Evidence map›Paper›PMID 26020271›Full record

ArticlePLoS genetics2015

Characterization of TCF21 Downstream Target Regions Identifies a Transcriptional Network Linking Multiple Independent Coronary Artery Disease Loci.

Olga Sazonova, Yuqi Zhao, Sylvia Nürnberg, Clint Miller, Milos Pjanic, Victor G Castano, Juyong B Kim, Elias L Salfati, Anshul B Kundaje, Gill Bejerano and 3 more

Open access · goldAbstract read
In one paragraph

Article in PLoS genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed
4.7field-weighted citation impact, top 5% of its field
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

33 citing papers in PubMed, 45 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. TCF21: a critical transcription factor in health and cancer.Journal of molecular medicine (Berlin, Germany) · 2020
    Review
  9. Article
  10. Developmental Pathways of Cardiac Fibroblasts.Cold Spring Harbor perspectives in biology · 2020
    Review
  11. Article
  12. Coronary Disease-Associated GeneCirculation research · 2020
    Article
  13. Review
  14. Genetic Insights Into Smooth Muscle Cell Contributions to Coronary Artery Disease.Arteriosclerosis, thrombosis, and vascular biology · 2019
    Review
  15. Article
  16. The Tcf21 lineage constitutes the lung lipofibroblast population.American journal of physiology. Lung cellular and molecular physiology · 2019
    Article
  17. Article
  18. Article
  19. Review
  20. Article
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

13 authors at 3 institutions in 1 country.

Olga SazonovaDepartment of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America; Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America.
Yuqi ZhaoDepartment of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California, United States of America.
Sylvia NürnbergDepartment of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America; Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America.
Clint MillerDepartment of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America; Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America.
Milos PjanicDepartment of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America; Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America.
Victor G CastanoDepartment of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America.
Juyong B KimDepartment of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America; Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America.
Elias L SalfatiDepartment of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America; Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America.
Anshul B KundajeDepartment of Genetics, Stanford University School of Medicine, Stanford, California, United States of America.
Gill BejeranoCardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America; Department of Computer Science, Stanford University School of Medicine, Stanford, California, United States of America; Department of Pediatrics, Stanford University School of Medicine, Stanford, California, United States of America; Department of Developmental Biology, Stanford University School of Medicine, Stanford, California, United States of America.
Themistocles AssimesDepartment of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America; Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America.
Xia YangDepartment of Integrative Biology and Physiology, University of California, Los Angeles, Los Angeles, California, United States of America.
Thomas QuertermousDepartment of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, California, United States of America; Cardiovascular Institute, Stanford University School of Medicine, Stanford, California, United States of America.
Stanford University · USCardiovascular Institute of the South · USUniversity of California, Los Angeles · US

Funding

Mechanism of the Coronary Heart Disease Association at Chromosome 6q23.2R01HL109512 · NHLBI · STANFORD UNIVERSITY · PI QUERTERMOUS, THOMAS · 2011 to 2019
$6.1M
Training in Myocardial Biology at Stanford (TIMBS)T32HL094274 · NHLBI · STANFORD UNIVERSITY · PI Euan A Ashley, Daniel Bernstein · 2010 to 2026
$5.0M
Identification and study of the vascular disease gene at 9p21.3R01HL103635 · NHLBI · STANFORD UNIVERSITY · PI QUERTERMOUS, THOMAS · 2010 to 2013
$2.4M
Identification of causal coronary heart disease variation in smooth muscle cellsR33HL120757 · NHLBI · STANFORD UNIVERSITY · PI QUERTERMOUS, THOMAS · 2016 to 2018
$1.6M
EPISTATIC REGULATORY MECHANISMS OF CORONARY HEART DISEASE RISKR00HL125912 · NHLBI · UNIVERSITY OF VIRGINIA · PI MILLER, CLINT L · 2017 to 2019
$747k
Identification of causal coronary heart disease variation in smooth muscle cellsR21HL120757 · NHLBI · STANFORD UNIVERSITY · PI QUERTERMOUS, THOMAS · 2014 to 2015
$434k
Epistatic Regulatory Mechanisms of Coronary Heart Disease RiskK99HL125912 · NHLBI · STANFORD UNIVERSITY · PI MILLER, CLINT L · 2015 to 2016
$285k
NHLBI NIH HHS K99 HL125912NHLBI NIH HHS R00 HL125912NHLBI NIH HHS R01 HL103635NHLBI NIH HHS R01HL103635NHLBI NIH HHS R01 HL109512NHLBI NIH HHS R01HL109512NHLBI NIH HHS R21 HL120757NHLBI NIH HHS R21HL120757NHLBI NIH HHS R33 HL120757NHLBI NIH HHS T32 HL094274
6 · The paper itself

Abstract

To functionally link coronary artery disease (CAD) causal genes identified by genome wide association studies (GWAS), and to investigate the cellular and molecular mechanisms of atherosclerosis, we have used chromatin immunoprecipitation sequencing (ChIP-Seq) with the CAD associated transcription factor TCF21 in human coronary artery smooth muscle cells (HCASMC). Analysis of identified TCF21 target genes for enrichment of molecular and cellular annotation terms identified processes relevant to CAD pathophysiology, including "growth factor binding," "matrix interaction," and "smooth muscle contraction." We characterized the canonical binding sequence for TCF21 as CAGCTG, identified AP-1 binding sites in TCF21 peaks, and by conducting ChIP-Seq for JUN and JUND in HCASMC confirmed that there is significant overlap between TCF21 and AP-1 binding loci in this cell type. Expression quantitative trait variation mapped to target genes of TCF21 was significantly enriched among variants with low P-values in the GWAS analyses, suggesting a possible functional interaction between TCF21 binding and causal variants in other CAD disease loci. Separate enrichment analyses found over-representation of TCF21 target genes among CAD associated genes, and linkage disequilibrium between TCF21 peak variation and that found in GWAS loci, consistent with the hypothesis that TCF21 may affect disease risk through interaction with other disease associated loci. Interestingly, enrichment for TCF21 target genes was also found among other genome wide association phenotypes, including height and inflammatory bowel disease, suggesting a functional profile important for basic cellular processes in non-vascular tissues. Thus, data and analyses presented here suggest that study of GWAS transcription factors may be a highly useful approach to identifying disease gene interactions and thus pathways that may be relevant to complex disease etiology.

Indexed as

Gene Regulatory NetworksAtherosclerosisBasic Helix-Loop-Helix ProteinsBinding SitesCoronary Artery DiseaseCoronary VesselsDNA-Binding ProteinsGene Expression RegulationGenome-Wide Association StudyHumansLinkage DisequilibriumPolymorphism, Single NucleotideQuantitative Trait LociTranscription Factor AP-1Basic Helix-Loop-Helix ProteinsDNA-Binding ProteinsTCF21 protein, humanTranscription Factor AP-1

Identifiers

PMID26020271
PMCPMC4447360
OpenAlexW597219917

What OpenQuestion holds

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LicenceCC BY
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.