Mujahed I Mustafa, Tebyan A Abdelhameed, Fatima A Abdelrhman, Soada A Osman, Mohamed A Hassan
{"title":"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","authors":"Mujahed I Mustafa, Tebyan A Abdelhameed, Fatima A Abdelrhman, Soada A Osman, Mohamed A Hassan","doi":"10.1155/2019/1651587","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Result: </strong>23 novel mutations out of 857 nsSNPs are found to have deleterious effect on the MEFV structure and function.</p><p><strong>Conclusion: </strong>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.</p>","PeriodicalId":39059,"journal":{"name":"Advances in Bioinformatics","volume":"2019 ","pages":"1651587"},"PeriodicalIF":0.0000,"publicationDate":"2019-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1155/2019/1651587","citationCount":"0","resultStr":"{\"title\":\"Novel Deleterious nsSNPs within <i>MEFV</i> Gene that Could Be Used as Diagnostic Markers to Predict Hereditary Familial Mediterranean Fever: Using Bioinformatics Analysis.\",\"authors\":\"Mujahed I Mustafa, Tebyan A Abdelhameed, Fatima A Abdelrhman, Soada A Osman, Mohamed A Hassan\",\"doi\":\"10.1155/2019/1651587\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Result: </strong>23 novel mutations out of 857 nsSNPs are found to have deleterious effect on the MEFV structure and function.</p><p><strong>Conclusion: </strong>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.</p>\",\"PeriodicalId\":39059,\"journal\":{\"name\":\"Advances in Bioinformatics\",\"volume\":\"2019 \",\"pages\":\"1651587\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1155/2019/1651587\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Advances in Bioinformatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1155/2019/1651587\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2019/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"Biochemistry, Genetics and Molecular Biology\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Advances in Bioinformatics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1155/2019/1651587","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2019/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"Biochemistry, Genetics and Molecular Biology","Score":null,"Total":0}
Novel Deleterious nsSNPs within MEFV Gene that Could Be Used as Diagnostic Markers to Predict Hereditary Familial Mediterranean Fever: Using Bioinformatics Analysis.
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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