Myalgic Encephalomyelitis / Chronic Fatigue Syndrome (ME / CFS) Post Treatment Lyme Disease Syndrome (PTLDS), Fibromyalgia Leading Research. Delivering Hope.Open Medicine Foundation® Canada

Driving research of Myalgic Encephalomyelitis / Chronic Fatigue Syndrome (ME / CFS),
Post Treatment Lyme Disease Syndrome (PTLDS), Fibromyalgia and Long COVID.

RAman SPectrometry Based biomarkER discoveRY for Myalgic Encephalomyelitis (RASPBERRY-ME)

  • From our MAESTRO project, we have seen that the profile of circulating microRNA can distinguish between ME and Fibromyalgia (FM) patients.
  • Our diagnostic panel of 11 circulating microRNA can be used (without induction of PEM) to identify individuals suffering of ME, FM or having both conditions.
  • We have also shown that miR-150-5p is associated with POTS/OI in ME patients. We proposed that miR-150-5p triggers POTS/OI through two distinct mechanisms:
    • Mechanism 1: Elevation of miR-150-5p expression occurs in ME patients with POTS/OI and block the translation of SLC6A2 mRNA resulting in a norepinephrine transporter (NET) deficiency.
    • Mechanism 2: Conversely, a severe reduction of miR-150-5p expression induces a similar effect by increasing the EZH2 expression, which leads to a transcriptional repression of SLC6A2 gene, lowering NET levels.
  • We are also exploring the role of circulating thrombospondin-1 (TSP-1) in the regulation of soluble SMPDL3B production
  • Lastly, we have identified 8 targets as potential therapeutic options and will be exploring these further–specifically how to increase, reduce, or block these potential biomarkers of ME.

STUDY HYPOTHESIS AND DESCRIPTION

Woman researcher working with a computer in a laboratory. Raman spectroscopy is a non-destructive, rapid, and low-cost technique allows the study of the molecular composition of biological fluids like blood, or inside a cell when combined with confocal microscopy. This innovative approach could lead to the development of diagnostic tools to better stratify ME patients and find the underlying causes of different symptoms like post-exertional malaise as well as clinical tools to validate the therapeutic potential of pharmacological treatments to treat, stop or mitigate ME through precision medicine.

We hypothesize that our approach will allow the identification of a biomolecular signature of ME both at baseline and in response to the application of a post-exertional stress challenge. We expect to stratify patients by differentiating severe cases from mild forms of ME. Results from this study will be further combined to ongoing proteomic and metabolomic profiling approaches to better understand the pathophysiology of ME.

Objective

  1. Characterize the biomolecular signature of ME patients and healthy age-matched controls using label-free Raman spectroscopy in plasma samples acquired at baseline and after PEM induction
  2. Determine cellular metabolite alterations between ME patients and age-matched controls using Raman spectroscopy combined with confocal microscopy with peripheral blood mononuclear cells (PBMCs) acquired at baseline and after PEM induction
  3. Develop molecular feature detection and machine-learning models capable to predict PEM response (baseline vs. post stress-test) and the disease (ME vs. control).