cross-sectional study – American ME and CFS Society

Abstract:

Purpose: Post COVID-19 Condition (PCC), being persistent COVID-19 symptoms, is reminiscent of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)-a chronic multi-systemic illness characterised by neurocognitive, autonomic, endocrinological and immunological disturbances. This novel cross-sectional investigation aims to: (1) compare symptoms among people with ME/CFS (pwME/CFS) and people with PCC (pwPCC) to inform developing PCC diagnostic criteria; and (2) compare health outcomes between patients and people without acute or chronic illness (controls) to highlight the illness burdens of ME/CFS and PCC.

Methods: Sociodemographic and health outcome data were collected from n = 61 pwME/CFS, n = 31 pwPCC and n = 54 controls via validated, self-administered questionnaires, including the 36-Item Short-Form Health Survey version 2 (SF-36v2) and World Health Organization Disability Assessment Schedule version 2.0 (WHODAS 2.0). PwME/CFS and pwPCC also provided self-reported severity and frequency of symptoms derived from the Canadian and International Consensus Criteria for ME/CFS and the World Health Organization case definition for PCC.

Results: Both illness cohorts similarly experienced key ME/CFS symptoms. Few differences in symptoms were observed, with memory disturbances, muscle weakness, lymphadenopathy and nausea more prevalent, light-headedness more severe, unrefreshed sleep more frequent, and heart palpitations less frequent among pwME/CFS (all p < 0.05). The ME/CFS and PCC participants’ SF-36v2 or WHODAS 2.0 scores were comparable (all p > 0.05); however, both cohorts returned significantly lower scores in all SF-36v2 and WHODAS 2.0 domains when compared with controls (all p < 0.001).

Conclusion: This Australian-first investigation demonstrates the congruent and debilitating nature of ME/CFS and PCC, thereby emphasising the need for multidisciplinary care to maximise patient health outcomes.

Source: Weigel B, Eaton-Fitch N, Thapaliya K, Marshall-Gradisnik S. Illness presentation and quality of life in myalgic encephalomyelitis/chronic fatigue syndrome and post COVID-19 condition: a pilot Australian cross-sectional study. Qual Life Res. 2024 Jul 3. doi: 10.1007/s11136-024-03710-3. Epub ahead of print. PMID: 38961009. https://link.springer.com/article/10.1007/s11136-024-03710-3 (Full text)

Abstract:

Introduction: Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS), is a debilitating illness affecting up to 24 million people worldwide but concerningly there is no known mechanism for ME/CFS and no objective test for diagnosis. A series of our neuroimaging findings in ME/CFS, including functional MRI (fMRI) signal characteristics and structural changes in brain regions particularly sensitive to hypoxia, has informed the hypothesis that abnormal neurovascular coupling (NVC) may be the neurobiological origin of ME/CFS. NVC is a critical process for normal brain function, in which glutamate from an active neuron stimulates Ca²⁺ influx in adjacent neurons and astrocytes. In turn, increased Ca²⁺ concentrations in both astrocytes and neurons trigger the synthesis of vascular dilator factors to increase local blood flow assuring activated neurons are supplied with their energy needs.

This study investigates NVC using multimodal MRIs: (1) hemodynamic response function (HRF) that represents regional brain blood flow changes in response to neural activities and will be modeled from a cognitive task fMRI; (2) respiration response function (RRF) represents autoregulation of regional blood flow due to carbon dioxide and will be modeled from breath-holding fMRI; (3) neural activity associated glutamate changes will be modeled from a cognitive task functional magnetic resonance spectroscopy. We also aim to develop a neuromarker for ME/CFS diagnosis by integrating the multimodal MRIs with a deep machine learning framework.

Methods and analysis: This cross-sectional study will recruit 288 participants (91 ME/CFS, 61 individuals with chronic fatigue, 91 healthy controls with sedentary lifestyles, 45 fibromyalgia). The ME/CFS will be diagnosed by consensus diagnosis made by two clinicians using the Canadian Consensus Criteria 2003. Symptoms, vital signs, and activity measures will be collected alongside multimodal MRI.

The HRF, RRF, and glutamate changes will be compared among four groups using one-way analysis of covariance (ANCOVA). Equivalent non-parametric methods will be used for measures that do not exhibit a normal distribution. The activity measure, body mass index, sex, age, depression, and anxiety will be included as covariates for all statistical analyses with the false discovery rate used to correct for multiple comparisons.

The data will be randomly divided into a training (N = 188) and a validation (N = 100) group. Each MRI measure will be entered as input for a least absolute shrinkage and selection operator—regularized principal components regression to generate a brain pattern of distributed clusters that predict disease severity. The identified brain pattern will be integrated using multimodal deep Boltzmann machines as a neuromarker for predicting ME/CFS fatigue conditions. The receiver operating characteristic curve of the identified neuromarker will be determined using data from the validation group.

Ethics and study registry: This study was reviewed and approved by University of the Sunshine Coast University Ethics committee (A191288) and has been registered with The Australian New Zealand Clinical Trials Registry (ACTRN12622001095752).

Dissemination of results: The results will be disseminated through peer reviewed scientific manuscripts and conferences and to patients through social media and active engagement with ME/CFS associations.

Source: Shan ZY, Mohamed AZ, Andersen T, Rendall S, Kwiatek RA, Fante PD, Calhoun VD, Bhuta S, Lagopoulos J. Multimodal MRI of myalgic encephalomyelitis/chronic fatigue syndrome: A cross-sectional neuroimaging study toward its neuropathophysiology and diagnosis. Front Neurol. 2022 Sep 16;13:954142. doi: 10.3389/fneur.2022.954142. PMID: 36188362; PMCID: PMC9523103. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9523103/ (Full text)