Genetic and epigenetic variation in the <i>DNMT3B</i> and <i>MTHFR</i> genes and colorectal adenoma risk
Bibliographic record
Abstract
Polymorphisms in DNMT3B and MTHFR have been implicated in cancer etiology; however, it is increasingly clear that gene-specific DNA methylation also affects gene expression. A cross-sectional study (N = 272) investigated the main and joint effects of polymorphisms and DNA methylation in DNMT3B and MTHFR on colorectal adenoma risk. Polymorphisms examined included DNMT3B c.-6-1045G > T, and MTHFR c.665C > T and c.1286A > C. DNA methylation of 66 and 28 CpG sites in DNMT3B and MTHFR, respectively, was quantified in blood leukocytes using Sequenom EpiTYPER®. DNA methylation was conceptualized using two approaches: (1) average methylation and (2) unsupervised principal component analysis to identify variables that represented methylation around the transcription start site and the gene coding area of both genes. Logistic regression was used to estimate odds ratios (ORs) and 95% confidence intervals (CIs) associated with the main and joint effects of polymorphisms and DNA methylation. DNA methyltransferase 3B (DNMT3B) TT versus GG/GT genotypes was associated with increased colorectal adenoma risk (OR = 2.12; 95% CI: 1.03-4.34). In addition, increasing DNA methylation in the gene-coding area of DNMT3B was associated with higher risk of colorectal adenomas (OR = 1.34; 95% CI: 1.01-1.79 per SD). In joint effect analyses, synergistic effects were observed among those with both the DNMT3B TT genotype and higher DNMT3B methylation levels compared to those with GT/GG genotypes and lower methylation levels (OR = 4.19; 95% CI: 1.45-12.13 for average methylation; OR = 4.26; 95%CI: 1.31-13.87 for methylation in the transcription start site). This research provides novel evidence that genetic and epigenetic variations contribute to colorectal adenoma risk, precursor to the majority of colorectal cancer (CRC).
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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".