Evidence map›Paper›PMID 26966275›Full record

ArticleArteriosclerosis, thrombosis, and vascular biology2016

Network-Based Identification and Prioritization of Key Regulators of Coronary Artery Disease Loci.

Yuqi Zhao, Jing Chen, Johannes M Freudenberg, Qingying Meng, Deepak K Rajpal, Xia Yang

Open access · bronzeAbstract read
In one paragraph

Article in Arteriosclerosis, thrombosis, and vascular biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
44citing papers in PubMed, 1 pooled it
4.9field-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

44 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Gene Regulatory Networks in Coronary Artery Disease.Current atherosclerosis reports · 2023
    Review
  8. Review
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Review
  15. Article
  16. Experimental and therapeutic medicine · 2020
    Article
  17. Observational
  18. Review
  19. Article
  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

6 authors at 1 institution in 1 country.

Yuqi ZhaoFrom the Department of Integrative Biology and Physiology, University of California, Los Angeles (Y.Z., Q.M., X.Y.); and Target Sciences Computational Biology (US), GSK, King of Prussia, PA (J.C., J.M.F., D.K.R.).
Jing ChenFrom the Department of Integrative Biology and Physiology, University of California, Los Angeles (Y.Z., Q.M., X.Y.); and Target Sciences Computational Biology (US), GSK, King of Prussia, PA (J.C., J.M.F., D.K.R.).
Johannes M FreudenbergFrom the Department of Integrative Biology and Physiology, University of California, Los Angeles (Y.Z., Q.M., X.Y.); and Target Sciences Computational Biology (US), GSK, King of Prussia, PA (J.C., J.M.F., D.K.R.).
Qingying MengFrom the Department of Integrative Biology and Physiology, University of California, Los Angeles (Y.Z., Q.M., X.Y.); and Target Sciences Computational Biology (US), GSK, King of Prussia, PA (J.C., J.M.F., D.K.R.).
Deepak K RajpalFrom the Department of Integrative Biology and Physiology, University of California, Los Angeles (Y.Z., Q.M., X.Y.); and Target Sciences Computational Biology (US), GSK, King of Prussia, PA (J.C., J.M.F., D.K.R.). xyang123@ucla.edu deepak.k.rajpal@gsk.com.
Xia YangFrom the Department of Integrative Biology and Physiology, University of California, Los Angeles (Y.Z., Q.M., X.Y.); and Target Sciences Computational Biology (US), GSK, King of Prussia, PA (J.C., J.M.F., D.K.R.). xyang123@ucla.edu deepak.k.rajpal@gsk.com.
University of California, Los Angeles · US

Funding

DHA Reverses Gene Network Signatures of Fructose-induced Metabolic SyndromeR01DK104363 · NIDDK · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI YANG, XIA · 2015 to 2019
$2.4M
NIDDK NIH HHS R01 DK104363
6 · The paper itself

Abstract

objectiveRecent genome-wide association studies of coronary artery disease (CAD) have revealed 58 genome-wide significant and 148 suggestive genetic loci. However, the molecular mechanisms through which they contribute to CAD and the clinical implications of these findings remain largely unknown. We aim to retrieve gene subnetworks of the 206 CAD loci and identify and prioritize candidate regulators to better understand the biological mechanisms underlying the genetic associations. APPROACH AND

resultsWe devised a new integrative genomics approach that incorporated (1) candidate genes from the top CAD loci, (2) the complete genetic association results from the 1000 genomes-based CAD genome-wide association studies from the Coronary Artery Disease Genome Wide Replication and Meta-Analysis Plus the Coronary Artery Disease consortium, (3) tissue-specific gene regulatory networks that depict the potential relationship and interactions between genes, and (4) tissue-specific gene expression patterns between CAD patients and controls. The networks and top-ranked regulators according to these data-driven criteria were further queried against literature, experimental evidence, and drug information to evaluate their disease relevance and potential as drug targets. Our analysis uncovered several potential novel regulators of CAD such as LUM and STAT3, which possess properties suitable as drug targets. We also revealed molecular relations and potential mechanisms through which the top CAD loci operate. Furthermore, we found that multiple CAD-relevant biological processes such as extracellular matrix, inflammatory and immune pathways, complement and coagulation cascades, and lipid metabolism interact in the CAD networks.

conclusionsOur data-driven integrative genomics framework unraveled tissue-specific relations among the candidate genes of the CAD genome-wide association studies loci and prioritized novel network regulatory genes orchestrating biological processes relevant to CAD.

Indexed as

Computational BiologyDatabases, GeneticGene Expression ProfilingGene Regulatory NetworksGenetic LociNeural Networks, ComputerAnimalsBayes TheoremCase-Control StudiesComputer SimulationCoronary Artery DiseaseGene Expression RegulationGenetic Predisposition to DiseaseGenome-Wide Association StudyGenomicsHumansLumicanLUM protein, humanSTAT3 protein, humanSTAT3 Transcription Factorcoronary artery diseasegene expressiongene regulatory networksgenome-wide association studygenomics

Identifiers

PMID26966275
PMCPMC5576868
OpenAlexW2294302252

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.