Genetic variations at the human <i>growth hormone receptor (GHR)</i> gene locus are associated with idiopathic short stature
Bibliographic record
Abstract
GH plays an essential role in the growing child by binding to the growth hormone receptor (GHR) on target cells and regulating multiple growth promoting and metabolic effects. Mutations in the GHR gene coding regions result in GH insensitivity (dwarfism) due to a dysfunctional receptor protein. However, children with idiopathic short stature (ISS) show growth impairment without GH or GHR defects. We hypothesized that decreased expression of the GHR gene may be involved. To test this, we investigated whether common genetic variants (microsatellites, SNPs) in regulatory regions of the GHR gene region were associated with the ISS phenotype. Genotyping of a GT-repeat microsatellite in the GHR 5'UTR in a Montreal ISS cohort (n = 37 ISS, n = 105 controls) revealed that the incidence of the long/short (L/S) genotype was 3.3× higher in ISS children than controls (P = 0.04, OR = 3.85). In an Italian replication cohort (n = 143 ISS, n = 282 controls), the medium/short (M/S) genotype was 1.9× more frequent in the male ISS than controls (P = 0.017, OR = 2.26). In both ISS cohorts, logistic regression analysis of 27 SNPs showed an association of ISS with rs4292454, while haplotype analysis revealed specific risk haplotypes in the 3' haploblocks. In contrast, there were no differences in GT genotype frequencies in a cohort of short stature (SS) adults versus controls (CARTaGENE: n = 168 SS, n = 207 controls) and the risk haplotype in the SS cohort was located in the most 5' haploblock. These data suggest that the variants identified are potentially genetic markers specifically associated with the ISS phenotype.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".