Multiple Sclerosis-related Fatigue: Structural and Functional Changes in the Brain

Massimo De Martinis^*
*Correspondence: Massimo De Martinis, Department of Cardiothoracic Surgery, Tehran New York Presbyterian Hospital, USA, Email:

Introduction

Multiple sclerosis (MS) is a central nervous system autoimmune illness characterised by inflammatory demyelinating demyelinating disease (CNS). According to the Atlas of MS 2013, the global MS population increased from 2.1 million in 2008 to 2.3 million in 2013. Autoreactive immune cells damage CNS neurons' axons and myelin, which is one of MS's pathological hallmarks. This trait creates lesions in the brain and spinal cord, resulting in sensory, motor and cognitive symptoms, as well as autonomic dysfunctions. The cause of MS is still a subject of discussion. The nature of MS appears to be influenced by a complex interaction of environmental and genetic factors.

The average age at the commencement of the condition is between 20 and 40 years. Late-onset (50 years or more) is not uncommon and the neurological symptoms are comparable to those of early-onset. The path to disability, on the other hand, is faster. Relapses are common in the early stages of MS, followed by complete recovery.

Description

Chronic fatigue is one of the most incapacitating symptoms of MS. Fatigue is defined as a subjective feeling of tiredness, an increase in the sense of effort, a mismatch between the effort expended and actual performance, or depletion. Fatigability is another notion that can be used to define weariness objectively. It's vital to remember that fatigue perception and fatigability are not synonymous. Fatigability is the quantity of change in a performance criterion over a specific time of movement task, rather than weariness, which is described as a subject sensation. Fatigue and fatigability are, in fact, not just separate but also possibly independent perceptions. Around 70–80 percent of MS patients report having this symptomatology [1].

Furthermore, for 55 percent of patients, fatigue is the most disabling symptom and it is linked to a lower quality of life. Fatigue can be caused by a variety of factors, both main and secondary. Fatigue is a direct result of the disease and its processes in the first scenario. The peripheral and central immunological and inflammatory processes appear to play a key role in fatigue aggravation, particularly in MS patients Indeed, cytokine levels are important in the progression of MS. Pro-inflammatory cytokines are widely known for causing illness behaviour, decreased desire, increased pain sensitivity, obvious fatigability and depressed mood by acting directly on the brain. They work by disrupting monoaminergic neurotransmission and causing damage to the mesocorticolimbic circuits [2].

Indeed, autonomic nervous system dysfunction appears to play a role in the worsening of fatigue in MS patients. In MS patients, Dinoto et al. discovered a clear link between fatigue and autonomic nervous system impairment. They discovered that patients with fatigue had considerably more dysautonomia than individuals without exhaustion. Indeed, it appears that the same brain areas that control fatigue perception also control the autonomic nervous system. Furthermore, pro-inflammatory cytokines influence the vagus nerve (which connects interoceptive areas to autonomic involvement) and its overactivation links fatigue to autonomic dysregulation.

Traditional sequences, such as FLAIR (fluid attenuated inversion recovery), T2-weighted sequences and gadolinium-enhanced T1-weighted sequences, have been recognised as the most sensitive and repeatable methods of detecting damage due to MS-like plaques, inflammatory activity and LL over the last decade. Non-traditional MR-derived brain imaging metrics have been created in recent years. They can be utilised to quantify important aspects of MS pathophysiology as well as observe the healing pathways. Measures of hypointense T1 lesions, CNS atrophy and MTR are among the metrics used. Indeed, the emergence of automated approaches for analysing structural MRI data, such as VBM or FreeSurfer, allows researchers to explore specific changes in brain architecture that are sometimes undetectable by visual inspection [3].

Axonal loss and localised demyelination are visible in these lesions. In patients with MS, the breakdown of axons in the CNS results in the recruitment of additional nerve fibres or areas in the brain as compared to healthy people. This could increase the fatigue problem. Most investigations investigate the link between the lesion status and the symptom of weariness in patients based on this concept. Several investigations looked at the changes in LL, LV, WM and GM atrophy, normal-appearing white matter (NWMV) and normal-appearing grey matter (NAGM) between F and NF patients (NGMV). The results of all of these researches are difficult to compare because the different outcomes suggest different concepts [4].

It's worth noting that brain volume loss has been linked to disability progression and cognitive impairment in MS patients. The loss of GM volume, rather than the loss of WM volume, is more closely associated with clinical impairment. Cross-sectional and longitudinal MRI techniques have both been used to assess global or regional brain volume. The automated technique: VBM is one of the most commonly used cross-sectional approaches in many investigations. VBM compares the regional volume or concentration of GM and WM between subject groups voxel by voxel [5].

Conclusion

Although evidence implies a link between fatigue and thalamus/ sensorimotor network dysfunction, the wide range of paradigm designs, data gathering methods and analytic methodologies makes it impossible to pinpoint the exact mechanism behind fatigue in MS patients. To better understand the relationship between tiredness and structural/functional changes, more research is required. In addition, because fatigue in MS patients is influenced by other symptoms like depression and pain, as well as pharmacological treatment and autonomic nervous system imbalance, future research should take a multiparametric approach.

Acknowledgement

None.

Conflict of Interest

No potential conflict of interest was reported by the authors.

References

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