Evidence map›Paper›PMID 24931982›Full record

ArticleBioinformatics (Oxford, England)2014

GRASP: analysis of genotype-phenotype results from 1390 genome-wide association studies and corresponding open access database.

Richard Leslie, Christopher J O'Donnell, Andrew D Johnson

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioinformatics (Oxford, England), 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 172 papers, 20 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
172citing papers in PubMed, 20 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

172 citing papers in PubMed, 20 syntheses or guidelines pooled it.

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  6. Epigenome-wide meta-analysis of DNA methylation and childhood asthma.The Journal of allergy and clinical immunology · 2019
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112 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

3 authors.

Richard LeslieCardiovascular Epidemiology and Human Genomics Branch, National Heart, Lung and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, University of Massachusetts Medical School, Worcester, MA 01655 and Division of Cardiology, Massachusetts General Hospital, Boston, MA 02114, USACardiovascular Epidemiology and Human Genomics Branch, National Heart, Lung and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, University of Massachusetts Medical School, Worcester, MA 01655 and Division of Cardiology, Massachusetts General Hospital, Boston, MA 02114, USA.
Christopher J O'DonnellCardiovascular Epidemiology and Human Genomics Branch, National Heart, Lung and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, University of Massachusetts Medical School, Worcester, MA 01655 and Division of Cardiology, Massachusetts General Hospital, Boston, MA 02114, USACardiovascular Epidemiology and Human Genomics Branch, National Heart, Lung and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, University of Massachusetts Medical School, Worcester, MA 01655 and Division of Cardiology, Massachusetts General Hospital, Boston, MA 02114, USA.
Andrew D JohnsonCardiovascular Epidemiology and Human Genomics Branch, National Heart, Lung and Blood Institute, The Framingham Heart Study, Framingham, MA 01702, University of Massachusetts Medical School, Worcester, MA 01655 and Division of Cardiology, Massachusetts General Hospital, Boston, MA 02114, USA.

Funding

Cardiovascular Genomics and Bioinformatics projectsZIAHL006170 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI JOHNSON, ANDREW · 2013 to 2025
$25.3M
Genomic Epidemiology of Cardiovascular DiseaseZIAHL006002 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI O'DONNELL, CHRISTOPHER · 2009 to 2015
$8.0M
Gene Expression for Functional Genomics in Human PopulationsZIAHL006175 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI O'DONNELL, CHRISTOPHER · 2013 to 2015
$2.2M
Functional Genetic Variation Underlying Cardiovascular Genomic EpidemiologyZIAHL006173 · NHLBI · NATIONAL HEART, LUNG, AND BLOOD INSTITUTE · PI O'DONNELL, CHRISTOPHER · 2013 to 2015
$2.0M
Intramural NIH HHS
6 · The paper itself

Abstract

summaryWe created a deeply extracted and annotated database of genome-wide association studies (GWAS) results. GRASP v1.0 contains >6.2 million SNP-phenotype association from among 1390 GWAS studies. We re-annotated GWAS results with 16 annotation sources including some rarely compared to GWAS results (e.g. RNAediting sites, lincRNAs, PTMs). MOTIVATION: To create a high-quality resource to facilitate further use and interpretation of human GWAS results in order to address important scientific questions.

resultsGWAS have grown exponentially, with increases in sample sizes and markers tested, and continuing bias toward European ancestry samples. GRASP contains >100 000 phenotypes, roughly: eQTLs (71.5%), metabolite QTLs (21.2%), methylation QTLs (4.4%) and diseases, biomarkers and other traits (2.8%). cis-eQTLs, meQTLs, mQTLs and MHC region SNPs are highly enriched among significant results. After removing these categories, GRASP still contains a greater proportion of studies and results than comparable GWAS catalogs. Cardiovascular disease and related risk factors pre-dominate remaining GWAS results, followed by immunological, neurological and cancer traits. Significant results in GWAS display a highly gene-centric tendency. Sex chromosome X (OR = 0.18[0.16-0.20]) and Y (OR = 0.003[0.001-0.01]) genes are depleted for GWAS results. Gene length is correlated with GWAS results at nominal significance (P ≤ 0.05) levels. We show this gene-length correlation decays at increasingly more stringent P-value thresholds. Potential pleotropic genes and SNPs enriched for multi-phenotype association in GWAS are identified. However, we note possible population stratification at some of these loci. Finally, via re-annotation we identify compelling functional hypotheses at GWAS loci, in some cases unrealized in studies to date.

conclusionPooling summary-level GWAS results and re-annotating with bioinformatics predictions and molecular features provides a good platform for new insights. AVAILABILITY: The GRASP database is available at http://apps.nhlbi.nih.gov/grasp.

Indexed as

Databases, GeneticGenome-Wide Association StudyGenotypePhenotypePolymorphism, Single NucleotideGenesHumansQuantitative Trait Loci

Identifiers

PMID24931982
PMCPMC4072913

What OpenQuestion holds

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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.