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EnDeCAD SIGNED

Enhancers Decoding the Mechanisms Underlying CAD Risk

Total Cost €

0

EC-Contrib. €

0

Partnership

0

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 EnDeCAD project word cloud

Explore the words cloud of the EnDeCAD project. It provides you a very rough idea of what is the project "EnDeCAD" about.

enhancer    collection    lying    data    hope    hundreds    gwas    pioneering    causal    complete    search    treatment    strives    linking    majority    snp    explained    function    stimuli    vast    biological    roles    snps    basis    small    progression    correlative    risk    interaction    endothelial    single    establishment    adipocytes    obtain    hepatocytes    biomarker    array    additionally    phenotypic    variants    regions    genetic    molecular    physical    gene    translatable    relationships    cardiovascular    artery    disease    combination    loci    association    metabolomics    enhancers    clinical    picture    date    fundamental    events    functional    genome    parallel    genes    mechanisms    portion    significantly    types    coronary    candidate    macrophages    trait    discoveries    ultimately    identification    cells    characterization    smooth    provides    polymorphisms    eqtl    breakthrough    wall    heritability    vessel    linked    cad    prediction    expression    nucleotide    driving    discovered    link    muscle    understand    regulatory    massively    cell    deep    noncoding   

Project "EnDeCAD" data sheet

The following table provides information about the project.

Coordinator
ITA-SUOMEN YLIOPISTO 

Organization address
address: YLIOPISTONRANTA 1 E
city: KUOPIO
postcode: 70211
website: www.uef.fi

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Finland [FI]
 Total cost 1˙498˙647 €
 EC max contribution 1˙498˙647 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2018-STG
 Funding Scheme ERC-STG
 Starting year 2019
 Duration (year-month-day) from 2019-01-01   to  2023-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    ITA-SUOMEN YLIOPISTO FI (KUOPIO) coordinator 1˙498˙647.00

Map

 Project objective

In recent years, genome-wide association studies (GWAS) have discovered hundreds of single nucleotide polymorphisms (SNPs) which are significantly associated with coronary artery disease (CAD). However, the SNPs identified by GWAS explain typically only small portion of the trait heritability and vast majority of variants do not have known biological roles. This is explained by variants lying within noncoding regions such as in cell type specific enhancers and additionally ‘the lead SNP’ identified in GWAS may not be the ‘the causal SNP’ but only linked with a trait associated SNP. Therefore, a major priority for understanding disease mechanisms is to understand at the molecular level the function of each CAD loci. In this study we aim to bring the functional characterization of SNPs associated with CAD risk to date by focusing our search for causal SNPs to enhancers of disease relevant cell types, namely endothelial cells, macrophages and smooth muscle cells of the vessel wall, hepatocytes and adipocytes. By combination of massively parallel enhancer activity measurements, collection of novel eQTL data throughout cell types under disease relevant stimuli, identification of the target genes in physical interaction with the candidate enhancers and establishment of correlative relationships between enhancer activity and gene expression we hope to identify causal enhancer variants and link them with target genes to obtain a more complete picture of the gene regulatory events driving disease progression and the genetic basis of CAD. Linking these findings with our deep phenotypic data for cardiovascular risk factors, gene expression and metabolomics has the potential to improve risk prediction, biomarker identification and treatment selection in clinical practice. Ultimately, this research strives for fundamental discoveries and breakthrough that advance our knowledge of CAD and provides pioneering steps towards taking the growing array of GWAS for translatable results.

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The information about "ENDECAD" are provided by the European Opendata Portal: CORDIS opendata.

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