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Enhancers Decoding the Mechanisms Underlying CAD Risk

Periodic Reporting for period 2 - EnDeCAD (Enhancers Decoding the Mechanisms Underlying CAD Risk)

Reporting period: 2020-07-01 to 2021-12-31

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 and tissues, namely those of the vascular wall, liver and adipose tissue. 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.
One of the major goals of this project is to provide a deeper understanding of the genetic basis of CAD through functional characterization of noncoding regulatory variants in disease relevant cell types. We have done this by pinpointing risk SNPs located within tissue-specific enhancers (WP1), identifying enhancers with allele specific activity using massively parallel reporter assays (WP2) and revealing their target coding genes using chromatin conformation capture and cis-coaccessibility networks (WP3) and experimentally validating selected candidates using CRISPR/Cas9 techniques (WP2/3). Main achievements are listed below:

1) We have extensively investigated the involvement of the liver in the progression of coronary artery disease. We show that over one third of risk variants for CAD are located in regulatory elements specific to liver, and they act to regulate the expression of genes implicated in traditional risk factors, such as glucose and cholesterol related traits (Ref #1). Our results not only confirm the correlation of cholesterol levels and the risk of coronary artery disease but also pinpoint for the first time the causal single nucleotide polymorphisms and the potential target genes that mediate the risk. Another important finding was the discovery that risk variant-containing regulatory elements often seem to regulate many genes, not just one. Our findings expand the list of genes and regulatory mechanisms acting in the liver and governing the risk of CAD development. Deciphering gene regulatory networks is becoming increasingly important in understanding disease mechanisms and developing next generation drug therapies.

2) We have harnessed the potential of single cell genomics techniques to present the first enhancer atlas of human atherosclerotic lesions in the native tissue context. We demonstrated that genetic risk variants associated with CAD are particularly enriched in cis-regulatory elements specific to ECs and SMCs, indicating that these cells play a significant role in transmitting susceptibility to the disease. Based on chromatin accessibility mapping and gene expression data, we were able to identify putative target genes for approximately 30% of all known loci associated with CAD. Finally, we performed experimental fine-mapping of the variants using MPRA and identified the most potential causal SNPs for over 30 CAD loci. We present several CAD loci where chromatin accessibility and gene expression could be assigned to one cell type predicting the cell type of action.

3) Our results above have demonstrated that noncoding regulatory elements are frequently cell-type specific. For these reasons, it is important to measure gene expression, epigenetic profiles and cell phenotypes in pure cell populations. To achieve this, we have collected genetic, transcriptomic, epigenetic and phenotypic data from SMCs and ECs extracted from 150+ multiethnic heart transplant donors. We demonstrate that almost half of the CAD-associated loci were associated with one of the CAD-relevant SMC phenotypes traits, migration, proliferation, and calcification. Furthermore, we found thousands of expression quantitative trait loci (eQTLs) and over 3,000 regulatory elements whose activity is modulated by genetic variants in ECs. Importantly, the regulatory SNPs identified were enriched in CAD loci, as exemplified by PECAM-1, FES, and AXL loci for which experimental evidence supports their contributions to vascular functions. Together our data supports the view that genetic predisposition for CAD is partly manifested through the ECs and SMCs. These findings could improve the interpretation of CAD GWAS and inform candidate targets for therapeutic intervention or risk prediction.
As the major progress beyond the state of the art we have adopted single-cell genomic approaches to uncover cell (sub)types in their native context and resolve the heterogeneity of genetic associations. This has enabled unprecedented resolution to identify subtypes of cells and regulatory elements mediating genetic predisposition to CAD thus substantially broadening our view of the contributions of different cell types and genes. We demonstrated that over one third of risk variants for CAD are located in regulatory elements specific to liver whereas the remainder is expected to largely act through ECs and SMCs of the vascular wall. Importantly, we demonstrate that enhancer variants nearby traditional risk genes with known exonic risk variants could represent another way by which genetic variation regulated predisposition to disease. Finally, we have been among the first to provide evidence of single SNPs capacity to regulate many nearby genes revealing the complexity of genetic architecture of CAD.

These results will ultimately lead to more complete picture of gene regulatory programs and causal events driving CAD progression. The mechanisms revealing causality of single variant loci will significantly advance the field, while increase in our understanding of the molecular landscape causing CAD across tissues represent a major breakthrough. Shedding light into the molecular mechanisms of these variants has the potential to improve biomarker and drug target identification, risk prediction and treatment selection in clinical practice.
Schematic overview