Evidence map›Paper›PMID 39196210›Full record

ReviewNature cardiovascular research2023

Current and future perspectives of single-cell multi-omics technologies in cardiovascular research.

Wilson Lek Wen Tan, Wei Qiang Seow, Angela Zhang, Siyeon Rhee, Wing H Wong, William J Greenleaf, Joseph C Wu

Abstract readReview
In one paragraph

Review in Nature cardiovascular research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

  1. Unique CD8bioRxiv : the preprint server for biology · 2026
    Article
  2. Article
  3. mRNA medicine for cardiovascular disease.Nature cardiovascular research · 2026
    Review
  4. Review
  5. Beyond transcription: RNA-binding proteins steering angiogenesis.American journal of physiology. Heart and circulatory physiology · 2026
    Review
  6. Review
  7. Article
  8. Dissecting endothelial cell heterogeneity with new tools.Cell regeneration (London, England) · 2025
    Review
  9. Article
  10. Review
  11. Review
  12. Review
  13. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Wilson Lek Wen TanStanford Cardiovascular Institute, Stanford, CA, USA.
Wei Qiang SeowStanford Cardiovascular Institute, Stanford, CA, USA.ORCID http://orcid.org/0000-0002-5019-9332
Angela ZhangStanford Cardiovascular Institute, Stanford, CA, USA.
Siyeon RheeStanford Cardiovascular Institute, Stanford, CA, USA.
Wing H WongDepartment of Statistics, Stanford University School of Medicine, Stanford, CA, USA.
William J GreenleafDepartment of Genetics, Stanford University School of Medicine, Stanford, CA, USA.
Joseph C WuStanford Cardiovascular Institute, Stanford, CA, USA. joewu@stanford.edu.ORCID http://orcid.org/0000-0002-6068-8041

Funding

Special EquipmentP50HG007735 · NHGRI · STANFORD UNIVERSITY · PI GREENLEAF, WILLIAM JAMES · 2014 to 2018
$15.2M
Elucidating Mechanism of Cardiac Fibrosis with Cell Village of Pooled Human iPSCsR01HL130020 · NHLBI · STANFORD UNIVERSITY · PI Ronglih Liao, MARK MERCOLA · 2016 to 2026
$7.3M
Human iPSCs for Elucidating Intercellular Crosstalk Signaling in Dilated CardiomyopathyR01HL141371 · NHLBI · STANFORD UNIVERSITY · PI WONG, WING H., WU, JOSEPH C. · 2018 to 2025
$6.2M
Genome Editing of Human iPSCs to Study Inherited Hypertrophic CardiomyopathyR01HL126527 · NHLBI · STANFORD UNIVERSITY · PI QI, LEI STANLEY, WU, JOSEPH C. · 2015 to 2022
$5.4M
Single Cell Sequencing of Human iPSC-CM Subtype Identity and FunctionR01HL145676 · NHLBI · STANFORD UNIVERSITY · PI MARK MERCOLA, Joseph C. Wu · 2019 to 2026
$5.1M
Human iPSC Model to Elucidate Metabolic Interplay in Diabetic CardimyopathyR01HL146690 · NHLBI · STANFORD UNIVERSITY · PI LIAO, RONGLIH, MERCOLA, MARK · 2019 to 2025
$5.1M
Statistical methods for gene regulatory analysis and single cell genomicsR01HG010359 · NHGRI · STANFORD UNIVERSITY · PI WONG, WING H. · 2019 to 2022
$1.5M
Using Deep Learning to Predict Induced Pluripotent Stem Cell-Derived Cardiomyocyte (iPSC-CM) Differentiation OutcomesF30HL156478 · NHLBI · STANFORD UNIVERSITY · PI ZHANG, ANGELA · 2021 to 2023
$118k
American Heart Association (American Heart Association, Inc.) 20POST35210896NHGRI NIH HHS P50 HG007735NHGRI NIH HHS R01 HG010359NHLBI NIH HHS F30 HL156478NHLBI NIH HHS R01 HL126527NHLBI NIH HHS R01 HL130020NHLBI NIH HHS R01 HL141371NHLBI NIH HHS R01 HL145676NHLBI NIH HHS R01 HL146690U.S. Department of Health & Human Services | NIH | Center for Information Technology (Center for Information Technology, National Institutes of Health) HL156478U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI) HL130020U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI) HL141371U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI) HL145676U.S. Department of Health & Human Services | NIH | National Heart, Lung, and Blood Institute (NHLBI) HL146690U.S. Department of Health & Human Services | NIH | National Human Genome Research Institute (NHGRI) HG010359
6 · The paper itself

Abstract

Single-cell technology has become an indispensable tool in cardiovascular research since its first introduction in 2009. Here, we highlight the recent remarkable progress in using single-cell technology to study transcriptomic and epigenetic heterogeneity in cardiac disease and development. We then introduce the key concepts in single-cell multi-omics modalities that apply to cardiovascular research. Lastly, we discuss some of the trending concepts in single-cell technology that are expected to propel cardiovascular research to the next phase of single-cell research.

Identifiers

PMID39196210
PMCPMC11974510

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.