The Role of the Microbiome in Pediatric Respiratory Diseases.

Numerous studies have examined the role of the microbiome and microbiome-based therapeutics in many childhood airway and lung diseases. In this narrative review, the authors first give a brief overview of the current methods used in microbiome research. The authors then review the literature linking the microbiome with (1) early-life acute respiratory infections due to respiratory syncytial virus, (2) childhood asthma onset, (3) cystic fibrosis, and (4) bronchopulmonary dysplasia, focusing on recent studies that have used culture-independent methods to characterize the respiratory or gut microbiome in the pediatric population.

Remote endpoints for clinical trials in cystic fibrosis: Report from the U.S. CF foundation remote endpoints task force.

The COVID-19 pandemic necessitated a rapid shift in clinical research to perform virtual visits and remote endpoint assessments, providing a key opportunity to optimize the use of remote endpoints for clinical trials in cystic fibrosis. The use of remote endpoints could allow more diverse participation in clinical trials while minimizing participant burden but must be robustly evaluated to ensure adequate performance and feasibility. In response, the Cystic Fibrosis Foundation convened the Remote Endpoint Task Force (Supplemental Table 1), a multidisciplinary group of CF researchers with remote endpoint expertise and community members tasked to better understand the current and future use of remote endpoints for clinical research. Here, we describe the current use of remote endpoints in CF clinical research, address key unanswered questions regarding their use and feasibility, and discuss the next steps to determine clinical trial readiness.

Integrating airway microbiome and blood proteomics data to identify multi-omic networks associated with response to pulmonary infection.

Host response to airway infections can vary widely. Cystic fibrosis (CF) pulmonary exacerbations provide an opportunity to better understand the interplay between respiratory microbes and the host. This study aimed to investigate the observed heterogeneity in airway infection recovery by analyzing microbiome and host response (i.e., blood proteome) data collected during the onset of 33 pulmonary infection events. We used sparse multiple canonical correlation network (SmCCNet) analysis to integrate these two types of -omics data along with a clinical measure of recovery. Four microbe-protein SmCCNet subnetworks at infection onset were identified that strongly correlate with recovery. Our findings support existing knowledge regarding CF airway infections. Additionally, we discovered novel microbe-protein subnetworks that are associated with recovery and merit further investigation.