PROJECT SUMMARY
Cardiovascular disease (CVD) is the most common cause of mortality in the world. Genome-wide association
studies (GWAS) have successfully identified numerous genetic variants associated with CVD. However, most
variants do not necessarily cause the observed phenotypes, but rather are in linkage disequilibrium with the truly
causal variants that influence disease pathophysiology via largely unknown molecular and cellular mechanisms.
Thus, three central challenges for CVD GWAS are: 1) Identifying causal variants, 2) Understanding which cell
types are most relevant for specific variants, and 3) Identifying the cis- and trans-regulatory target genes whose
expression is modulated by CVD variants. Currently, there is no consensus on how best to identify relevant cell
types and target genes. Furthermore, efforts to connect specific noncoding variants to target genes, such as
CRISPR-based insertion of specific variants coupled with phenotypic assays have been hampered by low
throughput. Here, we seek to develop scalable methods to address all three central challenges for CVD disease
GWAS, while leveraging the considerable benefits of population-scale, multi-ancestry GWAS — namely,
improved discovery of novel GWAS loci and increased resolution for causal variants at already known loci. Of
the many cell types and organ systems underlying CVD pathophysiology, we will focus on blood-related
mechanisms, which are currently understudied despite the importance of e.g., immune response and coagulation
in CVD, demonstrated by prior work and our preliminary data. In Aim 1, we will perform colocalization of CVD
and blood cell trait GWASes (as blood cells traits are naturally cell-type-specific) and produce a reference atlas
of 3D enhancer maps for 13 blood cell types and 2 endothelial cell types in donors of diverse ancestries. In Aim
2, we will combine CRISPR screens and single-cell multiomics (STING-seq) in blood and endothelial cells to
identify causal variants and target genes for CVD. We will further extend it by developing BeeSTING-seq, which
combines cytosine and adenine base editors with a more flexible CRISPR enzyme to insert precise SNPs. For
both STING methods, we will use a thoroughly-validated computational approach to identify cis and trans target
genes and regulatory networks. Further, we will deeply validate top variants using key functional assays
(electrical impedance, migration and stress response). This proposal takes an interdisciplinary approach with a
team of experts in noncoding biology and high-throughput single-cell CRISPR screens (Sanjana), in genetics
and systems biology (Lappalainen) and in CVD GWAS, cardiology and endothelial cell function (Gupta). Our
integrated experimental and computational approach will not only reveal how genomic variation shapes CVD
risk, but also develop a generalizable toolkit that leverages cutting-edge 3D genome mapping, gene editing and
single-cell profiling to map gene regulatory elements, specific variants and target genes to inform future CVD
therapeutics.