Diseases that are rooted in our DNA are often hidden and symptoms only appear once the disease has developed. For decades, researchers have been searching for ways to understand how mutations in the genome lead to disease. This exploration and extensive technological advances over the years ultimately led to genome-wide association studies (GWAS).

In these studies, researchers analyze the genomes of millions of people, both healthy and non-healthy people, to objectively identify common DNA variants that may increase the risk of certain diseases. Search objectively and hypothetically. This discovery lays the foundation for more accurately assessing a person’s risk of disease, detecting disease earlier, clarifying the molecular understanding of how certain diseases develop, and pointing to new therapeutic targets. may be built.

The first GWAS was science About 20 years ago, scientists discovered that a variant in the complement factor H gene increases the risk of age-related macular degeneration by a whopping seven times in individuals who inherited a copy of the variant from their parents. This study was based on only 96 cases and 50 controls. Since then, GWAS has grown exponentially, becoming more accurate and generating a wealth of information about human health and disease.

However, these genetic studies are not perfect. They identify mutations that influence risk, but stop short of determining the mechanisms by which specific DNA mutations cause disease.

A new study co-led by researchers at Stanford Medicine was published on February 7th. Natureaims to address this challenge by proposing a solution that links disease-causing DNA variants with the harmful processes they trigger.

We spoke to researcher Jesse Engleitz, Ph.D., assistant professor of genetics and lead author of the study, about the solution and what it reveals about the genetics underlying coronary artery disease. I asked. This Q&A has been condensed and edited for clarity.

GWAS approaches have proven to be valuable tools to help identify the genetic basis of disease. Are there any drawbacks?

The mutational and functional challenges of mapping genetic variants to the molecular causes of disease are major limitations that prevent us from fully unlocking the potential of the vast amount of beautiful genome-wide association research data obtained to date. past few decades.

Most mutations identified by GWAS are not located in easily interpreted regions of the genome. If we can understand each of these mutations, which genes and cells are affected and by what pathways the cells change, we can begin to design drugs that target specific genes and mechanisms within the cell. .

Your research analyzed genetic mutations that may increase the risk of coronary artery disease, which is caused by atherosclerosis, or the narrowing of arteries due to plaque buildup. Why did you study this disease?

Coronary artery disease is the number one killer in the United States, and although diet and other factors, especially cholesterol levels, also play a role, coronary artery disease is known to have a very strong genetic component. There are currently more than 300 known mutations associated with coronary artery disease.

Before doing this study, we knew that some of these DNA variants affect blood vessels where atherosclerosis develops, where cells are responding to things like high levels of cholesterol, thereby causing They thought it could cause disease-causing plaque buildup. Previously, research to identify the pathways affected by a single mutation took him six to seven years. We started this project to accelerate that process and study all 300 coronary artery disease variants at once.

What did the study include?

We focused on the endothelial cells that make up the lining of blood vessels, which come into contact with blood, sense LDL cholesterol, and interact with other cells. They are thought to be very important in the development of coronary artery disease, but it remains to be seen which of the 300 variants identified in GWAS affect endothelial cells and how they function. We did not know how this affects the processes and pathways that contribute to

Endothelial cells can perform many different functions encoded by genes that act together in specific pathways. We first wanted to define all these pathways that can be activated in endothelial cells and then relate variants associated with coronary artery disease to the genes and endothelial cell pathways in which they are involved.

We applied the gene editing technology CRISPR to knock down all genes near nearly all of these 300 coronary artery disease-associated mutations and measured the effects on endothelial cells in dishes. We were looking for cases where knocking down one gene associated with a disease mutation affects the expression of other genes associated with other disease mutations. This is a sign that we have discovered a pathway, or series of events, involved in the development of the disease that is influenced by natural human genetic variation.

This has proven to be a powerful method for building maps of genetic variation and how it affects overall function, and for identifying which pathways are important for coronary risk. It was helpful. In this study, we showed how 43 of his 300 variants identified in GWAS affect endothelial function.

Can this approach be applied to data from other GWAS studies?

This is one of the things we’re most looking forward to. The process we outlined in our paper is generalizable and can be applied to many other diseases to identify genetic pathways corresponding to those diseases. This can be applied to common diseases that have some genetic component.

We look forward to applying this to many other cells to try to understand other diseases, such as congenital heart disease, type 2 diabetes, and fatty liver disease associated with metabolic dysfunction. We hope that other researchers can use this tool to also interpret other variants identified in GWAS.

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