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AusME Biobank Biomarker project

Study Aim

The study will utilise the Australian ME/CFS biobank for metabolomics analyses and other assays to identify potential biomarkers for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome, contributing to a comprehensive dataset for large-scale analysis.

Investigators

  • Sarah Annesley, PhD
  • Paul Fisher, PhD
  • Brett Lidbury, PhD
  • Alice Richardson, PhD
  • Benjamin Heng, PhD
  • Elisha Josev, PhD
  • Paul Gooley, PhD
  • Christopher Armstrong, PhD

Updates and Potential

  • IRB/Ethics approval completed.
  • Samples completing collection in August.
  • Over 200 samples expected for metabolomics assays which will require 2 months with early scheduling.
  • Data analysis will require 2 months and publication of data may be possible in 2024 but more likely 2025.
STUDY HYPOTHESIS AND DESCRIPTION

To enhance the research capabilities within the Australian scientific community concerning Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) and Long COVID, we played a role in establishing an Australian biobank for ME/CFS managed by Emerge Australia. The establishment of this biobank and registry included conducting a biomarker study utilising patient samples. Although the progress of the biobank was hindered by the pandemic, we have now successfully collected hundreds of samples from willing participants over the past few years.

As part of this initiative, we are currently performing metabolomics analyses on all samples stored in the biobank. This metabolomics data will be integrated with findings from other assays conducted by our collaborators. We plan to disseminate research papers detailing individual projects and subsequently compile a comprehensive dataset for large-scale analysis aimed at identifying potential biomarkers.

OBJECTIVES

close-up of a gloved hand holding a test tube containing a blood sample. The test tube is labeled with barcode for identification and tracking purposes.

  1. Pattern metabolites corresponding to patient symptoms and co-morbid conditions.
  2. Validate markers from previous studies.
  3. Search for new potential markers in this large Australian dataset.
  4. Cluster patients based on similar biology-symptom.
  5. Combine data with collaborator assays on same patients.