Association of Dynamic Changes in the CD4 T-Cell Transcriptome With Disease Severity During Primary Respiratory Syncytial Virus Infection in Young Infants

Background: Nearly all children are infected with respiratory syncytial virus (RSV) within the first 2 years of life, with a minority developing severe disease (1%-3% hospitalized). We hypothesized that an assessment of the adaptive immune system, using CD4+ T-lymphocyte transcriptomics, would identify gene expression correlates of disease severity. Methods: Infants infected with RSV representing extremes of clinical severity were studied. Mild illness (n = 23) was defined as a respiratory rate (RR) \u3c 55 and room air oxygen saturation (SaO2) ≥ 97%, and severe illness (n = 23) was defined as RR ≥ 65 and SaO2 ≤ 92%. RNA from fresh, sort-purified CD4+ T cells was assessed by RNA sequencing. Results: Gestational age, age at illness onset, exposure to environmental tobacco smoke, bacterial colonization, and breastfeeding were associated (adjusted P \u3c .05) with disease severity. RNA sequencing analysis reliably measured approximately 60% of the genome. Severity of RSV illness had the greatest effect size upon CD4 T-cell gene expression. Pathway analysis identified correlates of severity, including JAK/STAT, prolactin, and interleukin 9 signaling. We also identified genes and pathways associated with timing of symptoms and RSV group (A/B). Conclusions: These data suggest fundamental changes in adaptive immune cell phenotypes may be associated with RSV clinical severity