Integrating New Genomic Discoveries with Genome Editing Towards Personalized Medicine

We have limited knowledge of the noncoding sequence aspect of the human genome. Defining the full monty of noncoding sequences and their function will provide a more advanced understanding of CV development, homeostasis, and disease. This will be facilitated best by a centralized repository of data modeled after the UCSC Genome Browser. Further, with all functional noncoding sequences in hand, it will be an easy exercise to place, in context, sequence variants that could impact noncoding sequence function. For example, it would be important to know whether a sequence variant in a specific TFBS confers protection or susceptibility to disease. CRISPR-Cas9 could easily model such noncoding sequence variants in cells (and animals) for further exploration of function and responsiveness to intervention. As the cost of WGS continues to fall, more and more genomes will be sequenced with the identification of rare alleles that could have large explanatory power for an individual's CVD and associated treatment responses. Integrating individual genomic data with electronic health data (obviously requiring careful planning and implentation) will, in turn, allow for hypothesis testing based on experimental data accumulating in the centralized database. Ultimately, personalized medicine will be achieved by intersecting patient genomic data with wet lab data that would, in turn, inform the best route of action using CRISPR-Cas9 in patient-derived pluripotent stem cells.

Developing an interactive and continually updated "Cardiovascular Browser" is certainly feasible. The approach should be much like that taken by the pioneers of the Human Genome Project; that is, all participating labs should make data freely available. The data would include, among other things, expression analysis of noncoding sequences and their relationship to protein-coding genes, regulatory aspects of all coding and noncoding genes in cells of the cardiovascular system and presence of regulatory SNPs, functional annotation of noncoding sequences and sequence variants therein using CRISPR-Cas9 genome editing, and systems biology data that would integrate the accumulating data. Challenges include organizational aspects of a centralized database, appropriate selection of cell types (primary or immortal) and experimental conditions (human cells or animal model?) to capture as much information relating to CVD progression as possible (eg, noncoding sequence expression and function in [a] ECs at disturbed flow regions, [b] SMCs following exposure to oxidized LDL and [c] cardiac myocytes treated with chemotherpy or pressure overload). A challenge with CRISPR-Cas9 continues to be that of inadvertant off target effects (especially in cells). Patient privacy and safeguards against discrimination (eg, insurability) will be key. A board of CV scientists (term limited) and lay persons would thus be needed to develop, implement, and continually revise data management and directions.