Evidence map›Paper›PMID 24219970›Full record

ArticleEuropean journal of human genetics : EJHG2014

Common genetic variants do not associate with CAD in familial hypercholesterolemia.

Erik P A van Iperen, Suthesh Sivapalaratnam, S Matthijs Boekholdt, G Kees Hovingh, Stephanie Maiwald, Michael W Tanck, Nicole Soranzo, Jonathan C Stephens, Jennifer G Sambrook, Marcel Levi and 4 more

Open access · bronzeAbstract read
In one paragraph

Article in European journal of human genetics : EJHG, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.1field-weighted citation impact, top 52% 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

3 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Calling and Phasing of Single-Nucleotide and Structural Variants of theInternational journal of molecular sciences · 2023
    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

14 authors at 3 institutions in 2 countries.

Erik P A van Iperen1] Department of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, Amsterdam, The Netherlands [2] Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands.
Suthesh SivapalaratnamDepartment of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands.
S Matthijs Boekholdt1] Department of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands [2] Department of Cardiology, Academic Medical Centre, Amsterdam, The Netherlands.
G Kees HovinghDepartment of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands.
Stephanie MaiwaldDepartment of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands.
Michael W TanckDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, Amsterdam, The Netherlands.
Nicole SoranzoHuman Genetics, Welcome Trust Sanger Institute, Hinxton, UK.ORCID 0000000310953852
Jonathan C Stephens1] Department of Haematology, University of Cambridge, Cambridge, UK [2] National Health Service Blood and Transplant, Cambridge, UK.
Jennifer G Sambrook1] Department of Haematology, University of Cambridge, Cambridge, UK [2] National Health Service Blood and Transplant, Cambridge, UK.
Marcel LeviDepartment of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands.
Willem H Ouwehand1] Human Genetics, Welcome Trust Sanger Institute, Hinxton, UK [2] Department of Haematology, University of Cambridge, Cambridge, UK [3] National Health Service Blood and Transplant, Cambridge, UK.
John Jp KasteleinDepartment of Vascular Medicine, Academic Medical Centre, Amsterdam, The Netherlands.
Mieke D TripDepartment of Cardiology, Academic Medical Centre, Amsterdam, The Netherlands.
Aeilko H ZwindermanDepartment of Clinical Epidemiology, Biostatistics and Bioinformatics, Academic Medical Centre, Amsterdam, The Netherlands.
Amsterdam UMC Location University of Amsterdam · NLNHS Blood and Transplant · GBWellcome Sanger Institute · GB

Funding

British Heart Foundation RG/09/012/28096Department of Health RP-PG-0310-1002
6 · The paper itself

Abstract

In recent years, multiple loci dispersed on the genome have been shown to be associated with coronary artery disease (CAD). We investigated whether these common genetic variants also hold value for CAD prediction in a large cohort of patients with familial hypercholesterolemia (FH). We genotyped a total of 41 single-nucleotide polymorphisms (SNPs) in 1701 FH patients, of whom 482 patients (28.3%) had at least one coronary event during an average follow up of 66 years. The association of each SNP with event-free survival time was calculated with a Cox proportional hazard model. In the cardiovascular disease risk factor adjusted analysis, the most significant SNP was rs1122608:G>T in the SMARCA4 gene near the LDL-receptor (LDLR) gene, with a hazard ratio for CAD risk of 0.74 (95% CI 0.49-0.99; P-value 0.021). However, none of the SNPs reached the Bonferroni threshold. Of all the known CAD loci analyzed, the SMARCA4 locus near the LDLR had the strongest negative association with CAD in this high-risk FH cohort. The effect is contrary to what was expected. None of the other loci showed association with CAD.

Indexed as

Polymorphism, Single NucleotideAgedCoronary Artery DiseaseDisease-Free SurvivalDNA HelicasesFemaleGene FrequencyGenetic Predisposition to DiseaseGenotypeHumansHyperlipoproteinemia Type IIMaleMiddle AgedNuclear ProteinsProportional Hazards ModelsRisk AssessmentDNA HelicasesNuclear ProteinsSMARCA4 protein, humanTranscription Factors

Identifiers

PMID24219970
PMCPMC4023217
OpenAlexW2009721750

What OpenQuestion holds

Textmetadata
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.