Integrated Bioinformatics and Network Analysis Identifies Key Molecular Targets and Hub Genes in Zika Virus-induced...

The Zika virus (ZIKV) infection has shown significant neurodevelopmental and neurological abnormalities. However, the molecular mechanisms of ZIKV-induced neuroinflammation are poorly understood. In the current study, an integrative approach of bioinformatics analysis was used to identify the molecular targets involved in the ZIKV infection. Microarray data sets consisting of 65 samples (35 ZIKV-positive and 30 controls) from the Gene Expression Omnibus (GEO) database were used for the study. The differentially expressed genes (DEGs) analysis revealed 1,268 differentially expressed genes, of which 505 genes were up-regulated, while 763 genes were found to be down-regulated. The analysis using the weighted gene co-expression network analysis (WGCNA) revealed two modules that showed significant correlation with the ZIKV-positive samples. A total of 535 overlapping genes were used for further analysis. The protein-protein interaction (PPI) network analysis revealed ten hub genes: ITGAM, CD86, PTPRC, FCGR3A, ITGB2, TNF, ITGAX, CSF1R, CCR5, and CD4. This study suggests that the immune response plays an important role in the ZIKV infection. The study also revealed a significant enrichment of genes associated with neurogenesis, synaptic organization, axon guidance, immune response and amyloid beta binding by performing gene ontology (GO) analysis. This data potentially indicates that ZIKV infection can modulate these key hub genes to cause neuroinflammation. In addition, the study also revealed that the ZIKV infection can regulate various transcription factors and microRNAs that regulate these hub genes, indicating the complex regulatory mechanism of the ZIKV infection. Furthermore, the study revealed that the receiver operating characteristic (ROC) curve analysis showed that these hub genes, especially CCR5, are of preliminary diagnostic potential value. The study provided new insights into the molecular mechanisms of ZIKV-induced neuroinflammation and revealed the potential biomarkers and therapeutic targets of ZIKV-induced neurological disorders.