Since the 1990s, genetic testing in cardiology has been recommended for patients who have symptoms of inherited cardiovascular disease or are at high risk because of a known pathogenic variant in their family. In 2020, the American Heart Association (AHA) issued a statement recommending genetic testing for patients diagnosed with all forms of cardiomyopathy, arrhythmic disorders, vascular disorders and lipid disorders, such as familial hypercholesterolaemia.
Today, clinicians have at their disposal a wide range of possibilities ranging from sequencing a single gene or a panel of genes that have been previously associated with the disease they are studying, to whole exome sequencing. whole exome (WES) or whole whole genome (WGS). The study of WGS is more common in research settings than in the clinic because it serves to expand knowledge of gene-disease relationships. Such studies reveal that there are often multiple common small-effect gene variants (SNPs, single nucleotide polymorphisms) that cumulatively increase the risk of cardiovascular disease. Researchers can use this information to generate polygenic risk scores that reflect a person's susceptibility to disease, even before they exhibit any symptoms, and thus the opportunity for preventive measures is likely to accelerate the use of WGS or WES studies in clinical practice.
Despite this apparent availability, cardiogenomics is still in a developmental phase. Many gene variants associated with cardiovascular disease are of unknown significance (VSI, variants of uncertain significance) and therefore of limited clinical utility.
In these cases, new studies are needed to better understand how these variants interact with other genes and environmental factors in order to determine their pathogenicity. Similarly, integration with other "omics" data with greater development in cardiovascular diseases, such as proteomics and metabolomics, will also help to achieve a deeper understanding of their pathophysiology.
Cardiogenomics, an indispensable tool
As researchers learn more about the mechanisms by which genetic variation contributes to disease, they can begin to examine the effects of known drugs in selected groups of patients or use this knowledge to develop new ones. For example, mutations in genes encoding ion channel subunits (KCNQ1, KCNH2, SCN5A) are responsible for 75% of cases of long QT syndrome. Testing of these genes not only confirms the diagnosis, but can also guide the best treatment strategies.
However, the move from research to the clinic is not immediate and it takes time for newly discovered mutations associated with heart disease to become clinical trials. For example, there is an effective treatment on the market for hereditary cardiac amyloidosis, a disease in which amyloid deposition in the heart muscles hampers the heart's ability to pump blood. Although the role of mutations in the TTR gene in the development of this disease is known, the failure to routinely test for this gene limits patients' access to treatment. Other similar examples would be the sequencing of the LMNA gene in patients with dilated cardiomyopathy or the LDLR, APOB and PCSK9 genes in patients with familial hypercholesterolaemia. Genetic testing to identify mutated versions of these genes is rarely performed, despite the fact that they increase the risk of this disease.
In short, deciphering how the genetic code is transcribed and expressed is key to the definitive development and clinical implementation of personalized medicine. The identification of potentially pathogenic mutations will have a substantial impact on the practice of cardiology, a medical specialty in which genomic medicine has had little relevance until now. As is already happening in other pathologies, this knowledge will help to prevent cardiovascular diseases and improve survival rates and the quality of life of patients through early intervention.
- Kalia SS, et al. Recommendations for reporting of secondary findings in clinical exome and genome sequencing, 2016 update (ACMG SF v2.0): a policy statement of the American College of Medical Genetics and Genomics. Genet Med. 2017 Feb;19(2):249-255.
- Ahn J, et al. Effectiveness of beta-blockers depending on the genotype of congenital long-QT syndrome: A meta-analysis. PLoS One. 2017 Oct 23;12(10):e0185680.
- Park J, et al. A genome-first approach to aggregating rare genetic variants in LMNA for association with electronic health record phenotypes. Genet Med. 2020 Jan;22(1):102-111.
- Sturm AC, et al. Convened by the Familial Hypercholesterolemia Foundation. Clinical Genetic Testing for Familial Hypercholesterolemia: JACC Scientific Expert Panel. J Am Coll Cardiol. 2018 Aug 7;72(6):662-680.
- Damrauer SM, et al. Association of the V122I Hereditary Transthyretin Amyloidosis Genetic Variant With Heart Failure Among Individuals of African or Hispanic/Latino Ancestry. JAMA. 2019 Dec 10;322(22):2191-2202.