Physicochemical property changes of amino acid residues that accompany missense mutations in SCN1A affect epilepsy phenotype severity. Issue 10 (7th July 2009)

• Record Type: Journal Article
• Authors: Kanai, K; Yoshida, S; Hirose, S; Oguni, H; Kuwabara, S; Sawai, S; Hiraga, A; Fukuma, G; Iwasa, H; Kojima, T; Kaneko, S
• Is Part Of: Journal of medical genetics. Volume 46:Issue 10(2009)
• Page Start: 671
• Page End: 679
• Publication Date: 2009-07-07
• Subjects: Medical genetics -- Periodicals; 616.042
• DOI: 10.1136/jmg.2008.060897
• Languages: English
• ISSNs: 1468-6244

Abstract

Abstract : Background: Several different missense mutations in the voltage-gated sodium channel subunit gene SCN1A have been identified in epileptic patients with benign phenotype and patients with severe phenotype. However, the reason why similar missense mutations in SCN1A result in different phenotypes has not yet been fully clarified. Objective: To clarify the phenotype–genotype relationship in SCN1A, a meta-analysis was performed to quantitatively determine the effect of amino acid substitutions in SCN1A on epilepsy severity phenotype using physicochemical property indices of the amino acid, and to discuss in the context of the molecular evolution of the proteins. Methods: PubMed was searched for articles and information was extracted on localisation and types of SCN1A missense mutations in patients with benign and severe epileptic syndromes; detailed information was also extracted. Results: Meta-analysis quantitatively revealed that the physicochemical properties of several amino acids significantly affected epilepsy phenotype severity. It showed that missense mutations that decreased protein hydrophobicity were significantly associated with severe epilepsy phenotypes. It also showed that the phenotype severity of SCN1A missense mutations in the transmembrane domains of SCN1A (128/155; 82.6%) could be predicted with high sensitivity and positive predictive values using the physicochemical property changes, indicating the possibility of phenotype prediction for entirely new missense mutations using analytical methods. Conclusions: The results show that changes in the physicochemical properties of amino acids affected both the phenotype and clinical symptoms of patients with SCN1A missense mutations. This meta-analysis study provides new insights into SCN1A gene functions and a new strategy for genetic diagnosis, genetic counselling and epilepsy treatment.