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Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy

BACKGROUND: International guidelines for variant interpretation in Mendelian disease set stringent criteria to report a variant as (likely) pathogenic, prioritising control of false-positive rate over test sensitivity and diagnostic yield. Genetic testing is also more likely informative in individua...

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Autores principales: Walsh, Roddy, Mazzarotto, Francesco, Whiffin, Nicola, Buchan, Rachel, Midwinter, William, Wilk, Alicja, Li, Nicholas, Felkin, Leanne, Ingold, Nathan, Govind, Risha, Ahmad, Mian, Mazaika, Erica, Allouba, Mona, Zhang, Xiaolei, de Marvao, Antonio, Day, Sharlene M., Ashley, Euan, Colan, Steven D., Michels, Michelle, Pereira, Alexandre C., Jacoby, Daniel, Ho, Carolyn Y., Thomson, Kate L., Watkins, Hugh, Barton, Paul J. R., Olivotto, Iacopo, Cook, Stuart A., Ware, James S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6350371/
https://www.ncbi.nlm.nih.gov/pubmed/30696458
http://dx.doi.org/10.1186/s13073-019-0616-z
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author Walsh, Roddy
Mazzarotto, Francesco
Whiffin, Nicola
Buchan, Rachel
Midwinter, William
Wilk, Alicja
Li, Nicholas
Felkin, Leanne
Ingold, Nathan
Govind, Risha
Ahmad, Mian
Mazaika, Erica
Allouba, Mona
Zhang, Xiaolei
de Marvao, Antonio
Day, Sharlene M.
Ashley, Euan
Colan, Steven D.
Michels, Michelle
Pereira, Alexandre C.
Jacoby, Daniel
Ho, Carolyn Y.
Thomson, Kate L.
Watkins, Hugh
Barton, Paul J. R.
Olivotto, Iacopo
Cook, Stuart A.
Ware, James S.
author_facet Walsh, Roddy
Mazzarotto, Francesco
Whiffin, Nicola
Buchan, Rachel
Midwinter, William
Wilk, Alicja
Li, Nicholas
Felkin, Leanne
Ingold, Nathan
Govind, Risha
Ahmad, Mian
Mazaika, Erica
Allouba, Mona
Zhang, Xiaolei
de Marvao, Antonio
Day, Sharlene M.
Ashley, Euan
Colan, Steven D.
Michels, Michelle
Pereira, Alexandre C.
Jacoby, Daniel
Ho, Carolyn Y.
Thomson, Kate L.
Watkins, Hugh
Barton, Paul J. R.
Olivotto, Iacopo
Cook, Stuart A.
Ware, James S.
author_sort Walsh, Roddy
collection PubMed
description BACKGROUND: International guidelines for variant interpretation in Mendelian disease set stringent criteria to report a variant as (likely) pathogenic, prioritising control of false-positive rate over test sensitivity and diagnostic yield. Genetic testing is also more likely informative in individuals with well-characterised variants from extensively studied European-ancestry populations. Inherited cardiomyopathies are relatively common Mendelian diseases that allow empirical calibration and assessment of this framework. METHODS: We compared rare variants in large hypertrophic cardiomyopathy (HCM) cohorts (up to 6179 cases) to reference populations to identify variant classes with high prior likelihoods of pathogenicity, as defined by etiological fraction (EF). We analysed the distribution of variants using a bespoke unsupervised clustering algorithm to identify gene regions in which variants are significantly clustered in cases. RESULTS: Analysis of variant distribution identified regions in which variants are significantly enriched in cases and variant location was a better discriminator of pathogenicity than generic computational functional prediction algorithms. Non-truncating variant classes with an EF ≥ 0.95 were identified in five established HCM genes. Applying this approach leads to an estimated 14–20% increase in cases with actionable HCM variants, i.e. variants classified as pathogenic/likely pathogenic that might be used for predictive testing in probands’ relatives. CONCLUSIONS: When found in a patient confirmed to have disease, novel variants in some genes and regions are empirically shown to have a sufficiently high probability of pathogenicity to support a “likely pathogenic” classification, even without additional segregation or functional data. This could increase the yield of high confidence actionable variants, consistent with the framework and recommendations of current guidelines. The techniques outlined offer a consistent and unbiased approach to variant interpretation for Mendelian disease genetic testing. We propose adaptations to ACMG/AMP guidelines to incorporate such evidence in a quantitative and transparent manner. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13073-019-0616-z) contains supplementary material, which is available to authorized users.
