Tumor Necrosis Factor (TNF) and Lymphotoxin- (LTA) Polymorphisms and Risk of Non-Hodgkin Lymphoma in the InterLymph Consortium
Bibliographic record
Abstract
In an International Lymphoma Epidemiology Consortium pooled analysis, polymorphisms in 2 immune-system-related genes, tumor necrosis factor (TNF) and interleukin-10 (IL10), were associated with non-Hodgkin lymphoma (NHL) risk. Here, 8,847 participants were added to previous data (patients diagnosed from 1989 to 2005 in 14 case-control studies; 7,999 cases, 8,452 controls) for testing of polymorphisms in the TNF -308G>A (rs1800629), lymphotoxin-alpha (LTA) 252A>G (rs909253), IL10 -3575T>A (rs1800890, rs1800896), and nucleotide-binding oligomerization domain containing 2 (NOD2) 3020insC (rs2066847) genes. Odds ratios were estimated for non-Hispanic whites and several ethnic subgroups using 2-sided tests. Consistent with previous findings, odds ratios were increased for "new" participant TNF -308A carriers (NHL: per-allele odds ratio (OR(allelic)) = 1.10, P(trend) = 0.001; diffuse large B-cell lymphoma (DLBCL): OR(allelic) = 1.23, P(trend) = 0.004). In the combined population, odds ratios were increased for TNF -308A carriers (NHL: OR(allelic) = 1.13, P(trend) = 0.0001; DLBCL: OR(allelic) = 1.25, P(trend) = 3.7 x 10(-6); marginal zone lymphoma: OR(allelic) = 1.35, P(trend) = 0.004) and LTA 252G carriers (DLBCL: OR(allelic) = 1.12, P(trend) = 0.006; mycosis fungoides: OR(allelic) = 1.44, P(trend) = 0.015). The LTA 252A>G/TNF -308G>A haplotype containing the LTA/TNF variant alleles was strongly associated with DLBCL (P = 2.9 x 10(-8)). Results suggested associations between IL10 -3575T>A and DLBCL (P(trend) = 0.02) and IL10 -1082A>G and mantle cell lymphoma (P(trend) = 0.04). These findings strengthen previous results for DLBCL and the LTA 252A>G/TNF -308A locus and provide robust evidence that these TNF/LTA gene variants, or others in linkage disequilibrium, are involved in NHL etiology.
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".