Impact of gene-environment interactions on atrial fibrillation and cardiac structure

Environmental pollution is a major burden of cardiovascular disease. The aim of the study was to investigate the interactions between combined environmental factors and genetic susceptibility on atrial fibrillation (AF) and cardiac structures. The study included 374,495 participants from the UK Biobank, utilizing genetic data and environmental variables (including air pollution, noise, greenspace and water quality). Polygenic risk score (PRS) was calculated to estimate individual genetic risk. Cox proportional hazard model was applied to estimate the impact of exposure factors on the risk of AF occurrence. The mediation analysis was applied to assess the relationship among environmental scores, AF and cardiac structures. Population attributable fraction (PAF) was employed to assess potential influence of mitigating unfavorable environment characteristics on AF. The results showed that the highest group of four domain scores exhibited 3.38-16.83% higher AF risk than the lowest. Individuals with higher scores in four domains and high PRS had hazard ratio (95%CI) of 2.76 (2.62, 2.91), 2.61 (2.47, 2.75), 2.86 (2.71, 3.02) and 2.84 (2.66, 3.02). Environmental factors could indirectly affect cardiac structures through AF. Up to 7.37% of AF cases could be preventable through environmental interventions. Our findings pointed that gene-environment interaction can increase AF risk, which further affect cardiac structures.

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Publication Details

Journal
Scientific Reports
Published
2025-05-15
DOI
https://doi.org/10.1038/s41598-025-00921-7
Citations
3
Primary Topic
Genetic Associations and Epidemiology
Type
article
Field-Weighted Citation Impact
5.45

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article

Impact of gene-environment interactions on atrial fibrillation and cardiac structure

Lei Zhao, Shanshan Cao, Min Liu, Panlong Li et al.
3 citations
Scientific Reports
Genetic Associations and Epidemiology
5.45
article

Impact of gene-environment interactions on atrial fibrillation and cardiac structure

Lei Zhao, Shanshan Cao, Min Liu, Panlong Li, Xirui Zhu, Yanfeng Wang, Yongmei Li, Meiyun Wang, Dandan Tian, Yuan Qiao, Chun Huang, Shan Tian, Jiwei Sun, Chaohua Cong, Jingjing Su, Junting Yang
article en
3 citations

Abstract

Environmental pollution is a major burden of cardiovascular disease. The aim of the study was to investigate the interactions between combined environmental factors and genetic susceptibility on atrial fibrillation (AF) and cardiac structures. The study included 374,495 participants from the UK Biobank, utilizing genetic data and environmental variables (including air pollution, noise, greenspace and water quality). Polygenic risk score (PRS) was calculated to estimate individual genetic risk. Cox proportional hazard model was applied to estimate the impact of exposure factors on the risk of AF occurrence. The mediation analysis was applied to assess the relationship among environmental scores, AF and cardiac structures. Population attributable fraction (PAF) was employed to assess potential influence of mitigating unfavorable environment characteristics on AF. The results showed that the highest group of four domain scores exhibited 3.38-16.83% higher AF risk than the lowest. Individuals with higher scores in four domains and high PRS had hazard ratio (95%CI) of 2.76 (2.62, 2.91), 2.61 (2.47, 2.75), 2.86 (2.71, 3.02) and 2.84 (2.66, 3.02). Environmental factors could indirectly affect cardiac structures through AF. Up to 7.37% of AF cases could be preventable through environmental interventions. Our findings pointed that gene-environment interaction can increase AF risk, which further affect cardiac structures.

Scientific ReportsVol. 15(1)
Shanghai Jiao Tong University (CN), Zhengzhou University of Light Industry (CN), Shanghai Ninth People's Hospital (CN)
National Natural Science Foundation of China, Zhengzhou University of Light Industry, Zhengzhou University, Shanghai Jiao Tong University, School of Medicine, Shanghai Jiao Tong University
Openalex Percentile: Top 5%
Genetic Associations and Epidemiology
5.45
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