Cargando…

Using Structural Analysis In Silico to Assess the Impact of Missense Variants in MEN1

Despite the rapid expansion in recent years of databases reporting either benign or pathogenic genetic variations, the interpretation of novel missense variants remains challenging, particularly for clinical or genetic testing laboratories where functional analysis is often unfeasible. Previous stud...

Descripción completa

Detalles Bibliográficos
Autores principales: Caswell, Richard C, Owens, Martina M, Gunning, Adam C, Ellard, Sian, Wright, Caroline F
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Endocrine Society 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6846327/
https://www.ncbi.nlm.nih.gov/pubmed/31737856
http://dx.doi.org/10.1210/js.2019-00260
_version_ 1783468859623211008
author Caswell, Richard C
Owens, Martina M
Gunning, Adam C
Ellard, Sian
Wright, Caroline F
author_facet Caswell, Richard C
Owens, Martina M
Gunning, Adam C
Ellard, Sian
Wright, Caroline F
author_sort Caswell, Richard C
collection PubMed
description Despite the rapid expansion in recent years of databases reporting either benign or pathogenic genetic variations, the interpretation of novel missense variants remains challenging, particularly for clinical or genetic testing laboratories where functional analysis is often unfeasible. Previous studies have shown that thermodynamic analysis of protein structure in silico can discriminate between groups of benign and pathogenic missense variants. However, although structures exist for many human disease‒associated proteins, such analysis remains largely unexploited in clinical laboratories. Here, we analyzed the predicted effect of 338 known missense variants on the structure of menin, the MEN1 gene product. Results provided strong discrimination between pathogenic and benign variants, with a threshold of >4 kcal/mol for the predicted change in stability, providing a strong indicator of pathogenicity. Subsequent analysis of seven novel missense variants identified during clinical testing of patients with MEN1 showed that all seven were predicted to destabilize menin by >4 kcal/mol. We conclude that structural analysis provides a useful tool in understanding the effect of missense variants in MEN1 and that integration of proteomic with genomic data could potentially contribute to the classification of novel variants in this disease.
format Online
Article
Text
id pubmed-6846327
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Endocrine Society
record_format MEDLINE/PubMed
spelling pubmed-68463272019-11-15 Using Structural Analysis In Silico to Assess the Impact of Missense Variants in MEN1 Caswell, Richard C Owens, Martina M Gunning, Adam C Ellard, Sian Wright, Caroline F J Endocr Soc Research Articles Despite the rapid expansion in recent years of databases reporting either benign or pathogenic genetic variations, the interpretation of novel missense variants remains challenging, particularly for clinical or genetic testing laboratories where functional analysis is often unfeasible. Previous studies have shown that thermodynamic analysis of protein structure in silico can discriminate between groups of benign and pathogenic missense variants. However, although structures exist for many human disease‒associated proteins, such analysis remains largely unexploited in clinical laboratories. Here, we analyzed the predicted effect of 338 known missense variants on the structure of menin, the MEN1 gene product. Results provided strong discrimination between pathogenic and benign variants, with a threshold of >4 kcal/mol for the predicted change in stability, providing a strong indicator of pathogenicity. Subsequent analysis of seven novel missense variants identified during clinical testing of patients with MEN1 showed that all seven were predicted to destabilize menin by >4 kcal/mol. We conclude that structural analysis provides a useful tool in understanding the effect of missense variants in MEN1 and that integration of proteomic with genomic data could potentially contribute to the classification of novel variants in this disease. Endocrine Society 2019-09-27 /pmc/articles/PMC6846327/ /pubmed/31737856 http://dx.doi.org/10.1210/js.2019-00260 Text en Copyright © 2019 Endocrine Society https://creativecommons.org/licenses/by/4.0/ This article has been published under the terms of the Creative Commons Attribution License (CC BY; https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Copyright for this article is retained by the author(s).
spellingShingle Research Articles
Caswell, Richard C
Owens, Martina M
Gunning, Adam C
Ellard, Sian
Wright, Caroline F
Using Structural Analysis In Silico to Assess the Impact of Missense Variants in MEN1
title Using Structural Analysis In Silico to Assess the Impact of Missense Variants in MEN1
title_full Using Structural Analysis In Silico to Assess the Impact of Missense Variants in MEN1
title_fullStr Using Structural Analysis In Silico to Assess the Impact of Missense Variants in MEN1
title_full_unstemmed Using Structural Analysis In Silico to Assess the Impact of Missense Variants in MEN1
title_short Using Structural Analysis In Silico to Assess the Impact of Missense Variants in MEN1
title_sort using structural analysis in silico to assess the impact of missense variants in men1
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6846327/
https://www.ncbi.nlm.nih.gov/pubmed/31737856
http://dx.doi.org/10.1210/js.2019-00260
work_keys_str_mv AT caswellrichardc usingstructuralanalysisinsilicotoassesstheimpactofmissensevariantsinmen1
AT owensmartinam usingstructuralanalysisinsilicotoassesstheimpactofmissensevariantsinmen1
AT gunningadamc usingstructuralanalysisinsilicotoassesstheimpactofmissensevariantsinmen1
AT ellardsian usingstructuralanalysisinsilicotoassesstheimpactofmissensevariantsinmen1
AT wrightcarolinef usingstructuralanalysisinsilicotoassesstheimpactofmissensevariantsinmen1