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Assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory
BACKGROUND: The widespread clinical application of genome-wide sequencing has resulted in many new diagnoses for rare genetic conditions, but testing regularly identifies variants of uncertain significance (VUS). The remarkable rise in the amount of genomic data has been paralleled by a rise in the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308257/ https://www.ncbi.nlm.nih.gov/pubmed/35869530 http://dx.doi.org/10.1186/s13073-022-01082-2 |
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author | Caswell, Richard C. Gunning, Adam C. Owens, Martina M. Ellard, Sian Wright, Caroline F. |
author_facet | Caswell, Richard C. Gunning, Adam C. Owens, Martina M. Ellard, Sian Wright, Caroline F. |
author_sort | Caswell, Richard C. |
collection | PubMed |
description | BACKGROUND: The widespread clinical application of genome-wide sequencing has resulted in many new diagnoses for rare genetic conditions, but testing regularly identifies variants of uncertain significance (VUS). The remarkable rise in the amount of genomic data has been paralleled by a rise in the number of protein structures that are now publicly available, which may have clinical utility for the interpretation of missense and in-frame insertions or deletions. METHODS: Within a UK National Health Service genomic medicine diagnostic laboratory, we investigated the number of VUS over a 5-year period that were evaluated using protein structural analysis and how often this analysis aided variant classification. RESULTS: We found 99 novel missense and in-frame variants across 67 genes that were initially classified as VUS by our diagnostic laboratory using standard variant classification guidelines and for which further analysis of protein structure was requested. Evidence from protein structural analysis was used in the re-assessment of 64 variants, of which 47 were subsequently reclassified as pathogenic or likely pathogenic and 17 remained as VUS. We identified several case studies where protein structural analysis aided variant interpretation by predicting disease mechanisms that were consistent with the observed phenotypes, including loss-of-function through thermodynamic destabilisation or disruption of ligand binding, and gain-of-function through de-repression or escape from proteasomal degradation. CONCLUSIONS: We have shown that using in silico protein structural analysis can aid classification of VUS and give insights into the mechanisms of pathogenicity. Based on our experience, we propose a generic evidence-based workflow for incorporating protein structural information into diagnostic practice to facilitate variant classification. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-022-01082-2. |
format | Online Article Text |
id | pubmed-9308257 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-93082572022-07-24 Assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory Caswell, Richard C. Gunning, Adam C. Owens, Martina M. Ellard, Sian Wright, Caroline F. Genome Med Research BACKGROUND: The widespread clinical application of genome-wide sequencing has resulted in many new diagnoses for rare genetic conditions, but testing regularly identifies variants of uncertain significance (VUS). The remarkable rise in the amount of genomic data has been paralleled by a rise in the number of protein structures that are now publicly available, which may have clinical utility for the interpretation of missense and in-frame insertions or deletions. METHODS: Within a UK National Health Service genomic medicine diagnostic laboratory, we investigated the number of VUS over a 5-year period that were evaluated using protein structural analysis and how often this analysis aided variant classification. RESULTS: We found 99 novel missense and in-frame variants across 67 genes that were initially classified as VUS by our diagnostic laboratory using standard variant classification guidelines and for which further analysis of protein structure was requested. Evidence from protein structural analysis was used in the re-assessment of 64 variants, of which 47 were subsequently reclassified as pathogenic or likely pathogenic and 17 remained as VUS. We identified several case studies where protein structural analysis aided variant interpretation by predicting disease mechanisms that were consistent with the observed phenotypes, including loss-of-function through thermodynamic destabilisation or disruption of ligand binding, and gain-of-function through de-repression or escape from proteasomal degradation. CONCLUSIONS: We have shown that using in silico protein structural analysis can aid classification of VUS and give insights into the mechanisms of pathogenicity. Based on our experience, we propose a generic evidence-based workflow for incorporating protein structural information into diagnostic practice to facilitate variant classification. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-022-01082-2. BioMed Central 2022-07-22 /pmc/articles/PMC9308257/ /pubmed/35869530 http://dx.doi.org/10.1186/s13073-022-01082-2 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Caswell, Richard C. Gunning, Adam C. Owens, Martina M. Ellard, Sian Wright, Caroline F. Assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory |
title | Assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory |
title_full | Assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory |
title_fullStr | Assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory |
title_full_unstemmed | Assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory |
title_short | Assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory |
title_sort | assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9308257/ https://www.ncbi.nlm.nih.gov/pubmed/35869530 http://dx.doi.org/10.1186/s13073-022-01082-2 |
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