Center for Enervating NeuroImmune Disease

We plan to integrate the analysis of datasets from different types of assays. We think this will yield additional insights into the pathophysiology of ME/CFS and in particular, point toward molecular mechanisms of PEM. Integrating our multi-omic data with the clinical and exercise physiology data of our patient cohort may allow us to identify unique molecular signatures in different subsets of ME/CFS patients. These molecular signatures may provide a basis for tailored diagnostics and treatments for clinical and demographic subsets of ME/CFS patients in the future.

Predictive modeling using a combination of molecules in different classes that have significantly different levels in ME/CFS patients and controls at baseline may enable more accurate classification of ME/CFS patients and healthy controls than could an assay utilizing biomarkers only from a single class.