New computational workflow for analyzing gene expression in single cells reveals potential drug targets to treat atherosclerosis

Researchers at the University of Chicago Medicine have found new potential drug targets to treat atherosclerosis and coronary artery disease by developing and implementing a new single-cell sequencing workflow that could improve upon those currently in use. The approach will make it easier for other scientists to analyze single-cell genetic data to better understand coronary artery disease as well as other disease states and biological systems.

The team used their cardioinformatics pipeline to reveal new types of vascular cells derived from the smooth muscle cells found in the walls of arteries, along with insight on the communication pathways among those cells.

“This is one of the first studies to show how big data, single-cell sequencing and genomics can be leveraged to find new drug targets in heart disease, which is the number one global killer,” said Bohdan Khomtchouk, PhD, co-senior author on the study and an instructor in the Section of Biomedical Data Science at and UChicago’s Master of Science in Biomedical Informatics (MScBMI) program.