Advances in BioinformaticsBioinformaticsPeer-reviewed journal article
Novel deleterious nsSNPs within MEFV gene that could be used as Diagnostic Markers to Predict Hereditary Familial Mediterranean Fever: Using bioinformatics analysis
Mujahed I. MustafaiD, Tebyan A. AbdelhameediD, Fatima A. AbdelrhmaniD, Soada Ahmed Osman, Mohamed Ahmed Salih HassaniD
Abstract
BackgroundFamilial Mediterranean Fever (FMF) is the most common auto inflammatory disease (AID) affecting mainly the ethnic groups originating from Mediterranean basin, we aimed to identify the pathogenic SNPs in MEFV by computational analysis software.\n\nMethodsWe carried out in silico prediction of structural effect of each SNP using different bioinformatics tools to predict substitution influence on protein structure and function.\n\nResult23 novel mutations out of 857 nsSNPs that are found to be deleterious effect on the MEFV structure and function.\n\nConclusionThis is the first in silico analysis in 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.
- organism: human
- assay: GWAS summary statistics
- research focus: variant effect prediction
- approach: statistical model
- Citations
- 6
- FWCI
- 0.60
- Field percentile
- top 34%
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