Mechanophenotyping RBC subpopulations in ME/CFS

ABSTRACT Myalgic encephalomyelitis, also known as chronic fatigue syndrome (ME/CFS), afflicts up to 2.5 million in the United States and millions more worldwide. Very little is known about its cause(s), most physicians are not adept at diagnosis, and no biological markers or approved treatments are available. ME/CFS is a heterogeneous and unpredictable disease with subsets of shared symptoms but most patients experience post-exertional malaise, orthostatic intolerance, and cognitive disturbances. Plasma inflammatory and oxidative stresses are increased in a subset of patients suggesting a multisystemic dyshomeostasis. Studies suggest that impaired oxygen delivery to the muscles during high metabolic demand may explain the symptoms common to most patients. Red blood cell (RBC) deformability is vital to microvascular oxygenation. We have observed that the deformability of RBC in ME/CFS patients is lower than that of healthy subjects, due to an increase in stiffer subpopulation of RBC in the patients. In this proposal, we will test the hypothesis that the deformability distribution in RBC can serve to differentiate ME/CFS patients from healthy subjects, and that the increased oxidative stress contributes to altered deformability distributions. We will implement an ultra-high throughput microfluidic fractionator to sort RBC based on their deformability, and in the sorted subpopulations, examine metabolic, structural, and functional changes. We will develop machine learning models to correlate the biophysical and biochemical properties of the RBC subpopulations with the clinical measures to classify ME/CFS into subtypes. Several undergraduate and master's students will actively engage at every stage of the project, and will receive rigorous training in interdisciplinary research of high clinical significance.