Personal network inference identifies children at risk of recurrent wheezing and asthma

Background: Wheezing and asthma exacerbations are leading causes of pediatric hospital admissions. Predicting which children will experience persistent exacerbations remains challenging. Prior research has identified immune endotypes in the nasal epithelium of children with acute asthma and wheezing, characterized by varying balances of interferons and inflammatory markers. Notably, children exhibiting low interferon responses coupled with high inflammation are at an increased risk for recurrent respiratory exacerbations. Objective: This study aims to determine if blood-based gene network biomarkers can detect immune endotypes in children presenting with acute wheeze and asthma, potentially serving as predictive tools for future exacerbations. Methods: We conducted gene expression analysis using microarrays of peripheral blood mononuclear cell (PBMC) samples from pediatric patients who presented to hospital for acute wheeze and asthma. Personal network inference was employed to discern gene expression patterns, facilitating the classification of patients into distinct immune endotypes. Results: Three immune endotypes were identified. One endotype, characterized by low interferon responses and elevated expression of both innate and adaptive immune pathways, was significantly associated with an increased risk of subsequent hospital respiratory presentations and a persistent pattern of respiratory exacerbations over time. Conclusion: PBMC-based personal gene network biomarkers can effectively identify immune endotypes correlating with clinical outcomes in pediatric asthma. The high-risk endotype represents a potential treatable trait in acute wheezing episodes. Therapeutic strategies aimed at enhancing interferon responses and/or reducing inflammation may benefit this subgroup.