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      Molecular Mechanisms of Neuroinflammation in ME/CFS and Long COVID to Sustain Disease and Promote Relapses

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          Abstract

          Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) is a disease now well-documented as having arisen commonly from a viral infection, but also from other external stressors, like exposure to agricultural chemicals, other types of infection, surgery, or other severe stress events. Research has shown these events produce a systemic molecular inflammatory response and chronic immune activation and dysregulation. What has been more difficult to establish is the hierarchy of the physiological responses that give rise to the myriad of symptoms that ME/CFS patients experience, and why they do not resolve and are generally life-long. The severity of the symptoms frequently fluctuates through relapse recovery periods, with brain-centered symptoms of neuroinflammation, loss of homeostatic control, “brain fog” affecting cognitive ability, lack of refreshing sleep, and poor response to even small stresses. How these brain effects develop with ME/CFS from the initiating external effector, whether virus or other cause, is poorly understood and that is what our paper aims to address. We propose the hypothesis that following the initial stressor event, the subsequent systemic pathology moves to the brain via neurovascular pathways or through a dysfunctional blood-brain barrier (BBB), resulting in chronic neuroinflammation and leading to a sustained illness with chronic relapse recovery cycles. Signaling through recognized pathways from the brain back to body physiology is likely part of the process by which the illness cycle in the peripheral system is sustained and why healing does not occur. By contrast, Long COVID (Post-COVID-19 condition) is a very recent ME/CFS-like illness arising from the single pandemic virus, SARS-CoV-2. We believe the ME/CFS-like ongoing effects of Long COVID are arising by very similar mechanisms involving neuroinflammation, but likely with some unique signaling, resulting from the pathology of the initial SARS-CoV-2 infection. The fact that there are very similar symptoms in both ongoing diseases, despite the diversity in the nature of the initial stressors, supports the concept of a similar dysfunctional CNS component common to both.

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          An interactive web-based dashboard to track COVID-19 in real time

          In December, 2019, a local outbreak of pneumonia of initially unknown cause was detected in Wuhan (Hubei, China), and was quickly determined to be caused by a novel coronavirus, 1 namely severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The outbreak has since spread to every province of mainland China as well as 27 other countries and regions, with more than 70 000 confirmed cases as of Feb 17, 2020. 2 In response to this ongoing public health emergency, we developed an online interactive dashboard, hosted by the Center for Systems Science and Engineering (CSSE) at Johns Hopkins University, Baltimore, MD, USA, to visualise and track reported cases of coronavirus disease 2019 (COVID-19) in real time. The dashboard, first shared publicly on Jan 22, illustrates the location and number of confirmed COVID-19 cases, deaths, and recoveries for all affected countries. It was developed to provide researchers, public health authorities, and the general public with a user-friendly tool to track the outbreak as it unfolds. All data collected and displayed are made freely available, initially through Google Sheets and now through a GitHub repository, along with the feature layers of the dashboard, which are now included in the Esri Living Atlas. The dashboard reports cases at the province level in China; at the city level in the USA, Australia, and Canada; and at the country level otherwise. During Jan 22–31, all data collection and processing were done manually, and updates were typically done twice a day, morning and night (US Eastern Time). As the outbreak evolved, the manual reporting process became unsustainable; therefore, on Feb 1, we adopted a semi-automated living data stream strategy. Our primary data source is DXY, an online platform run by members of the Chinese medical community, which aggregates local media and government reports to provide cumulative totals of COVID-19 cases in near real time at the province level in China and at the country level otherwise. Every 15 min, the cumulative case counts are updated from DXY for all provinces in China and for other affected countries and regions. For countries and regions outside mainland China (including Hong Kong, Macau, and Taiwan), we found DXY cumulative case counts to frequently lag behind other sources; we therefore manually update these case numbers throughout the day when new cases are identified. To identify new cases, we monitor various Twitter feeds, online news services, and direct communication sent through the dashboard. Before manually updating the dashboard, we confirm the case numbers with regional and local health departments, including the respective centres for disease control and prevention (CDC) of China, Taiwan, and Europe, the Hong Kong Department of Health, the Macau Government, and WHO, as well as city-level and state-level health authorities. For city-level case reports in the USA, Australia, and Canada, which we began reporting on Feb 1, we rely on the US CDC, the government of Canada, the Australian Government Department of Health, and various state or territory health authorities. All manual updates (for countries and regions outside mainland China) are coordinated by a team at Johns Hopkins University. The case data reported on the dashboard aligns with the daily Chinese CDC 3 and WHO situation reports 2 for within and outside of mainland China, respectively (figure ). Furthermore, the dashboard is particularly effective at capturing the timing of the first reported case of COVID-19 in new countries or regions (appendix). With the exception of Australia, Hong Kong, and Italy, the CSSE at Johns Hopkins University has reported newly infected countries ahead of WHO, with Hong Kong and Italy reported within hours of the corresponding WHO situation report. Figure Comparison of COVID-19 case reporting from different sources Daily cumulative case numbers (starting Jan 22, 2020) reported by the Johns Hopkins University Center for Systems Science and Engineering (CSSE), WHO situation reports, and the Chinese Center for Disease Control and Prevention (Chinese CDC) for within (A) and outside (B) mainland China. Given the popularity and impact of the dashboard to date, we plan to continue hosting and managing the tool throughout the entirety of the COVID-19 outbreak and to build out its capabilities to establish a standing tool to monitor and report on future outbreaks. We believe our efforts are crucial to help inform modelling efforts and control measures during the earliest stages of the outbreak.
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            NF-κB signaling in inflammation

