LZTR1 polymerization provokes cardiac pathology in recessive Noonan syndrome
Bibliographic record
Abstract
Abstract Noonan syndrome patients harboring causative variants in LZTR1 are particularly at risk to develop severe and early-onset hypertrophic cardiomyopathy. However, the underling disease mechanisms of LZTR1 missense variants driving the cardiac pathology are poorly understood. Hence, therapeutic options for Noonan syndrome patients are limited. In this study, we investigated the mechanistic consequences of a novel homozygous causative variant LZTR1 L580P by using patient-specific and CRISPR/Cas9-corrected iPSC-cardiomyocytes. Molecular, cellular, and functional phenotyping in combination with in silico prediction of protein complexes uncovered a unique LZTR1 L580P -specific disease mechanism provoking the cardiac hypertrophy. The homozygous variant was predicted to alter the binding affinity of the dimerization domains facilitating the formation of linear LZTR1 polymer chains. The altered polymerization resulted in dysfunction of the LZTR1-cullin 3 ubiquitin ligase complexes and subsequently, in accumulation of RAS GTPases, thereby provoking global pathological changes of the proteomic landscape ultimately leading to cellular hypertrophy. Furthermore, our data showed that cardiomyocyte-specific MRAS degradation is mediated by LZTR1 via the autophagosome, whereas RIT1 degradation is mediated by both LZTR1-dependent and LZTR1-independent proteasomal pathways. Importantly, uni-or biallelic genetic correction of the LZTR1 L580P missense variant rescued the molecular and cellular disease-associated phenotype, providing proof-of-concept for CRISPR-based gene therapies.
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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) | 0.002 | 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".