Models to study atherosclerosis: a mechanistic insight

Area of Science:

• Cardiovascular Research
• Drug Discovery
• Animal Models

Background:

• Recent failures of cholesterol ester transfer protein (CETP) and acyl-CoA:cholesterol acyltransferase (ACAT) inhibitors highlight limitations in current anti-atherosclerotic drug development.
• A revised approach is needed for screening and developing new anti-atherosclerotic drugs.

Purpose of the Study:

• To emphasize the importance of understanding disease mechanisms within specific models.
• To advocate for the development of advanced atherosclerosis models that incorporate hyperlipidemia, inflammation, and complications of diabetes and hypertension.
• To highlight the need for multi-level analysis (in vivo, in vitro) of candidate molecules across atherosclerosis progression.

Main Methods:

• Utilizing models that simultaneously exhibit hyperlipidemia, inflammation, and complications of diabetes and hypertension to better mimic clinical conditions.
• Employing various cell-based and process-based models relevant to atherosclerosis.
• Leveraging genomic sequencing, single nucleotide polymorphism (SNP) databases, and in silico quantitative trait loci (QTL) linkage analysis.

Main Results:

• The study identifies the need for comprehensive models that recapitulate key features of human atherosclerosis.
• It stresses the importance of analyzing therapeutic candidates across different stages and environments of the disease.
• Genomic and computational tools offer potential for enhanced understanding and target identification.

Conclusions:

• Developing sophisticated atherosclerosis models is crucial for effective anti-atherosclerotic drug screening.
• Bridging the gap between small animal and human-like models is a significant challenge.
• Genomic and in silico approaches hold promise for advancing atherosclerosis research and therapeutic target discovery.