Cytokine gene polymorphisms are associated with irritable bowel syndrome: a systematic review and meta‐analysis
Bibliographic record
Abstract
BACKGROUND: Low-grade inflammation has been increasingly implicated in the pathophysiology of irritable bowel syndrome (IBS). Imbalances of pro- and anti-inflammatory cytokines and polymorphisms in cytokine genes have been reported in IBS; however, these findings have not been consistently observed. This may be due to small sample sizes and differences in ethnicities. Therefore, we performed a meta-analysis on the studies that investigated cytokine gene polymorphisms in IBS patients compared to healthy controls. METHODS: A PubMed and EMBASE search was performed, and cytokine gene polymorphisms, which had been investigated in at least two case-control studies, were evaluated. Pooled odds ratios (OR) for the genotypes were calculated using random- or fixed-effects models. KEY RESULTS: Five studies that investigated interleukin-10 (IL-10; -1082 G/A), transforming growth factor-β1 (TGF-β1; +869 T/C and +915 G/C) and tumor necrosis factor (TNF; -308 G/A) polymorphisms in IBS patients and controls were included. High producer IL-10 (-1082 G/G; OR: 0.64 [95% CI: 0.48-0.87]) was significantly associated with a decreased risk of IBS. The intermediate producer TGF-β1 (+915 G/C) genotype showed a tendency toward decreasing the risk of IBS. No associations were found between TNF (-308 G/A) genotypes and IBS in the whole meta-analysis although an analysis of Asian studies revealed an association between TNF (-308 G/A and G/G) genotypes and IBS (OR: 0.50 [95% CI: 0.29-0.85]), and 1.82 [95% CI: 1.08-3.07], respectively). CONCLUSIONS & INFERENCES: This meta-analysis indicates a role for IL-10 polymorphisms in IBS in general and TNF in Asian populations. Whether or not gene polymorphisms are associated with alterations in cytokine levels leading to functional effects at the level of the gut needs further investigation.
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 | 0.006 | 0.015 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.022 |
| Bibliometrics | 0.004 | 0.008 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".