Research Spotlight: Finding the Source of Heart Disease in Our Genes
Cardiovascular disease has many causes. Clint Miller, PhD, professor of genome sciences and cardiovascular researcher, studies how naturally occurring genetic variation contributes to cardiovascular disease. Genome-wide association studies have identified hundreds of loci for these diseases. But most are in noncoding regions of the genome, and their target genes and cell types remain largely unknown.
At the Miller Lab, Miller and his team predict how genes are turned on and off. They map the networks that control genes. They also model how important genes can shift a cell from a healthy to diseased state as the disease gets worse.
The team then tests these predictions in the lab using human blood vessel cells. Their goals are to:
- Get better at predicting who is at risk
- Find out what actually causes disease
- Discover new treatment targets for atherosclerosis
Here, Miller shares more about his research in this video and Q&A.
Unlocking the Genetics of Heart Disease
I love finding patterns in discrete data sets that are collected over many time series and conditions and allows us to really hone in on some of those causal mechanisms for diseases, such as cardiovascular disease. I also enjoy the highly collaborative nature of our work. It allows us to interact with experts across the globe in fields such as computational biology and cardiovascular medicine.
Hi, my name is Clint Miller. I'm an associate professor of genome sciences. And our group studies the genetics and genomics of cardiovascular diseases using both computational and experimental approaches. More recently, we’re creating this large integrated atlas of human atherosclerosis, using single cell and spatial modalities. And we're really excited to identify some of those early markers of the disease to prevent some of the initiating events.
By studying the disease in its native context in primary human tissues, we can better capture some of these events that may drive transition states, and allow us to better target those with different modalities. And we're particularly excited about leveraging the resources of the Manning Institute to apply both cell and gene therapies to target some of these processes that go awry during atherosclerosis and in heart disease.
What are you working on right now?
Our group builds multimodal genomic resources to study the mechanisms of cardiovascular diseases, including coronary artery disease and cardiomyopathies. Genetic studies have identified hundreds of regions in the genome associated with heart disease risk, yet for most of these we still don’t know which genes or cell types are affected.
To address this, we generate high-resolution maps of human coronary arteries and heart tissue at the level of single cells and their spatial location within the tissue. A major focus has been mapping chromatin accessibility, which tells us where the regulatory switches, or enhancers, are active in each cell type. These maps have allowed us to link disease-associated variants to specific genes in smooth muscle cells, endothelial cells, fibroblasts and macrophages in the vessel wall.
We are also applying AI and machine-learning models trained on these data to predict how individual genetic variants alter gene regulation, and how changes in key genes shift cell states along the disease continuum from healthy artery to advanced plaque.
What are the most intriguing potential clinical applications of your work?
Atherosclerosis is the underlying cause of most heart attacks and strokes. Despite advances in lowering circulating cholesterol levels, many patients still have residual risk for these events. By taking an inside-out approach, we are identifying sets of genes and proteins in the vessel wall underlying early disease transitions, such as vascular calcification, which may predict severe clinical outcomes.
Our enhancer maps also point to new ways of intervening. Many disease genes play important roles systemically, so targeting them broadly can cause side effects. Enhancers, by contrast, are often active only in certain cell types or disease contexts. This raises the possibility of turning a disease gene up or down only in the cells and conditions where it is causing harm.
Using machine-learning models, we can now simulate these perturbations computationally and predict changes that shift harmful cell states back toward a healthier state, before testing them in human vascular cells. Ultimately, these studies may transform how we treat patients with atherosclerotic disease by targeting the causal disease processes in the vessel wall.
What made you choose UVA Health as the place to do your research?
UVA has a long history of strength in cardiovascular research and genomics, and a highly collaborative environment that makes it possible to work across these fields. Our studies rely heavily on human tissue, so close partnerships with UVA cardiologists, cardiac and vascular surgeons, and pathologists have been essential. The Department of Genome Sciences brings together geneticists, computational biologists, and vascular biologists who share a common interest in genome complexity and translating genomic discoveries. UVA is committed to moving these discoveries toward the clinic, and the Manning Institute of Biotechnology will further accelerate that path.
What do you wish more people knew about your area of research?
Most genetic variants linked to heart disease do not change the protein-coding part of genes. Instead, they fall in regulatory regions that control when, where and how much a gene is turned on. The effect of a variant may only be seen in one cell type, or only after that cell has been exposed to a disease stimulus such as inflammation or high cholesterol. This is why we study human tissue at single-cell resolution and across different stages of disease.
I also think it’s important for people to know that heart disease is not only a cholesterol problem. The cells in the artery wall actively respond to injury and stress, and these responses influence whether plaque remains stable or leads to a heart attack. Understanding this biology opens opportunities for treatments that complement existing therapies.
Much of this work is made possible by the generosity of patients and families who donate tissue for research.
How did you become interested in your area of research?
During my early training, I became interested in ‘experiments in nature’ in which natural genetic variation across human populations serves as a powerful discovery tool for unraveling disease mechanisms. I also appreciated the need to close the gap between the expanding number of genetic risk loci identified for coronary artery disease and how little we understood about how they function. I recognized an opportunity to apply emerging genomic technologies directly to biobanked human tissue to help close that gap and translate this knowledge back to patients.
Since starting my lab at UVA, we have established single-cell and spatial maps of human coronary arteries and applied them to link genetic risk to specific cells and gene regulatory programs. More recently, advances in AI and machine learning have made it possible to model these regulatory changes and make predictions that we can test experimentally. Our goal remains to translate these findings into better ways to predict and treat cardiovascular disease.
