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Background <p>The results of observational studies on the causal relationship between metabolic syndrome (MetS) and thyroid cancer (TC) are controversial. This study aimed to explore the potential causal link between metabolic syndrome (MetS) and thyroid cancer (TC) by Mendelian randomization (MR) analysis. Additionally, the genetic correlation was evaluated using Linkage Disequilibrium Score Regression (LDSC). </p> Methods <p>In this study, we derived instrumental variables (IVs) linked to metabolic syndrome and its components from publicly accessible genome-wide association study (GWAS) databases. These IVs were then used in a MR with TC data from the Finnish population. The primary method of analysis was inverse variance weighted (IVW), supplemented by various sensitivity analyses to ensure the robustness and reliability of the findings. </p> Results <p>MR analysis identified a significant positive causal link between MetS and TC (OR = 1.7003, 95%CI = 1.2631–2.2888, <i>P</i> = 0.0005), while high-density lipoprotein cholesterol (HDL-C) exhibited a negative causal relationship (OR = 0.7868,95%CI = 0.6822–0.9076, <i>P</i> = 0.0010). Sensitivity tests showed no evidence of heterogeneity or horizontal pleiotropy. LDSC analyses did not detect significant genetic correlations between MetS and its components and TC.</p> Conclusions <p>Our results indicate that MetS substantially elevates the risk of TC, while HDL-C may have a protective effect against TC. These findings offer fresh perspectives on the potential causal link between MetS and TC.</p>

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Assessing the influence of metabolic syndrome on thyroid cancer: insights from a Mendelian randomization approach

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  • 发表日期：

    2025年6月10日

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  • Xiaosong Ru,
  • Ziying Su,
  • Yong Guo

摘要

Background

The results of observational studies on the causal relationship between metabolic syndrome (MetS) and thyroid cancer (TC) are controversial. This study aimed to explore the potential causal link between metabolic syndrome (MetS) and thyroid cancer (TC) by Mendelian randomization (MR) analysis. Additionally, the genetic correlation was evaluated using Linkage Disequilibrium Score Regression (LDSC).

Methods

In this study, we derived instrumental variables (IVs) linked to metabolic syndrome and its components from publicly accessible genome-wide association study (GWAS) databases. These IVs were then used in a MR with TC data from the Finnish population. The primary method of analysis was inverse variance weighted (IVW), supplemented by various sensitivity analyses to ensure the robustness and reliability of the findings.

Results

MR analysis identified a significant positive causal link between MetS and TC (OR = 1.7003, 95%CI = 1.2631–2.2888, P = 0.0005), while high-density lipoprotein cholesterol (HDL-C) exhibited a negative causal relationship (OR = 0.7868,95%CI = 0.6822–0.9076, P = 0.0010). Sensitivity tests showed no evidence of heterogeneity or horizontal pleiotropy. LDSC analyses did not detect significant genetic correlations between MetS and its components and TC.

Conclusions

Our results indicate that MetS substantially elevates the risk of TC, while HDL-C may have a protective effect against TC. These findings offer fresh perspectives on the potential causal link between MetS and TC.