ME/CFS Specialization

Myalgic Encephalomyelitis (ME)* is a debilitating neurological disease[1] affecting an estimated 2.5 million people in the United States and up to $24 billion economic cost to society[2]. While most neurological conditions have fatigue as part of their etiology [3], the fatigue in ME is known to be severe and unrelenting enough to be considered a core aspect of the disease. Fatigue in ME has been associated with immunological dysfunction, whereas domains including autonomic and cognitive dysregulation (and their relationship to fatigue) have received less attention. The symptoms of ME also include problems with attention, concentration, memory, neural processing efficiency [4] as well as autonomic problems (e.g. maintaining upright posture, cardiovascular and blood pressure abnormalities, lightheadedness, nausea, headaches, pain sensitivity, etc.). The plethora of symptoms cause significant disruption to social and occupational functioning and approximately 25% of patients are either housebound or bedbound [2]. 

Post-exertional malaise (PEM) is an incapacitating feature of ME that appears to be associated with impaired energy metabolism [5]. Signs that include a marked inability to tolerate even trivial amounts of physical and/or cognitive activity, accompanied by worsening symptoms such as muscle or joint pain, memory & learning issues, and consciousness problems. The energy depletion aspects of PEM, often lasting 24 hours or more [6], greatly interfere with disease management (e.g. pacing daily activities). Thus, people with ME often have difficulty performing routine tasks such as getting dressed, going from sitting to standing position, climbing a flight of stairs, taking a shower, cooking meals, doing housework, driving a vehicle, and standing in line. Cognitive/behavioral impairments and PEM are considered core aspects of ME with central context underlying the manifestation of multi-systemic symptoms [7]. 

The NCRI uses powerful new techniques that offer prospect of accelerating new discoveries for improving lives of people with neurological diseases including ME.

There is an urgent need for research aimed at identifying biological indicators of ME for making accurate diagnosis. Without an accurate diagnosis, a larger percentage of patients go undiagnosed for years and are unable to gain access to services they need. The cause of ME is unknown. However, in nearly 50% of cases with viral encephalitis, the cause is not identified [8]. To that end, the NCRI uses powerful new techniques that offer prospect of accelerating new discoveries and facilitate translation of scientific findings from the lab to real-world applications. For example, state-of-the-art electrical neuroimaging techniques such as swLORETA (standardized weighted low-resolution electromagnetic tomography) which allow for accurate mapping of neuronal activities of the brain in 3 dimensions [9].  Electrical neuroimaging operates at the millisecond timescale which allows for a reliable linkage of brain states and brain regions linked to patient’s symptoms. Furthermore, it is far more practical in terms of cost and portability. These advantages allow researchers and clinicians to objectively measure brain function happening in real time and analyze waveform patterns for assessing the effects of disease on cognitive and behavioral functions [10]. 

Promising findings from previous studies we’ve conducted offer much support for alterations in the central nervous system in patients with ME. In our recent Stanford study [11] using exact LORETA (eLORETA) methods [12], widespread delta (slow-wave) abnormalities were found in prefrontal and limbic cortical locations and they were associated associated with clinical fatigue severity ratings. Pathological delta waves may result from damage to nuclei in the brainstem, localized damage to white matter tracts, and brain inflammatory conditions (e.g. encephalitis). At the same time, decreased beta (fast-wave activity) was also found in the primary motor cortex, indicating reduced CNS drive for voluntary movement, disturbances in pain sensations and hypersensitivity. These findings were consistent with a separate study conducted at DePaul University [13] which showed diminished functional brain network connectivity across three major networks thought to underlie cognitive deficits and goal-directed behavior [14]. Likewise, another study conducted at DePaul found that the disruption of timings within the brain corresponded with neurocognitive symptom severity, serving as evidence for the role of brain network inefficiency associated with deficits found in patients [15]. Together, the data for these studies reveal that functional alterations in the brain are contributing to the energy deficits, hypersensitivity, and neurocognitive symptoms in patients with ME.

