MC4R Marker Associated with Stature in Children and Young Adults: A Longitudinal Study
Bibliographic record
Abstract
We investigated the associations between a polymorphism in the melanocortin 4 receptor (MC4R) gene and changes in body size and composition from childhood to adulthood in the Québec Family Study. Ninety-one subjects (43 males) less than 18 years of age (mean age 13.5 +/- 2.4 years; range 8.4-17.8 years) at baseline were re-measured 11.2 years later on average. The anthropometric variables analyzed were height, weight, body mass index, percent body fat, sum of skinfolds, fat mass index, and fat free mass index (FFMI). All variables were adjusted for age and sex. The subjects were genotyped for the MC4R C-2745T polymorphism. Forty-five subjects were homozygotes for the common allele (C/C), 36 were heterozygotes (C/T) and 10 were homozygotes for the rare allele (T/T). The rare allele was associated with increased height at baseline as well as at the follow-up visit. Although FFMI tended to increase more in subjects carrying the rare allele, no significant differences were found for the changes over time for the other phenotypes. These results suggest that DNA sequence variation in the MC4R locus may contribute to the gain in body height from childhood to adulthood.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".