Informative parameters of predictive in silico computer programs in assessing clinical significance of missense variants of GJB2 (Cx26) gene

Currently, in the HGMD database (The Human Gene Mutation Database) in the GJB2 gene, coding protein connexin 26 (Cx26), 390 different nucleotide changes have been announced, most of which are associated with deafness, of which 73% are single nucleotide (missense/ nonsense) variants. The pathogenetic role of most nonsense substitutions is obvious, as they lead to premature termination of translation and interruption of protein synthesis. It is more difficult to assess the mechanism of action of the missens replacement on protein, since they may have a damaging/partially damaging or neutral effect, depending on the location in the amino acid sequence of the polypeptide chain. To assess the possible effect of amino acid substitutions on the structure and/or function of the protein, in the absence of structural and functional studies, the in silico prognostic method is used, which is completely performed by simulation computer programs. In this study, based on the established clinical significance, 7 missense variants of the GJB2 gene, detected as a result of the molecular genetics study of congenital deafness in Yakutia, 9 computer in silico predictive programs were tested. In order to identify the program with the most accurate prediction of the clinical significance of missense variants substitutions of the GJB2 gene, a comparative analysis of the informative parameters (accuracy, sensitivity and specificity) was carried out with the calculation of the correlation coefficient between the known clinical values of missense variants with in silico evaluation by the programs. In total, of the 9 analyzed programs, the most accurate in silico predictive estimates of the clinical significance of missense variants of the GJB2 gene were given by two programs - SIFT and PROVEAN (R = 0,73). The results obtained can help in carrying out bioinformatic analysis, in the case of detection of missense variants substitutions of the GJB2 gene, which were not described before in the literature.

1. GJB2 mutation spectrum in patients with congenital hearing loss in Yakutia / V.G. Pshennikova, N.A. Barashkov, F.M. Teryutin [et al.] // Russ. J. Med. Genetics. – 2015. – Vol. 6 (156). – P. 10-23.

2. A method and server for predicting damaging missense mutations / I.A. Adzhubei, S. Schmidt, L. Peshkin [et al.] // Nat. Methods. – 2010. – Vol. 7(4). – P. 248-249.

3. Automated inference of molecular mechanisms of disease from amino acid substitutions / B. Li, V.G. Krishnan, M.E. Mort. // Bioinformatics. – 2009. – Vol. 25(21). – Р. 2744-50. doi: 10.1093/bioinformatics/btp528

4. Assessment of in silico protein sequence analysis in the clinical classification of variants in cancer risk genes / I.D. Kerr, H.C. Cox, K. Moyes [et al.] // J Community Genet. – 2017. – Vol. 8(2). – Р. 87-95. doi: 10.1007/s12687-016-0289-x

5. Calibration of multiple in silico tools for predicting pathogenicity of mismatch repair gene missense substitutions / B.A. Thompson, M.S. Greenblatt, M.P. Vallee [et al.] // Hum Mutat. – 2013. – Vol. 34(1). – P. 255-65. doi: 10.1002/humu.22214

6. Choi Y. PROVEAN web server: a tool to predict the functional effect of amino acid substitutions and indels / Y. Choi, A.P. Chan // Bioinformatics. – 2015. – Vol. 31(16). – Р. 2745-2747.

7. Comparison and integration of deleteriousness prediction methods for nonsynonymous SNVs in whole exome sequencing studies / C. Dong, P. Wei, X. Jian [et al.] // Hum Mol Genet. – 2015. – Vol. 24(8). – Р. 2125-21237. doi: 10.1093/hmg/ddu733

8. Comprehensive statistical study of 452 BRCA1 missense substitutions with classification of eightrecurrent substitutions as neutral / S.V. Tavtigian, A.M. Deffenbaugh, L. Yin [et al.] // J Med Genet. – 2006. – Vol. 43(4). – Р. 295-305.

9. Computational approaches for predicting the biological effect of p53 missense mutations: a comparison of three sequence analysis based methods / E. Mathe, M. Olivier, S. Kato [et al.] // Nucleic Acids Res. – 2006. – Vol. 34(5). – Р. 1317-1325.

10. dbNSFP v3.0: A One-Stop Database of Functional Predictions and Annotations for Human Nonsynonymous and Splice-Site SNVs / X. Liu, C. Wu, C. Li [et al.] // Hum Mutat. – 2016. – Vol. 37(3). – Р. 235-241. doi: 10.1002/humu.22932

11. González-Pérez A. Improving the assessment of the outcome of nonsynonymous SNVs with a consensus deleteriousness score, Condel / A. González-Pérez, N. López-Bigas // Am J Hum Genet. – 2011. – Vol. 88(4). – Р. 440-449. doi: 10.1016/j.ajhg.2011.03.004

12. Kumar P. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm / P. Kumar, S. Henikoff, P.C. Ng // Nat Protoc. – 2009. – Vol. 4(7). – Р. 1073-1081.

