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Review
. 2015 Apr 1;105(4):397-408.
doi: 10.1093/cvr/cvv025. Epub 2015 Jan 29.

Genetic Advances in Sarcomeric Cardiomyopathies: State of the Art

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Free PMC article
Review

Genetic Advances in Sarcomeric Cardiomyopathies: State of the Art

Carolyn Y Ho et al. Cardiovasc Res. .
Free PMC article

Abstract

Genetic studies in the 1980s and 1990s led to landmark discoveries that sarcomere mutations cause both hypertrophic and dilated cardiomyopathies. Sarcomere mutations also likely play a role in more complex phenotypes and overlap cardiomyopathies with features of hypertrophy, dilation, diastolic abnormalities, and non-compaction. Identification of the genetic cause of these important conditions provides unique opportunities to interrogate and characterize disease pathogenesis and pathophysiology, starting from the molecular level and expanding from there. With such insights, there is potential for clinical translation that may transform management of patients and families with inherited cardiomyopathies. If key pathways for disease development can be identified, they could potentially serve as targets for novel disease-modifying or disease-preventing therapies. By utilizing gene-based diagnostic testing, we can identify at-risk individuals prior to the onset of clinical disease, allowing for disease-modifying therapy to be initiated early in life, at a time that such treatment may be most successful. In this section, we review the current application of genetics in clinical management, focusing on hypertrophic cardiomyopathy as a paradigm; discuss state-of-the-art genetic testing technology; review emerging knowledge of gene expression in sarcomeric cardiomyopathies; and discuss both the prospects, as well as the challenges, of bringing genetics to medicine.

Keywords: Dilated cardiomyopathy; Genetics; Hypertrophic cardiomyopathy; Next Generation Sequencing; Sarcomere.

Figures

Figure 1
Figure 1
NGS Strategy. It involved three major steps: library preparation from genomic DNA, enrichment of target regions by hybridization, and massively parallel sequencing of all captured fragments.
Figure 2
Figure 2
Workflow used to sequencing and filtering the variants detected by NGS. After library preparation and sequencing, bioinformatics analysis is performed. Variants identified are further prioritized and filtered to identify those likely to be clinically relevant. Variants are typically classified into four classes: pathogenic, likely pathogenic, VUS, or benign. 1KGP, 1000 Genomes Project; ESP, Exome Sequencing Project; ExAC, Exome Aggregation Consortium; MAF, minor allele frequency.
Figure 3
Figure 3
Schematic overview of locally acting variants on different positions (A, B, C, D) with influence on the mutated allele and the wild-type counterpart allele (red arrows), and the subsequent expected effect on the phenotype (less or more severe). UTR, untranslated region.

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