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Researchers in Pennsylvania are using genetic information to identify patients’ risk for familial hyercholesterolmia, said Michael F. Murray, MD, at the 2016 AHA Conference.
Investigators at one Pennsyvlania-based health system are laying the groundwork to use genetic information to identify a patient’s risk for specific disease and put that information in the hands of clinicians and patients to improve disease prevention.
Launched in 2007 by Geisinger Health System, the MyCode® Community Health Initiative is a precision medicine project that includes a system-wide biobank to store samples (blood, serum and DNA used for research that includes genomic analysis. There are currently over 100,000 participants who have joined the project. The plan is to obtain genomic sequencing on them all through a research collaboration between Geisinger Health System in Danville, Pennsylvania, and the Regeneron Genomics Center (a research subsidiary of Regeneron Pharmacuetials, Inc. in Tarrytown, New York), according to Michael F. Murray, MD, director of clinical genomics for Geisinger’s Genomic Medicine Institute.
During a session entitled “Precision Health in Cardiovascular Medicine” at the American Heart Association (AHA) Scientific Sessions in New Orleans, Murray discussed Geisinger’s GenomeFIRST project that builds on the MyCode® Community Health Initiative by using DNA samples obtained from the biobank to look at the genetic code linked to familial hypercholesterolemia. The goal is to then return those results to patients and their providers once the genetic information linked to familial hypercholesterolemia are clinically confirmed.
“No one has ever done this before at this scale in the U.S. healthcare system,” he said.
Instead of starting with a patient coming in with a heart attack, stroke or high cholesterol to tailor treatment approaches, Murray and his colleagues are identifying patients at risk of high cholesterol and associated coronary artery disease and stroke based on their genetic code with the eventual aim to use this information to prevent cardiovascular events.
To date, Murray and his colleagues have looked at genetic data from over 50,000 Geisenger patients taken from the biobank to see which patients have the single mutation associated with familial hypercholesterolemia. They found that more patients had the genetic mutation associated with familial hypercholesterolemia than would have been predicted based on published literature. Overall, they found that the genetic mutation showed up in 1 in every 222 patients versus 1 in 500 patients in frequently cited published data.
The goal now, Murray says, is to work on infrastructure development and cost to make it feasible to do this sort of genetic analysis on a larger scale. “We are planning on scaling this up to 250,000 patients in the next three years and prove that this works,” he said.
If it does, Murray and his colleagues expect that using genomic analysis to identify diseases such as familial hypercholesterolemia will become more widely used. “This is a pilot for what we think will become standard of practice in this century,” he said, adding that this new way of identifying disease risk through genetic analysis is both powerful and effective.
The next step will be to bring this information into the clinic.
“We’re working on getting this information back to patients and providers so they can more aggressively manage their elevated cholesterol,” Murray said. “Over time, we hope to show improved outcomes for patients who are identified and managed though a combination of genomic sequencing and standard cholesterol testing.”