<i>WNT2</i>promoter methylation in human placenta is associated with low birthweight percentile in the neonate
Bibliographic record
Abstract
Neonates with birthweights below the tenth percentile for gestational age are considered small for gestational age (SGA). Such infants have an increased risk for perinatal mortality and morbidity as well as an increased lifetime risk for adult onset disorders. Low birth weight percentile is etiologically heterogeneous and may result from maternal, fetal, placental and environmental factors. However, the molecular determinants of human SGA are not well elucidated. We proposed that fetal growth potential could be negatively impacted by the epigenetic dysregulation of specific genes in the placenta. Using methyl DNA immunoprecipitation coupled with Agilent CpG island microarrays, we analyzed the differences in DNA methylation between placentas of eight SGA neonates and eight controls with birthweight percentiles above the tenth percentile. We identified several candidate genomic regions with differential DNA methylation between the two groups. The DNA methylation differences identified in the promoter of the WNT2 gene were prioritized for further study in an extended cohort of 170 samples given the important function of this gene in mouse placental development and its high expression in human placenta. High WNT2 promoter methylation (WNT2PrMe) was found only in placental tissue and not in the cord blood of the fetus. It was significantly associated with reduced WNT2 expression in placenta and with low birthweight percentile in the neonate. Our results show that WNT2 expression can be epigenetically downregulated in the placenta by DNA methylation of its promoter and that high WNT2PrMe is an epigenetic variant that is associated with reduced fetal growth potential. Note: All of the array data in the manuscript can be accessed from the Gene Expression Omnibus (GEO) NCBI database under GEO accession number GSE22326.
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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 | 0.000 | 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) | 0.001 | 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 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".