Graphical summary. Credit: Cell Reports (2023). DOI: 10.1016/j.celrep.2023.113380
University of Virginia School of Medicine researchers have created an “atherosclerosis atlas” that reveals, at the individual cell level, the critical processes responsible for the formation of the harmful plaque buildup that causes heart attacks, strokes and coronary heart disease.
Atherosclerosis, or hardening of the arteries, affects half of Americans ages 45 to 84, and many don’t even know it, reports the National Institutes of Health. Over time, fatty plaques build up inside the arteries, where they can slow blood flow. When they break off, they can be deadly and trigger strokes and heart attacks.
Physicians and scientists are eager to better understand the complex factors that influence plaque formation and stability, and UVA’s new work offers unprecedented information that will facilitate the development of new ways to treat atherosclerosis, combat against coronary heart disease (CAD) and help prevent plaque formation.
“To begin to develop effective treatments targeting specific disease processes in the vessel wall, we need to characterize gene expression programs at single-cell resolution,” said faculty researcher Clint L. Miller, Ph.D. of Medicine from the University of Virginia. Center for Public Health Genomics, as well as its departments of Biochemistry and Molecular Genetics and Public Health Sciences.
“By establishing this map, we can inform strategies to reprogram dysregulated cellular states to prevent or reverse disease or identify biomarkers to assess a patient’s risk of clinical events.”
Understanding atherosclerosis
The formation of atherosclerotic plaques involves several types of cells, including immune cells, smooth muscle cells, and endothelial cells that line the arteries. Many of these cells transform into other cell types during plaque formation, making it difficult for scientists to determine the composition and origin of the plaque itself.
Miller and colleagues, led by graduate student Jose Verdezoto Mosquera, constructed a “comprehensive single-cell map of human atherosclerosis” encompassing nearly 120,000 cells from the atherosclerotic coronary and carotid arteries. In addition to mapping broad cell lineages, researchers have exploited this resource to dissect more granular and rarer cell subtypes within atherosclerotic plaques.
The study also reveals new information about the changes smooth muscle cells undergo during disease progression, some of which contribute to “calcification” or hardening of the coronary arteries. This led to the discovery that two genes, LTBP1 and CRTAC1, can be used to measure the progression of atherosclerosis.
“Beyond characterizing cellular diversity, integrating this newly constructed single-cell atherosclerosis benchmark with large-scale human genetic data was essential to begin to identify pathogenic cell types and subtypes,” Mosquera said. “For example, we identified the contribution of smooth muscle cell subtypes, such as fibroblast-like and lipid-rich smooth muscle cells, as well as the genes associated with these phenotypes.”
UVA researchers say their new atlas represents a “critical step” toward developing better, more targeted interventions to combat atherosclerosis and coronary artery disease, as well as to identify candidate biomarkers to prevent heart attacks and stroke and improve patient outcomes.
“We plan to expand this single-cell atlas with future iterations to include additional datasets from defined stages of disease and patients from diverse backgrounds,” Miller said. “By integrating the body of single-cell data generated by the scientific community, we can mitigate sampling bias and establish more robust candidate disease mechanisms and potential interventions.”
The researchers published their results in the journal Cell Reports.
More information:
Jose Verdezoto Mosquera et al, Integrative single-cell meta-analysis reveals disease-relevant vascular cell states and markers in human atherosclerosis, Cell Reports (2023). DOI: 10.1016/j.celrep.2023.113380
Provided by University of Virginia
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