Application of next generation sequencing in cardiology: current and future precision medicine implications

Abstract

Inherited cardiovascular diseases are highly heterogeneous conditions with multiple genetic loci involved. The application of advanced molecular tools, such as Next Generation Sequencing, has facilitated the genetic analysis of these disorders. Accurate analysis and variant identification are required to maximize the quality of the sequencing data. Therefore, the application of NGS for clinical purposes should be limited to laboratories with a high level of technological expertise and resources. In addition, appropriate gene selection and variant interpretation can result in the highest possible diagnostic yield. Implementation of genetics in cardiology is imperative for the accurate diagnosis, prognosis and management of several inherited disorders and could eventually lead to the realization of precision medicine in this field. However, genetic testing should also be accompanied by an appropriate genetic counseling procedure that clarifies the significance of the genetic analysis results for the proband and his family. In this regard, a multidisciplinary collaboration among physicians, geneticists, and bioinformaticians is imperative. In the present review, we address the current state of knowledge regarding genetic analysis strategies employed in the field of cardiogenetics. Variant interpretation and reporting guidelines are explored. Additionally, gene selection procedures are accessed, with a particular emphasis on information concerning gene-disease associations collected from international alliances such as the Gene Curation Coalition (GenCC). In this context, a novel approach to gene categorization is proposed. Moreover, a sub-analysis is conducted on the 1,502,769 variation records with submitted interpretations in the Clinical Variation (ClinVar) database, focusing on cardiology-related genes. Finally, the most recent information on genetic analysis's clinical utility is reviewed.

Keywords: cardiogenetics; cardiovascular diseases; genetic analysis; next generation sequencing; personalized treatment.

Figure 1

Upset plot of the different gene sets among the cardiovascular disease-related genes with the distinct combinations among categories. An interactive version of the plot is also in the supplementary files section and in the link https://tinyurl.com/upsetplot. DCM is highlighted as an example where 23/55 of the associated genes are unique for DCM and the remaining 32 show overlap among the different groups as shown in orange and through the lines that connect the dots at the level of DCM.

Figure 2

Statistics on classification and reclassification from ClinVar (Aug 2016–Aug 2022) for genes related to cardiac diseases. (A) The distribution of the 232,025 starting classifications for genes related to cardiac diseases to the five standard ACMG/AMP classification terms and reclassification statistics for each category relative to the percentage of the initial classification group. (B) Percentages relative to the number of all reclassifications.

Figure 3

Schematic representation of the workflow used for appropriate classification and interpretation of the genetic variants in clinical practice (details in text). 1000G, 1,000 Genomes; ESP6500, NHLBI Exome Sequencing Project; ExAC, Exome Aggregation Consortium; gnomAD, Genome Aggregation Database; ClinVar, Clinical Variation database; OMIM, Online Mendelian Inheritance in Man; LSDBs, Locus Specific Databases; HGVS, Human Genome Variation Society; HPO, Human Phenotype Ontology; ACMG, American College of Medical Genetics and Genomics; AMP, Association for Molecular Pathology; ClinGen, Clinical Genome Resource; VCEP, Variant Curation Expert Panel.