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Contemporary Insights Into the Genetics of Hypertrophic Cardiomyopathy: Toward a New Era in Clinical Testing?

Mazzarotto, Francesco, Olivotto, Iacopo, Boschi, Beatrice, Girolami, Francesca, Poggesi, Corrado, Barton, Paul J. R., Walsh, Roddy·2020·Journal of the American Heart Association
DOI 10.1161/jaha.119.015473PMC PMC7428545
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Abstract

Genetic testing for hypertrophic cardiomyopathy ( HCM ) is an established clinical technique, supported by 30 years of research into its genetic etiology. Although pathogenic variants are often detected in patients and used to identify at‐risk relatives, the effectiveness of genetic testing has been hampered by ambiguous genetic associations (yielding uncertain and potentially false‐positive results), difficulties in classifying variants, and uncertainty about genotype‐negative patients. Recent case‐control studies on rare variation, improved data sharing, and meta‐analysis of case cohorts contributed to new insights into the genetic basis of HCM . In particular, although research into new genes and mechanisms remains essential, reassessment of Mendelian genetic associations in HCM argues that current clinical genetic testing should be limited to a small number of validated disease genes that yield informative and interpretable results. Accurate and consistent variant interpretation has benefited from new standardized variant interpretation guidelines and innovative approaches to improve classification. Most cases lacking a pathogenic variant are now believed to indicate non‐Mendelian HCM , with more benign prognosis and minimal risk to relatives. Here, we discuss recent advances in the genetics of HCM and their application to clinical genetic testing together with practical issues regarding implementation. Although this review focuses on HCM , many of the issues discussed are also relevant to other inherited cardiac diseases.

