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Updated: Feb 22, 2026

A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Published on: June 15, 2011
Novel mutations and their genotype-phenotype correlations in patients with Noonan syndrome, using next-generation
Alireza Tafazoli1, Peyman Eshraghi2, Francesca Pantaleoni3
1Medical Genetics Research Center, Mashhad University of Medical Sciences, Mashhad, Iran.
Purpose:
Noonan Syndrome (NS) is an autosomal dominant disorder with many variable and heterogeneous conditions. The genetic basis for 20-30% of cases is still unknown. This study evaluates Iranian Noonan patients both clinically and genetically for the first time.
Materials/Methods:
Mutational analysis of PTPN11 gene was performed in 15 Iranian patients, using PCR and Sanger sequencing at phase one. Then, as phase two, Next Generation Sequencing (NGS) in the form of targeted resequencing was utilized for analysis of exons from other related genes. Homology modelling for the novel founded mutations was performed as well. The genotype, phenotype correlation was done according to the molecular findings and clinical features.
Results:
Previously reported mutation (p.N308D) in some patients and a novel mutation (p.D155N) in one of the patients were identified in phase one. After applying NGS methods, known and new variants were found in four patients in other genes, including: CBL (p. V904I), KRAS (p. L53W), SOS1 (p. I1302V), and SOS1 (p. R552G). Structural studies of two deduced novel mutations in related genes revealed deficiencies in the mutated proteins. Following genotype, phenotype correlation, a new pattern of the presence of intellectual disability in two patients was registered.
Conclusions:
NS shows strong variable expressivity along the high genetic heterogeneity especially in distinct populations and ethnic groups. Also possibly unknown other causative genes may be exist. Obviously, more comprehensive and new technologies like NGS methods are the best choice for detection of molecular defects in patients for genotype, phenotype correlation and disease management.
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