Neoplasms / genetics

Grants and funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This work was supported by the National Key R&D Program–Animal Experiment and Clinical Trial of Minimally Invasive Thyroid Tumor Surgery Robot (2019YFC0119200), the Shandong Provincial Natural Science Foundation General Project (ZR2021MH328), and the Dongying Natural Science Foundation Project (2023ZR030).