 

*ME is also known as chronic fatigue syndrome (CFS) and, more recently, systemic exertion intolerance disease (SEID). Most disease states are syndromes in that they typically involve multiple signs and symptoms, specifying which ones are necessary for a diagnosis, and which ones may or may not present. The idea of a syndrome is to help define what is, and what is not, a particular disease.

References

1. World Health Organization. (1992). The ICD-10 classification of mental and behavioral disorders: Clinical descriptions and diagnostic guidelines. World Health Organization.
2. Clayton, E.W., Biaggionni, I., Cockshell, S., Vermeculen, R., Snell, C., Rove, K. (2015). Beyond ME/CFS: Redefining an Illness. The National Academies Press: Washington DC.
3. Chaudhuri, A., & Behan, P. O. (2004). Fatigue in neurological disorders. The Lancet, 363(9413), 978–988. https://doi.org/10.1016/S0140-6736(04)15794-2
4. Cockshell, S. J., & Mathias, J. L. (2010). Cognitive functioning in chronic fatigue syndrome: A meta-analysis. Psychol Med, 40(8), 1253–1267. https://doi.org/10.1017/s0033291709992054
5. VanNess, J. M., Stevens, S. R., Bateman, L., Stiles, T. L., & Snell, C. R. (2010). Postexertional malaise in women with chronic fatigue syndrome. J Womens Health, 19(2), 239–244. https://doi.org/10.1089/jwh.2009.1507
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7. Carruthers, B. M., van de Sande, M. I., De Meirleir, K. L., Klimas, N. G., Broderick, G., Mitchell, T., … Stevens, S. (2011). Myalgic Encephalomyelitis: International Consensus Criteria. Journal of Internal Medicine. https://doi.org/10.1111/j.1365-2796.2011.02428.x
8. World Health Organization. (2006). Neurological disorders: Public health challenges. Geneva: World Health Organization.
9. Palmero-Soler, E., Dolan, K., Hadamschek, V., & Tass, P. A. (2007). SwLORETA: a novel approach to robust source localization and synchronization tomography. Phys Med Biol, 52(7), 1783–1800. https://doi.org/10.1088/0031-9155/52/7/002
10. Thatcher, R. W. (2016). Handbook of Quantitative Electroencephalography and EEG Biofeedback. St. Petersburg, FL: ANI Publishing.
11. Zinn, M. A., Zinn, M. L., Valencia, I., Jason, L. A., & Montoya, J. G. (2018). Cortical hypoactivation during resting EEG suggests central nervous system pathology in patients with chronic fatigue syndrome. Biological Psychology, 136, 87–99. https://doi.org/10.1016/j.biopsycho.2018.05.016
12. Pascual-Marqui, R. D., Lehmann, D., Koukkou, M., Kochi, K., Anderer, P., Saletu, B., … Kinoshita, T. (2011). Assessing interactions in the brain with exact low-resolution electromagnetic tomography. Philos Trans A Math Phys Eng Sci, 369(1952), 3768–3784. https://doi.org/10.1098/rsta.2011.0081
13. Zinn, M. L., Zinn, M. A., & Jason, L. A. (2016). Intrinsic functional hypoconnectivity in core neurocognitive networks suggests central nervous system pathology in patients with Myalgic Encephalomyelitis: A pilot study. Appl Psychophysiol Biofeedback, 41(3), 283–300. https://doi.org/10.1007/s10484-016-9331-3
14. Menon, V. (2011). Large-scale brain networks and psychopathology: A unifying triple network model. Trends Cogn Sci, 15(10), 483–506. https://doi.org/10.1016/j.tics.2011.08.003
15. Zinn, M. A., Zinn, M. L., & Jason, L. A. (2017). Small-world network analysis of cortical connectivity in chronic fatigue syndrome using quantitative EEG. NeuroRegulation, 4(3–4), 125. https://doi.org/10.15540/nr.4.3-4.125
     

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