Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 616

The DOI matches its Crossref record; 54 of the 54 references it cites were found in a registry or an index.

Single-Cell Genomics Reveals a Novel Cell State During Smooth Muscle Cell Phenotypic Switching and Potential Therapeutic Targets for Atherosclerosis in Mouse and Human

Open access
Pan, Huize, Xue, Chenyi, Auerbach, Benjamin J., Fan, Jiaxin, Bashore, Alexander C., Cui, Jian, Yang, Dina Y., Trignano, Sarah B., Liu, Wen, Shi, Jianting, Ihuegbu, Chinyere O., Bush, Erin C., Worley, Jeremy, Vlahos, Lukas, Laise, Pasquale, Solomon, Robert A., Connolly, Edward S., Califano, Andrea, Sims, Peter A., Zhang, Hanrui, Li, Mingyao, Reilly, Muredach P.·2020·Circulation

Abstract

Background: Smooth muscle cells (SMCs) play significant roles in atherosclerosis via phenotypic switching, a pathological process in which SMC dedifferentiation, migration, and transdifferentiation into other cell types. Yet how SMCs contribute to the pathophysiology of atherosclerosis remains elusive. Methods: To reveal the trajectories of SMC transdifferentiation during atherosclerosis and to identify molecular targets for disease therapy, we combined SMC fate mapping and single-cell RNA sequencing of both mouse and human atherosclerotic plaques. We also performed cell biology experiments on isolated SMC-derived cells, conducted integrative human genomics, and used pharmacological studies targeting SMC-derived cells both in vivo and in vitro. Results: We found that SMCs transitioned to an intermediate cell state during atherosclerosis, which was also found in human atherosclerotic plaques of carotid and coronary arteries. SMC-derived intermediate cells, termed “SEM” cells (stem cell, endothelial cell, monocyte), were multipotent and could differentiate into macrophage-like and fibrochondrocyte-like cells, as well as return toward the SMC phenotype. Retinoic acid (RA) signaling was identified as a regulator of SMC to SEM cell transition, and RA signaling was dysregulated in symptomatic human atherosclerosis. Human genomics revealed enrichment of genome-wide association study signals for coronary artery disease in RA signaling target gene loci and correlation between coronary artery disease risk alleles and repressed expression of these genes. Activation of RA signaling by all-trans RA, an anticancer drug for acute promyelocytic leukemia, blocked SMC transition to SEM cells, reduced atherosclerotic burden, and promoted fibrous cap stability. Conclusions: Integration of cell-specific fate mapping, single-cell genomics, and human genetics adds novel insights into the complexity of SMC biology and reveals regulatory pathways for therapeutic targeting of SMC transitions in atherosclerotic cardiovascular disease.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1161/circulationaha.120.048378

Cites

54 of 54 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 54 references

Cited by

See all 616

Metadata

Authors
Pan, H., Xue, C., Auerbach, B. J., Fan, J., Bashore, A. C., Cui, J., Yang, D. Y., Trignano, S. B., Liu, W., Shi, J., Ihuegbu, C. O., Bush, E. C., Worley, J., Vlahos, L., Laise, P., Solomon, R. A., Connolly, E. S., Califano, A., Sims, P. A., Zhang, H., Li, M., & Reilly, M. P.
Venue
Circulation
Published
2020-11-24
Volume
142
Issue
21
Pages
2060-2075
ISSN
  • 0009-7322 (ISSN-L)
  • 1524-4539
OpenAlex
W3088819072
Cited by
616
References
54
FWCI
19.87
Type
journal article
Language
en
Open access
green

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Single-Cell Genomics Reveals a Novel Cell State During Smooth Muscle Cell Phenotypic Switching and Potential Therapeutic Targets for Atherosclerosis in Mouse and Human. https://app.cochat.ai/papers/10.1161/circulationaha.120.048378
The paper
Pan, H., Xue, C., Auerbach, B. J., Fan, J., Bashore, A. C., Cui, J., Yang, D. Y., Trignano, S. B., Liu, W., Shi, J., Ihuegbu, C. O., Bush, E. C., Worley, J., Vlahos, L., Laise, P., Solomon, R. A., Connolly, E. S., Califano, A., Sims, P. A., . . . Reilly, M. P. (2020). Single-Cell Genomics Reveals a Novel Cell State During Smooth Muscle Cell Phenotypic Switching and Potential Therapeutic Targets for Atherosclerosis in Mouse and Human. Circulation. https://doi.org/10.1161/circulationaha.120.048378

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.