Evidence map›Paper›PMID 26277204›Full record

ReviewTrends in cardiovascular medicine2016

Gene scanning and heart attack risk.

Andreas S Barth, Gordon F Tomaselli

Open access · greenAbstract readReview
In one paragraph

Review in Trends in cardiovascular medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed, 1 pooled it
3.2field-weighted citation impact, top 8% 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

9 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.

  1. Pooled it
  2. Analysis of the differences in immune-related genes and immune cell subtypes in acute myocardial infarction.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologica · 2024
    Article
  3. Article
  4. Genetic Markers for Coronary Artery Disease.Medicina (Kaunas, Lithuania) · 2018
    Review
  5. Article
  6. Article
  7. Ischemia/Reperfusion.Comprehensive Physiology · 2016
    Review
  8. Article
  9. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors at 1 institution in 1 country.

Andreas S BarthDivision of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD.
Gordon F TomaselliDivision of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD. Electronic address: gtomase1@jhmi.edu.
Johns Hopkins University · US

Funding

Pathobiology of Cardiac Dyssynchrony &ResynchronizationP01HL077180 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI KASS, DAVID ALAN · 2004 to 2014
$22.8M
Expression Profiling in Canine Models of Human DiseaseR01HL072488 · NHLBI · JOHNS HOPKINS UNIVERSITY · PI TOMASELLI, GORDON FRANK · 2002 to 2005
$3.2M
NHLBI NIH HHS P01 HL077180NHLBI NIH HHS R01 HL072488
6 · The paper itself

Abstract

Coronary heart disease remains the leading cause of death in the Western World. The advent of microarray and next-generation sequencing technologies has generated multi-dimensional data sets, allowing for new pathophysiological insights into this complex disease. To date, genome-wide association studies (GWAS) have identified 152 associated loci and 320 candidate genes, contributing to the genetic risk of coronary artery disease (CAD) and acute myocardial infarction (AMI). The majority of single nucleotide polymorphisms (SNPs) mediate their risk by unknown mechanisms. A functional analysis based on Gene Ontology and KEGG pathways of candidate genes that are associated with CAD/AMI-SNPs showed the strongest evidence for genes regulating cholesterol metabolism. Additional clusters were significantly enriched for pathways, which play prominent roles during AMI and the development of atherosclerotic plaques in vascular tissue, including focal adhesion/extracellular matrix interaction, TGF-β signaling, apoptosis, regulation of vascular smooth muscle contraction, angiogenesis, calcium ion binding, and transcription factors. A systems genetics approach, which incorporates genetic risk with gene expression data, metabolomic data, and protein biochemistry into genome-wide network studies, holds promise to elucidate the complex interplay between genetic risk and environmental factors for coronary artery disease.

Indexed as

Polymorphism, Single NucleotideComputational BiologyCoronary Artery DiseaseDatabases, FactualGene Regulatory NetworksGenetic MarkersGenetic Predisposition to DiseaseGenome-Wide Association StudyGenomicsHumansMyocardial InfarctionPhenotypePrognosisProtein Interaction MapsRisk FactorsSignal TransductionGenetic MarkersCoronary artery diseaseFunctional genomicsGeneGenome-wide association studies

Identifiers

PMID26277204
PMCPMC5266753
OpenAlexW998388588

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.