Rhinovirus as a Driver of Airway T-Cell Dynamics in Children with Treatment-Refractory Wheeze

Severe asthma in children is notoriously difficult to treat, and its immunopathogenesis is complex. In particular, the contribution of T cells and relationships to anti-viral 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.

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Publication Details

Journal
Libra
Published
2025-04-29
DOI
https://doi.org/10.18130/tscq-gv56
Primary Topic
Asthma and respiratory diseases
Type
article
Field-Weighted Citation Impact
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article

Rhinovirus as a Driver of Airway T-Cell Dynamics in Children with Treatment-Refractory Wheeze

Libra
Asthma and respiratory diseases
article

Rhinovirus as a Driver of Airway T-Cell Dynamics in Children with Treatment-Refractory Wheeze

article en

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 anti-viral 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.

Libra
University of Virginia (US)
Openalex Percentile: Top 47%
Asthma and respiratory diseases
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