Myalgic Encephalomyelitis (ME) /Chronic Fatigue Syndrome (CFS) is a severely debilitating and complex illness of uncertain aetiology, affecting the lives of millions and characterised by prolonged fatigue. The initiating factors and mechanisms leading to chronic debilitating muscle fatigue in ME/CFS are unknown and are complicated by the time required for diagnosis. Both mitochondrial dysfunction and inflammation have been proposed to be central to the pathogenesis of ME/CFS. This original and extensive study demonstrated that although there was little dysfunction evident in the muscle mitochondria of patients with ME/CFS, particular blood plasma and skeletal muscle cytokines, when adjusted for age, gender and cytokine interactions could predict both diagnosis and a number of measures common to patients with ME/CFS. These included MVC and perceived fatigue as well as cognitive indices such as pattern and verbal reaction times. We employed advanced multivariate analyses to cytokine profiles that leverages covariation and intrinsic redundancy to identify patterns of immune signaling that can be evaluated for their predictions of disease phenotype. The current study identified discriminatory cytokine profiles that can be sufficiently used to distinguish HCs from patients with ME/CFS and provides compelling evidence that a limited number of cytokines are associated with diagnosis and fatigue. Moreover, this study demonstrates significant potential of using multiplex cytokine profiles and bioinformatics as diagnostic tools for ME/CFS, potentiating the possibility of not only diagnosis, but also being able to individually personalise therapies.
|Publication status||E-pub ahead of print - 21 Aug 2020|