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Biomedical Insights that Inform the Diagnosis of ME/CFS
Brett A. Lidbury and Paul R. Fisher
2020
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Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a severe chronic health condition that is often misunderstood or ignored by health establishments. The lack of definitive diagnostic markers to separate ME/CFS patients from the healthy population as well as from other chronic disorders is problematic for both health professionals and researchers. A consortium of Australian researchers gathered to systematically understand ME/CFS, ranging from a deep analysis of clinical and pathology data to metabolomic profiles and the investigation of mitochondrial function. From this broad collaboration, a number of compelling insights have arisen that may form the basis of specific serum, blood, and/or urinary biomarkers of ME/CFS. This Special Edition reports on a conference centred on these biomedical discoveries, with other contributions, with a translation focus for predictive markers for ME/CFS diagnosis. By supporting health professionals with developments in diagnostics for this condition, the patients and their families will hopefully benefit from an improved recognition of the biomedical underpinnings of the condition and will be better able to access the care that is urgently required. This Special Edition contains a mix of speaker submissions and other accepted manuscripts that contributed to our objective of advancing biomedical insights to enable the accurate diagnosis of ME/CFS.
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Keywords
- 3-dioxygenase
- activin
- assessment
- biomarker
- bistability
- CFS (Chronic Fatigue Syndrome)
- chronic
- chronic fatigue syndrome
- Circadian Rhythm
- critical point
- cytokine
- Diagnosis
- diagnostic biomarker
- Energy Metabolism
- Epstein Barr virus
- Exercise
- fatigue syndrome
- Gut Microbiota
- histone deacetylation
- hypoacetylation
- hypothalamic–pituitary–adrenal axis
- Immune system
- immunological
- indoleamine-2
- indoleamine-2,3-dioxygenase
- Inflammation
- inflammation and immunity
- kynurenine pathway
- Machine learning
- Mathematical model
- ME (Myalgic Encephalomyelitis)
- ME/CFS
- medical retirement
- Metabolism
- methylhistidine
- Mitochondria
- Muscles
- myalgic encephalomyelitis
- myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)
- n/a
- neuro-inflammation
- neuroimmune
- Neurology
- Participatory research
- Pathology
- patient-driven questionnaire
- post-exertional malaise
- potential biomarkers
- prognosis
- reference intervals
- signaling
- substrate inhibition
- symptoms
- tryptophan metabolism
- work rehabilitation
Links
DOI: 10.3390/books978-3-03928-391-0Editions
