A systematic review of the colorectal microbiome in adult cystic fibrosis patients
Bibliographic record
Abstract
AIM: Cystic fibrosis (CF) is a hereditary, life-limiting, multi-system condition that results in chronic respiratory infections, pancreatic insufficiency and intestinal inflammation. Evidence indicates that CF patients develop colorectal cancer (CRC) earlier and more often than the general population. Intestinal dysbiosis resulting from genetics and CF treatment is a contributing factor. This systematic review aims to evaluate the literature to compare the microbiome of adult CF patients to non-CF patients and to assess if these changes correspond with known CRC microbiome alterations. METHODS: A systematic review across five databases was performed according to PRISMA guidelines. Studies focusing on adult CF patients using next generation sequencing and with appropriate non-CF controls were included. Two reviewers independently screened results and assessed study quality using the Newcastle-Ottawa scale. RESULTS: The search generated 2757 results. 118 studies were retained after reviewing the title/abstract and full article review found five studies met the inclusion criteria. All studies consistently showed reduced microbial diversity in CF patients and unique clustering between CF and control cohorts. Thirty-four genera and 27 species were differently expressed between CF and controls. The CF cohort had a reduced number of short-chain fatty acid (SCFA) producing bacteria and a higher abundance of bacteria associated with CRC compared to controls. CONCLUSION: There was substantial heterogeneity across all the studies with regard to methodologies and reporting. However, all studies consistently found CF patients had reduced microbial diversity, fewer SCFA producing bacteria and increased CRC-associated bacteria. Further prospective studies employing consistent multi-omics approaches are needed to improve our understanding of the CF gut microbiome and its involvement in early onset CRC. SIGNIFICANCE STATEMENT: This is the first systematic review to assess adult CF colorectal microbiome changes. This study shows CF patients have reduced SCFA producing bacteria and increased CRC-associated bacteria compared to non-CF patients and may help to explain the increased risk of CRC in the CF cohort.
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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 | 0.007 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.009 | 0.008 |
| Bibliometrics | 0.014 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".