High-throughput investigation of human genetic variants affecting cholesterol uptake and efflux

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Project Summary Genetic differences in cholesterol metabolism are major contributors to the risk of coronary artery disease (CAD), which is the leading cause of death in the USA. Unraveling the genetics of cholesterol has continued to yield promising therapeutics for heart disease. Nonetheless, the genetics of cholesterol levels are far from completely understood-- there are dozens to hundreds of genomic regions whose variation meaningfully alters cholesterol levels in the population, yet we can only explain the genetic basis of a small fraction of these loci. We have established a powerful approach combining CRISPR screening, gene network analysis, and human biobank coding variant burden analysis to dissect the genetics of cholesterol uptake and efflux. Through this pipeline, we have identified dozens of new genes that contribute to LDL cholesterol (LDL-C) uptake in cellular models and for which coding variants alter serum LDL-C levels in the population. In this proposal, we will refine and extend this pipeline to develop a coherent understanding of the variants, genes, and pathways underlying cholesterol uptake and efflux. In Aim 1, we pioneer a novel pipeline combining CRISPR screening, gene network analysis, and human biobank burden analysis to characterize ~500 genes we have found to alter cellular LDL-C uptake. We will develop a sensitive approach to extract the effects of rare coding variants on serum LDL-C levels using large exome sequencing biobank cohorts. We will group LDL-C uptake-altering genes into pathways through a combination of CRISPR screening and gene network analysis. We will perform mechanistic follow-up of novel candidate LDL- C-altering pathways in cellular and mouse in vivo models. In Aim 2, we will pioneer a new, more sensitive approach to CRISPR base editing screens to identify GWAS-associated variants that alter LDL-C uptake in liver cells. We will then use a suite of computational and experimental tools we have developed dissect the cis- regulatory mechanisms by which these variants act and connect them to trans-regulatory inputs controlling them. We expect to connect transcriptional drivers of hepatocyte LDL-C uptake with their cis-regulatory GWAS- associated variant targets and downstream LDL-C uptake-altering genes, shedding light on how human genetic variation influences serum LDL-C level. In Aim 3, we will use the pipeline of CRISPR-Cas9 screening and human biobank analysis to identify genes and pathways associated with monocyte/macrophage reverse cholesterol transport, a process thought to be important in CAD risk but which is incompletely understood at the genetic level. We will dissect disease-relevant genetic mechanisms involved in reverse cholesterol transport, helping to define the role of macrophage efflux in CAD risk. In sum, through high-throughput CRISPR screening followed by mechanistic follow-up, we will provide the most extensive experimental and computational analyses to date of the non-coding loci, genes, and pathways that underlie variation in human cellular cholesterol uptake and efflux.