Perspective:

The following are 10 points to consider from this review.

1. One strand of the human genome is 3 billion base pairs. Traditional automated high-throughput Sanger sequencing machines read about 2 million bases per day while next-generation sequencing (NGS) methods read up to 50 billion bases per day.

2. The protein-coding region of genes (exons) comprise about 1% of the genome yet contain approximately 85% of mutations with large effects on disease. Thus, targeted sequencing of exons, or the exome, may be sufficient for some research and diagnostic applications.

3. Many inherited cardiac conditions (ICCs) are genetically heterogeneous, as mutations in many different genes can lead to similar phenotypes (i.e., >9 genes may cause hypertrophic cardiomyopathy, >13 genes may cause long QT syndrome, and >20 genes may cause dilated cardiomyopathy.

4. Confirmation that a mutation is responsible for a disease is often difficult, especially when the disease is not completely penetrant (i.e., not all carriers of mutation develop the disease). In addition, several coexisting modifying gene variants may affect the expression of disease. Finally, understanding the spectrum of rare, non-pathogenic genetic variation is still evolving.

5. With reduced costs, increased availability, and a more comprehensive analysis, NGS will likely lead to more testing and diagnoses in patients with ICCs. This broadened testing may include molecular autopsies in subjects with unexplained sudden death and prenatal diagnosis of cardiac (and other) diseases.

6. As more extensive phenotype-genotype profiles are studied, genotype-specific risk calculators may be developed. Treatments could potentially be targeted to specific molecular defects, as is done in some cases of monogenic hypertension and monogenic type 2 diabetes mellitus.

7. NGS may also be useful in common diseases to better determine effect sizes of multiple gene variants affecting a complex phenotype. This could ultimately guide therapy.

8. The clinical usefulness of identifying specific gene variants that affect drug metabolism (i.e., clopidogrel, warfarin, statins) is currently controversial. The clinical impact of pharmacogenetics may become much greater with the availability of NGS.

9. Ethical issues will arise with the vast amounts of genetic information generated by this technology. It may be prudent to obtain consent for results only related to the disease genes of interest.

10. Substantial investment towards informatics and physician training will be required to take optimal advantage of this exciting technology.