Polymorphisms in the tumour necrosis factor alpha-induced protein 3 (TNFAIP3) gene are associated with chronic rhinosinusitis.
Bibliographic record
Abstract
BACKGROUND: Factors conferring susceptibility to chronic rhinosinusitis remain unknown. However, advances in genomics offer powerful tools to explore this disorder. Tumour necrosis factor (TNF) is a crucial proinflammatory cytokine that exerts inflammatory and immunomodulatory activities important in host defense. Our objective was to determine whether polymorphisms in genes in the TNF superfamily (TNF, TNF-alpha-induced protein 3, TNF-alpha-induced protein 6) were associated with chronic rhinosinusitis. METHODS: Deoxyribonucleic acid (DNA) extracted from a population of 206 patients with severe chronic rhinosinusitis and 196 postal code-matched controls was used. Three candidate genes related to the TNF inflammatory pathway were assessed. For each gene, an informative set of single nucleotide polymorphisms was genotyped. RESULTS: Thirty-five single nucleotide polymorphisms were genotyped. Two polymorphisms located within the TNF-alpha-induced protein 3 gene (TNFAIP3) reached the nominal p value threshold (p < .05) for association with chronic rhinosinusitis. However, none of these polymorphisms resist multiple testing adjustments. CONCLUSIONS: Our data suggest that two polymorphisms in TNFAIP3 are weakly associated with severe chronic rhinosinusitis but do not support an association with genetic variants in TNF or TNF-alpha-induced protein 6. Although these results do not support correction for multiple testing and have to be validated in a second population, they nevertheless suggest that further studies of the role of TNFAIP3 in the pathogenesis of disease are warranted.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".