Sex dimorphic associations of Prader–Willi imprinted gene expressions in umbilical cord with prenatal and postnatal growth in healthy infants
Bibliographic record
Abstract
BACKGROUND: The impact of Prader-Willi syndrome (PWS) domain gene expression on the growth of healthy children is not well understood. This study investigated associations between PWS domain gene expression in umbilical cord tissue and prenatal and postnatal growth, considering potential sex differences. METHODS: Relative gene expression of paternally expressed MAGEL2, NDN, and SNURF-SNRPN, and the small nucleolar RNAs SNORD116 and SNORD115 were determined by real-time quantitative polymerase chain reaction in umbilical cord tissue from 122 healthy newborns (59 girls and 63 boys). Gene expression levels were correlated with auxological measures at birth, infancy, and childhood (ages 2, 4, and 6 years). RESULTS: MAGEL2, NDN, SNORD116, and SNORD115 expression in the umbilical cord was negatively associated with birth weight, length, and placental weight (P < 0.001). Postnatally, these genes were positively associated with weight and length at 3 months (P < 0.001) and weight gain from birth to ages 1, 2, and 4 years (P < 0.01). Negative associations at birth were stronger in girls (P < 0.001), while positive associations during infancy and childhood were stronger in boys (P < 0.001). MAGEL2, SNORD116, and SNORD115 expression predicted early-postnatal growth, explaining the higher growth rate in boys compared to girls and accounting for sex differences up to 1.5 kg in weight and 3 cm in height during infancy. CONCLUSIONS: Paternally expressed PWS domain gene expression in the umbilical cord was negatively associated with prenatal growth and positively with early-postnatal growth in healthy infants. This gene expression may predict early human postnatal growth and promote the well-known sex dimorphism in growth. These results can also help in understanding the etiology of PWS, which remains unclear.
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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 | 0.001 |
| 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".