Evidence map›Paper›PMID 31718536›Full record

ArticleBMC genetics2019

SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies.

Ivan Gorlov, Xiangjun Xiao, Maureen Mayes, Olga Gorlova, Christopher Amos

Open access · diamondAbstract read
In one paragraph

Article in BMC genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 19% 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

6 citing papers in PubMed, 9 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Ivan GorlovThe Geisel School of Medicine, Department of Biomedical Data Science, Dartmouth College, HB7936, One Medical Center Dr., Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA. ivan.p.gorlov@dartmouth.edu.ORCID 0000-0002-9006-7203
Xiangjun XiaoDepartment of Medicine, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA.
Maureen MayesDepartment of Internal Medicine, Division of Rheumatology, University of Texas McGovern Medical School, Houston, TX, USA.
Olga GorlovaThe Geisel School of Medicine, Department of Biomedical Data Science, Dartmouth College, HB7936, One Medical Center Dr., Dartmouth-Hitchcock Medical Center, Lebanon, NH, 03756, USA.
Christopher AmosDepartment of Medicine, Baylor College of Medicine, One Baylor Plaza, Houston, TX, 77030, USA.
Baylor College of Medicine · USDartmouth College · US

Funding

Transdisciplinary Research in Cancer of the Lung (TRICL)U19CA148127 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI AMOS, CHRISTOPHER I., LE MARCHAND, LOIC · 2010 to 2014
$10.9M
Sex Differences in Methylome Alterations and Mutational Burden in Early Stage MelanomaP01CA206980 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI BERWICK, MARIANNE, THOMAS, NANCY E. · 2017 to 2022
$10.1M
Predicting SNP priors for Cancer GWASsR56LM012371 · NLM · DARTMOUTH COLLEGE · PI DEMIDENKO, EUGENE · 2017 to 2018
$640k
NCI NIH HHS P01 CA206980NCI NIH HHS U19 CA148127NLM NIH HHS R56 LM012371
6 · The paper itself

Abstract

backgroundOver the relatively short history of Genome Wide Association Studies (GWASs), hundreds of GWASs have been published and thousands of disease risk-associated SNPs have been identified. Summary statistics from the conducted GWASs are often available and can be used to identify SNP features associated with the level of GWAS statistical significance. Those features could be used to select SNPs from gray zones (SNPs that are nominally significant but do not reach the genome-wide level of significance) for targeted analyses.

methodsWe used summary statistics from recently published breast and lung cancer and scleroderma GWASs to explore the association between the level of the GWAS statistical significance and the expression quantitative trait loci (eQTL) status of the SNP. Data from the Genotype-Tissue Expression Project (GTEx) were used to identify eQTL SNPs.

resultsWe found that SNPs reported as eQTLs were more significant in GWAS (higher -log

conclusionsThe results of this study indicate that the SNP's eQTL status, as well as eQTL density in the adjacent region are positively associated with the level of statistical significance of the SNP in GWAS.

Indexed as

Polymorphism, Single NucleotideQuantitative Trait LociBreast NeoplasmsFemaleGene Expression ProfilingGene Expression RegulationGenetic Predisposition to DiseaseGenome-Wide Association StudyHumansLung NeoplasmsMaleModels, StatisticalOrgan SpecificityRegulatory Elements, TranscriptionalScleroderma, SystemicCancerExpression quantitative trait loci (eQTL)Gene expressionGenome wide association studies (GWASs)Statistical significance

Identifiers

PMID31718536
PMCPMC6852916
OpenAlexW2989167897

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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.