Drinking Water Chlorination By-Products and Intra-Uterine Growth Restriction: is there an effect modification of the CYP2E1 G1259C gene polymorphism?
Bibliographic record
Abstract
Background. Genetic polymorphisms could interact with disinfection by-products metabolism and increase their toxicity which may result in an increased risk of intrauterine growth restriction (IUGR). Aim. To evaluate whether the single nucleotide polymorphism (SNP) rs3813867 (G1259C) of CYP2E1 gene modifies the relationship between IUGR and trihalomethanes (THMs) exposure during pregnancy as previously reported by Infante-Rivard (2004). Methods. The design and THMs exposure of our population-based case-control study were presented recently (Levallois et al, 2012). Cases were term single neonates with birth weight <10th percentile of the age- and sex-specific Canadian birth weight distribution. Three controls (birth weight >10th percentile) per case were chosen among births from the same calendar week. Exposure of mothers during the last trimester of pregnancy was based on intensive monitoring of DBPs of the water distribution systems serving the residences and a phone questionnaire of mothers two months after birth. DNA samples of infants and mothers were extracted from either blood or saliva samples. SNPs were genotyped with a multiplexed PCR reaction (MassARRAY SNP Multiplex Sequenom). Non-caucasian infants were excluded from the analysis. Odds Ratios (OR) were estimated by a non-conditional logistic regression on infant and mother genotype. Risk factors for IUGR were included in the model. Results. SNP genotypes were available for 298 cases and 1182 controls and their mothers. For total THMs ? 80?g/L, the adjusted OR for children with 1 or 2 variant alleles of CYP2E1 G1259C was estimated at 3.44 (95% CI: 0.63-18.57) in comparison with 1.20 (95%CI:0.80-1.73) for the wild type group (p value for interaction=0.325). Conclusion. We did not observe any significant effect modification of the CYP2E1 G1259C SNP on the association between DBP exposure and IUGR.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".