Toxic effects of long-term pesticides exposure and key gene discovery

Abstract

Objective: Bioinformatics methods were used to mine differentially expressed genes (DEGs) and enriched signal pathways induced by chronic pesticide exposure, and explore its potential pathogenic mechanisms and key genes. Methods: In July 2021, high-throughput gene expression profile data related to pesticide toxicity was downloaded from Gene Expression Omnibus (GEO) database to obtain DEGs. The samples were from American male farm workers who had been exposed to pesticides for a long time and other industry workers. The functional enrichment analysis of GO, KEGG and Geme Set Enrichment Analysis (GSEA) were performed by R package clusterProfiler. STRING, Cytoscape and other tools were applied to construct and visualize the protein interaction network. With the help of MCODE and Cytohubba plugins, gene function modules were obtained, and hub gene was screened out. Results: 189 DEGs were screened from GSE30335 dataset, including 101 up-regulated genes and 88 down-regulated genes. The results of GO, KEGG and GSEA were mainly enriched in biological functions such as regulation of neuron projection development, regulation of locomotion, ribosomal protein synthesis, and pathways related to complex nervous system diseases such as Parkinson's disease. And the comprehensive screening showed that KLF1 was the hub gene of pesticide exposure, with a fold change of 0.456 (t=-3.82, P=0.021) . Conclusion: Long term exposure to pesticides results in the differential expression of multiple genes in the exposed population, which may be involved in the pathological changes of nervous system by down regulating KLF1 and related biological pathways.