Comparison of Predictive In Silico Tools on Missense Variants in GJB2, GJB6, and GJB3 Genes Associated with Autosomal Recessive Deafness 1A (DFNB1A)‎

Joint Authors

Posukh, Olga L.
Pshennikova, Vera G.
Barashkov, Nikolay A.
Romanov, Georgii P.
Teryutin, Fedor M.
Solov’ev, Aisen V.
Gotovtsev, Nyurgun N.
Nikanorova, Alena A.
Nakhodkin, Sergey S.
Sazonov, Nikolay N.
Morozov, Igor V.
Bondar, Alexander A.
Dzhemileva, Lilya U.
Khusnutdinova, Elza K.
Fedorova, Sardana

Source

The Scientific World Journal

Issue

Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-9, 9 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2019-03-20

Country of Publication

Egypt

No. of Pages

9

Main Subjects

Medicine
Information Technology and Computer Science

Abstract EN

In silico predictive software allows assessing the effect of amino acid substitutions on the structure or function of a protein without conducting functional studies.

The accuracy of in silico pathogenicity prediction tools has not been previously assessed for variants associated with autosomal recessive deafness 1A (DFNB1A).

Here, we identify in silico tools with the most accurate clinical significance predictions for missense variants of the GJB2 (Cx26), GJB6 (Cx30), and GJB3 (Cx31) connexin genes associated with DFNB1A.

To evaluate accuracy of selected in silico tools (SIFT, FATHMM, MutationAssessor, PolyPhen-2, CONDEL, MutationTaster, MutPred, Align GVGD, and PROVEAN), we tested nine missense variants with previously confirmed clinical significance in a large cohort of deaf patients and control groups from the Sakha Republic (Eastern Siberia, Russia): Сх26: p.Val27Ile, p.Met34Thr, p.Val37Ile, p.Leu90Pro, p.Glu114Gly, p.Thr123Asn, and p.Val153Ile; Cx30: p.Glu101Lys; Cx31: p.Ala194Thr.

We compared the performance of the in silico tools (accuracy, sensitivity, and specificity) by using the missense variants in GJB2 (Cx26), GJB6 (Cx30), and GJB3 (Cx31) genes associated with DFNB1A.

The correlation coefficient (r) and coefficient of the area under the Receiver Operating Characteristic (ROC) curve as alternative quality indicators of the tested programs were used.

The resulting ROC curves demonstrated that the largest coefficient of the area under the curve was provided by three programs: SIFT (AUC = 0.833, p = 0.046), PROVEAN (AUC = 0.833, p = 0.046), and MutationAssessor (AUC = 0.833, p = 0.002).

The most accurate predictions were given by two tested programs: SIFT and PROVEAN (Ac = 89%, Se = 67%, Sp = 100%, r = 0.75, AUC = 0.833).

The results of this study may be applicable for analysis of novel missense variants of the GJB2 (Cx26), GJB6 (Cx30), and GJB3 (Cx31) connexin genes.

American Psychological Association (APA)

Pshennikova, Vera G.& Barashkov, Nikolay A.& Romanov, Georgii P.& Teryutin, Fedor M.& Solov’ev, Aisen V.& Gotovtsev, Nyurgun N.…[et al.]. 2019. Comparison of Predictive In Silico Tools on Missense Variants in GJB2, GJB6, and GJB3 Genes Associated with Autosomal Recessive Deafness 1A (DFNB1A). The Scientific World Journal،Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1211846

Modern Language Association (MLA)

Pshennikova, Vera G.…[et al.]. Comparison of Predictive In Silico Tools on Missense Variants in GJB2, GJB6, and GJB3 Genes Associated with Autosomal Recessive Deafness 1A (DFNB1A). The Scientific World Journal No. 2019 (2019), pp.1-9.
https://search.emarefa.net/detail/BIM-1211846

American Medical Association (AMA)

Pshennikova, Vera G.& Barashkov, Nikolay A.& Romanov, Georgii P.& Teryutin, Fedor M.& Solov’ev, Aisen V.& Gotovtsev, Nyurgun N.…[et al.]. Comparison of Predictive In Silico Tools on Missense Variants in GJB2, GJB6, and GJB3 Genes Associated with Autosomal Recessive Deafness 1A (DFNB1A). The Scientific World Journal. 2019. Vol. 2019, no. 2019, pp.1-9.
https://search.emarefa.net/detail/BIM-1211846

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1211846