Molecular and Cellular Dynamics of Aortic Aneurysms Revealed by Single-Cell Transcriptomics

Arterioscler Thromb Vasc Biol. 2021 Nov;41(11):2671-2680. doi: 10.1161/ATVBAHA.121.315852. Epub 2021 Oct 7.

Abstract

The aorta is highly heterogeneous, containing many different types of cells that perform sophisticated functions to maintain aortic homeostasis. Recently, single-cell RNA sequencing studies have provided substantial new insight into the heterogeneity of vascular cell types, the comprehensive molecular features of each cell type, and the phenotypic interrelationship between these cell populations. This new information has significantly improved our understanding of aortic biology and aneurysms at the molecular and cellular level. Here, we summarize these findings, with a focus on what single-cell RNA sequencing analysis has revealed about cellular heterogeneity, cellular transitions, communications among cell populations, and critical transcription factors in the vascular wall. We also review the information learned from single-cell RNA sequencing that has contributed to our understanding of the pathogenesis of vascular disease, such as the identification of cell types in which aneurysm-related genes and genetic variants function. Finally, we discuss the challenges and future directions of single-cell RNA sequencing applications in studies of aortic biology and diseases.

Keywords: aneurysm; biology; homeostasis; transcription factor; vascular disease.

Publication types

  • Research Support, N.I.H., Extramural
  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Animals
  • Aorta / metabolism*
  • Aorta / pathology
  • Aortic Aneurysm / genetics*
  • Aortic Aneurysm / metabolism
  • Aortic Aneurysm / pathology
  • Dilatation, Pathologic
  • Endothelial Cells / metabolism
  • Endothelial Cells / pathology
  • Fibroblasts / metabolism
  • Fibroblasts / pathology
  • Gene Expression Profiling*
  • Humans
  • Myocytes, Smooth Muscle / metabolism
  • Myocytes, Smooth Muscle / pathology
  • RNA-Seq
  • Single-Cell Analysis*
  • Transcriptome*