Abstract 4370980: Vascular smooth muscle cell atherosclerosis trajectories characterized at single cell resolution identify causal transcriptomic and epigenomic mechanisms of disease risk

Background: Vascular smooth muscle cells (SMC) contribute to heritable coronary artery disease (CAD) risk and undergo complex cell state transitions to multiple disease related phenotypes. To investigate the genetic basis of trajectories that underlie the SMC component of CAD causality we developed a dense timecourse single cell transcriptomic and epigenetic map of atherosclerosis in a murine disease animal model. Methods/Results: Deep multiomic profiling of aortic roots from control atherosclerosis model ( Myh11Cre ERT2 , ROSA tdT/+ , ApoE -/- ) mice with SMC specific lineage tracing on high fat diet were harvested for 7 scRNA and 6 scATAC timepoints across 16 weeks. Cellular trajectories were derived from the temporal data and probabilistic fate modeling with Waddington-Optimal Transport (WOT). We created transcription factor (TF) centered regulons mapped across the developmental timeline and through network-based prioritization with WOT predicted TFs and in silico TF perturbation, identified key drivers of cell state changes associated with epithelial-to-mesenchymal transition, vascular development, circadian clock, and hypoxia-inducible factor functions. This strategy nominated CAD gene Tcf21 as a top TF that drove early SMC transition. Parallel studies using Tcf21 SMC-knockout at 3 timepoints for scRNA and scATAC revealed the impact of Tcf21 on SMC transition molecular phenotypes and disease risk genes, due in part to a role regulating SMC cells in with secondary heart field origins and broadly altered TF accessibility. ChIPseq and proximity ligation assay in human coronary artery SMC showed TEAD1 colocalization with TCF21 across CAD risk loci to epigenetically regulate SMC transition functions, confirmed via dual luciferase reporter assays. Lastly, integration of mouse disease data with human CAD genetic findings identified the transition TF regulons that mediate disease risk and point to causal molecular mechanisms. Conclusion: We construct the first multimodal single cell course in a mouse atherosclerosis model to characterize SMC cell state changes in a disease setting. We validate the regulatory predictions from this model in vivo by perturbing CAD gene Tcf21 to discover novel epigenetic and transcriptional mechanisms which affect key SMC transition elements. Our study provides a comprehensive reference to advance our understanding of SMC cell state changes in a murine atherosclerosis model and enhance future gene regulation studies in vascular biology.

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Journal
Circulation
Published
2025-11-03
DOI
https://doi.org/10.1161/circ.152.suppl_3.4370980
Primary Topic
Single-cell and spatial transcriptomics
Type
article
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article

Abstract 4370980: Vascular smooth muscle cell atherosclerosis trajectories characterized at single cell resolution identify causal transcriptomic and epigenomic mechanisms of disease risk

Ramendra Kundu, Trieu Nguyen, William T. Jackson, Matthew D. Worssam et al.
Circulation
Single-cell and spatial transcriptomics
article

Abstract 4370980: Vascular smooth muscle cell atherosclerosis trajectories characterized at single cell resolution identify causal transcriptomic and epigenomic mechanisms of disease risk

Ramendra Kundu, Trieu Nguyen, William T. Jackson, Matthew D. Worssam, Soumya Kundu, Quanyi Zhao, Thomas Quertermous, Brian T. Palmisano, Robert Wirka, Wenduo Gu, D. Li, João P. Monteiro, Chad S. Weldy, Anshul Kundaje, Paul P. Cheng
article en

Abstract

Background: Vascular smooth muscle cells (SMC) contribute to heritable coronary artery disease (CAD) risk and undergo complex cell state transitions to multiple disease related phenotypes. To investigate the genetic basis of trajectories that underlie the SMC component of CAD causality we developed a dense timecourse single cell transcriptomic and epigenetic map of atherosclerosis in a murine disease animal model. Methods/Results: Deep multiomic profiling of aortic roots from control atherosclerosis model ( Myh11Cre ERT2 , ROSA tdT/+ , ApoE -/- ) mice with SMC specific lineage tracing on high fat diet were harvested for 7 scRNA and 6 scATAC timepoints across 16 weeks. Cellular trajectories were derived from the temporal data and probabilistic fate modeling with Waddington-Optimal Transport (WOT). We created transcription factor (TF) centered regulons mapped across the developmental timeline and through network-based prioritization with WOT predicted TFs and in silico TF perturbation, identified key drivers of cell state changes associated with epithelial-to-mesenchymal transition, vascular development, circadian clock, and hypoxia-inducible factor functions. This strategy nominated CAD gene Tcf21 as a top TF that drove early SMC transition. Parallel studies using Tcf21 SMC-knockout at 3 timepoints for scRNA and scATAC revealed the impact of Tcf21 on SMC transition molecular phenotypes and disease risk genes, due in part to a role regulating SMC cells in with secondary heart field origins and broadly altered TF accessibility. ChIPseq and proximity ligation assay in human coronary artery SMC showed TEAD1 colocalization with TCF21 across CAD risk loci to epigenetically regulate SMC transition functions, confirmed via dual luciferase reporter assays. Lastly, integration of mouse disease data with human CAD genetic findings identified the transition TF regulons that mediate disease risk and point to causal molecular mechanisms. Conclusion: We construct the first multimodal single cell course in a mouse atherosclerosis model to characterize SMC cell state changes in a disease setting. We validate the regulatory predictions from this model in vivo by perturbing CAD gene Tcf21 to discover novel epigenetic and transcriptional mechanisms which affect key SMC transition elements. Our study provides a comprehensive reference to advance our understanding of SMC cell state changes in a murine atherosclerosis model and enhance future gene regulation studies in vascular biology.

CirculationVol. 152(Suppl_3)
University of North Carolina at Chapel Hill (US), University of North Carolina Health Care (US), Stanford Health Care (US), Stanford University (US)
Openalex Percentile: Top 71%
Single-cell and spatial transcriptomics
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