4.8 Article

Epidemiology meets toxicogenomics: Mining toxicologic evidence in support of an untargeted analysis of pesticides exposure and Parkinson?s disease

Journal

ENVIRONMENT INTERNATIONAL
Volume 170, Issue -, Pages -

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.envint.2022.107613

Keywords

Parkinson?s disease; Pesticides; Toxicogenomics; Tox21; Chlorpyrifos; Copper sulfate

Funding

  1. Michael J. Fox Foundation
  2. National Institute of Environmental Health Science
  3. [MJFF-001018]
  4. [2R01ES010544]
  5. [R56ES026600]
  6. [W81XWH1910696]

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Scientists conducted a data mining study to assess the biological plausibility of 70 pesticides implicated with Parkinson's disease (PD). Through linking toxicology and toxicogenomics databases, they found that the majority of these pesticides were associated with PD genes or gene products. Additionally, these pesticides showed activity on various assays and were toxic to human cell lines. This knowledge can be used to prioritize targets for future studies and improve understanding of the role of pesticides in PD etiology.
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 regu-lation 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.

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