Wu Xueyan, Wei Dandan, Zhou Yilin, Cao Qingqing, Han Guozhen, Han Erbao, Chen Zhiwei, Guo Yao, Huo Wenqian, Wang Chongjian, Huang Shan, Zeng Xin, Wang Xinlu, Mao Zhenxing
Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China.
Department of Occupational and Environmental Health Sciences, College of Public Health, Zhengzhou University, Zhengzhou, Henan, PR China.
J Hazard Mater. 2025 Mar 5;485:136835. doi: 10.1016/j.jhazmat.2024.136835. Epub 2024 Dec 10.
Recent studies link pesticide exposures to cardiovascular disease risk factors. However, research on the combined effects of multiple pesticides on atherosclerotic cardiovascular disease (ASCVD) is limited, particularly in rural areas. Despite advances in toxicogenomics, the mechanisms underlying these effects remain unclear. This study aims to investigate the combined effects and mechanisms of pesticide exposures on ASCVD.
In the cross-sectional study section, 2291 participants were included. Variables were filtered using machine learning models, and associations between mixed exposure to multiple pesticides and ASCVD were explored using environmental mixed exposure models (weighted quartile sum (WQS) regression and quantile-based g-computation (QGC)). In the bioinformatics analysis section, the GEO, CTD, Malacards, and GeneCards databases were used to retrieve target genes for pesticide exposure and atherosclerotic diseases. Enrichment analysis was then performed to identify the biological pathways associated with these genes.
Three machine models screened 34 pesticides. Single pesticide exposures, such as atrazine, oxadiazon, p,p'-DDE, α-BHC, β-BHC, fenitrothion, malathion, fenitrothion, cypermethrin, cypermethrin, and cypermethrin might increase the 10-year ASCVD risk (all P < 0.05). Total mixed pesticide exposure was positively associated with 10-year ASCVD risk in both the QGC (3.223(2.196, 4.730)) and WQS models (4.642(3.070, 7.020)). Notably, there was a linear relationship between total (P_ < 0.001; P_ = 0.864) and high 10-year ASCVD risk. In toxicogenomic bioinformatics analysis, we identified 112 potential atherosclerosis target genes affected by pesticide exposure. Pathway enrichment analysis suggests pesticide-induced atherosclerosis is linked to pathways such as metabolic pathways, lipid metabolism, MAPK, AMPK, FoxO signaling, apoptosis, fluid shear stress, endocrine resistance, TNF, and PI3K-Akt. Key genes were identified based on maximal clique centrality, including AKT1, TP53, IL6, BCL2, TNF, JUN, PTGS2, CASP3, MAPK3, and CASP9.
Individual and combined exposure to pesticides increased the 10-year ASCVD risk, especially in patients with T2DM. Mixed levels of pesticide exposure were linearly and positively associated with high 10-year ASCVD risk. The mechanism of atherogenesis by mixed pesticide exposure may involve pathways such as lipid metabolism, MAPK, AMPK, FoxO signaling, apoptosis, fluid shear stress, endocrine resistance, TNF, and PI3K-Akt.
近期研究将农药暴露与心血管疾病风险因素联系起来。然而，关于多种农药对动脉粥样硬化性心血管疾病（ASCVD）联合作用的研究有限，尤其是在农村地区。尽管毒理基因组学取得了进展，但这些作用背后的机制仍不清楚。本研究旨在调查农药暴露对ASCVD的联合作用及机制。
在横断面研究部分，纳入了2291名参与者。使用机器学习模型对变量进行筛选，并使用环境混合暴露模型（加权四分位数和（WQS）回归和基于分位数的g计算（QGC））探索多种农药混合暴露与ASCVD之间的关联。在生物信息学分析部分，使用GEO、CTD、Malacards和GeneCards数据库检索农药暴露和动脉粥样硬化疾病的靶基因。然后进行富集分析以确定与这些基因相关的生物学途径。
三个机器学习模型筛选出34种农药。单一农药暴露，如莠去津、恶草酮、p,p'-滴滴伊、α-六六六、β-六六六、杀螟硫磷、马拉硫磷、杀螟硫磷、氯氰菊酯、氯氰菊酯和氯氰菊酯可能会增加10年ASCVD风险（所有P<0.05）。在QGC模型（3.223(2.196, 4.730)）和WQS模型（4.642(3.070, 7.020)）中，总混合农药暴露与10年ASCVD风险呈正相关。值得注意的是，总暴露（P_<0.001；P_ = 0.864）与高10年ASCVD风险之间存在线性关系。在毒理基因组生物信息学分析中，我们确定了112个受农药暴露影响的潜在动脉粥样硬化靶基因。通路富集分析表明，农药诱导的动脉粥样硬化与代谢途径、脂质代谢、MAPK、AMPK、FoxO信号、凋亡、流体剪切应力、内分泌抵抗、TNF和PI3K-Akt等途径有关。基于最大团中心性确定了关键基因，包括AKT1、TP53、IL6、BCL2、TNF、JUN、PTGS2、CASP3、MAPK3和CASP9。
个体和联合接触农药会增加10年ASCVD风险，尤其是2型糖尿病患者。农药混合暴露水平与高10年ASCVD风险呈线性正相关。混合农药暴露导致动脉粥样硬化的机制可能涉及脂质代谢、MAPK、AMPK、FoxO信号、凋亡、流体剪切应力、内分泌抵抗、TNF和PI3K-Akt等途径
