False Utopia of One Unifying Description of the Vulnerable Atherosclerotic Plaque: A Call for Recalibration That Appreciates the Diversity of Mechanisms Leading to Atherosclerotic Disease.
Gerard PasterkampHester M den RuijterChiara GiannarelliPublished in: Arteriosclerosis, thrombosis, and vascular biology (2022)
Atherosclerosis is a complex disease characterized by the formation of arterial plaques with a broad diversity of morphological phenotypic presentations. Researchers often apply one description of the vulnerable plaque as a gold standard in preclinical and clinical research that could be applied as a surrogate measure of a successful therapeutic intervention, despite the variability in lesion characteristics that may underly a thrombotic occlusion. The complex mechanistic interplay underlying progression of atherosclerotic disease is a consequence of the broad range of determinants such as sex, risk factors, hemodynamics, medications, and the genetic landscape. Currently, we are facing an overwhelming amount of data based on genetic, transcriptomic, proteomic, and metabolomic studies that all point to heterogeneous molecular profiles of atherosclerotic lesions that lead to a myocardial infarction or stroke. The observed molecular diversity implies that one unifying model cannot fully recapitulate the natural history of atherosclerosis. Despite emerging data obtained from -omics studies, a description of a natural history of atherosclerotic disease in which cell-specific expression of proteins or genes are included is still lacking. This also applies to the insights provided by genome-wide association studies. This review will critically discuss the dogma that the progression of atherosclerotic disease can be captured in one unifying natural history model of atherosclerosis.
Keyphrases
- single cell
- risk factors
- randomized controlled trial
- cardiovascular disease
- heart failure
- genome wide
- gene expression
- type diabetes
- atrial fibrillation
- poor prognosis
- machine learning
- cell therapy
- left ventricular
- electronic health record
- big data
- case control
- artificial intelligence
- dna methylation
- binding protein
- mesenchymal stem cells
- copy number