Citation Information: JCI Insight. 2025;10(9):e189480. https://doi.org/10.1172/jci.insight.189480.
Abstract
Severe asthma in children is notoriously difficult to treat, and its immunopathogenesis is complex. In particular, the contribution of T cells and relationships to antiviral immunity remain enigmatic. Here, we coupled deep phenotyping with machine learning methods to elucidate the dynamics of T cells in the lower airways of children with treatment-refractory recurrent wheeze, and examine rhinovirus (RV) as a driver. Our strategy revealed a T cell landscape dominated by type 1 and type 17 CD8+ signatures. Interrogation of phenotypic relationships coupled with trajectory mapping identified T cell migratory and differentiation pathways spanning the blood and airways that culminated in tissue residency, and involved transitions between type 1 and type 17 tissue-resident types. These dynamics were reflected in cytokine polyfunctionality. Use of machine learning tools to cross-compare T cell populations that were enriched in the airways of RV-positive children with those induced in the blood following experimental RV challenge precisely pinpointed RV-responsive signatures that contributed to T cell migratory and differentiation pathways. Despite their rarity, these signatures were also detected in the airways of RV-negative children. Together, our results underscore the aberrant nature of type 1 immunity in the airways of children with recurrent wheeze, and implicate an important viral trigger as a driver.
Authors
Naomi Bryant, Lyndsey M. Muehling, Kristin Wavell, W. Gerald Teague, Judith A. Woodfolk
