Evidence map›Paper›PMID 24520200›Full record

ReviewThe application of clinical genetics2014

Pathogenesis of coronary artery disease: focus on genetic risk factors and identification of genetic variants.

Sergi Sayols-Baixeras, Carla Lluís-Ganella, Gavin Lucas, Roberto Elosua

Abstract readReview
In one paragraph

Review in The application of clinical genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 74 papers, 10 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
74citing papers in PubMed, 10 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

74 citing papers in PubMed, 10 syntheses or guidelines pooled it.

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14 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

4 authors.

Sergi Sayols-BaixerasCardiovascular epidemiology and Genetics Research Group, Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain.
Carla Lluís-GanellaCardiovascular epidemiology and Genetics Research Group, Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain.
Gavin LucasCardiovascular epidemiology and Genetics Research Group, Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain.
Roberto ElosuaCardiovascular epidemiology and Genetics Research Group, Institut Hospital del Mar d'Investigacions Mèdiques, Barcelona, Spain.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coronary artery disease (CAD) is the leading cause of death and disability worldwide, and its prevalence is expected to increase in the coming years. CAD events are caused by the interplay of genetic and environmental factors, the effects of which are mainly mediated through cardiovascular risk factors. The techniques used to study the genetic basis of these diseases have evolved from linkage studies to candidate gene studies and genome-wide association studies. Linkage studies have been able to identify genetic variants associated with monogenic diseases, whereas genome-wide association studies have been more successful in determining genetic variants associated with complex diseases. Currently, genome-wide association studies have identified approximately 40 loci that explain 6% of the heritability of CAD. The application of this knowledge to clinical practice is challenging, but can be achieved using various strategies, such as genetic variants to identify new therapeutic targets, personal genetic information to improve disease risk prediction, and pharmacogenomics. The main aim of this narrative review is to provide a general overview of our current understanding of the genetics of coronary artery disease and its potential clinical utility.

Indexed as

coronary artery diseasegenetic risk factorsgenetic variantspathogenesis

Identifiers

PMID24520200
PMCPMC3920464

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.