Harnessing the Potential of CRISPR/Cas in Atherosclerosis: Disease Modeling and Therapeutic Applications.
Wei Sheng SiewYin Quan TangChee Kei KongBey Hing GohSerena ZacchignaKamal DuaDinesh Kumar ChellappanAcharaporn DuangjaiSurasak SaokaewPochamana PhisalprapaWei Hsum YapPublished in: International journal of molecular sciences (2021)
Atherosclerosis represents one of the major causes of death globally. The high mortality rates and limitations of current therapeutic modalities have urged researchers to explore potential alternative therapies. The clustered regularly interspaced short palindromic repeats-associated protein 9 (CRISPR/Cas9) system is commonly deployed for investigating the genetic aspects of Atherosclerosis. Besides, advances in CRISPR/Cas system has led to extensive options for researchers to study the pathogenesis of this disease. The recent discovery of Cas9 variants, such as dCas9, Cas9n, and xCas9 have been established for various applications, including single base editing, regulation of gene expression, live-cell imaging, epigenetic modification, and genome landscaping. Meanwhile, other Cas proteins, such as Cas12 and Cas13, are gaining popularity for their applications in nucleic acid detection and single-base DNA/RNA modifications. To date, many studies have utilized the CRISPR/Cas9 system to generate disease models of atherosclerosis and identify potential molecular targets that are associated with atherosclerosis. These studies provided proof-of-concept evidence which have established the feasibility of implementing the CRISPR/Cas system in correcting disease-causing alleles. The CRISPR/Cas system holds great potential to be developed as a targeted treatment for patients who are suffering from atherosclerosis. This review highlights the advances in CRISPR/Cas systems and their applications in establishing pathogenetic and therapeutic role of specific genes in atherosclerosis.
Keyphrases
- crispr cas
- genome editing
- cardiovascular disease
- gene expression
- nucleic acid
- dna methylation
- genome wide
- end stage renal disease
- newly diagnosed
- ejection fraction
- coronary artery disease
- machine learning
- risk factors
- cancer therapy
- single molecule
- transcription factor
- circulating tumor
- artificial intelligence
- risk assessment
- circulating tumor cells
- combination therapy
- single cell