Consortium to Map Heart Disease-Causing Genetic Variations

Donnelly Centre investigator Fritz Roth is co-leading a consortium seeking to map genetic variants behind heart disease to improve diagnosis, prognosis and treatment.

One in 100 people have genetic variations that can cause potentially life-threatening heart conditions, including high cholesterol (lipid disorders), heart muscle disease (cardiomyopathies), and abnormal heart rhythms (arrhythmias).

Yet the functional impact of most of these cardiovascular genetic variants — whether they disrupt normal function or are harmless — is unknown. That is about to change.

Roth has joined forces with leading experts from Vanderbilt University Medical Center, Stanford Medicine and Women’s Hospital in Boston to “map” the specific variations in more than 25 key cardiac disease genes that negatively affect heart function.

Funded by a four-year, US $8.2-million grant, or 10.8 million in Canadian dollars, from the National Health Lung and Blood Institute of the National Institutes of Health (NIH), their newly formed CardioVar Consortium will generate a comprehensive atlas of “variant effect maps” to distinguish disease-causing variants from those that are harmless.

The goal is to illuminate the molecular mechanisms of cardiovascular diseases, the leading causes of death and disability worldwide, and to improve real-time diagnosis and early treatment.

Genetic testing often returns ambiguous results where an identified variant has no known function and therefore has no prognostic value. Large scale studies of encoded protein variants in the lab have the potential to identify genetic changes that damage protein function and contribute to disease.

Known worldwide for his work in experimental and computational genomics, Roth and his colleagues have published variant effect maps for nine human proteins already, including one for the calcium-sensing protein calmodulin, enabling rapid diagnosis of life-threatening arrhythmias in young children and genetic testing of their family members.

“As genetic testing in patients with heart disease becomes increasingly adopted, a common result is a ‘variant of uncertain significance,’” said one of the grant’s principal investigator, Dan Roden, MD, Senior Vice President for Personalized Medicine at VUMC who is internationally known for his studies of arrhythmias and of the role that genetic variations can play in adverse drug reactions.

 “Our high-throughput studies will provide data on function for thousands of variants–that will both help guide treatment for individual patients and provide insights into underlying biology.”.

“At the current rate of clinical sequencing, it would take over a hundred years to find most genetic variants relevant for heart disease even once in the population,” said Ashley, Associate Dean and Roger and Joelle Burnell Professor of Genomics and Precision Health at the Stanford School of Medicine who is also a co-principal investigator. “The variant maps we are building will allow us to dramatically accelerate that timeline, providing vital information for families we are seeing in clinic today.”

Another key co-investigator is Calum MacRae, MD, PhD, Vice Chair for Scientific Innovation at the Department of Medicine at Brigham and Women’s Hospital, Co-Director of the Genomic Medicine Clinic and Professor of Medicine at Harvard Medical School.

“Understanding the functional consequences of individual variants is the central requirement for interpreting genetic test results,” MacRae said. “This project will transform clinicians’ ability to diagnose and manage every patient with inherited heart diseases.”

As a first step, the researchers will develop, optimize, and validate a range of high-throughput cellular assays that can directly measure variant function and discriminate pathogenic from benign variants.

They will then use cutting-edge techniques to mutate or insert altered gene sequencies into pools of cells and use the assays they developed to generate and validate variant effect maps of the cells.

Finally, through a combination of hypothesis-driven analysis and machine learning models, they will reveal relationships among variant effects, protein structure and function, and human phenotypes — the specific effects of disease-causing variants on heart function.

The goal is to develop a variant-centric decision support system that will be shared widely to help clinicians evaluate functional evidence of disease in patients undergoing genetic testing for heart disease.

The research is funded by NHLBI grant number HL164675.

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