Identification of common biological pathways and drug targets across multiple respiratory viruses based on human host gene expression analysis

Abstract

Background: Pandemic and seasonal respiratory viruses are a major global health concern. Given the genetic diversity of respiratory viruses and the emergence of drug resistant strains, the targeted disruption of human host-virus interactions is a potential therapeutic strategy for treating multi-viral infections. The availability of large-scale genomic datasets focused on host-pathogen interactions can be used to discover novel drug targets as well as potential opportunities for drug repositioning.

Methods/results: In this study, we performed a large-scale analysis of microarray datasets involving host response to infections by influenza A virus, respiratory syncytial virus, rhinovirus, SARS-coronavirus, metapneumonia virus, coxsackievirus and cytomegalovirus. Common genes and pathways were found through a rigorous, iterative analysis pipeline where relevant host mRNA expression datasets were identified, analyzed for quality and gene differential expression, then mapped to pathways for enrichment analysis. Possible repurposed drugs targets were found through database and literature searches. A total of 67 common biological pathways were identified among the seven different respiratory viruses analyzed, representing fifteen laboratories, nine different cell types, and seven different array platforms. A large overlap in the general immune response was observed among the top twenty of these 67 pathways, adding validation to our analysis strategy. Of the top five pathways, we found 53 differentially expressed genes affected by at least five of the seven viruses. We suggest five new therapeutic indications for existing small molecules or biological agents targeting proteins encoded by the genes F3, IL1B, TNF, CASP1 and MMP9. Pathway enrichment analysis also identified a potential novel host response, the Parkin-Ubiquitin Proteasomal System (Parkin-UPS) pathway, which is known to be involved in the progression of neurodegenerative Parkinson's disease.

Conclusions: Our study suggests that multiple and diverse respiratory viruses invoke several common host response pathways. Further analysis of these pathways suggests potential opportunities for therapeutic intervention.

Figure 1. Outline of iterative filtering process.

Analysis pipeline to select and quality control GEO datasets linked to respiratory virus mRNA expression. Specific inclusion criteria are described in the Materials and Methods.

Figure 2. Example of quality analysis for subset of GSE17156: RSV treatment and control groups.

Kernel density plot a) before and b) after removal of samples GSM429279 and GSM429252: blue lines indicate baseline samples, green lines indicate RSV peak symptom samples (∼141 hours); PCA plot c) before and d) after removal of samples GSM429279 and GSM429252 :blue circles indicate control (baseline) samples, green circles indicate RSV peak symptom samples (∼141 hours). Ellipse represents Hotelling T2 alpha threshold of 0.05. Eigenvalues for panel c components 1 and 2 are, respectively, 119335.7 and 50356.11. Eigenvalues for panel d components 1 and 2 are, respectively, 86014.46 and 50705.63.

Figure 3. Parkin-Ubiquitin Proteasomal System pathway with viral frequency.

Viral frequencies superimposed for each of most frequently differentially expressed proteins, where red circles are differential expression of genes by 7 viruses, orange circles are differential expression of genes by at least 6 viruses, and blue circles are differential expression of genes by 5 viruses. See MetaCore website at http://www.genego.com/pdf/MC_legend.pdf for figure legend and Table S4 for pathway map gene products' corresponding HUGO gene names.