Causal Associations Between Nitrogen Dioxide Exposure and Thyroid Nodules: a Two-Sample Mendelian Randomization Analysis

Abstract Background Recent epidemiological studies have pointed to nitrogen dioxide (NO₂) as a contributing factor in the formation of thyroid nodules. Nevertheless, causal inference remains challenging due to the limitations of conventional observational studies. In this investigation, we applied two-sample Mendelian randomization (TSMR) to evaluate the causal relationship between NO₂ concentrations and the risk of thyroid nodules Methods Using publicly available aggregated data from genome-wide association studies (GWAS) within the IEU Open GWAS database, we conducted a TSMR analysis. Seven single nucleotide polymorphisms (SNPs) associated with NO₂ levels were chosen as instrumental variables (IVs). Inverse-variance weighting (IVW) served as the primary analytical method, complemented by sensitivity analyses through MR-Egger, weighted median, simple mode, and weighted mode methods Results The Mendelian randomization analysis identified a significant positive causal effect of NO₂ on thyroid nodule risk. A one standard deviation (SD) increase in NO₂ concentrations was linked to a 112.0% heightened risk of thyroid nodules (odds ratio 2.12, 95% confidence interval 1.07–4.18, P = 0.031), based on IVW analysis. No notable heterogeneity or pleiotropic effects were observed Conclusion Our findings demonstrate a causal association between higher NO₂ exposure and an elevated risk of thyroid nodules. This study underscores the need for public health interventions targeting air pollution reduction as a strategy for preventing thyroid nodules. Graphical abstract

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Journal
Aerosol and Air Quality Research
Published
2025-05-01
DOI
https://doi.org/10.1007/s44408-025-00023-z
Primary Topic
Genetic Associations and Epidemiology
Type
article
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article

Causal Associations Between Nitrogen Dioxide Exposure and Thyroid Nodules: a Two-Sample Mendelian Randomization Analysis

Chengxiang Liu, Sainan Li, Hong Chen, Shan Chen et al.
1 links
Aerosol and Air Quality Research
Genetic Associations and Epidemiology
article

Causal Associations Between Nitrogen Dioxide Exposure and Thyroid Nodules: a Two-Sample Mendelian Randomization Analysis

Chengxiang Liu, Sainan Li, Hong Chen, Shan Chen, Zhu Chen, Juan Zhou
article en

Abstract

Abstract Background Recent epidemiological studies have pointed to nitrogen dioxide (NO₂) as a contributing factor in the formation of thyroid nodules. Nevertheless, causal inference remains challenging due to the limitations of conventional observational studies. In this investigation, we applied two-sample Mendelian randomization (TSMR) to evaluate the causal relationship between NO₂ concentrations and the risk of thyroid nodules Methods Using publicly available aggregated data from genome-wide association studies (GWAS) within the IEU Open GWAS database, we conducted a TSMR analysis. Seven single nucleotide polymorphisms (SNPs) associated with NO₂ levels were chosen as instrumental variables (IVs). Inverse-variance weighting (IVW) served as the primary analytical method, complemented by sensitivity analyses through MR-Egger, weighted median, simple mode, and weighted mode methods Results The Mendelian randomization analysis identified a significant positive causal effect of NO₂ on thyroid nodule risk. A one standard deviation (SD) increase in NO₂ concentrations was linked to a 112.0% heightened risk of thyroid nodules (odds ratio 2.12, 95% confidence interval 1.07–4.18, P = 0.031), based on IVW analysis. No notable heterogeneity or pleiotropic effects were observed Conclusion Our findings demonstrate a causal association between higher NO₂ exposure and an elevated risk of thyroid nodules. This study underscores the need for public health interventions targeting air pollution reduction as a strategy for preventing thyroid nodules. Graphical abstract

Aerosol and Air Quality ResearchVol. 25(5)
Anhui Medical University (CN), Second Affiliated Hospital of Anhui Medical University (CN)
Openalex Percentile: Top 89%
Genetic Associations and Epidemiology
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