Absence of fMRI adaptation in patients with chronic fatigue syndrome
Poster No:
139
Submission Type:
Abstract Submission
Authors:
Zack Shan1, Laura Schönberg2, Abdalla Mohamed1, Richard Kwiatek1, Peter Del Fante1, Vince Calhoun3
Institutions:
1Thompson Institute, University of the Sunshine Coast, Birtinya, QLD, 2Department of Health Sciences and Technology, ETH Zurich, Zurich, Zurich, 3Georgia State University, Atlanta, GA
First Author:
Co-Author(s):
Introduction:
Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a debilitating disease of unknown etiology. The hallmark feature of ME/CFS is severe and persistent fatigue that does not improve following rest. Many factors can cause fatigue. However, fatigue is essentially a feeling generated by the brain. Thus, task fMRI (tfMRI) may provide valuable insights into neural mechanisms associated with fatigue in ME/CFS.
A systematic review of tfMRI studies in ME/CFS identified a consistent observation of larger recruitment of brain regions during cognitive tasks in ME/CFS patients compared to healthy controls (HCs) (3). Patients with other neuropathologies with diffuse damage, such as traumatic brain injury, have similarly shown augmented functional recruitment (4). Moreover, Kohl et al. observed that traumatic brain injury patients showed progressively increased fMRI signals over time, while HCs' fMRI activities decreased after multiple trial repetitions during a prolonged cognitive task (5).
This study investigates how fMRI signal changes during cognitive tasks in patients with ME/CFS. We hypothesise that sustained cognitive function induces cognitive fatigue, i.e., an increase in cerebral activity over time as indexed by BOLD response, in ME/CFS but not in HCs. In contrast, we hypothesise that HCs will show decreased cerebral activity over time because of an adaptation to the task.
A systematic review of tfMRI studies in ME/CFS identified a consistent observation of larger recruitment of brain regions during cognitive tasks in ME/CFS patients compared to healthy controls (HCs) (3). Patients with other neuropathologies with diffuse damage, such as traumatic brain injury, have similarly shown augmented functional recruitment (4). Moreover, Kohl et al. observed that traumatic brain injury patients showed progressively increased fMRI signals over time, while HCs' fMRI activities decreased after multiple trial repetitions during a prolonged cognitive task (5).
This study investigates how fMRI signal changes during cognitive tasks in patients with ME/CFS. We hypothesise that sustained cognitive function induces cognitive fatigue, i.e., an increase in cerebral activity over time as indexed by BOLD response, in ME/CFS but not in HCs. In contrast, we hypothesise that HCs will show decreased cerebral activity over time because of an adaptation to the task.
Methods:
This prospective study uses data collected for the ongoing study of ME/CFS (6), approved by the University of the Sunshine Coast Ethic Committee (A191288) and registered with The Australian New Zealand Clinical Trials Registry (ACTRN12622001095752). Sixty-eight participants, 34 ME/CFS participants (mean age, 38 ± 10 [standard deviation]; 27 women) and 34 HCs (mean age, 38 ± 10 [standard deviation]; 27 women), were included. The fMRI paradigm consisted of two task blocks where participants performed a symbol digit modalities test (SDMT) alternating with resting conditions. Details of the structural and tfMRI data collection parameters were reported previously (6).
Standard pre-processing of fMRI was conducted and then analysed using the two-level general linear model approach of SPM12. The subject-specific activation maps were built on correctly answered trials only with realignment parameters as nuisance regressors. Four first-level contrasts were determined for task vs rest, block 1 vs block 2, block 1 – 1st set vs block 1 – 2nd set and block 2 – 1st set vs block 2 – 2nd set. At the second level, first-level contrasts were entered into random-effect one-sample t-tests for within-group analyses and two-sample t-tests for between-group analyses. Sex, age, and BMI were included as nuisance covariates in all analyses. The significance was determined at the cluster level PFWE < .05 with cluster-forming of uncorrected P < .001 at the voxel level and number of voxels ≥ 25.
Standard pre-processing of fMRI was conducted and then analysed using the two-level general linear model approach of SPM12. The subject-specific activation maps were built on correctly answered trials only with realignment parameters as nuisance regressors. Four first-level contrasts were determined for task vs rest, block 1 vs block 2, block 1 – 1st set vs block 1 – 2nd set and block 2 – 1st set vs block 2 – 2nd set. At the second level, first-level contrasts were entered into random-effect one-sample t-tests for within-group analyses and two-sample t-tests for between-group analyses. Sex, age, and BMI were included as nuisance covariates in all analyses. The significance was determined at the cluster level PFWE < .05 with cluster-forming of uncorrected P < .001 at the voxel level and number of voxels ≥ 25.
Results:
Within-group analyses of BOLD responses associated with the SDMT showed patients with ME/CFS recruited broader brain areas in the right dorsolateral prefrontal and left somatosensory cortex than HCs (Fig 1).
In the second block, within-group analyses investigating the changes between its first and second set showed an increase in brain activity in the ME/CFS group, whereas HCs showed a decrease in brain activity. Between-group analysis showed significantly higher brain activity in the bilateral pre- and post-central gyrus, inferior parietal lobule, and the right superior temporal gyrus in ME/CFS compared to HCs (block 2 - second set vs block 2 -first set) (Fig. 2).
In the second block, within-group analyses investigating the changes between its first and second set showed an increase in brain activity in the ME/CFS group, whereas HCs showed a decrease in brain activity. Between-group analysis showed significantly higher brain activity in the bilateral pre- and post-central gyrus, inferior parietal lobule, and the right superior temporal gyrus in ME/CFS compared to HCs (block 2 - second set vs block 2 -first set) (Fig. 2).
Conclusions:
Neurophysiologic and hemodynamic adaptation in HCs may improve the energy economy. Conversely, this adaptation was absent in our ME/CFS group, which may provide an underlying neurophysiological process for neurological symptoms in ME/CFS.
Disorders of the Nervous System:
Neurodegenerative/ Late Life (eg. Parkinson’s, Alzheimer’s) 1
Physiology, Metabolism and Neurotransmission :
Cerebral Metabolism and Hemodynamics 2
Keywords:
FUNCTIONAL MRI
Infections
Neurological
Perception
Other - Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS)
1|2Indicates the priority used for review
·Fig. 1 Neural correlates of symbol digit modalities test task.
·Fig. 2 Differences in fMRI changes comparing the first and second half trials in the second block between patients and health controls (HC).
Provide references using author date format
2. Holgate S, Komaroff A, Mangan D, Wessely S. Chronic fatigue syndrome: understanding a complex illness. Nat Rev Neurosci 2011;12:539-544.
3. Shan ZY, Barnden LR, Kwiatek RA, Bhuta S, Hermens DF, Lagopoulos J. Neuroimaging characteristics of myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS): a systematic review. J Transl Med 2020;18(1):335. doi: 10.1186/s12967-020-02506-6
4. Turner GR, Levine B. Augmented neural activity during executive control processing following diffuse axonal injury. Neurology 2008;71(11):812-818. doi: 10.1212/01.wnl.0000325640.18235.1c
5. Kohl AD, Wylie GR, Genova HM, Hillary FG, Deluca J. The neural correlates of cognitive fatigue in traumatic brain injury using functional MRI. Brain Inj 2009;23(5):420-432. doi: 10.1080/02699050902788519
6. 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;13:954142. doi: 10.3389/fneur.2022.954142