Effect of atmospheric traffic pollutants on gene expression profile in peripheral blood of children
SUN Na1, GUO Ya-shou2, LIU Qi-ling1, ZHANG Rong-qiang1, DUAN Li-fang1, LI Xing-hui1, LI Xiang-wen1
1. School of Public Health, Shaanxi University of Chinese Medicine, Xianyang, Shaanxi 712046, China; 2. Xianyang Central Hospital, Xianyang, Shaanxi 712000, China
Abstract：Objective To analyze the impact of air pollution on the gene expression profile in peripheral blood of children by using bioinformatics research method, and to provide a theoretical basis for the prevention, diagnosis and treatment in the later stage.Methods A set of peripheral blood gene chip data fromchildren exposed todifferent air pollution was downloaded from the Gene Expression Omnibus, and the data were imported into the analysis software QOE3.1, GenClip2.0 and GATHER, etc. We analyzed gene expression profiles, protein-protein interaction networks, molecular biological processes and gene functions, and found key genes for the effects of air pollution on children.Results A total of 2,172 differentially expressed genes were found. According to the purpose of the study, 223 children differentially expressed genes with Fold Change ≥ 3 were analyzed. The results showed that these target genes were mainly involved in the biological functions of cells, such as cell response to external stimuli, cell signaling transduction, and nucleoside phosphate binding. Further analysis revealed that the NR4A1, SGK1, TUBB1, PINK1 and THOC3 genes were central nodes of the protein-protein interaction network. After deleting these nodule proteins, the network structure was scattered. At the same time, the gene PINK1 was found to have the highest sensitivity, specificity and diagnostic value.Conclusions The gene expression of children in different pollution states is different. The differential genes are mainly involved in the biological functions of cells, such as response to external stimuli, cell signaling transduction, and nucleoside phosphate binding. The diagnostic ability of the PINK1 gene is the strongest.
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2019, Vol. 26 
