Developing a Blood Cell‐Based Diagnostic Test for Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Peripheral Blood Mononuclear Cells

Author:

Xu Jiabao12ORCID,Lodge Tiffany3,Kingdon Caroline4,Strong James W. L.3,Maclennan John5,Lacerda Eliana4,Kujawski Slawomir6,Zalewski Pawel67,Huang Wei E.1,Morten Karl J.3ORCID

Affiliation:

1. Department of Engineering Science University of Oxford Parks Road Oxford OX1 3PJ UK

2. Division of Biomedical Engineering, James Watt School of Engineering University of Glasgow Glasgow G12 8LT UK

3. Nuffield Department of Women's and Reproductive Health University of Oxford The Women Centre John Radcliffe Hospital Headley Way, Headington Oxford OX3 9DU UK

4. Faculty of Infectious Diseases London School of Hygiene and Tropical Medicine Keppel St London WC1E 7HT UK

5. Soft Cell Biological Research Attwood Innovation Center 453 S 600 E St. George UT 84770 USA

6. Department of Exercise Physiology and Functional Anatomy Collegium Medicum in Bydgoszcz Nicolaus Copernicus University in Torun Swietojanska 20 Bydgoszcz 85‐077 Poland

7. Department of Experimental and Clinical Physiology Warsaw Medical University Stefana Banacha 2a Warszawa 02‐097 Poland

Abstract

AbstractMyalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is characterized by debilitating fatigue that profoundly impacts patients' lives. Diagnosis of ME/CFS remains challenging, with most patients relying on self‐report, questionnaires, and subjective measures to receive a diagnosis, and many never receiving a clear diagnosis at all. In this study, a single‐cell Raman platform and artificial intelligence are utilized to analyze blood cells from 98 human subjects, including 61 ME/CFS patients of varying disease severity and 37 healthy and disease controls. These results demonstrate that Raman profiles of blood cells can distinguish between healthy individuals, disease controls, and ME/CFS patients with high accuracy (91%), and can further differentiate between mild, moderate, and severe ME/CFS patients (84%). Additionally, specific Raman peaks that correlate with ME/CFS phenotypes and have the potential to provide insights into biological changes and support the development of new therapeutics are identified. This study presents a promising approach for aiding in the diagnosis and management of ME/CFS and can be extended to other unexplained chronic diseases such as long COVID and post‐treatment Lyme disease syndrome, which share many of the same symptoms as ME/CFS.

Funder

ME Association

Publisher

Wiley

Subject

General Physics and Astronomy,General Engineering,Biochemistry, Genetics and Molecular Biology (miscellaneous),General Materials Science,General Chemical Engineering,Medicine (miscellaneous)

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