Discriminating Myalgic Encephalomyelitis/Chronic Fatigue Syndrome and comorbid conditions using metabolomics in UK Biobank
This study provides an end-to-end analytical workflow that explores the potential clinical utility that association scores may have for ME/CFS and other difficult to diagnose conditions.
Authors
- Natalie Thomas (ORCID: https://orcid.org/0000-0002-3388-7408)
- Alex G. C. de Sá (ORCID: https://orcid.org/0000-0002-7276-7839)
- Robert D. Phair (ORCID: https://orcid.org/0000-0001-7979-2386)
- Paul R. Gooley (ORCID: https://orcid.org/0000-0002-0323-449X)
- Katherine Huang (ORCID: https://orcid.org/0000-0003-0171-6820)
- Christopher W. Armstrong (ORCID: https://orcid.org/0000-0002-5964-5618)
- David B. Ascher (ORCID: https://orcid.org/0000-0003-2948-2413)
Institutions
- Baker Heart and Diabetes Institute (AU)
- The University of Queensland (AU)
- The University of Melbourne (AU)
Publication Details
- Journal
- Communications Medicine
- Published
- 2024-11-26
- DOI
- https://doi.org/10.1038/s43856-024-00669-7
- Citations
- 14
- Primary Topic
- Fibromyalgia and Chronic Fatigue Syndrome Research
- Type
- article
- Field-Weighted Citation Impact
- 5.40
Funders
- Judith Jane Mason and Harold Stannett Williams Memorial Foundation
- Open Medicine Foundation
- State Government of Victoria
- Medical Research Council
- National Health and Medical Research Council