Characterization of the association between 8q24 and colon cancer: gene-environment exploration and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Genome-wide association studies and subsequent replication studies have shown that single nucleotide polymorphisms (SNPs) in the chromosomal region 8q24 are associated with colorectal cancer susceptibility. METHODS: We examined 11 SNP markers in the 8q24 region between 128.47 and 128.54 Mb, using a total of 1,987 colon cases and 2,339 controls who self-reported as white from two independent, well-characterized study populations. Analysis was performed separately within each study, and combined using random effects meta-analysis. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (95% CIs) and to test for effect modification by known colon cancer risk factors. We also performed a meta-analysis combining our results with previous studies. RESULTS: We observed evidence of association for four SNPs in low to high linkage disequilibrium (r2 ranging from 0.18 to 0.93) localized in a 16.2 kb region defined by rs10505477 and rs1056368. The combined results for our two studies of colon cancer showed an OR of 1.10 (95% CI: 1.01-1.20, Ptrend = 0.023), and a meta-analysis of our results with previously reported studies of colon and colorectal cancer strongly support the association for this SNP (combined OR for rs6983267 = 1.21, 95% CI: 1.18-1.24, p = 5.5 × 10-44). We did not observe any notable evidence of effect modification by known colon cancer risk factors, and risk did not differ significantly by tumor site or stage. CONCLUSIONS: Our study confirms the association between polymorphisms on chromosome 8q24 and colon cancer risk and suggests that the susceptibility locus in region 8q24 is not strongly modified by various lifestyle, environmental, and demographic risk factors for colon cancer.
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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 | 0.019 | 0.022 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.049 |
| Bibliometrics | 0.007 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".