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Figure 1 Examples of molecular complexes and proteins of the cardiomyocyte encoded by genes associated with sarcomeric HCM, its mimics and syndromic conditions featuring HCM with different levels of supporting evidence. Strength of evidence in favor of pathogenicity (top right panel) is coded as in the curation effort by the ClinGen consortium.48 Details about genetic associations for definitive genes displayed in the bottom left and bottom right panel, and genes with ≥ moderate supportive evidence are provided in Tables 1, 2 through 3. HCM, hypertrophic cardiomyopathy.
Figure 1 Examples of molecular complexes and proteins of the cardiomyocyte encoded by genes associated with sarcomeric HCM, its mimics and syndromic conditions featuring HCM with different levels of supporting evidence. Strength of evidence in favor of pathogenicity (top right panel) is coded as in the curation effort by the ClinGen consortium.48 Details about genetic associations for definitive genes displayed in the bottom left and bottom right panel, and genes with ≥ moderate supportive evidence are provided in Tables 1, 2 through 3. HCM, hypertrophic cardiomyopathy.CC BY · PubMed Central
Figure 2 Number of genes implicated in HCM in the literature with different levels of supporting evidence (black line, left y axis) ranging from fully validated genes (darker green line) to those without substantial evidence supporting pathogenicity. The black line indicates the number of scientific publications in PubMed featuring next‐generation sequencing (colored lines, right y axis). The classification criteria for evidence in favor of pathogenicity (as detailed in the legend) and the genes included (n=39) reflect the analysis and curation effort by Walsh et al.49 HCM, hypertrophic cardiomyopathy; and NGS, next‐generation sequencing.
Figure 2 Number of genes implicated in HCM in the literature with different levels of supporting evidence (black line, left y axis) ranging from fully validated genes (darker green line) to those without substantial evidence supporting pathogenicity. The black line indicates the number of scientific publications in PubMed featuring next‐generation sequencing (colored lines, right y axis). The classification criteria for evidence in favor of pathogenicity (as detailed in the legend) and the genes included (n=39) reflect the analysis and curation effort by Walsh et al.49 HCM, hypertrophic cardiomyopathy; and NGS, next‐generation sequencing.CC BY · PubMed Central
Figure 3 Proposal for a tiered approach to genetic testing in HCM. Initial testing is restricted to validated HCM genes using either a targeted gene panel or a virtual panel by focused analysis of WGS or WES data. The latter allows for reanalysis of genes subsequently linked to HCM, and WGS can detect additional variant classes including CNVs and deep intronic splice variants, though sequencing coverage is likely to be inferior to targeted panel sequencing. In the case of negative results, variant prioritization in the research setting can aid identification of the causative variant, directly translating into a diagnostic finding. The likelihood of detecting variation in novel genes with broader WGS/WES analysis depends on the profile of the patient and family being tested. In general, large pedigrees informative for segregation and trios (affected child with unaffected parents, indicating likely de novo variant occurrence or recessive inheritance) can enable filtering to a manageably small number of potentially causative variants for detailed evaluation. CNV, copy number variant; HCM, hypertrophic cardiomyopathy; WES, whole‐exome sequencing; and WGS, whole‐genome sequencing.
Figure 3 Proposal for a tiered approach to genetic testing in HCM. Initial testing is restricted to validated HCM genes using either a targeted gene panel or a virtual panel by focused analysis of WGS or WES data. The latter allows for reanalysis of genes subsequently linked to HCM, and WGS can detect additional variant classes including CNVs and deep intronic splice variants, though sequencing coverage is likely to be inferior to targeted panel sequencing. In the case of negative results, variant prioritization in the research setting can aid identification of the causative variant, directly translating into a diagnostic finding. The likelihood of detecting variation in novel genes with broader WGS/WES analysis depends on the profile of the patient and family being tested. In general, large pedigrees informative for segregation and trios (affected child with unaffected parents, indicating likely de novo variant occurrence or recessive inheritance) can enable filtering to a manageably small number of potentially causative variants for detailed evaluation. CNV, copy number variant; HCM, hypertrophic cardiomyopathy; WES, whole‐exome sequencing; and WGS, whole‐genome sequencing.CC BY · PubMed Central
Figure 4 Variant interpretation guidelines issued by the ACMG/AMP and independent laboratories/societies/associations (below the timeline) and some of the main resources contributing to a finer interpretation of sequence variants (above the timeline) as they became available. Several sequence variation databases with a focus on variants’ role in disease were released in time, particularly in the late 1990s (eg, the Human Gene Mutation Database in 1996) but also in more recent years (eg, ClinVar in 2013). The advent of cost‐effective, high‐throughput NGS in the years between 2005 and 2010 enabled the establishment of progressively large genome‐wide population variation databases, starting with the Pilot data set of the 1000 Genomes Project in 2009. All these increasingly complex and large‐scale resources on one hand allow a much more detailed characterization of genetic variants, but on the other contribute to the constant growth in the variability and quantity of data types and information on single variants, variant classes, and genes and require increasingly articulated guidelines for variant interpretation. Several efforts are in place to finely tune variant interpretation in a gene‐ and disease‐specific manner (eg, gene curation efforts such as ClinGen,80 established in 2015) and to render interpretation easier and quicker for the geneticist with automated variant interpretation tools (eg, CardioClassifier92 and CardioVAI,93 that interpret variants in the context of cardiomyopathies). ACMG, American College of Medical Genetics; AMP, Association for Molecular Pathology; and NGS, next‐generation sequencing.
Figure 4 Variant interpretation guidelines issued by the ACMG/AMP and independent laboratories/societies/associations (below the timeline) and some of the main resources contributing to a finer interpretation of sequence variants (above the timeline) as they became available. Several sequence variation databases with a focus on variants’ role in disease were released in time, particularly in the late 1990s (eg, the Human Gene Mutation Database in 1996) but also in more recent years (eg, ClinVar in 2013). The advent of cost‐effective, high‐throughput NGS in the years between 2005 and 2010 enabled the establishment of progressively large genome‐wide population variation databases, starting with the Pilot data set of the 1000 Genomes Project in 2009. All these increasingly complex and large‐scale resources on one hand allow a much more detailed characterization of genetic variants, but on the other contribute to the constant growth in the variability and quantity of data types and information on single variants, variant classes, and genes and require increasingly articulated guidelines for variant interpretation. Several efforts are in place to finely tune variant interpretation in a gene‐ and disease‐specific manner (eg, gene curation efforts such as ClinGen,80 established in 2015) and to render interpretation easier and quicker for the geneticist with automated variant interpretation tools (eg, CardioClassifier92 and CardioVAI,93 that interpret variants in the context of cardiomyopathies). ACMG, American College of Medical Genetics; AMP, Association for Molecular Pathology; and NGS, next‐generation sequencing.CC BY · PubMed Central

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Metadata

Authors
Mazzarotto, F., Olivotto, I., Boschi, B., Girolami, F., Poggesi, C., Barton, P. J. R., & Walsh, R.
Venue
Journal of the American Heart Association
Publisher
Ovid Technologies (Wolters Kluwer Health)
Published
2020-04-21
Volume
9
Issue
8
ISSN
2047-9980
DOI
10.1161/jaha.119.015473
PMC
PMC7428545
Cited by
63
References
8
Language
en

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Mazzarotto, F., Olivotto, I., Boschi, B., Girolami, F., Poggesi, C., Barton, P. J. R., & Walsh, R. (2020). Contemporary Insights Into the Genetics of Hypertrophic Cardiomyopathy: Toward a New Era in Clinical Testing? Journal of the American Heart Association. https://doi.org/10.1161/jaha.119.015473