Dataset Information

In Silico Study of Correlation between Missense Variations of F8 Gene and Inhibitor Formation in Severe Hemophilia A

ABSTRACT: Objective:Deleterious substitutions of the F8 gene are responsible for causing hemophilia A, which is an inherited bleeding disorder resulting from reduced or absent activity of the coagulant protein factor VIII (FVIII). The most important complication in treatment is inhibitor development toward therapeutic factor VIII. In this study, we aimed to analyze the effects of deleterious substitutions in the F8 gene upon protein structure and function. Materials and Methods:All tests were conducted by computational methods from the CHAMP (CDC Hemophilia A Mutation Project) database. We performed an in silico analysis of deleterious variations using five software programs, Sift, PolyPhen-2, Align-GVGD, KD4v, and MutationTaster, in order to analyze the correlation between variation and the disease. We also studied the correlation between these variations and inhibitor formation. Results:Our analysis showed that these in silico tools are coherent and that there are more variations in the A than the C domains. Moreover, we noticed that there are more deleterious variations than neutral variations in each of the A and C domains. We also found that 13.51% of the patients suffered from a severe form of hemophilia A and that carriers of missense variations developed inhibitors. Also, for the first time, we determined that variation nature is not associated with inhibitor formation. Furthermore, this analysis showed that the risk of developing inhibitors increases when the variation causes a change of amino acid class. Conclusion:This study will help to correctly associate variations with inhibitor development and aid in early characterization of novel variants.

SUBMITTER: Fodil M

PROVIDER: S-EPMC7236410 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature

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In Silico Study of Correlation between Missense Variations of <i>F8</i> Gene and Inhibitor Formation in Severe Hemophilia A

Fodil Mostefa M Zemani Faouzia F

Turkish journal of haematology : official journal of Turkish Society of Haematology 20191226 2

<h4>Objective</h4>Deleterious substitutions of the <i>F8</i> gene are responsible for causing hemophilia A, which is an inherited bleeding disorder resulting from reduced or absent activity of the coagulant protein factor VIII (FVIII). The most important complication in treatment is inhibitor development toward therapeutic factor VIII. In this study, we aimed to analyze the effects of deleterious substitutions in the <i>F8</i> gene upon protein structure and function.<h4>Materials and methods</h ...[more]

PMID: 31876401

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Project description:BackgroundMissense mutations in the first five exons of F9, which encodes factor FIX, represent 40% of all mutations that cause hemophilia B. To address the ongoing debate regarding in silico identification of disease-causing mutations at these exons, we analyzed 215 missense mutations from www.factorix.org using six in silico prediction tools, which are the most common used programs for analysis prediction of impact of mutations on the protein structure and function, with further advantage of using similar approaches. We developed different algorithms to integrate multiple predictions from such tools. In order to approach a structural analysis on FIX we performed a modeling of five selected pathogenic mutations.ResultsSIFT, PolyPhen-2 HumDiv, SNAP2, and MutationAssessor were the most successful in identifying true non-causative and causative mutations. A proposed function integrating these algorithms (wgP4) was the most sensitive (90.1%), specific (22.6%), and accurate (87%) than similar functions, and identified 187 variants as deleterious. Clinical phenotype was significantly associated with predicted causative mutations at all five exons. However, PolyPhen-2 HumDiv was more successful in linking clinical severity to specific exons, while functions that integrate 4-6 predictions were more successful in linking phenotype to genotypes at the light chain (exons 3-5). The most important value of integrating multiple predictions is the inclusion of scores derived from different approaches. Modeling of protein structure showed the effects of pathogenic nsSNPs on structure and function of FIX.ConclusionsA simple function that integrates information from different in silico programs yields the best prediction of mutated phenotypes. However, the specificity, sensitivity, and accuracy of genotype-phenotype predictions depend on specific characteristics of the protein domain and the disease of interest as we validated by the structural analysis of selected pathogenic F9 mutations. The proposed function integrating algorithm (wgP4) might be useful for the analysis of nsSNPs impact on other genes.

Dataset Information

In Silico Study of Correlation between Missense Variations of F8 Gene and Inhibitor Formation in Severe Hemophilia A

Publications

In Silico Study of Correlation between Missense Variations of <i>F8</i> Gene and Inhibitor Formation in Severe Hemophilia A

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