Genotype-Phenotype Correlation in Noonan Syndrome – Focus on LZTR1 and its Substrates
Notice bibliographique
Résumé
Noonan syndrome (NS) is a multisystemic disorder that is known as one of the most common monogenetic diseases associated with early-onset congenital heart defects, such as hypertrophic cardiomyopathy (HCM). Infants diagnosed with NS and HCM have a worse late survival and are more likely to develop heart failure than non-syndromic HCM patients harboring classical mutations in sarcomeric genes (e.g. ß-myosin heavy chain, MYH7). In recent years, many germline mutations affecting different components of the RAS/mitogen-activated protein kinase (RAS/MAPK) pathway (including LZTR1, which negatively regulates signalling activity) have been identified as responsible for the development of NS and NS-associated diseases. Indeed, RASopathies result from of a signalling hyperactivation of the RAS/MAPK signalling and further cross-linked signalling pathways. However, based on clinical genotype-phenotype data as well as in vitro and in vivo studies, it has been suggested that the underlying, potentially overlapping pathomechanisms might be dependent on the cell type and the specific disease-causing variant. Patient-specific induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) from different NS patients are a powerful tool to study a genotype-phenotype correlation by investigating their molecular and functional properties in physiological relevant cells and tissues. In this work, a novel gene variant p.L580P in Leucine Zipper like Transcription Regulator 1 (LZTR1) has been identified as causative for recessive NS. Patient-derived as well as CRISPR-corrected induced pluripotent stem cells (iPSCs) were differentiated into ventricular-like iPSC-CMs and characterized on the molecular and functional level. Upon recapitulation of the patient’s phenotype by showing increased cell diameters as a characteristic of HCM and a hyperactivation of the RAS/MAPK pathway, we could reveal a novel gene variant-specific pathomechanism by which mutated LZTR1 shows dysfunction in ubiquitinating active RAS proteins. We could also prove that, besides the classical RAS GTPases (HRAS, NRAS and KRAS), MRAS was one of the main interaction partners of LZTR1 in the heart. Importantly, CRISPR/Cas9 based correction of this specific gene variant was able to rescue the disease phenotype in vitro. As gene variants in MRAS are also linked to NS and NS-associated HCM, the NS-associated mutation MRAS p.G23V was introduced into wild-type (WT) iPSCs to study its impact on cardiac physiology. Furthermore, we generated an iPSC line harboring a cancer-associated mutation KRAS p.G12V, known to cause severe signalling hyperactivity. Future work will proceed in uncovering the MRAS- and KRAS-specific phenotypes on the molecular and functional levels. In addition, the established iPSC models will be used to test new personalized treatment strategies based on pharmacological interventions and CRISPR/Cas9 gene therapy. To summarize, we successfully showed that the application of patient-derived iPSCs is a suitable model system to recapitulate the patients' cardiac phenotypes in vitro and to perform deeper investigations to understand the gene-specific molecular pathomechanisms of NS-associated HCM.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».