Since the 1990s cardiovascular genomics has been a popular area of research, heading toward a genome-first approach to the diagnosis and therapy of Mendelian cardiovascular diseases. With the advent of cost-effective sequencing and the availability of greater computing power, analysing genomic data for entire populations has enabled exponential advancements in our ability to examine variant pathogenicity based on allele rarity. The investigation of rare diseases has been greatly aided by the sizeable data sets now available. The ultimate goal of the genome-first approach to cardiovascular medicine is to be able to determine the risk of a disease to an asymptomatic individual based on an analysis of their genome. There are limitations to the accuracy of population genomics which include the characteristics of the populations studied and also the evolutionary constraints on human Mendelian variation. To overcome some of these challenges it is optimal to combine population-based discovery with the investigation of existing and prospective variant analysis. Wider genomic analysis of the general population is important to understand the presence of an asymptomatic patient. Another method applied to overcome some of the limitations presented has been to do a comparison of variant prevalence in general population genetic data compared to a large rare disease cohort. The findings of these comparisons have led to substantial discoveries related to the gene and variants which can cause genetically inherited cardiomyopathy (Parikh, 2021).
Population datasets have also been utilised by researchers in the study of monogenic diseases. It was found that for those with European ancestry, the existence of the Titin truncating variant (TTNtv) meant an increased incidence of atrial arrhythmia and an increased chance of suffering a lower left ventricular ejection fraction (Haggerty et al., 2019). Another study found that loss of function variants in Lamin A/C meant correlated strongly with an increase in the likelihood of cardiomyopathy, conduction disease, and renal disease (Park et al., 2020).
Population datasets have been an integral part to find solutions for those affected by and at risk for Mendelian cardiovascular disease. To increase these benefits, population-based genomics data should be integrated into clinical practice alongside further research to create robust data sets. Our cutting-edge egSEQ library preparation and targeted sequencing panels enable the generation of an unprecedented amount of genomic data to aid population studies. Contact us to explore what we can offer.
Citations:
Haggerty, C., Damrauer, S., Levin, M., Birtwell, D., Carey, D., & Golden, A. et al. (2019). Genomics-First Evaluation of Heart Disease Associated With Titin-Truncating Variants. Circulation, 140(1), 42-54. doi: 10.1161/circulationaha.119.039573
Parikh, V. (2021). Promise and Peril of Population Genomics for the Development of Genome-First Approaches in Mendelian Cardiovascular Disease. Circulation: Genomic And Precision Medicine, 14(1). doi: 10.1161/circgen.120.002964
Park, J., Levin, M., Haggerty, C., Hartzel, D., Judy, R., & Kember, R. et al. (2020). A genome-first approach to aggregating rare genetic variants in LMNA for association with electronic health record phenotypes. Genetics In Medicine, 22(1), 102-111. doi: 10.1038/s41436-019-0625-8
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