The diseases rooted in our DNA are too often hidden, showing themselves only in the form of symptoms once the disease has developed. For decades, researchers have sought methods to reveal how variations in our genome may lead to illness. This search, and massive technological advances over the years, eventually led to the genome-wide association study (GWAS).
In these studies, researchers analyze the genomes of millions of people, healthy and otherwise, to conduct an objective, hypothesis-free search for common DNA variants that may raise a person's risk for a given disease. The findings can lay the groundwork to more precisely assess a person's risk for disease, detect diseases earlier, reveal a molecular understanding of how certain illnesses arise, and point to new therapeutic targets.
The first GWAS, published in Science nearly 20 years ago, uncovered a variant in the complement factor H gene that, in individuals who inherited a copy of the variant from both parents, raised risk for age-related macular degeneration by a whopping seven times. That study was based on just 96 cases and 50 controls. GWAS has since grown exponentially, becoming more precise and producing an abundance of information about human health and disease.
But these genetic studies aren't perfect. They identify variants that affect risk - but stop short of revealing the mechanism by which a given DNA variant causes a disease.
A new study co-led by researchers at Stanford Medicine and others, published Feb. 7 in Nature, aims to address this challenge by proposing a solution that links disease-causing DNA variants to the deleterious processes they set in motion.
We asked researcher Jesse Engreitz, PhD, assistant professor of genetics and the study's senior author, to discuss the solution and what it revealed about the genetics underlying coronary artery disease. This Q&A has been condensed and edited for clarity.
The GWAS approach has proven to be a valuable tool in helping to identify genetic underpinnings of disease. Are there drawbacks?
The variant-to-function challenge, which maps a genetic variant to a molecular cause of disease, is the big limitation that has blocked us from fully unlocking the promise of the immense amount of beautiful genome-wide association study data that has come out of the past couple of decades.
Most variants that GWAS identifies are not in easily interpretable regions of the genome. If we could figure out for every one of these variants -- what genes and cells are affected, and in what pathway the cells are altered, we could start to design drugs that target those particular genes or mechanisms in the cells.
Your study analyzed genetic variants that might raise risk for coronary artery disease, which is caused by atherosclerosis, or the narrowing of arteries from plaque buildup. Why did you study this disease?
Coronary artery disease is the No. 1 killer in the United States, and we know it has a very large genetic component, though diet and other factors, particularly cholesterol levels, also play roles. There are now over 300 known variants associated with coronary artery disease.
Before this study, we thought that some of these DNA variants might affect the blood vessels where atherosclerosis develops, where cells are responding, for example, to the high levels of cholesterol, thereby triggering the plaque buildup that leads to disease. In the past, research to identify the pathway affected by even a single variant took six or seven years. We started this project to accelerate that process and study all 300 coronary artery disease variants at once.
What did the study entail?
We looked at endothelial cells, which make up the lining of the blood vessels that contact the blood, sense LDL cholesterol and interact with other cells. They are thought to be very important in coronary artery disease development, but we didn't know which of the 300 GWAS-identified variants might affect endothelial cells or how the variants might impact processes or pathways that contribute to endothelial cell function.
Endothelial cells can carry out many different functions, which are encoded by genes acting together in particular pathways. We first wanted to define all these pathways that can be activated in endothelial cells and then link the variants related to coronary artery disease to the genes and endothelial-cell pathways in which they are involved.
We applied CRISPR, a gene-editing technology, to knock down every possible gene near every one of these 300 coronary artery disease-related variants and measure the impact on endothelial cells in a dish. We were looking for cases where you knock down one gene linked to a disease variant and it affects the expression of other genes linked to other disease variants. That's a sign that we've found a pathway, or chain of events involved in the development of the disease, that is affected by natural human genetic variation.
This turned out to be a powerful way to build a map of genetic variants and how they affect function overall, helping us home in on which pathways are important for coronary artery risk. This study showed us how 43 of the 300 GWAS-identified variants affect endothelial function.
Can you apply this approach to data from other GWAS studies?
This is one of the things that we're most excited about. The process that we've outlined in the paper is generalizable and can be applied to many other diseases to home in on the genetic pathways that correspond to that disease. It's applicable to any common disease that has some genetic component.
We are excited to apply it in many other cells to try to understand other diseases, such as congenital heart disease, type-2 diabetes, metabolic dysfunction-associated fatty liver disease, and more. We hope that other researchers can use this tool to interpret other GWAS-identified variants, too.
Image: greenbutterfly
