This protocol would be useful for tracking the development of ME/CFS, provide an understanding of the biology of the disease process in the individual, stratify ME/CFS individuals into biologically-defined subsets, test the efficacy of treatments, and monitor outcomes in clinical treatment trials.
A condensed personalized research protocol would be the minimum number of samples from specific conditions that can accurately develop a biological signature unique to an individual with ME/CFS that can be used predict the improvement or worsening of their symptoms.
Initially, the biology of 100 people with ME/CFS will be characterized by continuously monitoring their health data and sporadically sampling and analyzing their blood and urine over the course of a year.
Metabolite and Symptom Data will be analyzed to identify signatures of disease severity in individuals that predict increased and decreased disease severity.
Pattern-recognition software will be developed specifically to recognize these signatures and compare them across patients to identify patterns that can then reduce the complexity and length of the personalized research method.