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Updated: Oct 25, 2026

A Strategy to Identify de Novo Mutations in Common Disorders such as Autism and Schizophrenia
Published on: June 15, 2011
[Clinical heterogeneity and prediction complexity associated with nucleotide sequence abnormalities in the SCN2A
P L Sokolov1, N V Chebanenko2, S A Tulupova2
1Scientific and Practical Center for Specialized Care for Children named after N.V. Voino-Yasenetsky, Moscow, Russia.
Abstract:
Numerous variants of the SCN2A gene have been identified, including missense mutations, deletions, insertions, frameshifting, nonsense mutations, and splice site mutations. The emergence of severe phenotypes is generally associated with de novo and missense variants. The clinical manifestations linked to SCN2A abnormalities exhibit considerable diversity, including varying severities of epileptic episodes with onset in neonatal or subsequent periods, autism spectrum disorders, schizophrenia (including catatonic manifestations), and episodic ataxia. With rare exceptions, all identified phenotypes are associated with developmental delay or regression. The phenotypic diversity associated with SCN2A genetic variants is influenced by the extensive expression of the gene in neuronal populations across various brain regions, its impact on numerous processes critical for the development and functionality of the central nervous system, the distinct localization of mutations within the gene, and the type of mutations (missense, nonsense, frameshift). Variants in nucleotide sequences may increase or decrease gene function (gain-of-function and loss-of-function, respectively) and are associated with ion channel activity influenced by neuroglial effects. An analysis of four cases of SCN2A genetic variants (one case shown to be associated with DENND5A) demonstrated a high efficacy in predicting phenotypes based on existing descriptions of nucleotide sequence abnormalities. However, predictions proved ineffective for similar mutations and for de novo mutations. It is concluded that advances in predicting the phenotypic outcomes of genomic abnormalities depend on the accumulation of clinical data and a thorough investigation of the molecular mechanisms governing gene function.
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