The discovery of new and effective treatments for human cardiovascular disease (CVD) requires the identification and validation of novel disease mechanisms. Recently, studies of genomic variation entered a new phase, in which unbiased genome-wide association studies (GWAS) can identify novel genetic loci associated with common diseases. We have recently described 95 loci associated with blood lipid levels LDL cholesterol (LDL-C), HDL cholesterol (HDL-C), or triglycerides (TG), which are strongly associated with risk for CVD. Much work will be needed to convert the novel associations into functional insights and, ultimately, therapies to reduce the risk of CVD. A key step is to determine how these genetic loci affect phenotypes in human tissue types relevant to lipid metabolism, principally liver and adipose. We have performed expression quantitative trait locus (eQTL) analyses of genotype vs. gene expression in surgical liver and adipose tissue samples from patients;from this work, we found strong associations between a number of lipid-associated tag single nucleotide polymorphisms (SNPs) and either hepatic or adipose expression of nearby genes. These observations suggest that causal SNPs in linkage disequilibrium (LD) with the tag SNPs directly influence the expression of causal genes that are responsible for changes in blood lipid levels in humans. Identifying these causal SNPs and causal genes would lead to insights into the molecular mechanisms by which the DNA variants drive phenotypic changes in liver and adipose and, ultimately, affect the risk of disease. Our general strategy is to combine several innovations to identify casual SNPs. We will: (1) perform high- throughput screening of candidate SNPs in eQTL loci for alteration of reporter gene expression in the appropriate tissue type, using a novel massively parallel reporter assay (MPRA), to prioritize SNPs for further study;(2) use human genome editing with cutting-edge TAL effector nuclease (TALEN) technology to alter each high-priority SNP in human pluripotent stem cells (hPSCs), so as to generate isogenic cell lines that differ only at the SNP;(3) differentiate the isogenic hPSCs into the appropriate tissue type;and (4) measure nearby gene expression to confirm that the SNP is truly causal for the eQTL. We propose to implement this general strategy for 57 lipid-associated loci with eQTLs in human liver and adipose. Success in completing this project will not only provide fresh new insights into the biology of lipid metabolism, but will also establish a new methodological paradigm by which investigators can determine which DNA sequence variants identified in next-generation human genetic studies underlie the genetic basis of complex phenotypes.
To develop new therapies to prevent cardiovascular disease, the leading cause of death worldwide, we have performed genetic studies to identify novel cholesterol genes. We have identified numerous DNA variants associated with cholesterol;our challenge is to determine which of the DNA variants affect gene function. We will use novel methodologies to (1) rapidly screen through thousands of DNA variants to determine which ones affect gene expression and (2) insert these DNA variants into stem cells to determine which genes are affected and thus are likely to be cholesterol genes.