ArticlePediatric research2026
Gut-lung microbial dynamics with lumacaftor/ivacaftor in children with cystic fibrosis: a prospective multicenter study.
Article in Pediatric research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
20 authors.
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Abstract
backgroundCFTR 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.
methodsIn 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.
resultsLUM/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.
conclusionLUM/IVA influences gut-lung microbiota-mycobiota dynamics, with heterogeneous responses between paediatric patients. Identifying factors predictive of response is a key future challenge. IMPACT: 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.
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Registered trials
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