A Study of Relationships Between Single Nucleotide Polymorphisms from the Growth Hormone-Insulin-like Growth Factor Axis and Bone Mass: the Hertfordshire Cohort Study
Bibliographic record
Abstract
OBJECTIVE: We sought evidence of association of candidate single nucleotide polymorphisms (SNP) within the growth hormone-insulin-like growth factor 1 (IGF1) axis, largely selected on the basis of functional data available at the time of our study, with adult bone mass. METHODS: Four hundred ninety-eight men and 468 women aged 59-71 years were recruited. A lifestyle questionnaire was administered, and bone mineral content (BMC) and bone mineral density (BMD) were measured at the lumbar spine and femoral neck. Two hundred fifty-four men and 271 women had repeat bone densitometry 4 years later. DNA was obtained from whole blood samples using standard extraction techniques. Single nucleotide variants in the growth hormone releasing hormone gene (GHRH, G/A 223 Phe75Leu, rs4988492), growth hormone releasing hormone receptor gene (GHRHR, G/A 217, Ala57Thr, rs4988496), the growth hormone secretagogue receptor gene (GHSR, T/C, Gly57Gly, rs495225), and the growth hormone receptor gene (GHR, T/G, noncoding, rs2940944) were analyzed. RESULTS: In both sexes, allelic variation in the gene encoding GHRH was associated with BMC and BMD at the proximal femur and lumbar spine, with results generally stronger in women. In women, the mean BMC lumbar spine within the GHRH 11 genotype was 56.9 g, while that of the GHRH 12 genotype was 68.4 g [p < 0.001, fully adjusted for age, body mass index, cigarette and alcohol consumption, dietary calcium intake, physical activity, years since menopause, and hormone replacement therapy (HRT) use]; corresponding figures for BMD lumbar spine (GHRH 11 genotype) were 0.96 g/cm(2) versus 1.10 g/cm(2) (p < 0.001 fully adjusted). CONCLUSION: We have demonstrated a relationship between allelic variation in the gene encoding GHRH and bone density; we welcome attempts at replication in other populations.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".