Newborn MTHFR rs1801133 Variant and Extremely Low Birth Weight: A Case–Control Study and Meta-Analysis
Bibliographic record
Abstract
Background: Extremely low birth weight (ELBW) and extremely low gestational age (ELGA) remain major challenges in neonatology, contributing to neonatal morbidity and mortality. This study aims to examine the association between functional variants of MTHFR and PON1, genes involved in homocysteine metabolism, and the risk of ELGA, ELBW, and other complications of prematurity. A meta-analysis was also conducted to integrate literature data with the results of this study. Methods: The study included 377 premature infants, 164 mothers, and a population-based sample of 404 individuals. Genotyping was performed using TaqMan assays. Results: The fetal, but not maternal, MTHFR rs1801133 genotype was associated with ELBW (OR = 1.65; 95% CI: 1.09–2.51; p = 0.017, dominant model), bronchopulmonary dysplasia (p = 0.028), patent ductus arteriosus (p = 0.017), and neonatal mortality. The meta-analysis, which included five studies spanning 1156 cases and 1124 controls, confirmed the association between the neonatal MTHFR genotype and low birth weight (LBW), demonstrating an association of the rs1801133T allele with LBW in the TT homozygote model (vs. CT: OR = 1.41; 95% CI: 1.08–1.80; p = 0.0097). Subgroup analyses indicated that the rs1801133T allele is a protective factor against LBW in more developed countries, such as Canada and the UK (dominant model), whereas in other countries, such as China, Turkey, and Poland, it is a risk factor for LBW (recessive model). No association with PON1 variants with ELBW or ELGA was found. Conclusions: This study provides the first global evidence confirming that the neonatal MTHFR genotype contributes to LBW, underscoring the population-specific effects of this genetic variant.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.005 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".