Gut-lung microbial dynamics with lumacaftor/ivacaftor in children with cystic fibrosis: a prospective multicenter study.
prospective_cohort · Level II
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- Record sourced from PubMed, PMID 41645021.
- Also identified by DOI 10.1038/s41390-026-04774-2.
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Abstract
CFTR modulators such as lumacaftor/ivacaftor (LUM/IVA) may reshape microbiota-mycobiota composition in the lungs and gut. While the gut-lung axis is established in other settings, little is known about its role following modulator therapy, particularly in the 2-11 age group. In a prospective national multicentre study, 116 children with cystic fibrosis (2-11 years) starting LUM/IVA were followed for 12 months. Stool and sputum were collected at baseline, 3, 6 and 12 months. Bacterial and fungal communities were profiled by 16S rRNA and ITS2 sequencing; diversity, dysbiosis indices, faecal and sputum calprotectin, and gut-lung microbial networks were analysed. LUM/IVA was associated with increased bacterial diversity and compositional shifts in gut and lung microbiota, alongside a significant reduction in faecal calprotectin. Airway mycobiota diversity remained stable. Two lung microbiome response profiles emerged: "responders" (greater bacterial diversity gain) and "non-responders" (minimal change). Baseline gut and lung composition predicted these profiles with 81% accuracy in a random-forest model. Inter-organ microbial interactions peaked at 3 months after initiation and then diverged between profiles, indicating distinct gut-lung axis remodelling. LUM/IVA influences gut-lung microbiota-mycobiota dynamics, with heterogeneous responses between paediatric patients. Identifying factors predictive of response is a key future challenge. In 116 children aged 2-11, lumacaftor/ivacaftor reshaped gut and lung microbiota and reduced fecal calprotectin over 12 months. First pediatric multicenter study integrating bacterial and fungal profiling of stool and sputum with gut-lung network analyses; identifies two distinct lung microbiome response profiles. Baseline gut and lung composition predicted the response profile with approximately 81% accuracy. Highlights a 3-month interaction peak and baseline profiling as practical markers to guide monitoring and microbiome-informed precision care.