Carnegie Mellon University
March 01, 2024

Tepper School Part of Team that Developed New Non-Invasive Blood Test That Can Accurately Detect Heart Disease

Sheila Davis
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Coronary artery disease (CAD)—diseases involving dysfunctions of the heart and blood vessels—is the most common type of heart disease and the leading cause of death in both men and women worldwide. Early detection of CAD is critical for decreasing death, prolonging survival, and improving patients’ quality of life. In a new study, researchers describe a new diagnostic blood test that can detect CAD with high levels of accuracy offering a non-invasive screening option for high-risk patients.

The study was conducted by researchers from several institutions, including Carnegie Mellon University’s Tepper School of Business.

“An ideal test for coronary artery disease should be non-invasive, easy to perform, reproducible, and sensitive,” said Andrew Li, Assistant Professor of Operations Research at the Tepper School, who coauthored the study. “Our findings demonstrate that a blood test can be an innovative and effective tool for diagnosing CAD.”

The study noted that in 2017, approximately nine million deaths worldwide were attributed to CAD, and scientists project that the number of people with CAD will rise more than 40 percent in the next two decades, causing approximately 11 million deaths. Managing the disease is expensive: In the United States alone, medical management of CAD is estimated to cost $100 billion annually. Currently, the most precise and widely accepted method to diagnose CAD is coronary angiography, an invasive procedure that is expensive and risky; a CT scan for arteries in the heart is a non-invasive alternative for some patients, but it might not catch every case of CAD or it may incorrectly identify CAD in patients to who do not have the disease.

Li and his coauthors used a nanoparticle-based diagnostic technology, in which nanoparticles are introduced into the bloodstream and interact with the body's proteins. Because the types of proteins change when someone has CAD, the nanoparticles can "pick up" these changes by collecting different proteins on their surfaces, creating what's called a "protein corona." By analyzing the unique pattern of proteins collected, scientists can tell whether CAD is present.

Their results suggest that such an approach can detect CAD with an accuracy of 93 percent. Due to the versatility of the test, similar methods could be used to detect other human diseases, they said.

Profiling diseases by using multiple nanoparticles has recently gained recognition as a way to gain deeper insight into diseased plasma and achieve more precise protein-related profiling. By studying the protein corona on different types of nanoparticles, researchers have made a sensor array nanosystem, which is like a grid to detect specific changes at the molecular level, which can help identify diseases.

“We believe this is the first time the application of the protein corona sensor array has been used to detect CAD,” says Gha Young Lee, an M.D./Ph.D student at Harvard Medical School and a second-year Ph.D. candidate in chemistry at MIT, who coauthored the study. “The ease of a blood-based test with no side effects has immense potential to reduce coronary artery disease complications through early detection and more frequent testing.”

The study was funded by the Italian Ministry of Health and the University of Milano Bicocca.

Summarized from an article in Small Journal, "Protein Corona Sensor Array Nanosystem for Detection of Coronary Artery Disease" by Lee, GY (Harvard Medical School), Li, AA (Carnegie Mellon University), Moon, I (Massachusetts Institute of Technology), Katritsis, D (Hygeia Hospital and Johns Hopkins Medicine), Pantos, Y (Hygeia Hospital), Stingo, F (University of Florence), Fabbrico, D (University of Florence), Molinaro, R (Harvard Medical School), Taraballi, F (Houston Methodist Hospital), Tao, W (Harvard Medical School), and Corbo, C (University of Milano-Bicocca and IRCCS Istituto Ortopedico Galeazzi ). Copyright 2024. All rights reserved.