Evidence map›Paper›PMID 32231331›Full record

ReviewNature reviews. Cardiology2020

Single-cell RNA sequencing in cardiovascular development, disease and medicine.

David T Paik, Sangkyun Cho, Lei Tian, Howard Y Chang, Joseph C Wu

Abstract readReview
In one paragraph

Review in Nature reviews. Cardiology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 188 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
188citing papers in PubMed, 1 pooled it
–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

188 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Article

128 more citing papers are in PubMed but not listed here.

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

5 authors.

David T PaikStanford Cardiovascular Institute, Stanford, CA, USA. dtpaik@stanford.edu.ORCID http://orcid.org/0000-0002-7830-312X
Sangkyun ChoStanford Cardiovascular Institute, Stanford, CA, USA.
Lei TianStanford Cardiovascular Institute, Stanford, CA, USA.
Howard Y ChangCenter for Personal Dynamic Regulomes, 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

Project 3 (Mercola)P01HL141084 · NHLBI · STANFORD UNIVERSITY · PI Joseph C. Wu · 2019 to 2026
$21.1M
Center for Personal Dynamic RegulomesRM1HG007735 · NHGRI · STANFORD UNIVERSITY · PI CHANG, HOWARD Y · 2019 to 2023
$13.8M
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
Modeling Tyrosine Kinase Inhibitor-Induced Vascular Dysfunction Using Human iPSCsR01HL141851 · NHLBI · STANFORD UNIVERSITY · PI WONG, WING H., WU, JOSEPH C. · 2018 to 2025
$5.7M
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
Identifying Angiocrine Factors for Cardiomyocyte Maturation Using Single-Cell SequencingK99HL150216 · NHLBI · STANFORD UNIVERSITY · PI PAIK, DAVID T · 2020 to 2021
$325k
NHGRI NIH HHS RM1 HG007735NHLBI NIH HHS K99 HL150216NHLBI NIH HHS P01 HL141084NHLBI NIH HHS R01 HL130020NHLBI NIH HHS R01 HL141371NHLBI NIH HHS R01 HL141851NHLBI NIH HHS R01 HL145676NHLBI NIH HHS R01 HL146690
6 · The paper itself

Abstract

Advances in single-cell RNA sequencing (scRNA-seq) technologies in the past 10 years have had a transformative effect on biomedical research, enabling the profiling and analysis of the transcriptomes of single cells at unprecedented resolution and throughput. Specifically, scRNA-seq has facilitated the identification of novel or rare cell types, the analysis of single-cell trajectory construction and stem or progenitor cell differentiation, and the comparison of healthy and disease-related tissues at single-cell resolution. These applications have been critical in advances in cardiovascular research in the past decade as evidenced by the generation of cell atlases of mammalian heart and blood vessels and the elucidation of mechanisms involved in cardiovascular development and stem or progenitor cell differentiation. In this Review, we summarize the currently available scRNA-seq technologies and analytical tools and discuss the latest findings using scRNA-seq that have substantially improved our knowledge on the development of the cardiovascular system and the mechanisms underlying cardiovascular diseases. Furthermore, we examine emerging strategies that integrate multimodal single-cell platforms, focusing on future applications in cardiovascular precision medicine that use single-cell omics approaches to characterize cell-specific responses to drugs or environmental stimuli and to develop effective patient-specific therapeutics.

Indexed as

Cardiovascular DiseasesGene Expression ProfilingSequence Analysis, RNASingle-Cell AnalysisAnimalsHumansMice

Identifiers

PMID32231331
PMCPMC7528042

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

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.