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

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