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spelling pubmed-63503712019-02-04 Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy Walsh, Roddy Mazzarotto, Francesco Whiffin, Nicola Buchan, Rachel Midwinter, William Wilk, Alicja Li, Nicholas Felkin, Leanne Ingold, Nathan Govind, Risha Ahmad, Mian Mazaika, Erica Allouba, Mona Zhang, Xiaolei de Marvao, Antonio Day, Sharlene M. Ashley, Euan Colan, Steven D. Michels, Michelle Pereira, Alexandre C. Jacoby, Daniel Ho, Carolyn Y. Thomson, Kate L. Watkins, Hugh Barton, Paul J. R. Olivotto, Iacopo Cook, Stuart A. Ware, James S. Genome Med Research BACKGROUND: International guidelines for variant interpretation in Mendelian disease set stringent criteria to report a variant as (likely) pathogenic, prioritising control of false-positive rate over test sensitivity and diagnostic yield. Genetic testing is also more likely informative in individuals with well-characterised variants from extensively studied European-ancestry populations. Inherited cardiomyopathies are relatively common Mendelian diseases that allow empirical calibration and assessment of this framework. METHODS: We compared rare variants in large hypertrophic cardiomyopathy (HCM) cohorts (up to 6179 cases) to reference populations to identify variant classes with high prior likelihoods of pathogenicity, as defined by etiological fraction (EF). We analysed the distribution of variants using a bespoke unsupervised clustering algorithm to identify gene regions in which variants are significantly clustered in cases. RESULTS: Analysis of variant distribution identified regions in which variants are significantly enriched in cases and variant location was a better discriminator of pathogenicity than generic computational functional prediction algorithms. Non-truncating variant classes with an EF ≥ 0.95 were identified in five established HCM genes. Applying this approach leads to an estimated 14–20% increase in cases with actionable HCM variants, i.e. variants classified as pathogenic/likely pathogenic that might be used for predictive testing in probands’ relatives. CONCLUSIONS: When found in a patient confirmed to have disease, novel variants in some genes and regions are empirically shown to have a sufficiently high probability of pathogenicity to support a “likely pathogenic” classification, even without additional segregation or functional data. This could increase the yield of high confidence actionable variants, consistent with the framework and recommendations of current guidelines. The techniques outlined offer a consistent and unbiased approach to variant interpretation for Mendelian disease genetic testing. We propose adaptations to ACMG/AMP guidelines to incorporate such evidence in a quantitative and transparent manner. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s13073-019-0616-z) contains supplementary material, which is available to authorized users. BioMed Central 2019-01-29 /pmc/articles/PMC6350371/ /pubmed/30696458 http://dx.doi.org/10.1186/s13073-019-0616-z Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research
Walsh, Roddy
Mazzarotto, Francesco
Whiffin, Nicola
Buchan, Rachel
Midwinter, William
Wilk, Alicja
Li, Nicholas
Felkin, Leanne
Ingold, Nathan
Govind, Risha
Ahmad, Mian
Mazaika, Erica
Allouba, Mona
Zhang, Xiaolei
de Marvao, Antonio
Day, Sharlene M.
Ashley, Euan
Colan, Steven D.
Michels, Michelle
Pereira, Alexandre C.
Jacoby, Daniel
Ho, Carolyn Y.
Thomson, Kate L.
Watkins, Hugh
Barton, Paul J. R.
Olivotto, Iacopo
Cook, Stuart A.
Ware, James S.
Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy
title Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy
title_full Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy
title_fullStr Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy
title_full_unstemmed Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy
title_short Quantitative approaches to variant classification increase the yield and precision of genetic testing in Mendelian diseases: the case of hypertrophic cardiomyopathy
title_sort quantitative approaches to variant classification increase the yield and precision of genetic testing in mendelian diseases: the case of hypertrophic cardiomyopathy
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6350371/
https://www.ncbi.nlm.nih.gov/pubmed/30696458
http://dx.doi.org/10.1186/s13073-019-0616-z
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