When cells expire, they leave behind an activity log of sorts: RNA expelled into blood plasma that reveal changes in gene expression, cellular signaling, tissue injury and other biological processes.
When cells expire, they leave behind an activity log of sorts: RNA expelled into blood plasma that reveal changes in gene expression, cellular signaling, tissue injury and other biological processes.
Cornell researchers developed machine-learning models that can sift through this cell-free RNA and identify key biomarkers for myalgic encephalomyelitis, also known as chronic fatigue syndrome (ME/CFS). The approach could lead to the development of diagnostic testing for a debilitating disease that has proved challenging to confirm in patients because its symptoms can be easily confused with those of other illnesses.
The findings were published Aug. 11 in Proceedings of the National Academy of Sciences. The lead author is Anne Gardella, a doctoral student in biochemistry, molecular and cell biology in the De Vlaminck Lab.
Read More: Cornell University
