A longitudinal multi-omic dataset of pediatric cystic fibrosis patients receiving lumacaftor/ivacaftor therapy: clinical, microbiome, inflammatory and metabolomic measurements collected over 24 months

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This article describes a longitudinal multiomic dataset generated within a prospective phase IV pilot study of eight children with cystic fibrosis homozygous for the F508del mutation who initiated lumacaftor/ivacaftor therapy. Participants were followed for up to 24 months with repeated collection of clinical metadata, anthropometric measurements, sweat chloride concentrations, lung function assessments, inflammatory markers, conventional microbiology results, stool samples, respiratory samples, and serum metabolomics. The resulting dataset links host phenotypes, microbiome composition, inflammatory parameters, and metabolomic measurements across multiple body sites and time points. Microbiome data were generated from stool, sputum and throat swab samples using 16S rRNA gene sequencing, while serum metabolomics was assessed using untargeted mass spectrometry. The dataset is publicly available through SRA, MassIVE and GitHub repositories and may support future studies of longitudinal host–microbiome interactions, biomarker discovery, methodological benchmarking and comparative analyses across CFTR modulator eras.

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