Novel Promoter Polymorphism in Insulin-Like Growth Factor-Binding Protein-3: Correlation with Serum Levels and Interaction with Known Regulators<sup>1</sup>
Bibliographic record
Abstract
Insulin-like growth factor (IGF)-binding protein-3 (IGFBP-3) is a major determinant of circulating levels of the IGFs and is clinically useful for the evaluation of GH deficiency and for predicting the response to GH treatment. Recent studies provide evidence that the circulating level of IGFBP-3 is inversely related to the risk of several common cancers, and that antiproliferative agents such as antiestrogens and retinoids act in part by up-regulating IGFBP-3 gene (IGFBP3) expression. Although approximately 50% of the substantial interindividual variability in circulating IGFBP-3 levels is known to have a genetic basis, the specific loci involved are unknown. Direct sequencing of genomic DNA specimens from a multiethnic population identified several single nucleotide polymorphisms in the promoter region of IGFBP3. For the most common single nucleotide polymorphism (nucleotide -202) found to be in Hardy-Weinberg equilibrium, genotype was highly correlated to circulating level of IGFBP-3 in 478 men from the Physicians' Health Study. In vitro, we documented significantly higher promoter activity of the A allele at the -202 locus compared with the C allele, consistent with the relationship observed between genotype and circulating IGFBP-3 (AA > AC > CC). A positive correlation was observed between circulating retinol levels and circulating IGFBP-3 levels; subset analysis by genotype showed that this relationship was only present among individuals carrying an A allele at -202 (AA > AC > CC). Tall individuals or individuals with a body mass index of 27 or greater had levels of circulating IGFBP-3 that were significantly higher when they possessed at least one A allele (AA > AC > CC). The IGFBP3 promoter region deserves investigation as a locus where polymorphic variation occurs frequently and may influence GH responsiveness, somatic growth, and possibly cancer risk.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".