13. Matthews B.W. Comparison of the predicted and observed secondary structure of T4 phage lysozyme / B.W. Matthews // J. Biochim Biophys Acta – 1975. – Vol. 405. – Р. 442-451.

14. MutationTaster evaluates disease-causing potential of sequence alterations / J.M. Schwarz, C. Rödelsperger, M. Schuelke [et al.] // Nat Methods. – 2010. – Vol. 7(8). – P. 575-576.

15. MutationTaster2: mutation prediction for the deep-sequencing age / J.M. Schwarz, D.N. Cooper, M. Schuelke, D. Seelow // Nat Methods. – 2014. – Vol. 11(4). – Р. 361-362. doi: 10.1038/nmeth.2890

16. Ng P.C. Predicting Deleterious Amino Acid Substitutions / P.C. Ng, S. Henikoff // Genome Res. – 2001. – Vol. 11(5). – Р. 863-874.

17. Ng P.C. Accounting for Human Polymorphisms Predicted to Affect Protein Function / P.C. Ng, S. Henikoff // Genome Res. – 2002. – Vol. 12(3). – Р. 436-446.

18. Ng P.C. SIFT: predicting amino acid changes that affect protein function / P.C. Ng, S. Henikoff // Nucleic Acids Res. – 2003. – Vol. 31(13). – Р. 3812-3814.

19. Ng P.C. Predicting the Effects of Amino Acid Substitutions on Protein Function / P.C. Ng, S. Henikoff // Annu Rev Genomics Hum Genet. – 2006. – Vol. 7. – Р. 61-80.

20. Schiemann A.H. Comparison of pathogenicity prediction tools on missense variants in RYR1 and CACNA1S associated with malignant hyperthermia / A.H. Schiemann, K.M. Stowell // Br J Anaesth. – 2016. – Vol. 117(1). – P. 124-128. doi: 10.1093/bja/aew065.

21. Spectrum and Frequency of the GJB2 Gene Pathogenic Variants in a Large Cohort of Patients with Hearing Impairment Living in a Subarctic Region of Russia (the Sakha Republic) / N.A. Barashkov, V.G. Pshennikova, O.L. Posukh [et al.] // PLoS One. – 2016. – Vol. 11(5):e0156300. doi: 10.1371/journal.pone.0156300.

22. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology / S. Richards, N. Aziz, S. Bale [et al]; ACMG Laboratory Quality Assurance Committee // Genet Med. – 2015. – Vol. 17(5). – Р. 405-24. doi: 10.1038/gim.2015.30.

23. Thusberg J. Performance of mutation pathogenicity prediction methods on missense variants / J. Thusberg, A. Olatubosun, M. Vihinen // Hum Mutat. – 2011. – Vol. 32(4). – Р. 358-368. doi: 10.1002/humu.21445.

24. Predicting the functional effect of amino acid substitutions and indels / Y. Choi, G.E. Sims, S. Murphy [et al.] // PLoS One. – 2012. – Vol. 7(10):e46688. doi: 10.1371/journal.pone.0046688.

25. Predicting the functional, molecular, and phenotypic consequences of amino acid substitutions using hidden Markov models / H.A. Shihab, J. Gough, D.N. Cooper [et al.] // Hum Mutat. – 2013. – Vol. 34(1). – Р. 57-65. doi: 10.1002/humu.22225.

26. Ranking Non-Synonymous Single Nucleotide Polymorphisms based on Disease Concepts / H.A. Shihab, J. Gough, M. Mort [et al.] // Human Genomics. – 2014. – Vol. 8. – Р. 11. doi: 10.1186/1479-7364-8-11.

27. Reva B. Determinants of protein function revealed by combinatorial entropy optimization / B. Reva, Y. Antipin, C. Sander // Genome Biol. – 2007. – Vol. – 8(11). – P. 232.

28. Reva B. Predicting the functional impact of protein mutations: application to cancer genomics / B. Reva, Y. Antipin, C. Sander // Nucleic Acids Res. – 2011. – Vol. 39(17). – Р. 118. doi: 10.1093/nar/gkr407.

29. Van Camp G. Hereditary Hearing Loss Homepage: URL: http://hereditaryhearingloss.org, 2016 / G. Van Camp, R.J.H. Smith.

30. Variability in pathogenicity prediction programs: impact on clinical diagnostics / L.C. Walters-Sen, S. Hashimoto, D.L. Thrush [et al.] // Mol Genet Genomic Med. – 2015. – Vol. 3(2). – Р. 99-110. doi: 10.1002/mgg3.116.

31. Yilmaz A. Bioinformatic Analysis of GJB2 Gene Missense Mutations / A. Yilmaz // Cell Biochem Biophys. – 2015. – Vol. 71(3). – Р. 1623-1642. doi: 10.1007/s12013-014-0385-7