Association between breast cancer and thyroid cancer risk: a two-sample Mendelian randomization study

Author:

Tan Hong,Wang Sisi,Huang Feifei,Tong Zhongyi

Abstract

BackgroundBreast and thyroid cancer are increasingly prevalent, but it remains unclear whether the observed associations are due to heightened medical surveillance or intrinsic etiological factors. Observational studies are vulnerable to residual confounding, reverse causality, and bias, which can compromise causal inference. In this study, we employed a two-sample Mendelian randomization (MR) analysis to establish a causal link between breast cancer and heightened thyroid cancer risk.MethodsWe obtained the single nucleotide polymorphisms (SNPs) associated with breast cancer from a genome-wide association study (GWAS) conducted by the Breast Cancer Association Consortium (BCAC). The FinnGen consortium’s latest and largest accessible GWAS thyroid cancer data at the summary level. We performed four MR analyses, including the inverse-variance-weighted (IVW), weighted median, MR-Egger regression, and weighted mode, to evaluate the potential causal connection between genetically predicted breast cancer and higher risk for thyroid cancer. Sensitivity analysis, heterogeneity and pleiotropy tests were used to ensure the reliability of our findings.ResultsOur study revealed causal relationship between genetically predicted breast cancer and thyroid cancer (IVW method, odds ratio (OR) = 1.135, 95% confidence interval (CI): 1.006 to 1.279, P = 0.038). However, there was no causal association between genetically predicted triple-negative breast cancer and thyroid cancer (OR = 0.817, 95% CI: 0.610 to 1.095, P = 0.177). There was no directional pleiotropy or horizontal pleiotropy in the present study.ConclusionThis two-sample MR study supports a causal link between ER-positive breast cancer and heightened the risk of thyroid cancer. Our analysis did not reveal a direct correlation between triple-negative breast cancer and thyroid cancer.

Publisher

Frontiers Media SA

Subject

Endocrinology, Diabetes and Metabolism

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