Evidence map›Paper›PMID 30786239›Full record

ArticleCirculation. Genomic and precision medicine2019

High-Resolution Regulatory Maps Connect Vascular Risk Variants to Disease-Related Pathways.

Örjan Åkerborg, Rapolas Spalinskas, Sailendra Pradhananga, Anandashankar Anil, Pontus Höjer, Flore-Anne Poujade, Lasse Folkersen, Professor Per Eriksson, Pelin Sahlén

Erratum issuedOpen access · greenAbstract read
In one paragraph

Article in Circulation. Genomic and precision medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
2.2field-weighted citation impact, top 13% 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

9 citing papers in PubMed, 18 citations in OpenAlex.

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  6. Schizophrenia risk alleles often affect the expression of many genes and each gene may have a different effect on the risk: A mediation analysis.American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics · 2021
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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Örjan ÅkerborgScience for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.).
Rapolas SpalinskasScience for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.).
Sailendra PradhanangaScience for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.).
Anandashankar AnilScience for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.).
Pontus HöjerScience for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.).
Flore-Anne PoujadeCardiovascular Medicine Unit, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden (F.-A.P., P.E.).
Lasse FolkersenDepartment of Bioinformatics, Technical University of Denmark, Copenhagen, Denmark (L.F.).
Professor Per ErikssonCardiovascular Medicine Unit, Department of Medicine, Center for Molecular Medicine, Karolinska Institutet, Stockholm, Sweden (F.-A.P., P.E.).
Pelin SahlénScience for Life Laboratory, Division of Gene Technology, School of Engineering Sciences in Chemistry, Biotechnology and Health, KTH Royal Institute of Technology, Solna, Sweden (Ö.Å., R.S., S.P., A.A., P.H., P.S.).
KTH Royal Institute of Technology · SEKarolinska Institutet · SETechnical University of Denmark · DK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundGenetic variant landscape of coronary artery disease is dominated by noncoding variants among which many occur within putative enhancers regulating the expression levels of relevant genes. It is crucial to assign the genetic variants to their correct genes both to gain insights into perturbed functions and better assess the risk of disease.

methodsIn this study, we generated high-resolution genomic interaction maps (≈750 bases) in aortic endothelial, smooth muscle cells and THP-1 (human leukemia monocytic cell line) macrophages stimulated with lipopolysaccharide using Hi-C coupled with sequence capture targeting 25 429 features, including variants associated with coronary artery disease. We also sequenced their transcriptomes and mapped putative enhancers using chromatin immunoprecipitation with an antibody against H3K27Ac.

resultsThe regions interacting with promoters showed strong enrichment for enhancer elements and validated several previously known interactions and enhancers. We detected interactions for 727 risk variants obtained by genome-wide association studies and identified novel, as well as established genes and functions associated with cardiovascular diseases. We were able to assign potential target genes for additional 398 genome-wide association studies variants using haplotype information, thereby identifying additional relevant genes and functions. Importantly, we discovered that a subset of risk variants interact with multiple promoters and their expression levels were strongly correlated.

conclusionsIn summary, we present a catalog of candidate genes regulated by coronary artery disease-related variants and think that it will be an invaluable resource to further the investigation of cardiovascular pathologies and disease.

Indexed as

Gene Regulatory NetworksCell LineCoronary Artery DiseaseEnhancer Elements, GeneticGenetic VariationGenome-Wide Association StudyGenomicsHaplotypesHumansLinkage DisequilibriumPolymorphism, Single NucleotidePromoter Regions, GeneticRisk Factorscoronary artery diseasegenegenomicshaplotypeinflammation

Identifiers

PMID30786239
PMCPMC8104016
OpenAlexW2951039473

What Socratic 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 Socratic graph.