Abstract 245: Genetic variation related to innate immunity and colorectal cancer risk
Bibliographic record
Abstract
Abstract Introduction: Previous studies have shown that polymorphisms in the Toll-like receptor 4 (TLR4) gene may be associated with obesity, inflammatory bowel disease, and various cancers, including prostate, breast, and gastric cancer. However, the data regarding the associations between various TLR4 single-nucleotide polymorphisms (SNPs) and colorectal cancer (CRC) risk are inconsistent. In addition, the effect of interactions between TLR4 SNPs and obesity on the risk of CRC remains unclear. Methods: We selected candidate SNPs involved in the TLR4 pathway that were previously associated with the risk of CRC or other cancer (N=31). SNPs with low minor allele frequency (MAF < 0.05) were excluded (N=2), leaving 29 SNPs in the main analysis. We examined the associations of these SNPs with CRC risk using logistic regression on 10,998 cases of colorectal cancer and 10,691 controls drawn from 14 studies within the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and the Colon Cancer Family Registry (CCFR). BMI was dichotomized into non-obese (BMI ≤25) and obese (BMI >25) categories. Overall and BMI-stratified analyses were performed across studies, with regression models adjusting for sex, age, study site, and the first three principal components from EIGENSTRAT to account for potential population substructure. A false discovery rate at 0.2 was applied to correct for multiple testing. Results: Before adjustment for multiple comparisons, TLR4 SNPs rs10116253, rs11536891, rs7873784, rs1927911, rs4986791, and rs4986790 were associated with CRC risk. Additionally, for both rs4986791 and rs4986790, this association was more pronounced in those with a BMI ≤25 (rs4986791 - OR: 1.17; 95% CI: 1.02-1.34; rs4986790 - OR: 1.20; 95% CI: 1.04-1.38) compared to those who had a BMI >25 (rs4986791 - OR: 1.03; 95% CI: 0.93-1.15; rs4986790 - OR: 1.03; 95% CI: 0.92-1.15). However, after accounting for multiple comparisons, there were no statistically significant associations between candidate SNPs and CRC nor any statistically significant SNP interactions with BMI. Conclusion: This large study provides evidence that neither these identified TLR4 SNPs nor their interaction with obesity are associated with CRC risk. Citation Format: Jessica Citronberg, Barbara Banbury, Andrew T. Chan, Peter T. Campbell, Graham Casey, Jenny Chang-Claude, Steven J. Gallinger, Tabitha Harrison, Michael Hoffmeister, Mark A. Jenkins, Loic Le Marchand, Hongmei Nan, Hongmei Nan, Li Jiao, Robert E. Schoen, Hermann Brenner, Emily White, Ulrike Peters, Polly A. Newcomb. Genetic variation related to innate immunity and colorectal cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 245.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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".