Key result
Basic science methods offer emerging frameworks to improve VUS reclassification in HCM.
Why the study?
Identifying variants of uncertain significance in inheritable hypertrophic cardiomyopathy causes ambiguity in interpretation, risk stratification, and clinical practice.
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This review highlights emerging basic science technologies and proposes a workflow to better characterize variants of uncertain significance in genetic cardiomyopathies.
With the advent of next-generation whole genome sequencing, many variants of uncertain significance (VUS) have been identified in individuals suffering from inheritable hypertrophic cardiomyopathy (HCM). Unfortunately, this classification of a genetic variant results in ambiguity in interpretation, risk stratification, and clinical practice. Here, we aim to review some basic science methods to gain a more accurate characterization of VUS in HCM. Currently, many genomic data-based computational methods have been developed and validated against each other to provide a robust set of resources for researchers. With the continual improvement in computing speed and accuracy, in silico molecular dynamic simulations can also be applied in mutational studies and provide valuable mechanistic insights. In addition, high throughput in vitro screening can provide more biologically meaningful insights into the structural and functional effects of VUS. Lastly, multi-level mathematical modeling can predict how the mutations could cause clinically significant organ-level dysfunction. We discuss emerging technologies that will aid in better VUS characterization and offer a possible basic science workflow for exploring the pathogenicity of VUS in HCM. Although the focus of this mini review was on HCM, these basic science methods can be applied to research in dilated cardiomyopathy (DCM), restrictive cardiomyopathy (RCM), arrhythmogenic cardiomyopathy (ACM), or other genetic cardiomyopathies.
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Doh et al. (2023) conducted a review in Hypertrophic cardiomyopathy (HCM). Basic science methods (computational, in vitro, mathematical modeling) was evaluated. Basic science methods, including computational algorithms, high-throughput in vitro screening, and mathematical modeling, offer emerging frameworks to improve the characterization and reclassification of variants of uncertain significance in hypertrophic cardiomyopathy.
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