Abstract
Vascular smooth muscle cells contribute to heritable coronary artery disease risk and undergo complex transitions to multiple disease-related phenotypes. To investigate the genetic basis of these trajectories, we develop a dense timecourse single-cell transcriptomic and epigenetic map of atherosclerosis in a murine disease model accompanied by high-plex in situ spatial data. Using temporal data and probabilistic fate modeling, we identify key transcription factors that drive cell state changes through a combination of network-based prioritization and in silico transcription factor perturbation. Parallel knockout studies of validated coronary artery disease gene Tcf21 uncover its molecular mechanisms in smooth muscle cell transition, due in part to a role regulating the transition of smooth muscle cells in the secondary heart field. Integrating the murine atlas with human coronary artery disease genetics pinpoint smooth muscle cell phenotypes that mediate disease risk, highlighting causal disease mechanisms. Together, these studies resolve atherosclerosis trajectories at single-cell resolution and identify genetic causal transcriptomic and epigenomic mechanisms of coronary artery disease risk.
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Data availability
The single-cell processed RNA and ATAC data generated in this study have been deposited in CellxGene under accession code 7a3044e4-6b16-4693-9504-212d9a573f80 (https://cellxgene.cziscience.com/collections/7a3044e4-6b16-4693-9504-212d9a573f80). The raw data is deposited to National Center for Biotechnology Information Gene Expression Omnibus (GEO) under accession code GSE321762. The Xenium mouse aorta spatial transcriptomic data, all human coronary artery smooth muscle ChIPseq data (CEBPB, H3K27ac, TEAD1), and Bulk RNASeq data (TEAD1) generated in this study are deposited to GEO under the following accession codes. Xenium: GSE316666, ChIPseq: GSE316714, RNASeq: GSE316713). For previously published data, TCF21-pooled ChIPseq and HNF1A ChIPseq, scRNA data from Pan et al., Alencar et al., and Cheng et al., and Bulk RNASeq primary HCASMC data from Liu et al. are downloaded from GEO: GSE141752, GSE59395, GSE155513, GSE150644, PRJNA794806, GSE113348, respectively. Human spatial data from Zhao et al. downloaded from CellxGene: 8f17ac63-aaba-44b5-9b78-60f121da4c2f (https://cellxgene.cziscience.com/collections/8f17ac63-aaba-44b5-9b78-60f121da4c2f).GWAS Catalog data were downloaded from (https://www.ebi.ac.uk/gwas/) and Million Veteran Program (MVP) were downloaded from dbGap with accession number phs001672.v3.p1 (https://dbgap.ncbi.nlm.nih.gov/beta/study/phs001672.v13.p1/#study). Source data are provided in the Source Data File. Source data are provided with this paper.
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Acknowledgements
Support was provided to DL through the NIH grants F32HL165819, K08HL177173, and the Sarnoff Scholar Career Development Award. This work was supported by National Institutes of Health grants R01HL171045 (T.Q.), R01HL134817 (TQ), R01HL139478 (T.Q.), R01HL156846 (T.Q.), R01HL158525 (T.Q.), UM1HG011972 (T.Q.), U01HG011762 (T.Q.), R01HL171275 (R.W.), K08HL152308 (R.W.), R01HL171045 (A.K.), U01HG012069 (A.K.), K08HL153798 (P.C.), R01HL179083 (P.C.), R01HL181441(P.C.), K08HL167699 (C.W.), K08HL177251 (B.P.). This work was supported by American Heart Association Grants 23POST1018991 (W.G.), 24POST1187860 (J.M.), 24SCEFIA1248386 (P.C.), 20CDA35310303 (P.C.), the William G. Irwin Foundation (T.Q.), the Marfan Foundation Everest Award (P.C.) as well as a Human Cell Atlas grant (ZF2019-002437) from the Chan Zuckerberg Foundation (T.Q.). “Supplementary Figs.” created in BioRender. Li, D. (https://BioRender.com/22if1p3) is licensed under CC BY 4.0.
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T.Q., R.W., and A.K. conceived and supervised the research plan. R. W., D. L., P.C., S. K., A.Y., J.M., W.G., W.J., S.D., R.C., B.P., M.R., C.W., performed single-cell captures and single-cell analyses, D. L., and T. N. performed experiments with cultured cells, and helped with genomic analyses. M.W. collected samples for spatial transcriptomics, and D.L. and Q.Z. analyzed data. D.L., R.K., R.W., P.C., W.J., maintained mouse colonies and performed RNAScope experiments, D.L., S.K., R.W., P.C., A.Y., and Q.Z. performed analyses. D.L. and T. Q. wrote the manuscript, R.W. and S.K. contributed to writing and proofreading.
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T.Q. is on the scientific advisory board of Amgen. A.K. is a scientific co-founder Immunera; on the scientific advisory board of SerImmune, TensorBio; is a consultant with Bristol Myers Squibb, Arcardia Science, Inari, Precede Biosciences; and has a financial stake in DeepGenomics, Immunai, SerImmune, Freenome, Immunera and TensorBio. The remaining authors declare no competing interests.
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Li, D.Y., Kundu, S., Cheng, P. et al. Vascular smooth muscle cell state trajectories mediate molecular mechanisms of coronary disease risk. Nat Commun (2026). https://doi.org/10.1038/s41467-026-70530-z
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DOI: https://doi.org/10.1038/s41467-026-70530-z
