Clinical Genetics · 2019 · 51 citations · 32 references
Artificial IntelligenceMolecular Diagnostic TechniquesAutoimmune DiseaseAllergyDisease EtiologyNext-generation SequencingPathogenesisImmunologyGenetic EpidemiologyPathologyNoonan SyndromeDisease Gene IdentificationMedicineImmune-related Gene PolymorphismClinical Genetics
Noonan syndrome (NS) is a common autosomal dominant/recessive disorder. No large-scale study has been conducted on NS in China, which is the most populous country in the world. Next-generation sequencing (NGS) was used to identify pathogenic variants in patients that exhibited NS-related phenotypes. We assessed the facial features and clinical manifestations of patients with pathogenic or likely pathogenic variants in the RAS-MAPK signaling pathway. Gene-related Chinese NS facial features were described using artificial intelligence (AI).NGS identified pathogenic variants in 103 Chinese patients in eight NS-related genes: PTPN11 (48.5%), SOS1 (12.6%), SHOC2 (11.7%), KRAS (9.71%), RAF1 (7.77%), RIT1 (6.8%), CBL (0.97%), NRAS (0.97%), and LZTR1 (0.97%). Gene-related facial representations showed that each gene was associated with different facial details. Eight novel pathogenic variants were detected and clinical features because of specific genetic variants were reported, including hearing loss, cancer risk due to a PTPN11 pathogenic variant, and ubiquitous abnormal intracranial structure due to SHOC2 pathogenic variants. NGS facilitates the diagnosis of NS, especially for patients with mild/moderate and atypical symptoms. Our study describes the genotypic and phenotypic spectra of NS in China, providing new insights into distinctive clinical features due to specific pathogenic variants.
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