UCI News

UCI researchers help invent blood-based assay to detect chronic fatigue syndrome

May 15, 2019
UCI researchers help invent blood-based assay to detect chronic fatigue syndrome
Rahim Esfandyarpour, UCI assistant professor of electrical engineering & computer science, holds up a device that he and colleagues developed for detecting a biomarker for chronic fatigue syndrome, which has been notoriously difficult to diagnose.

About 2 million people in the U.S. suffer from a mysterious illness known as myalgic encephalomyelitis, or chronic fatigue syndrome. One of the challenges healthcare professionals have faced in diagnosing it has been the lack of a clear biomarker, something in a patient’s bloodstream to signal the cause of the problem. Researchers at UCI and Stanford University have developed a blood-based assay tool that has shown early signs of being an effective test for the condition in humans. The team’s findings were published recently in Proceedings of the National Academy of Sciences. The new technology developed by lead author Rahim Esfandyarpour, UCI assistant professor of electrical engineering & computer science, and his collaborators relies on the different responses to stress exhibited by blood cells of ME/CFS sufferers versus blood cells of healthy individuals. Aggravating the cells in both samples with a dose of salt, the researchers then applied electric current and measured the results. Among the cells of those feeling the symptoms of fatigue, there was a marked change in the current, an indication that the cells were affected by ME/CFS. The assay device relies on advancements in nanotechnology, microfabrication, and direct electrical detection of cellular and molecular properties. Test results are further refined through artificial intelligence and machine learning algorithms. “We still have further experiments to conduct to understand the contributing mechanisms and whether the responses are specific to ME/CFS,” Esfandyarpour said. “We envision integrating the nanoelectronic sensing arrays with the data acquisition and AI-based computing units to create a portable and handheld diagnostic and preclinical drug-screening platform that can be used by doctors, physicians and other researchers.”