Association of IGF-1 Levels With Height From Childhood to Adulthood: An Observational and Mendelian Randomization Study
Bibliographic record
Abstract
CONTEXT: Growth hormone therapy, which increases circulating levels of insulin-like growth factor 1 (IGF-1), effectively enhances adult height in children with idiopathic short stature, although with varying responses. OBJECTIVE: To explore the question whether normal IGF-1 variation within a population is causally associated with height across childhood and in adulthood. METHODS: We used two-sample Mendelian randomization (MR) to assess the causal effect of serum IGF-1 on adult height. Genetic instruments for IGF-1 were derived from a UK Biobank genome-wide association study (GWAS), and their effects on adult height were identified in the GIANT Consortium GWAS, excluding UK Biobank (Non-Hispanic White: N = 1 176 465; African descent: N = 168 191; South Asian: N = 49 032; East Asian: N = 361 369; Hispanic: N = 58 709). Using the Avon Longitudinal Study of Parents and Children (ALSPAC), we investigated cross-sectional and longitudinal associations between measured IGF-1 levels at ages 7 to 11 years or a genetic risk score (GRS) for IGF-1, with repeated height measurements at ages 7 to 17 years, adjusting for sex, body mass index (BMI), and pubertal stage. RESULTS: Inverse-variance weighted MR showed that a 1 SD increase in IGF-1 confers 0.09 SD taller adult height, which persisted after adjusting for childhood BMI. In ALSPAC, both measured IGF-1 levels at ages 7 to 8 years and IGF-1 GRS were positively associated with height at ages 7 to 17 years at both cross-sectional and longitudinal analyses. CONCLUSION: Our findings suggest that IGF-1 normal variation has small effects on height in childhood and on final adult height.
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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".