Researchers join forces to ‘map’ identified differences in more than 25 key heart disease genes

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

However, the functional impact of most of these cardiovascular genetic variants -; whether it disrupts normal function or is harmless -; unknown. This is about to change.

Researchers from Vanderbilt University Medical Center, Stanford Medicine, University of Toronto and Brigham and Women’s Hospital in Boston, have teamed up to “identify” specific differences in more than 25 major heart disease genes that negatively affect heart function.

Funded by a four-year, $8.2 million grant from the National Institutes of Health, Lung, and Blood of the National Institutes of Health (NIH), the newly formed CardioVar Consortium will create a comprehensive atlas of “variable impact maps” to distinguish pathogen variants from harmless ones.

The goal is to shed light on the molecular mechanisms of cardiovascular disease, the leading causes of death and disability worldwide, and to improve diagnosis and early treatment in real time.

With the increasing adoption of genetic testing in heart patients, a common finding is “a variant of uncertain significance. Our high-throughput studies will provide data on function for thousands of variants – which will help guide treatment for individual patients and provide insight into basic biology.”

Dan Rudin, MD, Principal Investigator in Grant, Senior Vice President of Personalized Medicine at VUMC

Rhoden, who holds the Sam L. Clark Chair, MD, PhD, at Vanderbilt University School of Medicine, is internationally known for his studies of arrhythmias and the role genetic differences can play in adverse drug interactions.

Rhoden’s co-principal investigators are Ewan Ashley, MBBS, MD, professor of medicine, genetics, and biomedical data science at Stanford School of Medicine and founding director of the Stanford Genetic Cardiovascular Center, and Frederick Roth, PhD, professor of genetics Molecular and Computer Science at the University of Toronto’s Donnelly Center and Departments of Molecular Genetics and Computer Science.

“At the current rate of clinical sequencing, it would take more than a hundred years to find most genetic variants relevant to heart disease even once in the population,” said Ashley, associate dean and Roger and Joel Burnell, professor of genomics and exact health at Stanford School of Medicine. “The diverse maps that we’re building will allow us to significantly speed up this schedule, providing vital information to the families we see in the clinic today.”

Approximately Added Roth, a senior researcher at the Lunenfeld-Tanenbaum Research Institute at Sinai Health, and co-founder of the Atlas Variable Effects Alliance. Keep testing one variable at a time? We are grateful that the National Institutes of Health is supporting our efforts to organize and begin to systematically test all variants.”

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

Another principal investigator is Callum McCray, MD, PhD, vice president of scientific innovation in 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,” McCray said. “This project will transform clinicians’ ability to diagnose and manage every patient with genetic heart disease.”

As a first step, researchers will develop, improve and validate a set of high-throughput cellular assays that can directly measure altered function and distinguish pathogen from benign variants.

They will then use sophisticated techniques to alter or introduce modified gene sequences into populations of cells and use the assays they have developed to generate and validate maps of the cells’ altered effects.

Finally, through a combination of hypothesis-based analysis and machine learning models, they will reveal the relationships between variable effects, protein structure and function, and human phenotypes—; Specific effects of pathogenic variants on cardiac function.

The goal is to develop a centered variable decision support system that will be widely shared 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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