MEK-ERK pathway modulation ameliorates disease phenotypes in a mouse model of Noonan syndrome associated with the Raf1L613V mutation
Bibliographic record
Abstract
Hypertrophic cardiomyopathy (HCM) is a leading cause of sudden death in children and young adults. Abnormalities in several signaling pathways are implicated in the pathogenesis of HCM, but the role of the RAS-RAF-MEK-ERK MAPK pathway has been controversial. Noonan syndrome (NS) is one of several autosomal-dominant conditions known as RASopathies, which are caused by mutations in different components of this pathway. Germline mutations in RAF1 (which encodes the serine-threonine kinase RAF1) account for approximately 3%-5% of cases of NS. Unlike other NS alleles, RAF1 mutations that confer increased kinase activity are highly associated with HCM. To explore the pathogenesis of such mutations, we generated knockin mice expressing the NS-associated Raf1(L613V) mutation. Like NS patients, mice heterozygous for this mutation (referred to herein as L613V/+ mice) had short stature, craniofacial dysmorphia, and hematologic abnormalities. Valvuloseptal development was normal, but L613V/+ mice exhibited eccentric cardiac hypertrophy and aberrant cardiac fetal gene expression, and decompensated following pressure overload. Agonist-evoked MEK-ERK activation was enhanced in multiple cell types, and postnatal MEK inhibition normalized the growth, facial, and cardiac defects in L613V/+ mice. These data show that different NS genes have intrinsically distinct pathological effects, demonstrate that enhanced MEK-ERK activity is critical for causing HCM and other RAF1-mutant NS phenotypes, and suggest a mutation-specific approach to the treatment of RASopathies.
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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 | 0.001 | 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".