Big Data and Genome Editing Technology: A New Paradigm of Cardiovascular Genomics

Title:Big Data and Genome Editing Technology: A New Paradigm of Cardiovascular Genomics

Volume: 13 Issue: 4

Author(s): Chayakrit Krittanawong*, Tao Sun and Eyal Herzog

Affiliation:

• Department of Internal Medicine, Icahn School of Medicine at Mount Sinai, 1000 10th Ave, New York, NY 10019,United States

Keywords: Genome editing technology, genome, genome engineering, GWAS, genome-wide association studies.

Abstract: Opinion Statements: Cardiovascular diseases (CVDs) encompass a range of conditions extending from congenital heart disease to acute coronary syndrome most of which are heterogenous in nature and some of them are multiple genetic loci. However, the pathogenesis of most CVDs remains incompletely understood. The advance in genome-editing technologies, an engineering process of DNA sequences at precise genomic locations, has enabled a new paradigm that human genome can be precisely modified to achieve a therapeutic effect. Genome-editing includes the correction of genetic variants that cause disease, the addition of therapeutic genes to specific sites in the genomic locations, and the removal of deleterious genes or genome sequences. Site-specific genome engineering can be used as nucleases (known as molecular scissors) including zinc finger nucleases (ZFNs), transcription activator-like effector nucleases (TALENs), and the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated 9 (Cas9) systems to provide remarkable opportunities for developing novel therapies in cardiovascular clinical care. Here we discuss genetic polymorphisms and mechanistic insights in CVDs with an emphasis on the impact of genome-editing technologies. The current challenges and future prospects for genomeediting technologies in cardiovascular medicine are also discussed.

Cite this article as:

Krittanawong Chayakrit *, Sun Tao and Herzog Eyal , Big Data and Genome Editing Technology: A New Paradigm of Cardiovascular Genomics, Current Cardiology Reviews 2017; 13 (4) . https://dx.doi.org/10.2174/1573403X13666170804152432