Evidence map›Paper›PMID 22510845›Full record

ArticleEuropean journal of human genetics : EJHG2012

Pathway-based genome-wide association analysis of coronary heart disease identifies biologically important gene sets.

Lisa de las Fuentes, Wei Yang, Victor G Dávila-Román, C Charles Gu

Open access · bronzeAbstract read
In one paragraph

Article in European journal of human genetics : EJHG, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 2 pooled it
3.5field-weighted citation impact, top 7% 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

16 citing papers in PubMed, 2 syntheses or guidelines pooled it, 30 citations in OpenAlex.

  1. Pooled it
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  7. Precision medicine validation: identifying theJournal of feline medicine and surgery · 2019
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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 at 1 institution in 1 country.

Lisa de las FuentesCardiovascular Imaging and Clinical Research Core Laboratory, Cardiovascular Division, Department of Medicine, Washington University School of Medicine, St Louis, MO 63110, USA.
Wei Yang
Victor G Dávila-Román
C Charles Gu
Washington University in St. Louis · US

Funding

Washington University Institute of Clinical and Translational SciencesUL1TR000448 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$41.4M
Washington University Institute of Clinical and Translational SciencesKL2TR000450 · NCATS · WASHINGTON UNIVERSITY · PI EVANOFF, BRADLEY A · 2012 to 2016
$8.8M
GENETIC DETERMINANTS OF THE LVH PHENOTYPER01HL071782 · NHLBI · WASHINGTON UNIVERSITY · PI DAVILA-ROMAN, VICTOR G., GU, C CHARLES · 2003 to 2010
$4.7M
RESEARCH EDUCATION PROGRAM ON COMPUTATIONAL AND STATISTICAL TOOL DEVELOPMENT FOR ADDICTION GENETICSR25DA027995 · NIDA · WASHINGTON UNIVERSITY · PI MADDEN, PAMELA ANN, RICE, JOHN P. · 2009 to 2019
$4.3M
VARIABLE SELECTION IN GENETIC EPIDEMIOLOGICAL STUDIES OF CARDIOVASCULAR DISEASESR01HL091028 · NHLBI · WASHINGTON UNIVERSITY · PI GU, C CHARLES · 2008 to 2010
$913k
SLEEP AND ENTRAINMENT OF SCN FUNCTIONR01HL064278 · NHLBI · CASE WESTERN RESERVE UNIVERSITY · PI STROHL, KINGMAN PERKINS · 1999 to 2002
$871k
MYOCARDIAL FA METABOLISM GENE-GENE INTERACTIONS IN HYPERTENSIVE HEART DISEASER21HL094668 · NHLBI · WASHINGTON UNIVERSITY · PI DE LAS FUENTES, LISA · 2009 to 2010
$418k
THE FRAMINGHAM HEART STUDY-N01HC25195-268025195-268025195N01HC025195 · HC · TRUSTEES OF BOSTON UNIVERSITY · PI WOLF, PHILIP A · 2002 to 2006
–
NCATS NIH HHS KL2 TR000450NCATS NIH HHS UL1 TR000448NHLBI NIH HHS HL071782NHLBI NIH HHS HL091028NHLBI NIH HHS HL094668NHLBI NIH HHS N01 HC025195NHLBI NIH HHS N01-HC-25195NHLBI NIH HHS N02 HL064278NHLBI NIH HHS R01 HL071782NHLBI NIH HHS R01 HL091028NHLBI NIH HHS R21 HL094668NIDA NIH HHS R25 DA027995
6 · The paper itself

Abstract

Genome-wide association (GWA) studies of complex diseases including coronary heart disease (CHD) challenge investigators attempting to identify relevant genetic variants among hundreds of thousands of markers being tested. A selection strategy based purely on statistical significance will result in many false negative findings after adjustment for multiple testing. Thus, an integrated analysis using information from the learned genetic pathways, molecular functions, and biological processes is desirable. In this study, we applied a customized method, variable set enrichment analysis (VSEA), to the Framingham Heart Study data (404,467 variants, n=6421) to evaluate enrichment of genetic association in 1395 gene sets for their contribution to CHD. We identified 25 gene sets with nominal P<0.01; at least four sets are previously known for their roles in CHD: vascular genesis (GO:0001570), fatty-acid biosynthetic process (GO:0006633), fatty-acid metabolic process (GO:0006631), and glycerolipid metabolic process (GO:0046486). Although the four gene sets include 170 genes, only three of the genes contain a variant ranked among the top 100 in single-variant association tests of the 404,467 variants tested. Significant enrichment for novel gene sets less known for their importance to CHD were also identified: Rac 1 cell-motility signaling pathway (h_rac1 Pathway, P<0.001) and sulfur amino-acid metabolic process (GO:0000096, P<0.001). In summary, we showed that the pathway-based VSEA can help prioritize association signals in GWA studies by identifying biologically plausible targets for downstream searches of genetic variants associated with CHD.

Indexed as

Genome, HumanCase-Control StudiesCoronary DiseaseGenetic LociGenome-Wide Association StudyHumansMetabolic Networks and PathwaysPolymorphism, Single Nucleotiderac1 GTP-Binding Proteinrac1 GTP-Binding ProteinRAC1 protein, human

Identifiers

PMID22510845
PMCPMC3477866
OpenAlexW2090642869

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.