Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study.
Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study.
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基于问卷调查的全暴露组关联研究 (ExWAS) 揭示了个性化环境和基因研究中与心血管结果相关的预期和新的危险因素。
DOI：
10.1016/j.envres.2022.113463
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发表时间：
2022
影响因子：
8.3
通讯作者：
Motsinger-Reif,AlisonA
中科院分区：
文献类型：
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作者：
Lee,EuniceY;Akhtari,Farida;House,JohnS;SimpsonJr,RossJ;Schmitt,CharlesP;Fargo,DavidC;Schurman,ShepherdH;Hall,JanetE;Motsinger-Reif,AlisonA
虽然多种因素与心血管疾病（CVD）有关，但许多可能导致CVD的环境暴露尚未得到研究。为了了解环境对心血管健康的影响，我们进行了一项全人群关联研究（ExWAS），一种无假设的方法，使用家庭和工作中内源性和外源性暴露的调查数据以及来自北卡罗来纳州个性化环境和基因研究（PEGS）的健康和病史数据（n = 5015）。我们使用逻辑回归和5%的错误发现率分别对六种心血管结局（心律失常、充血性心力衰竭、冠状动脉疾病、心脏病发作、卒中和动脉粥样硬化相关结局（包括心绞痛、血管成形术、动脉粥样硬化、冠状动脉疾病、心脏病发作和卒中））进行了ExWAS分析。对于每个CVD结果，我们测试了502个单次暴露，并使用删除-替换-添加（DSA）算法构建了多次暴露模型。为了评估复杂的非线性关系，我们采用了敲除提升树（KOBT）算法。我们调整了年龄，性别，种族，BMI和家庭年收入的所有分析。ExWAS分析揭示了新的关联，包括A型血（Rh-）与心脏病发作（OR[95%CI] = 8.2[2.2：29.7]）;油漆暴露伴中风（油漆相关化学品：6.1[2.2：16.0]，丙烯酸漆：8.1[2.6：22.9]，底漆：6.7[2.2：18.6]）;生物危害材料暴露伴心律失常（1.8[1.5：2.3]）;父亲教育水平较高，多种CVD结局（卒中、心脏病发作、冠状动脉疾病和合并动脉粥样硬化结局）的风险降低。在多次暴露模型中，睡眠障碍和吸烟仍然是重要的风险因素。KOBT确定了睡眠障碍、定期摄入葡萄柚和凝血问题家族史对多种CVD结局（合并动脉粥样硬化结局、充血性心力衰竭和冠状动脉疾病）的显著非线性影响。总之，使用统计学和机器学习，这些发现确定了CVD的新的潜在风险因素，使假设生成成为可能，为风险因素和CVD之间的复杂关系提供了见解，并强调了在检查CVD结果时考虑多次暴露的重要性。
While multiple factors are associated with cardiovascular disease (CVD), many environmental exposures that may contribute to CVD have not been examined. To understand environmental effects on cardiovascular health, we performed an exposome-wide association study (ExWAS), a hypothesis-free approach, using survey data on endogenous and exogenous exposures at home and work and data from health and medical histories from the North Carolina-based Personalized Environment and Genes Study (PEGS) (n = 5015). We performed ExWAS analyses separately on six cardiovascular outcomes (cardiac arrhythmia, congestive heart failure, coronary artery disease, heart attack, stroke, and a combined atherogenic-related outcome comprising angina, angioplasty, atherosclerosis, coronary artery disease, heart attack, and stroke) using logistic regression and a false discovery rate of 5%. For each CVD outcome, we tested 502 single exposures and built multi-exposure models using the deletion-substitution-addition (DSA) algorithm. To evaluate complex nonlinear relationships, we employed the knockoff boosted tree (KOBT) algorithm. We adjusted all analyses for age, sex, race, BMI, and annual household income. ExWAS analyses revealed novel associations that include blood type A (Rh-) with heart attack (OR[95%CI] = 8.2[2.2:29.7]); paint exposures with stroke (paint related chemicals: 6.1[2.2:16.0], acrylic paint: 8.1[2.6:22.9], primer: 6.7[2.2:18.6]); biohazardous materials exposure with arrhythmia (1.8[1.5:2.3]); and higher paternal education level with reduced risk of multiple CVD outcomes (stroke, heart attack, coronary artery disease, and combined atherogenic outcome). In multi-exposure models, trouble sleeping and smoking remained important risk factors. KOBT identified significant nonlinear effects of sleep disorder, regular intake of grapefruit, and a family history of blood clotting problems for multiple CVD outcomes (combined atherogenic outcome, congestive heart failure, and coronary artery disease). In conclusion, using statistics and machine learning, these findings identify novel potential risk factors for CVD, enable hypothesis generation, provide insights into the complex relationships between risk factors and CVD, and highlight the importance of considering multiple exposures when examining CVD outcomes.