            The transcription factor NF-κB regulates multiple aspects of innate and adaptive immune functions and serves as a pivotal mediator of inflammatory responses. NF-κB induces the expression of various pro-inflammatory genes, including those encoding cytokines and chemokines, and also participates in inflammasome regulation. In addition, NF-κB plays a critical role in regulating the survival, activation and differentiation of innate immune cells and inflammatory T cells. Consequently, deregulated NF-κB activation contributes to the pathogenic processes of various inflammatory diseases. In this review, we will discuss the activation and function of NF-κB in association with inflammatory diseases and highlight the development of therapeutic strategies based on NF-κB inhibition.
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              Chronic inflammation in the etiology of disease across the life span

              Although intermittent increases in inflammation are critical for survival during physical injury and infection, recent research has revealed that certain social, environmental and lifestyle factors can promote systemic chronic inflammation (SCI) that can, in turn, lead to several diseases that collectively represent the leading causes of disability and mortality worldwide, such as cardiovascular disease, cancer, diabetes mellitus, chronic kidney disease, non-alcoholic fatty liver disease and autoimmune and neurodegenerative disorders. In the present Perspective we describe the multi-level mechanisms underlying SCI and several risk factors that promote this health-damaging phenotype, including infections, physical inactivity, poor diet, environmental and industrial toxicants and psychological stress. Furthermore, we suggest potential strategies for advancing the early diagnosis, prevention and treatment of SCI.
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                Author and article information

                Contributors
                Journal
                Front Neurol
                Front Neurol
                Front. Neurol.
                Frontiers in Neurology
                Frontiers Media S.A.
                1664-2295
                25 May 2022
                2022
                25 May 2022
                : 13
                : 877772
                Affiliations
                [1] 1Department of Biochemistry, University of Otago , Dunedin, New Zealand
                [2] 2Brain Health Research Centre, University of Otago , Dunedin, New Zealand
                [3] 3School of Biological Sciences, Victoria University of Wellington , Wellington, New Zealand
                [4] 4Graduate School of Health, University of Technology Sydney , Sydney, NSW, Australia
                [5] 5Department of Pathology, University of Otago , Dunedin, New Zealand
                Author notes

                Edited by: Sarah Jane Annesley, La Trobe University, Australia

                Reviewed by: Bindu Diana Paul, Johns Hopkins Medicine, United States; Wakiro Sato, National Center of Neurology and Psychiatry, Japan; Christopher Armstrong, The University of Melbourne, Australia

                *Correspondence: Warren Tate warren.tate@ 123456otago.ac.nz

                This article was submitted to Neuroinfectious Diseases, a section of the journal Frontiers in Neurology

                Article
                10.3389/fneur.2022.877772
                9174654
                35693009
                7868ca64-7341-4405-a0c8-5a9543e1cb2c
                Copyright © 2022 Tate, Walker, Sweetman, Helliwell, Peppercorn, Edgar, Blair and Chatterjee.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 17 February 2022
                : 19 April 2022
                Page count
                Figures: 4, Tables: 1, Equations: 0, References: 121, Pages: 20, Words: 15324
                Categories
                Neurology
                Hypothesis and Theory

                Neurology
                me/cfs,long covid,systemic inflammation,neuroinflammation,disease persistence,relapse
                Neurology
                me/cfs, long covid, systemic inflammation, neuroinflammation, disease persistence, relapse

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