BACKGROUND Genetic susceptibility to chemicals is incompletely characterized. However, nervous system disease development following pesticide exposure can vary in a population, implying some individuals may have higher genetic susceptibility to pesticide-induced nervous system disease. OBJECTIVES We aimed to build a computational approach to characterize single-nucleotide polymorphisms (SNPs) implicated in chemically induced adverse outcomes and used this framework to assess the link between differential population susceptibility to pesticides and human nervous system disease. METHODS We integrated publicly available datasets of Chemical-Gene, Gene-Pathway, and SNP-Disease associations to build Chemical-Pathway-Gene-SNP-Disease linkages for humans. As a case study, we integrated these linkages with spatialized pesticide application data for the US from 1992 to 2018 and spatialized nervous system disease rates for 2018. Through this, we characterized SNPs that may be important in states with high disease occurrence based on the pesticides used there. RESULTS We found that the number of SNP hits per pesticide in US states positively correlated with disease incidence and prevalence for Alzheimer's disease, Parkinson disease, and multiple sclerosis. We performed frequent itemset mining to differentiate pesticides used over time in states with high and low disease occurrence and found that only 19% of pesticide sets overlapped between 10 states with high disease occurrence and 10 states with low disease occurrence rates, and more SNPs were implicated in pathways in high disease occurrence states. Through a cross-validation of subsets of five high and low disease occurrence states, we characterized SNPs, genes, pathways, and pesticides more frequently implicated in high disease occurrence states. DISCUSSION Our findings support that pesticides contribute to nervous system disease, and we developed priority lists of SNPs, pesticides, and pathways for further study. This data-driven approach can be adapted to other chemicals, diseases, and locations to characterize differential population susceptibility to chemical exposures. https://doi.org/10.1289/EHP14108.

中文翻译：

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美国人口疾病途径和农药诱发的神经系统疾病的遗传变异性的数据驱动表征。


背景技术对化学品的遗传易感性尚未完全表征。然而，接触农药后神经系统疾病的发展在人群中可能有所不同，这意味着某些个体可能对农药引起的神经系统疾病具有更高的遗传易感性。目标我们旨在建立一种计算方法来表征与化学诱导的不良后果有关的单核苷酸多态性（SNP），并使用该框架来评估不同人群对农药的易感性与人类神经系统疾病之间的联系。方法 我们整合了化学-基因、基因-通路和 SNP-疾病关联的公开数据集，以建立人类的化学-通路-基因-SNP-疾病联系。作为案例研究，我们将这些联系与美国 1992 年至 2018 年的空间化农药应用数据以及 2018 年的空间化神经系统疾病发病率相结合。通过这一点，我们根据农药描述了在疾病高发州可能重要的 SNP在那里使用。结果我们发现，美国各州每种农药的 SNP 命中数与阿尔茨海默病、帕金森病和多发性硬化症的发病率和患病率呈正相关。我们进行了频繁的项集挖掘，以区分疾病发生率高和低的州随时间推移使用的农药，发现在疾病发生率高的 10 个州和疾病发生率低的 10 个州之间，只有 19% 的农药集重叠，并且涉及更多的 SNP在疾病高发状态的途径中。 通过对五种高疾病发生状态和低疾病发生状态的子集进行交叉验证，我们描述了与高疾病发生状态更频繁相关的 SNP、基因、途径和杀虫剂的特征。讨论 我们的研究结果支持农药会导致神经系统疾病，并且我们制定了 SNP、农药和进一步研究途径的优先列表。这种数据驱动的方法可以适应其他化学品、疾病和地点，以表征不同人群对化学品暴露的敏感性。 https://doi.org/10.1289/EHP14108。