Quantitative Sustainability Assessment, Department of Environmental and Resource Engineering, Technical University of Denmark, Kgs. Lyngby, Denmark.
Department of Environmental Toxicology, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, Switzerland.
Environ Health Perspect. 2024 May;132(5):57003. doi: 10.1289/EHP14108. Epub 2024 May 16.
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.
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.
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.
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.
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.
对化学品的遗传易感性尚未完全阐明。然而，接触农药后神经系统疾病的发展在人群中存在差异，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。
我们旨在构建一种用于描述与化学物质诱导的不良后果相关的单核苷酸多态性（SNP）的计算方法，并利用该框架评估人群对农药易感性的差异与人类神经系统疾病之间的联系。
我们整合了公开的化学物质-基因、基因-途径和 SNP-疾病关联数据集，以构建人类的化学物质-途径-基因-SNP-疾病关联。作为案例研究，我们将这些关联与 1992 年至 2018 年美国的空间化农药应用数据以及 2018 年的神经系统疾病发生率的空间化数据进行整合。通过这种方式，我们根据当地使用的农药，描述了在疾病高发状态下可能具有重要意义的 SNP。
我们发现，美国各州每一种农药的 SNP 命中数与阿尔茨海默病、帕金森病和多发性硬化症的疾病发生率和患病率呈正相关。我们进行了频繁项集挖掘，以区分疾病高发和低发州在不同时间使用的农药，并发现仅 19%的农药集在疾病高发的 10 个州和低发率的 10 个州之间重叠，而在疾病高发状态下涉及的途径则有更多的 SNP。通过对五个疾病高发和低发州的子集进行交叉验证，我们确定了在疾病高发状态下更常涉及的 SNP、基因、途径和农药。
我们的研究结果支持农药会导致神经系统疾病，并且我们确定了更频繁涉及疾病高发状态的 SNP、农药和途径的优先级列表，以供进一步研究。这种基于数据的方法可以适用于其他化学物质、疾病和地点，以描述对化学暴露的人群差异易感性。
