Novel Deleterious nsSNPs within MEFV Gene that Could Be Used as Diagnostic Markers to Predict Hereditary Familial Mediterranean Fever: Using Bioinformatics Analysis.

Q1 Biochemistry, Genetics and Molecular Biology

Advances in Bioinformatics Pub Date : 2019-06-04 eCollection Date: 2019-01-01 DOI:10.1155/2019/1651587

Mujahed I Mustafa, Tebyan A Abdelhameed, Fatima A Abdelrhman, Soada A Osman, Mohamed A Hassan

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Abstract

Background: Familial Mediterranean Fever (FMF) is the most common autoinflammatory disease (AID) affecting mainly the ethnic groups originating from Mediterranean basin. We aimed to identify the pathogenic SNPs in MEFV by computational analysis software.

Methods: We carried out in silico prediction of structural effect of each SNP using different bioinformatics tools to predict substitution influence on protein structure and function.

Result: 23 novel mutations out of 857 nsSNPs are found to have deleterious effect on the MEFV structure and function.

Conclusion: This is the first in silico analysis of MEFV gene to prioritize SNPs for further genetic mapping studies. After using multiple bioinformatics tools to compare and rely on the results predicted, we found 23 novel mutations that may cause FMF disease and it could be used as diagnostic markers for Mediterranean basin populations.

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MEFV基因内新的有害非单核苷酸多态性可作为预测遗传性家族性地中海热的诊断标记:应用生物信息学分析

背景:家族性地中海热(FMF)是最常见的自身炎症性疾病(AID)，主要影响地中海盆地地区的少数民族。我们的目的是通过计算分析软件鉴定MEFV的致病snp。方法:利用不同的生物信息学工具对每个SNP的结构效应进行计算机预测，预测替代对蛋白质结构和功能的影响。结果:857个非单核苷酸多态性中有23个突变对MEFV的结构和功能有不良影响。结论:这是MEFV基因的首次计算机分析，为进一步的遗传作图研究优先考虑snp。在使用多种生物信息学工具对预测结果进行比较和依赖后，我们发现了23个可能导致FMF疾病的新突变，并可作为地中海盆地人群的诊断标记。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Advances in Bioinformatics Biochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (miscellaneous)

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