Coronary artery is the leading cause of death in the US. While lipid-lowering and anti-hypertensive drugs have
helped decrease CAD-related mortality by approximately 50% since the 1980s, these therapies only modify
CAD risk factors. To date, no approved drug acts at the vascular wall directly against atherosclerosis, the
underlying cause of CAD. One opportunity to develop novel therapies is through genetics: CAD is partially
heritable, and recent genome-wide association studies identified over 200 loci associated with elevated risk for
CAD. While 40% of these CAD loci having established associations with known risk factors, the molecular and
cellular mechanisms of the remaining 60% of the CAD loci are unknown. The majority of these unknown loci
are predicted to function by regulating gene expression in the vascular wall where the disease develops.
Vascular smooth muscle cells (SMCs), which make up the medial layer of arteries, play a critical role in the
progression of atherosclerosis, the precursor to coronary artery disease. During initiation and progression of
atherosclerosis, SMCs transdifferentiate from a quiescent (healthy) phenotype to a proliferative (pathological)
phenotype representative of myogenic, osteochondrogenic, and macrophage-like phenotypes that contribute to
plaque build-up. Identifying the molecular mechanisms driving SMC phenotypic plasticity will open up new
avenues of treatment for CAD. Preservation analysis of co-expression networks from RNAseq data generated
from the ascending aortas of 151 multi-ethnic smooth muscle cell donors cultured in quiescent and proliferative
conditions, respectively, revealed phenotype-specific network architecture enriched for nitrogen metabolic
processes. Previous studies have shown that metabolic pathways are not only involved in phenotypic changes
of other cell types in the vascular wall, but also have the capability to drive them. Therefore, the goal of this
proposal is to characterize the role nitrogen metabolism plays in SMC phenotypic plasticity and identify the key
regulatory genes driving dysregulation. The project will address this problem through 2 aims. In aim 1, I will
characterize the role nitrogen metabolism plays in SMCs during the progression of atherosclerosis using a
combined approach of metabolomics, cell type marker identification, and cellular phenotyping assays in
response to activation or silencing of the nitrogen metabolism pathway. In aim 2, I will create Bayesian
networks (BNs) of genes involved in nitrogen metabolic processes using gene expression data and
transcription factor-gene expression relationships generated from time-series experiments linking differentially
expressed ATACseq peaks and differentially expressed RNAseq peaks in response to pro-atherogenic
stimulus. I will then identify the key driver genes (KDs) of nitrogen metabolic pathways whose expression
regulates the changes across the gene expression networks. Gain-of-function and loss-of-function experiments
for KDs in SMCs using lentiviral particles will be completed with cellular phenotyping assays to quantify the
impact on SMC proliferation, migration, and de-differentiation.