Influence of polymorphisms in xenobiotic‐metabolizing genes and DNA‐repair genes on diepoxybutane‐induced SCE frequency
Bibliographic record
Abstract
Analysis of the combined effects of polymorphisms in genes encoding xenobiotic metabolizing enzymes (XMEs) and DNA repair proteins may be a key to understanding the role of these genes in the susceptibility of individuals to mutagens. In the present study, we performed an in vitro experiment on lymphocytes from 118 healthy donors that measured the frequency of diepoxybutane (DEB) induced sister chromatid exchanges (SCEs) in relation to genetic polymorphisms in genes coding for XMEs (CYP1A1, CYP2E1, GSTT1, EPHX, and NAT2), as well as DNA repair proteins (XRCC1, XRCC2, XRCC3, XPD, XPA, XPC, XPG, XPF, ERCC1, BRCA1, NBS1, and RAD51). We found that GSTT1(-) and CYP2E1 c1/c2 polymorphisms were associated with higher DEB-induced SCE frequencies, and that NAT2 G(590)A was associated with lower SCE induction by DEB. Analysis of the effect of pairs of genes showed that for a fixed GSTT1 genotype, the SCE level increased with an increasing number of Tyr alleles in EPHX codon 113. We found that among GSTT1(+) individuals the DEB-induced SCE level was significantly lower when the EPHX 139 codon was His/Arg rather than His/His. An interaction between polymorphisms in CYP2E1 and at EPHX codon 113 was also observed. The results of our study confirm observations in cancer patients and in people exposed to xenobiotics indicating that sensitivity to mutagens depends upon a combined effect of a variety of "minor impact" genes. Moreover, our results indicate that polymorphisms in genes coding for XMEs have a greater influence on the genotoxic activity of DEB, measured by DEB-induced SCE frequency, than polymorphisms in genes encoding DNA repair proteins.
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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".