Noonan syndrome-causing SHP2 mutants inhibit insulin-like growth factor 1 release via growth hormone-induced ERK hyperactivation, which contributes to short stature
Bibliographic record
Abstract
Noonan syndrome (NS), a genetic disease caused in half of cases by activating mutations of the tyrosine phosphatase SHP2 (PTPN11), is characterized by congenital cardiopathies, facial dysmorphic features, and short stature. How mutated SHP2 induces growth retardation remains poorly understood. We report here that early postnatal growth delay is associated with low levels of insulin-like growth factor 1 (IGF-1) in a mouse model of NS expressing the D61G mutant of SHP2. Conversely, inhibition of SHP2 expression in growth hormone (GH)-responsive cell lines results in increased IGF-1 release upon GH stimulation. SHP2-deficient cells display decreased ERK1/2 phosphorylation and rat sarcoma (RAS) activation in response to GH, whereas expression of NS-associated SHP2 mutants results in ERK1/2 hyperactivation in vitro and in vivo. RAS/ERK1/2 inhibition in SHP2-deficient cells correlates with impaired dephosphorylation of the adaptor Grb2-associated binder-1 (GAB1) on its RAS GTPase-activating protein (RASGAP) binding sites and is rescued by interfering with RASGAP recruitment or function. We demonstrate that inhibition of ERK1/2 activation results in an increase of IGF-1 levels in vitro and in vivo, which is associated with significant growth improvement in NS mice. In conclusion, NS-causing SHP2 mutants inhibit GH-induced IGF-1 release through RAS/ERK1/2 hyperactivation, a mechanism that could contribute to growth retardation. This finding suggests that, in addition to its previously shown beneficial effect on NS-linked cardiac and craniofacial defects, RAS/ERK1/2 modulation could also alleviate the short stature phenotype in NS caused by PTPN11 mutations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".