Remodelling of cystic fibrosis respiratory microbiota in response to extended Elexacaftor–Tezacaftor–Ivacaftor therapy
Bibliographic record
Abstract
BACKGROUND: Cystic fibrosis (CF) has profoundly changed since the introduction of CF Transmembrane Conductance Regulator modulator therapies (CFTRmt), a class of medications that improve function of the CFTR protein encoded by certain CF-causing gene mutations. Amongst these, the triple combination therapy elexacaftor-tezacaftor-ivacaftor (ETI) has been the most impactful and widely used to date. Given chronic respiratory infection and concomitant inflammation is the leading cause of morbidity and early mortality for the majority in CF, what is not certain are the long-term effects of ETI therapy on the respiratory microbiota and pathogens embedded within. Here, we assessed the effects of ETI CFTRmt over 3 years on the respiratory microbiota, using sputum and cough swab samples, from a multi-centre cohort of 276 adults with CF (awCF) from 6 CF centres in the UK, USA, and Canada, and compared to a non-CF healthy cohort. RESULTS: Using Kruskal-Wallis analyses with post hoc Dunn's tests, Wilcoxon signed-rank tests, and PERMANOVA analyses with Bonferroni correction, we determined that respiratory microbiota characteristics (diversity, dominance, and composition) became decreasingly like those of awCF pre-ETI and remodelled to align more with the healthy cohort, where canonical CF pathogens increasingly became less ecologically important in terms of their distributions and abundances across awCF with increased duration on therapy. However, the on-ETI microbiota was impeded from becoming fully 'healthy' due to continued antibiotic exposure and irreversible lung damage experienced by awCF. Specifically, we found that azithromycin, an antibiotic widely used principally for its immunomodulatory benefits, was associated with adverse effects on the respiratory microbiota nullifying the observed positive effects of ETI treatment. Our results indicated that when administered alongside ETI therapy, azithromycin contributed to a pre-ETI microbiota dysbiosis and enabled enhanced persistence of emblematic CF pathogens. CONCLUSIONS: The highly anticipated introduction of ETI CFTRmt has greatly changed the course of CF for many people living with this inherited disease. Here, we find that ETI CFTRmt enabled positive remodelling of the respiratory microbiota towards a healthy-like state. However, azithromycin appeared to impede total remodelling, making it an ideal candidate for evaluation for discontinuation in the CFTRmt era. While traditional pathogens become less ecologically important, the potential evolution and emergence of virulent strains should be investigated. Additionally, the impacts and implications of ETI therapy on the understudied fungal microbiota should also be explored. Video Abstract.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".