Asthma is the most common chronic disease of childhood and has a strong genetic component. This technology identifies gene expression signatures that differentiate stable asthma and acute exacerbations. Researchers profiled gene expression patterns in nasal respiratory epithelial cells from children who had stable asthma, those experiencing asthma exacerbation, and children without asthma. Distinct gene clusters were identifiable in each population sample, and exacerbated asthma status was readily distinguished based on the occurrence of strong gene expression signatures in nasal epithelial samples. This technology allows clinicians to identify genes and cells poised for an asthma attack, and to predict treatment response of individual patients.