University of Khartoum

Computational analysis of single nucleotide polymorphisms in SCN1A gene of epilepsy, and implications in sodium

Computational analysis of single nucleotide polymorphisms in SCN1A gene of epilepsy, and implications in sodium

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Title: Computational analysis of single nucleotide polymorphisms in SCN1A gene of epilepsy, and implications in sodium
Author: Salama, H.; Hammad, E.; Alfaki, M.; Ezaldin, M.; . Salih, A
Abstract: Background: A transient ischemic attack (TIA) is a brief ischemic incident distinguished by rapid clinical improvement within 24 hours and no cerebral infarction. Objective: To assess the role of proinflammatory cytokines specially TNF-α and IL-6 polymorphisms as clinical predictors of recurrent TIA and subsequent stroke. Methods: one hundred and six participants (54 group 1 and 52 group 2) were enrolled with clinically resolved TIA and 34 (group 3) age-matched controls. DNA was extracted from blood samples of all subjects. Polymerase chain reaction for DNA amplification was done followed by digestion using NcoI and NIaIII restriction endonuclease enzymes for detection of promoter single nucleotide polymorphism (SNP) of TNFa-308GNA and IL-6 -174G/C respectively. Results: Molecular analysis showed significant increase in TNFa- 308GNA allele polymorphismin patients with high risk TIA (group 1) compared to both low risk (group 2) and control (group 3) groups [Odds ratio (95% confidence intervals): 3.3 (1.83–5.9), P = 0.0001 and 3.5 (1.85–6.79), P = 0.0001respectively] with significant increase of genotypes TNF-α − 308 AA [Odds ratio (95% confidence intervals): 10 (2.5- 3.2), p ≤ 0.05 and 8.5 (2.4- 30), p ≤ 0.05] was detected when compared to groups 2 and 3 respectively. IL6 allele polymorphism or genotypic distribution did not reveal any significance. Conclusion: TNFa-308GNA but not IL-6 -174G/C SNP plays a significant role in evaluating and predicting recurrent TIA with subsequent high risk of actual stroke development and in this manner may contribute to primary stroke prevention. doi:10.1016/j.jns.2015.09.025 1465 WFN15-1644 Late Breaking Abstract Session 1 Computational analysis of single nucleotide polymorphisms in SCN1A gene of epilepsy, and implications in sodium voltage gated channel function M. Alfaki, M. Ezaldin, A. Hassan, A. Salih, M. Taha, M. Abd Elmotalib, M. Abdelrahim, M. Dafaalla, A. Hussein, M. Hassan. Daoud Research Group, Africa City of Technology, Khartoum, Sudan Background: SCN1A is recognized as the most important epilepsy gene discovered to date. It encodes the alpha1 subunit of the voltage gated sodium channel. Objectives: Single nucleotide polymorphisms (SNPs) are by far the most prevalent of all DNA sequence variations. Therefore thiswork focused on analysis of SNPs in coding and 3’untranslated regions (3’ UTR). Materials and methods: 1279 non synonymous SNPs in coding region of SCN1A gene were analyzed concerning degree of structural and functional impact in protein product, as predicted by SIFT and polyphen-2 server. Then protein modeling was performed according to each damaging SNP by using Raptor X and Chimera 1.10.1. PolymiRTS software was used to investigate SNPs in 3’UTR. Results: Analysis with SIFT and polyphen-2 predicted 33 damaging SNPs out of total SNPs in coding region; nine of them are located in exon 30, and 20 SNPs were found in cytoplasm domains. These SNPs result in mutant amino acids which differ in their physiochemical properties from the wild type one. Among them 7 SNPs are located near highly conserved regions. Moreover, 14 of these SNPs affect the main activity of the protein. Analysis of 84 SNPs in 3’ UTR resulted in no SNPs which could disrupt miRNA site. Conclusion: The Large number of detected SNPs that could potentially affect SCN1A gene highlights the importance of such computational analysis, in order to contribute to the ability to recognize and diagnose epilepsy, and to find new treatment modalities
URI: http://khartoumspace.uofk.edu/123456789/25300


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