Background

Pesticides have been widely used in agriculture for more than half a century. However, with thousands currently in use, most have not been adequately assessed for influence Parkinson’s disease (PD).

Objectives

Here we aimed to assess biologic plausibility of 70 pesticides implicated with PD through an agnostic pesticide-wide association study using a data mining approach linking toxicology and toxicogenomics databases.

Methods

We linked the 70 targeted pesticides to quantitative high-throughput screening assay findings from the Toxicology in the 21st Century (Tox21) program and pesticide-related genetic/disease information with the Comparative Toxicogenomics Database (CTD). We used the CTD to determine networks of genes each pesticide has been linked to and assess enrichment of relevant gene ontology (GO) annotations. With Tox21, we evaluated pesticide induced activity on a series of 43 nuclear receptor and stress response assays and two cytotoxicity assays.

Results

Overall, 59 % of the 70 pesticides had chemical-gene networks including at least one PD gene/gene product. In total, 41 % of the pesticides had chemical-gene networks enriched for ≥ 1 high-priority PD GO terms. For instance, 23 pesticides had chemical-gene networks enriched for response to oxidative stress, 21 for regulation of neuron death, and twelve for autophagy, including copper sulfate, endosulfan and chlorpyrifos. Of the pesticides tested against the Tox21 assays, 79 % showed activity on ≥ 1 assay and 11 were toxic to the two human cell lines. The set of PD-associated pesticides showed more activity than expected on assays testing for xenobiotic homeostasis, mitochondrial membrane permeability, and genotoxic stress.

Conclusions

Overall, cross-database queries allowed us to connect a targeted set of pesticides implicated in PD via epidemiology to specific biologic targets relevant to PD etiology. This knowledge can be used to help prioritize targets for future experimental studies and improve our understanding of the role of pesticides in PD etiology.

中文翻译：

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流行病学与毒理学基因组学相遇：挖掘毒理学证据以支持对农药暴露和帕金森病的非靶向分析

背景

半个多世纪以来，农药在农业中得到广泛应用。然而，目前有数千种药物在使用中，但大多数药物尚未对帕金森病 (PD) 的影响进行充分评估。

目标

在这里，我们旨在通过使用连接毒理学和毒理学基因组学数据库的数据挖掘方法，通过不可知的农药范围关联研究评估与 PD 相关的 70 种农药的生物学合理性。

方法

我们将 70 种目标农药与 21 世纪毒理学 (Tox21) 计划的定量高通量筛选分析结果以及与毒物基因组学比较数据库 (CTD) 的农药相关遗传/疾病信息相关联。我们使用 CTD 来确定每种农药关联的基因网络，并评估相关基因本体论 (GO) 注释的丰富程度。对于 Tox21，我们在一系列 43 种核受体和应激反应测定以及两种细胞毒性测定中评估了杀虫剂诱导的活性。

结果

总体而言，70 种农药中有 59% 具有化学基因网络，包括至少一种 PD 基因/基因产物。总共有 41% 的农药具有化学基因网络，丰富了 ≥ 1 个高优先级 PD GO 术语。例如，23 种农药具有丰富的化学基因网络以响应氧化应激，21 种用于调节神经元死亡，12 种用于自噬，包括硫酸铜、硫丹和毒死蜱。在针对 Tox21 检测进行测试的杀虫剂中，79% 在 ≥ 1 次检测中显示出活性，并且 11 种对两种人类细胞系具有毒性。这组与 PD 相关的杀虫剂在外源性稳态、线粒体膜通透性和基因毒性应激的测定测试中显示出比预期更高的活性。

结论

总体而言，跨数据库查询使我们能够通过流行病学将一组与 PD 相关的目标农药连接到与 PD 病因学相关的特定生物靶点。这些知识可用于帮助确定未来实验研究目标的优先顺序，并提高我们对农药在 PD 病因学中的作用的理解。