Evidence map›Paper›PMID 25658981›Full record

Trial reportPloS one2015

Analysis of gene-gene interactions among common variants in candidate cardiovascular genes in coronary artery disease.

Muntaser D Musameh, William Y S Wang, Christopher P Nelson, Carla Lluís-Ganella, Radoslaw Debiec, Isaac Subirana, Roberto Elosua, Anthony J Balmforth, Stephen G Ball, Alistair S Hall and 5 more

Abstract readClinical TrialMulticenter Study
In one paragraph

Trial report in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–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

4 citing papers in PubMed.

  1. Biomolecules · 2022
    Article
  2. Article
  3. Review
  4. 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

15 authors.

Muntaser D MusamehDepartment of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom; NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, United Kingdom.
William Y S WangSchool of Medicine, University of Queensland, Brisbane, Queensland, Australia.
Christopher P NelsonDepartment of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom; NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, United Kingdom.
Carla Lluís-GanellaCardiovascular Epidemiology and Genetics, IMIM, Barcelona, Spain.
Radoslaw DebiecDepartment of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom; NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, United Kingdom.
Isaac SubiranaCardiovascular Epidemiology and Genetics, IMIM, Barcelona, Spain; Epidemiology and Public Health Network (CIBERESP), Barcelona, Spain.
Roberto ElosuaCardiovascular Epidemiology and Genetics, IMIM, Barcelona, Spain.
Anthony J BalmforthDivision of Epidemiology, LIGHT, School of Medicine, University of Leeds, Leeds, United Kingdom.
Stephen G BallUniversity of Leeds, MCRC, Leeds Institute of Genetics, Health and Therapeutics, Leeds, United Kingdom.
Alistair S HallDivision of Epidemiology, LIGHT, School of Medicine, University of Leeds, Leeds, United Kingdom.
Sekar KathiresanThe Broad Institute of MIT and Harvard, Cambridge, Massachusetts, United States of America.
John R ThompsonDepartment of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom.
Gavin LucasCardiovascular Epidemiology and Genetics, IMIM, Barcelona, Spain.
Nilesh J SamaniDepartment of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom; NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, United Kingdom.
Maciej TomaszewskiDepartment of Cardiovascular Sciences, University of Leicester, Glenfield Hospital, Leicester, United Kingdom; NIHR Leicester Cardiovascular Biomedical Research Unit, Glenfield Hospital, Leicester, United Kingdom.

Funding

A Genome-wide Association Study for Early-Onset Myocardial InfarctionR01HL087676 · NHLBI · MASSACHUSETTS GENERAL HOSPITAL · PI ALTSHULER, DAVID · 2007 to 2009
$4.7M
Medical Research Council MR/L01629X/1NHLBI NIH HHS R01 HL087676Wellcome TrustWellcome Trust 085475
6 · The paper itself

Abstract

objectiveOnly a small fraction of coronary artery disease (CAD) heritability has been explained by common variants identified to date. Interactions between genes of importance to cardiovascular regulation may account for some of the missing heritability of CAD. This study aimed to investigate the role of gene-gene interactions in common variants in candidate cardiovascular genes in CAD. APPROACH AND

results2,101 patients with CAD from the British Heart Foundation Family Heart Study and 2,426 CAD-free controls were included in the discovery cohort. All subjects were genotyped with the Illumina HumanCVD BeadChip enriched for genes and pathways relevant to the cardiovascular system and disease. The primary analysis in the discovery cohort examined pairwise interactions among 913 common (minor allele frequency >0.1) independent single nucleotide polymorphisms (SNPs) with at least nominal association with CAD in single locus analysis. A secondary exploratory interaction analysis was performed among all 11,332 independent common SNPs surviving quality control criteria. Replication analyses were conducted in 2,967 patients and 3,075 controls from the Myocardial Infarction Genetics Consortium. None of the interactions amongst 913 SNPs analysed in the primary analysis was statistically significant after correction for multiple testing (required P<1.2x10-7). Similarly, none of the pairwise gene-gene interactions in the secondary analysis reached statistical significance after correction for multiple testing (required P = 7.8x10-10). None of 36 suggestive interactions from the primary analysis or 31 interactions from the secondary analysis was significant in the replication cohort. Our study had 80% power to detect odds ratios > 1.7 for common variants in the primary analysis.

conclusionsModerately large additive interactions between common SNPs in genes relevant to cardiovascular disease do not appear to play a major role in genetic predisposition to CAD. The role of genetic interactions amongst less common SNPs and with medium and small magnitude effects remain to be investigated.

Indexed as

Epistasis, GeneticPolymorphism, Single NucleotideAdultCohort StudiesCoronary Artery DiseaseFemaleHumansMaleMiddle AgedUnited Kingdom

Identifiers

PMID25658981
PMCPMC4320092

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Registered trials

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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.