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This study analyzed blood samples from 491 children with asthma to identify microRNAs that predict treatment response and disease control over 12 months. Researchers found that specific circulating microRNAs were associated with asthma symptom severity in a treatment-dependent manner, with different molecular signatures emerging in children receiving the corticosteroid budesonide versus placebo. Machine learning models using these microRNA profiles could predict asthma control status with 78% accuracy in the budesonide group and 71% in the placebo group.
Why it matters
These findings suggest that blood-based microRNA measurements could potentially complement traditional symptom assessments to predict which asthma patients will respond well to specific treatments. This could enable more personalized treatment strategies and earlier intervention adjustments in pediatric asthma management.
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⚠️ Preprint – Noch nicht peer-reviewed
Dieser Artikel wurde noch nicht von unabhängigen Experten begutachtet. Die Ergebnisse sind vorläufig und sollten mit Vorsicht interpretiert werden.
Background: GINA-based clinical assessment of asthma control provides limited insight into the molecular mechanisms driving disease progression and treatment response. Circulating microRNAs (miRNAs) are implicated in immune regulation and airway remodeling, but their relationship to longitudinal, treatment-specific asthma control is not well characterized. We aimed to identify treatment-specific miRNAs associated with longitudinal asthma control and evaluate their ability to discriminate well-controlled from uncontrolled asthma. Methods: Baseline serum miRNA sequencing data from 491 children in the Childhood Asthma Management Program (CAMP), a randomized trial of budesonide versus placebo, were analyzed, with GINA-based composite symptom scores assessed at baseline and 2, 4, 8, and 12 months. Cumulative link mixed models were fitted across 266 miRNAs to identify associations with longitudinal ordinal asthma control, adjusting for time, baseline status, and treatment. Random Forest classifiers were trained within each treatment group using Group K-Fold cross-validation. Pathway enrichment of validated miRNA targets was performed with DAVID. Results: In the budesonide group, hsa-miR-1224-5p was associated with lower symptom severity and hsa-miR-199a-3p|hsa-miR-199b-3p with higher severity; both associations persisted at 12 months. The placebo group showed a broader pattern, with ten miRNAs associated with symptoms. Random Forest classifiers achieved mean AUC of 0.776 (budesonide) and 0.714 (placebo) for 12-month control status. Budesonide-associated targets were enriched for glucocorticoid-responsive and MAPK/Ras signaling, while placebo-associated targets showed broad enrichment for general regulatory processes. Conclusion: Treatment-specific circulating miRNAs distinguish asthma control over time and implicate distinct signaling pathways, supporting their potential as complementary molecular markers for asthma monitoring in children.
Source: Circulating microRNAs Predict Longitudinal Asthma Control and Treatment Response