Evidence map›Paper›PMID 33105808›Full record

ArticleGenes2020

Expression Quantitative Trait Locus Mapping in Pulmonary Arterial Hypertension.

Anna Ulrich, Pablo Otero-Núñez, John Wharton, Emilia M Swietlik, Stefan Gräf, Nicholas W Morrell, Dennis Wang, Allan Lawrie, Martin R Wilkins, Inga Prokopenko and 3 more

Open access · goldAbstract read
In one paragraph

Article in Genes, 2020. 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
0.5field-weighted citation impact, top 29% 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

4 citing papers in PubMed, 7 citations in OpenAlex.

  1. [Research progress on bioinformatics in pulmonary arterial hypertension].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2024
    Review
  2. Article
  3. Pulmonary circulation · 2023
    Article
  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

13 authors at 4 institutions in 1 country.

Anna UlrichNational Heart and Lung Institute, Hammersmith Campus, Imperial College London, London SW7 2BU, UK.ORCID 0000-0003-3280-9974
Pablo Otero-NúñezNational Heart and Lung Institute, Hammersmith Campus, Imperial College London, London SW7 2BU, UK.
John WhartonNational Heart and Lung Institute, Hammersmith Campus, Imperial College London, London SW7 2BU, UK.
Emilia M SwietlikDepartment of Medicine, University of Cambridge, Cambridge CB2 3AX, UK.
Stefan GräfDepartment of Medicine, University of Cambridge, Cambridge CB2 3AX, UK.ORCID 0000-0002-1315-8873
Nicholas W MorrellDepartment of Medicine, University of Cambridge, Cambridge CB2 3AX, UK.
Dennis WangSheffield Institute for Translational Neuroscience, University of Sheffield, Sheffield S10 2TN, UK.ORCID 0000-0003-0068-1005
Allan LawrieDepartment of Infection, Immunity & Cardiovascular Disease, University of Sheffield, Sheffield S10 2TN, UK.ORCID 0000-0003-4192-9505
Martin R WilkinsNational Heart and Lung Institute, Hammersmith Campus, Imperial College London, London SW7 2BU, UK.
Inga ProkopenkoDepartment of Clinical and Experimental Medicine, University of Surrey, Guildford GU2 7XH, UK.
Christopher J RhodesNational Heart and Lung Institute, Hammersmith Campus, Imperial College London, London SW7 2BU, UK.
On Behalf Of The Nihr BioResource-Rare Diseases Consortium
Uk Pah Cohort Study Consortium
Imperial College London · GBUniversity of Cambridge · GBUniversity of Sheffield · GBUniversity of Surrey · GB

Funding

British Heart Foundation CH/09/001/25945British Heart Foundation FS/15/59/31839British Heart Foundation FS/18/52/33808British Heart Foundation RE/18/4/34215British Heart Foundation RG/08/006/25302British Heart Foundation RG/10/16/28575British Heart Foundation RG/13/4/30107British Heart Foundation SP/12/12/29836Department of HealthMedical Research Council MR/K020919/1NIH HHS HL105333Wellcome Trust WT205915
6 · The paper itself

Abstract

Expression quantitative trait loci (eQTL) can provide a link between disease susceptibility variants discovered by genetic association studies and biology. To date, eQTL mapping studies have been primarily conducted in healthy individuals from population-based cohorts. Genetic effects have been known to be context-specific and vary with changing environmental stimuli. We conducted a transcriptome- and genome-wide eQTL mapping study in a cohort of patients with idiopathic or heritable pulmonary arterial hypertension (PAH) using RNA sequencing (RNAseq) data from whole blood. We sought confirmation from three published population-based eQTL studies, including the GTEx Project, and followed up potentially novel eQTL not observed in the general population. In total, we identified 2314 eQTL of which 90% were cis-acting and 75% were confirmed by at least one of the published studies. While we observed a higher GWAS trait colocalization rate among confirmed eQTL, colocalisation rate of novel eQTL reported for lung-related phenotypes was twice as high as that of confirmed eQTL. Functional enrichment analysis of genes with novel eQTL in PAH highlighted immune-related processes, a suspected contributor to PAH. These potentially novel eQTL specific to or active in PAH could be useful in understanding genetic risk factors for other diseases that share common mechanisms with PAH.

Indexed as

Base SequenceFamilial Primary Pulmonary HypertensionFemaleGenetic Association StudiesGenetic Predisposition to DiseaseGenomeGenome-Wide Association StudyHumansMalePolymorphism, Single NucleotidePulmonary Arterial HypertensionQuantitative Trait LociSequence Analysis, RNATranscriptomebloodeQTLexpression quantitative trait locusgeneticspulmonary arterial hypertension

Identifiers

PMID33105808
PMCPMC7690609
OpenAlexW3093860938

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.