Association of apolipoprotein E polymorphisms and dietary factors in colorectal cancer
Bibliographic record
Abstract
ApoE single nucleotide polymorphisms (SNPs) Cys112Arg (Epsilon-4), and Arg158Cys (Epsilon-2) have been implicated in cardiovascular and Alzheimer's disease, but their role in colorectal cancer (CRC) has not been extensively studied. We investigated whether ApoE polymorphisms alone or in combination with dietary factors selectively contribute to mismatch-repair (MMR) proficient (microsatellite stable/low or MSS/L) vs deficient (microsatellite unstable or MSI-H) CRCs. We carried out a case-control study with 906 CRC cases and 911 unaffected controls to examine the associations between ApoE polymorphisms and dietary factors and assessed their contribution to MSS/L and MSI-H CRCs. We used unconditional logistic regression to evaluate the associations between ApoE SNPs, tumour MSI status, and dietary factors after adjusting for age and sex. All statistical tests were two-sided. No significant differences in ApoE genotype frequencies were observed between CRC cases and unaffected controls. We observed that increased dietary intake of total fat, saturated fat, cholesterol, and red meat was significantly associated with CRC. Among non-ApoE4 carriers, 2-4 and >4 red meat servings/week were associated with developing MSS/L CRC (OR=1.51, 95% CI 1.10-2.07 and OR=1.80, 95% CI 1.30-2.48, respectively), whereas among ApoE4 allele carriers, four or more red meat servings/week were associated with MSI-H CRC (OR=4.62, 95% CI 1.20-17.77) when compared with the controls. ApoE isoforms modulate the risk of MSI-H and MSS/L CRCs among high red meat consumers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".