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CFTR modulator therapy drives microbiome restructuring through improved host physiology in cystic fibrosis: the IMMProveCF phase IV trial

Authors

  • Rebecca Luise Knoll
  • Melanie Meihu Brauny
  • Evelyn Robert
  • Louisa Cloos
  • Lydia Waser
  • Katja Hilbert
  • Nina Ulmer
  • Barlo Hillen
  • Till Birkner
  • Theda Ulrike Patricia Bartolomaeus
  • Oliver Nitsche
  • Víctor Hugo Jarquín-Díaz
  • Susan Lynch
  • Stephan Gehring
  • Lisa Maier
  • Krystyna Poplawska
  • Sofia Kirke Forslund-Startceva

Journal

  • Nature Communications

Citation

  • Nat Commun 16 (1): 10111

Abstract

  • Cystic fibrosis (CF) is a genetic disorder caused by mutations in the CFTR gene, leading to impaired CFTR function, mucus accumulation, chronic infections, and inflammation. The triple combination elexacaftor/tezacaftor/ivacaftor (ETI) has transformed CF treatment by restoring CFTR function. However, how ETI-induced physiological improvements affect long-standing dysbiosis and pathogen colonization across microbiome habitats remains poorly understood. In this prospective longitudinal study (DRKS00023862), we analyzed sputum, throat, and stool microbiomes of pwCF (n = 35) before and after ETI initiation, alongside healthy controls (n = 49). The primary endpoint was longitudinal change in diversity, species richness, and microbial composition in the respiratory and intestinal microbiome, profiled by 16S rRNA gene sequencing. Secondary endpoints included changes in lung function, systemic and gastrointestinal inflammation. We show how improved CFTR function and direct antibacterial effects of ETI create a niche disadvantage for Staphylococcus in the sputum microbiome. Respiratory microbiome shifts were immediate, while gut changes emerged gradually. Escherichia abundance in stool, initially elevated in pwCF, decreased post-ETI and correlated with lower fecal calprotectin. These findings demonstrate that ETI can partially reverse CF-associated dysbiosis through improved host physiology. They offer insights into host-microbiome dynamics under therapeutic modulation and emphasize the need for confounder-aware models in complex clinical populations.


DOI

doi:10.1038/s41467-025-64218-z