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Stress-Activated MicroRNAs
in ME / CFS Pathogenesis

ME / CFS is a multi-systemic complex chronic disease exhibiting a clinical heterogeneity as main symptoms vary between affected individuals and also overtime. This situation adds to the complexity to decipher its causes and mechanisms as well as to find potential therapeutic targets. Furthermore, severely affected persons with ME / CFS are rarely being investigated.

Identifying a specific microRNA signature in ME / CFS will aid in the development of disease risk prediction and improve the clinical stratification of symptomatic patients.

Ultimately, discovery of biomarkers may lead to diagnoses that are more accurate, disease prevention measures, and indications on how to treat ME / CFS effectively.


We designed a clinical intervention, safely producing a post-exertional malaise (PEM), a hallmark symptom of ME / CFS. We hypothesized that a standardized stress-test inducing PEM, will reveal a more specific disease signature associated with ME / CFS symptoms. In that context, we investigated the role of circulating microRNAs, which are small non-coding RNA molecules that can be detected in the blood as well as in other biological fluids.


Studying microRNAs might help to bridge the conceptual gap between genetic predisposition and environmental factors causing ME / CFS or exacerbating specific symptoms. Equally important, the design of a portable clinical intervention allows investigating severely ill persons with ME / CFS, especially the ones that are housebound.


  • This strategy led us to identify 32 circulating microRNAs in a case-control cohort.
  • Several of the miRNAs identified in our discovery cohort are associated with inflammation, regulation of immunity and/or a physiological response to exercise (endurance regulators).
  • Implementation of bioinformatics tools like Machine Learning algorithm (Random Forest Algorithm) led to a validation of a first diagnostic panel of 8 microRNAs (miR-28-5p, miR-29a-5p, miR-127-3p, miR-140-5p, miR-374b-5p, miR-486-5p, miR-3620-3p and miR-6819-3p) using a dataset of individuals with ME / CFS and matched healthy controls.
  • This panel has a predictive accuracy of 90% with a sensitivity of 100% and a specificity of 75% when the expression of each microRNA is compared after the stess-test versus their respective values at baseline (without stimulation). Conversely, when only the baseline values are used (without the stress-test), the predictive accuracy is lowered to 60% with a sensitivity of 71% and a specificity of 33% (non-specific). These preliminary results clearly indicated the superiority of our stress-test approach to reveal the molecular signature underlying ME / CFS.
  • This approach led also to an unbiased method to separate the persons with ME / CFS, called clustering, along three distinct clusters showing specific correlations between each cluster and symptom severity. Indeed, persons with ME / CFS classified in cluster 1 exhibit less general fatigue than those classified into cluster 2 and 3, while individuals in cluster 3 suffer of more severe sleep disturbances and PEM.
  • Interestingly, high expression of specific circulating microRNAs could help in predicting the respond toward specific treatment like Ampligen, Rituximab and many others.
  • To find out more about the outcomes of this study, read Profile of Circulating MicroRNAspaper.•The next phase of our investigation into microRNAs continued with the MAESTRO project.
Myalgic Encephalomyelitis / Chronic Fatigue Syndrome (ME / CFS) Post Treatment Lyme Disease Syndrome (PTLDS), Fibromyalgia Leading Research. Delivering Hope.Open Medicine Foundation®

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