Meta-Analysis of Whole Blood Transcriptome Datasets Characterizes the Immune Response of Respiratory Syncytial Virus Infection in Children

Abstract

Respiratory syncytial virus (RSV) is the most common and critical viral pathogen causing acute lower respiratory tract infection in infants and young children and has a huge disease burden worldwide. At present, there are many studies on RSV transcriptomics exploring the mechanism of disease, but different studies show different gene expression patterns and results due to different sample collection platforms and data analysis strategies. A meta-analysis was performed on eight whole blood transcriptome datasets containing 436 children with acute RSV infection and 241 healthy children. A total of 319 differentially expressed genes (DEGs) (P value <0.0001) were identified in a meta-analysis using a random effect model. Functional enrichment analysis showed that several pathways related to immunity were significantly altered, including the “chemokine signaling pathway”, “natural killer cell mediated cytotoxicity” and “cytokine–cytokine receptor interaction”. Immune cell type analysis showed that the proportion of neutrophils in most RSV-infected children was higher than that in healthy children. These immune characteristics may help to provide new insights into RSV infection in children.