Descrizione del progetto
La genetica contribuisce a far progredire la conoscenza sulla coronaropatia
Gli scienziati conducono studi di associazione sull’intero genoma per identificare i geni coinvolti nelle malattie umane e prevedere la presenza di malattie. Negli scorsi anni, gli studi di associazione sull’intero genoma hanno scoperto centinaia di polimorfismi a singolo nucleotide (il tipo più frequente di variazione genetica riscontrato nelle persone), strettamente interconnessi alla coronaropatia. Tuttavia, questi polimorfismi a singolo nucleotide descrivono generalmente solo pochi tratti ereditabili. Per comprendere meglio i meccanismi della malattia, il progetto EnDeCAD, finanziato dall’UE, esplorerà il ruolo di ogni locus della coronaropatia a livello molecolare. La conoscenza acquisita dovrebbe migliorare la previsione del rischio, l’identificazione dei biomarcatori e la selezione del trattamento nell’erogazione dell’assistenza sanitaria.
Obiettivo
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.
Campo scientifico
Parole chiave
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Meccanismo di finanziamento
ERC-STG - Starting GrantIstituzione ospitante
70211 KUOPIO
Finlandia