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Computational study finds genetic links, therapy targets for varicose veins

Computational systems biologists at ORNL worked with the U.S. Department of Veterans Affairs and other institutions to identify 139 locations across the human genome tied to risk factors for varicose veins, marking a first step in the development of new treatments. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

As part of a multi-institutional research project, scientists at the Department of Energy’s Oak Ridge National Laboratory leveraged their computational systems biology expertise and the largest, most diverse set of health data to date to explore the genetic basis of varicose veins. The team identified 139 locations across the human genome tied to risk factors for the disorder that can guide the development of new treatments.

In the project, led by the Department of Veterans Affairs, ORNL scientists analyzed data from the VA’s Million Veteran Program, or MVP, along with information from four other global biobanks of human health data. They conducted a genome-wide association study, or GWAS, which uses the genome of a large group to search for small genetic variations linked to particular traits of the group — in this case the disorder that causes twisted, enlarged veins typically in legs and feet.

As detailed in Nature Cardiovascular Research, the project examined data from nearly 50,000 individuals with varicose veins and another 1.3 million people without the disease. To conduct the analysis, scientists used novel machine learning and network biology tools, as well as the supercomputing resources at the Oak Ridge Leadership Computing Facility, a DOE Office of Science user facility at ORNL.

Researchers focused on finding the genetic origins of traits that put people at risk for varicose veins, such as increased blood pressure in the veins that can weaken vein walls and damage valves, inflammation and immune cell activation and adhesion, remodeling of the vascular wall, formation of new and branching veins, and inability to heal from wounds. The project also found some genetic overlap between varicose veins and other vascular diseases.

The biological interpretation of the 139 risk loci — or locations on the chromosome where the genes for specific disease risk factors reside — was enhanced by the systems-level approach that ORNL scientists brought to the project. The approach recognizes that there is not one single genetic link to a disease, but rather many genes that can trigger disease progression.

“What we’re discovering is the genes are involved in a network fashion so that we better understand the biological function of what’s going on in the different stages of disease,” said ORNL staff scientist Michael Garvin.

Dan Jacobson, ORNL’s principal investigator for the project, said there’s been “little bits of understanding about this disease scattered around dozens and dozens of papers. People have found one gene at a time or one partial mechanism at a time. But this project allowed us to bring all of that together and get an understanding of the entire mechanism, which makes you think differently about therapeutic interventions” and supports a personalized medicine approach.

“These genes do not operate in isolation from each other,” ORNL staff scientist David Kainer said. “This approach to the science is something we have been building our computational capabilities toward for years. This project is a great example of putting those tools into action.”

The study is the largest multi-ancestry GWAS of varicose veins to date, mostly owing to data from the MVP, which, with the other biobanks provided a diverse genetic data source spanning four major ancestral populations — African, East Asian, European and Hispanic.  

“This is one of the largest genetic studies ever conducted into this disease, providing high statistical power to give us confidence in the robustness of the final results,” said ORNL postdoctoral researcher Kyle Sullivan. Much of that is predicated, Sullivan said, on MVP representing the most diverse set of genomic data in the world.

The project demonstrates the power of uniting VA resources with scientists from the DOE national labs and other institutions, Jacobson said.

ORNL has been working with the VA as part of the MVP Computational Health Analytics for Medical Precision to Improve Outcomes Now, or MVP-CHAMPION, big-data initiative to create a large, precision medicine platform to host the VA’s vast dataset, which represents the health records of more than 23 million veterans. In one such project, the VA database and ORNL’s Summit supercomputer improved a model that identifies veterans at risk for suicide.

The size and robustness of the vein study “gets to the holistic, mechanistic understanding that we need to foster experimental research and improve clinical care,” Jacobson said. “There are drug candidates already known to target some of the genes identified in the study, and there will likely be no shortage of follow-up work by labs all over the world.”

The research was supported by MVP-CHAMPION, as well as with grants from the National Institutes of Health and other research institutions. Other collaborators on the project include the University of Pennsylvania Perelman School of Medicine, Argonne National Laboratory, the Bredesen Center for Interdisciplinary Research and Graduate Education under the UT-Oak Ridge Innovation Institute; University of North Carolina Chapel Hill, Stanford University, Northwestern University’s Feinberg School of Medicine, University of Washington Medical Center, The Children’s Hospital of Philadelphia Center for Applied Genomics and Vanderbilt University School of Medicine.

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