AI Utilised to Recognise Key Genes in Cardiovascular Disease

Investigators at the Icahn School of Medicine at Mount Sinai have discovered unusual coding variations in 17 genes that provide insight into the molecular causes of coronary artery disease (CAD), a major cause of death. They have done this by using a sophisticated artificial intelligence technology.

The findings provide new opportunities for specific therapies and individualised strategies to cardiovascular treatment by revealing genetic variables influencing heart disease.

The difficulties encountered over the past ten years in locating uncommon coding variations linked to CAD using conventional techniques that depend on patients and controls who have been identified as the impetus for the investigation. The inability of diagnostic codes to adequately represent the intricacy of CAD led the investigators to look into alternative lines of inquiry.

lead author Ben Omega Petrazzini, BS, Associate Bioinformatician in Dr. Do’s lab at Icahn Mount Sinai stated: “Our previous Lancet paper showed that a machine learning model trained with electronic health records can generate an in silico score for coronary artery disease, capturing disease across its spectrum.”

He continued: “Based on these findings, we hypothesized that the in-silico score for CAD could reveal novel rare coding variants related to CAD by offering a more holistic view of the disease.”