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Single Day Longitudinal Study

This study seeks to understand the biological mechanisms driving the symptomatology of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) using metabolomic and lipidomic high-throughput analysis and high-frequency blood sampling over a 6.5 to 7.5 hour period conducted at two separate sites (Melbourne and Uppsala).

  • Martin Lewis, PhD
  • Michael Musker, PhD
  • Jonas Bergquist, MD, PhD
  • Christopher Armstrong, PhD
  • Analysis complete.
  • Working on publication for submission by the end of 2024.
STUDY HYPOTHESIS AND DESCRIPTION

In our research into Myalgic Encephalomyelitis / Chronic Fatigue Syndrome (ME/CFS), we’re exploring how energy, amino acids, and fats are processed differently in patients compared to healthy people. Previous studies have identified various changes in these substances in ME/CFS patients, but these changes aren’t consistent across all studies, possibly due to the diverse symptoms and biological characteristics of ME/CFS patients.

To address this, our study uses a method where we take multiple samples from the same patient over time. This approach allows each patient to serve as their own comparison point, which helps minimize differences that aren’t related to ME/CFS. This type of study, called a repeated-measures design, is especially useful for diseases like ME/CFS, where symptoms and biological markers can vary a lot from one patient to another.

By closely analyzing metabolites (substances produced during metabolism) and lipids (fats) in these repeated samples, we aim to better understand what causes ME/CFS at a biological level. This could lead to more accurate tests to diagnose ME/CFS and the development of new treatments that target these specific biological changes.

OBJECTIVES

  1. Pattern biology that corresponds to patient symptoms over the course of a day in two international cohorts.
  2. Track the biological impact of meals, social tasks, mental tasks and exercise tasks on ME/CFS patients compared to controls.
  3. Cluster patients based on similar biology-symptom dynamics.

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