Causal role of the gut microbiome in certain human diseases: a narrative review
Bibliographic record
Abstract
Composed of an elaborate ecosystem of bacteria, fungi, viruses and protozoa residing in the human digestive tract, the gut microbiome influences metabolism, immune modulation, bile acid homeostasis and host defence. Through observational and preclinical data, the gut microbiome has been implicated in the pathogenesis of a spectrum of chronic diseases ranging from psychiatric to gastrointestinal in nature. Until recently, the lack of unequivocal evidence supporting a causal link between gut microbiome and human health outcomes incited controversy regarding its significance. However, recent randomised controlled trial (RCT) evidence in conditions, such as Clostridioides difficile infection, cancer immunotherapy and ulcerative colitis, has supported a causal relationship and has underscored the potential of the microbiome as a therapeutic target. This review delineates the RCT evidence substantiating the potential for a causal relationship between the gut microbiome and human health outcomes, the seminal observational evidence that preceded these RCTs and the remaining knowledge gaps.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".