Host Genetic Variation Influences Gene Expression Response to Rhinovirus Infection

Abstract

Rhinovirus (RV) is the most prevalent human respiratory virus and is responsible for at least half of all common colds. RV infections may result in a broad spectrum of effects that range from asymptomatic infections to severe lower respiratory illnesses. The basis for inter-individual variation in the response to RV infection is not well understood. In this study, we explored whether host genetic variation is associated with variation in gene expression response to RV infections between individuals. To do so, we obtained genome-wide genotype and gene expression data in uninfected and RV-infected peripheral blood mononuclear cells (PBMCs) from 98 individuals. We mapped local and distant genetic variation that is associated with inter-individual differences in gene expression levels (eQTLs) in both uninfected and RV-infected cells. We focused specifically on response eQTLs (reQTLs), namely, genetic associations with inter-individual variation in gene expression response to RV infection. We identified local reQTLs for 38 genes, including genes with known functions in viral response (UBA7, OAS1, IRF5) and genes that have been associated with immune and RV-related diseases (e.g., ITGA2, MSR1, GSTM3). The putative regulatory regions of genes with reQTLs were enriched for binding sites of virus-activated STAT2, highlighting the role of condition-specific transcription factors in genotype-by-environment interactions. Overall, we suggest that the 38 loci associated with inter-individual variation in gene expression response to RV-infection represent promising candidates for affecting immune and RV-related respiratory diseases.

Leveraging gene-environment interactions and endotypes for asthma gene discovery

“…This network includes 58 genes with eQTLs in rhinovirus-treated PBMCs, 79 including STAT2 and IRF5 as hubs (shown as green symbols ), supporting the hypothesis that genetic variation in response to rhinovirus might modulate response to this virus and to asthma severity more generally. Molecule shapes: oval = transcriptional regulator, diamond = enzyme, dashed line rectangle = channel, up triangle = phosphatase, down triangle = kinase, trapezoid = transporter, circle = other.…”

“…Overall, the overlapping genes had a median 3.2-fold change in expression response to rhinovirus (median P = 3.4 × 10 −58 ). Moreover, among the 61 genes in this network, 2 (3.3%), IRF5 and OAS1 , had reQTLs in the study by Calışkan et al 79 compared with 0.035% of all genes tested ( P = .026, Fisher exact test). These data suggest that a significant proportion of the transcriptional response in the airways of children with asthma during an exacerbation can be attributed to rhinovirus or other viruses, which is consistent with epidemiologic data, and further suggest that genetic variation between subjects might contribute to a portion of these responses.…”

“…The combined results from the studies by Calışkan et al 79 and Bosco et al 81 demonstrate that cell models of GEIs capture biologically relevant gene regulatory networks and can identify genetic variants that modulate response to an important asthma-associated exposure. Further studies are needed to determine whether the SNPs that are eQTLs or reQTLs in this model are themselves associated with exacerbations or asthma severity.…”

“…A recent study by Calışkan et al 79 addressed this by studying gene expression in PBMCs from 98 subjects before and after rhinovirus infection in vitro. In this model more than half of the nearly 11,000 genes detected as expressed in PBMCs were upregulated (n = 2242) or downregulated (n = 3779) with rhinovirus exposure.…”

“…To explore this possibility, we compared the list of rhinovirus-responsive genes in rhinovirustreated cells reported in the study by Calışkan et al 79 described above with genes that were differentially expressed in nasal lavage samples collected from children during an acute asthma exacerbation and then again 7 to 14 days later, as reported by Bosco et al 81 We focused on one network from their weighted gene coexpression network analysis that included STAT2 as a hub (Fig 2) 79,81 because of the enrichment for STAT2-binding sites near reQTLs. Among the 71 genes in this network, 61 were detected as expressed in the study by Calışkan et al 79 Ninety-five percent (n = 58) of those genes showed significant expression changes in response to rhinovirus compared with 55.3% of all genes tested ( P =.0038, Fisher exact test). Overall, the overlapping genes had a median 3.2-fold change in expression response to rhinovirus (median P = 3.4 × 10 −58 ).…”