Respiratory Syncytial Virus Genotypes, Host Immune Profiles, and Disease Severity in Young Children Hospitalized With Bronchiolitis

Abstract

Background: Data on how respiratory syncytial virus (RSV) genotypes influence disease severity and host immune responses is limited. Here, we characterized the genetic variability of RSV during 5 seasons, and evaluated the role of RSV subtypes, genotypes, and viral loads in disease severity and host transcriptional profiles.

Methods: A prospective, observational study was carried out, including a convenience sample of healthy infants hospitalized with RSV bronchiolitis. Nasopharyngeal samples for viral load quantitation, typing, and genotyping, and blood samples for transcriptome analyses were obtained within 24 hours of hospitalization. Multivariate models were constructed to identify virologic and clinical variables predictive of clinical outcomes.

Results: We enrolled 253 infants (median age 2.1 [25%-75% interquartile range] months). RSV A infections predominated over RSV B and showed greater genotype variability. RSV A/GA2, A/GA5, and RSV B/BA were the most common genotypes identified. Compared to GA2 or BA, infants with GA5 infections had higher viral loads. GA5 infections were associated with longer hospital stay, and with less activation of interferon and increased overexpression of neutrophil genes.

Conclusions: RSV A infections were more frequent than RSV B, and displayed greater variability. GA5 infections were associated with enhanced disease severity and distinct host immune responses.

Keywords: bronchiolitis; genomic loads; host responses.

Figure 1.

Selection of study patients. From March 2004 to April 2011 we enrolled 281 children <2 years of age, hospitalized with respiratory syncytial virus (RSV) bronchiolitis; 28 children were excluded: 6 patients with RSV A and B confections and 22 children with comorbidities including prematurity <36 weeks of gestational age, chronic lung disease, other lung diseases, and congenital heart diseases; 253 children <2 years of age were included in further analyses. Abbreviation: NT: nontyped.

Figure 2.

Distribution of respiratory syncytial virus (RSV) types and RSV genotypes in infants with RSV bronchiolitis from 2004 to 2011. A, The horizontal (x) axis represents the study years and the vertical (y) axis the percentage of RSV A and B isolates. B, The horizontal (x) axis represents the study years and the vertical (y) axis the percentage of RSV A and B genotypes. Abbreviation: NT: nontyped.

Figure 3.

Respiratory syncytial virus (RSV) distribution by genotypes and genotype loads. A, Pie graphs represent the genetic variability within RSV A and B isolates. Within RSV A genotypes, GA2 was the most commonly identified in 75% of children, followed by GA5 in 19% of patients. Of the 11 remaining RSV A genotypes, 1 corresponded to RSV GA7, 1 to the newly identified ON1 genotype, and 5% were not typed. Within the RSV B types, 88% corresponded to the BA genotype, 1 to RSV GB3, 1 to SAB1, and 9% were not typed. B, RSV genomic loads (vertical [y] axis) according to the 3 main genotypes BA (light red), GA2 (dark blue), and GA5 (light blue). Analyses performed using Kruskal–Wallis test following Benjamini–Hochberg to adjust for multiple comparisons. * Adjusted P < .05 was considered significantly different.

Figure 4.

Host transcriptional profiles according to respiratory syncytial virus (RSV) types and genotypes. A, class comparisons (Benjamini–Hochberg corrected FDR <0.01 and ≥1.25 fold change) using linear mixed models between infants with RSV A (n = 49) versus age-matched controls (n = 12), and infants with RSV B (n = 13) versus the same controls, identified 1394 transcripts that were present in either of these infections. Transcripts are organized in a heatmap format where each row represents a single transcript and each column represents a patient sample. Red indicates overexpression and blue underexpression of a transcript compared to the median expression of healthy controls (yellow). Color bars above and below the heatmap indicate the patient groups, controls, or RSV types (A or B), and genotypes (GA2, GA5, and BA). One RSV A sample and one RSV B sample were not typed due to insufficient RNA (white). B and C, To characterize biological functions of the differentially expressed genes, we used a modular-based analysis. Analysis was performed separately for (B) infants with RSV A and RSV B compared to healthy controls and (C) the 3 main genotypes: GA2 (n = 43), GA5 (n = 5), and BA (n = 12). The intensity of the modules (dots) indicates the proportion of overexpressed (red) or underexpressed (blue) transcripts within each module in relation to the healthy control baseline. Numeric values indicate the percentage of transcripts expressed in each specific module. Abbreviation: NK cell, natural killer cell.

Figure 4.

Host transcriptional profiles according to respiratory syncytial virus (RSV) types and genotypes. A, class comparisons (Benjamini–Hochberg corrected FDR <0.01 and ≥1.25 fold change) using linear mixed models between infants with RSV A (n = 49) versus age-matched controls (n = 12), and infants with RSV B (n = 13) versus the same controls, identified 1394 transcripts that were present in either of these infections. Transcripts are organized in a heatmap format where each row represents a single transcript and each column represents a patient sample. Red indicates overexpression and blue underexpression of a transcript compared to the median expression of healthy controls (yellow). Color bars above and below the heatmap indicate the patient groups, controls, or RSV types (A or B), and genotypes (GA2, GA5, and BA). One RSV A sample and one RSV B sample were not typed due to insufficient RNA (white). B and C, To characterize biological functions of the differentially expressed genes, we used a modular-based analysis. Analysis was performed separately for (B) infants with RSV A and RSV B compared to healthy controls and (C) the 3 main genotypes: GA2 (n = 43), GA5 (n = 5), and BA (n = 12). The intensity of the modules (dots) indicates the proportion of overexpressed (red) or underexpressed (blue) transcripts within each module in relation to the healthy control baseline. Numeric values indicate the percentage of transcripts expressed in each specific module. Abbreviation: NK cell, natural killer cell.