Associations of TNF-Α -308 and -238 Polymorphisms with Inflammatory Bowel Disease: A Case-Control Study and Meta-Analysis of Published Data
Bibliographic record
Abstract
Background: Inflammatory bowel disease (IBD) is a chronic relapsing-remitting inflammatory disease of the intestinal tract. Tumor necrosis factor-alpha (TNF-α) signaling plays a major role in the pathogenesis of IBD and is commonly targeted for therapeutic purposes. Results on the contribution of TNF-α -308 and -238 single nucleotide polymorphisms (SNP) to the susceptibility to IBD have been contradictory in differ- ent populations. Methods: Allele frequency and genotype status of TNF-α -308 and -238 SNPs were investigated in 75 un- related patients with IBD [40 Crohn’s disease (CD) and 35 ulcerative colitis (UC)] and 140 healthy controls by polymerase chain reaction with sequence-specific primers (PCR-SSP). We also conducted a systematic review and meta-analysis of the published reports. Results: TNF-α -238 GG was detected at a higher frequency in CD and UC. TNF-α -308 GG was more frequently detected in UC compared to control. There was no significant association between TNF-α -238 or -308 gene polymorphisms and patients’ demography (i.e., gender and age) or disease phenotype (i.e., extraintestinal manifestations, treatment, activity index, age at onset, and duration of the disease). In the meta-analysis, TNF-α -238 (AA/AG) genotype tended to be less frequent in patients with UC compared to healthy controls. There was no association between TNF-α -238 gene polymorphisms (AA/AG or GG genotypes) and either form of IBD. Conclusion: TNF-α -308 and -238 SNPs are associated with IBD in Iranian patients. TNF-α -308 AA gen- otype is positively correlated with UC in this meta-analysis.
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 | 0.010 | 0.023 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.012 | 0.027 |
| Bibliometrics | 0.005 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".