Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: From Pathophysiological Insights to Novel Therapeutic Opportunities

Abstract:

Myalgic encephalomyelitis (ME) or chronic fatigue syndrome (CFS) is a common and disabling condition with a paucity of effective and evidence-based therapies reflecting a major unmet need. Cognitive behavioural therapy and graded exercise are of modest benefit for only some ME/CFS patients, and many sufferers report aggravation of symptoms of fatigue with exercise.

The presence of a multiplicity of pathophysiological abnormalities, in at least the subgroup of people with ME/CFS diagnosed with the current international consensus “Fukuda” criteria, points to numerous potential therapeutic targets. Such abnormalities include extensive data showing that at least a subgroup has a pro-inflammatory state, increased oxidative and nitrosative stress, disruption of gut mucosal barriers and mitochondrial dysfunction together with dysregulated bioenergetics.

In this paper, these pathways are summarised, and data regarding promising therapeutic options that target these pathways are highlighted; they include coenzyme Q10, melatonin, curcumin, molecular hydrogen and N-acetylcysteine. These data are promising yet preliminary, suggesting hopeful avenues to address this major unmet burden of illness.

Copyright © 2019. Published by Elsevier Ltd.

Source: Morris G, Puri BK, Walker AJ, Maes M, Carvalho AF, Walder K, Mazza C, Berk M. Myalgic Encephalomyelitis/Chronic Fatigue Syndrome: From Pathophysiological Insights to Novel Therapeutic Opportunities. Pharmacol Res. 2019 Sep 8:104450. doi: 10.1016/j.phrs.2019.104450. [Epub ahead of print] https://www.ncbi.nlm.nih.gov/pubmed/31509764

High-fidelity discrete modeling of the HPA axis: a study of regulatory plasticity in biology

Abstract:

BACKGROUND: The hypothalamic-pituitary-adrenal (HPA) axis is a central regulator of stress response and its dysfunction has been associated with a broad range of complex illnesses including Gulf War Illness (GWI) and Chronic Fatigue Syndrome (CFS). Though classical mathematical approaches have been used to model HPA function in isolation, its broad regulatory interactions with immune and central nervous function are such that the biological fidelity of simulations is undermined by the limited availability of reliable parameter estimates.

METHOD: Here we introduce and apply a generalized discrete formalism to recover multiple stable regulatory programs of the HPA axis using little more than connectivity between physiological components. This simple discrete model captures cyclic attractors such as the circadian rhythm by applying generic constraints to a minimal parameter set; this is distinct from Ordinary Differential Equation (ODE) models, which require broad and precise parameter sets. Parameter tuning is accomplished by decomposition of the overall regulatory network into isolated sub-networks that support cyclic attractors. Network behavior is simulated using a novel asynchronous updating scheme that enforces priority with memory within and between physiological compartments.

RESULTS: Consistent with much more complex conventional models of the HPA axis, this parsimonious framework supports two cyclic attractors, governed by higher and lower levels of cortisol respectively. Importantly, results suggest that stress may remodel the stability landscape of this system, favoring migration from one stable circadian cycle to the other. Access to each regime is dependent on HPA axis tone, captured here by the tunable parameters of the multi-valued logic. Likewise, an idealized glucocorticoid receptor blocker alters the regulatory topology such that maintenance of persistently low cortisol levels is rendered unstable, favoring a return to normal circadian oscillation in both cortisol and glucocorticoid receptor expression.

CONCLUSION: These results emphasize the significance of regulatory connectivity alone and how regulatory plasticity may be explored using simple discrete logic and minimal data compared to conventional methods.

Source: Sedghamiz H, Morris M, Craddock TJA, Whitley D, Broderick G. High-fidelity discrete modeling of the HPA axis: a study of regulatory plasticity in biology. BMC Syst Biol. 2018 Jul 17;12(1):76. doi: 10.1186/s12918-018-0599-1. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6050677/ (Full article)

A Comparison of Neuroimaging Abnormalities in Multiple Sclerosis, Major Depression and Chronic Fatigue Syndrome (Myalgic Encephalomyelitis): is There a Common Cause?

Abstract:

There is copious evidence of abnormalities in resting-state functional network connectivity states, grey and white matter pathology and impaired cerebral perfusion in patients afforded a diagnosis of multiple sclerosis, major depression or chronic fatigue syndrome (CFS) (myalgic encephalomyelitis). Systemic inflammation may well be a major element explaining such findings. Inter-patient and inter-illness variations in neuroimaging findings may arise at least in part from regional genetic, epigenetic and environmental variations in the functions of microglia and astrocytes.

Regional differences in neuronal resistance to oxidative and inflammatory insults and in the performance of antioxidant defences in the central nervous system may also play a role. Importantly, replicated experimental findings suggest that the use of high-resolution SPECT imaging may have the capacity to differentiate patients afforded a diagnosis of CFS from those with a diagnosis of depression. Further research involving this form of neuroimaging appears warranted in an attempt to overcome the problem of aetiologically heterogeneous cohorts which probably explain conflicting findings produced by investigative teams active in this field. However, the ionising radiation and relative lack of sensitivity involved probably preclude its use as a routine diagnostic tool.

Source: Morris G, Berk M, Puri BK. A Comparison of Neuroimaging Abnormalities in Multiple Sclerosis, Major Depression and Chronic Fatigue Syndrome (Myalgic Encephalomyelitis): is There a Common Cause? Mol Neurobiol. 2017 May 17. doi: 10.1007/s12035-017-0598-z. https://www.ncbi.nlm.nih.gov/pubmed/28516431