Acute pulmonary exacerbations cause significant morbidity in the lives of children with cystic fibrosis (CF). As the etiologies of exacerbations continue to be defined, characterizing the role of the pulmonary microbiota in chronic infection and inflammation provides an opportunity for insight into the pathophysiology of CF.~This point is particularly true for a subset of pediatric CF patients with severe disease and frequent exacerbations.~The present application proposes to test the overall hypothesis that the composition of the pediatric CF airway microbiota plays an etiologic role in frequent pulmonary exacerbations in pediatric CF patients. To address the working hypothesis, next-generation sequencing based 16S rRNA sequencing will be undertaken to dissect the microbiome of pediatric CF patients subject to frequent pulmonary exacerbations, relative to the microbiome in clinically stable CF patients. This strategy promises to more specifically and definitively identify the key characteristics of the pediatric CF microbiota that are associated with the occurrence of exacerbations. Record clinical measures of pulmonary function, patient reported symptoms, sleep quality, and antibiotic usage, and correlate these findings with the lung microbiota data. This insight would in turn provide noninvasive biomarkers to identify those patients at a higher risk for experiencing repeated pulmonary exacerbations, which over the long-term significantly compromise lung function.
The present application proposes to study the role the composition of the pediatric CF airway microbiota plays in frequent pulmonary exacerbations in pediatric CF patients.~In order to accomplish this goal the dynamics of the composition of the CF airway microbiota in two distinct subsets of pediatric patients with CF will be characterized, those with frequent pulmonary exacerbations and clinically stable children. Clinical measures of pulmonary function, patient reported symptoms, sleep quality, and antibiotic usage will be recorded, and these findings will be correlated with the lung microbiota data.~This strategy promises to identify the key characteristics of the pediatric CF microbiota, which can in turn be used as noninvasive markers to identify those patients at a higher risk for experiencing repeated pulmonary exacerbations.