Multiple sclerosis and fatigue: A review on the contribution of inflammation and immune-mediated neurodegeneration.

Multiple sclerosis (MS) is an immune mediated disease of the central nervous system (CNS) and the leading cause of non-traumatic disability among young and middle-aged adults in the western world. One of its most prevalent and debilitating symptoms is fatigue. Despite the general acceptance of the idea of an immune pathogenesis of MS itself, the role of autoimmunity in the course of MS-fatigue is a matter of debate. Both immune-related processes (acute inflammation, chronic inflammation, immune-mediated neurodegeneration, immune-mediated alterations of endocrine functions related to fatigue) and presumably non-immune-mediated disturbances and factors (sleep disturbances, depression, cognitive alterations, chronic infections, adverse effects of medications) contribute to the clinical picture. Data from in vitro and animal experiments has provided evidence for a role of cytokines as IL-1 and TNF-alpha. This association could not be verified directly in blood samples from humans whereas whole blood stimulation protocols gave some indirect evidence for a role of cytokines in MS-fatigue. MRI being able to detect acute and chronic immune mediated damage to the CNS could depict that global atrophy of gray or white matter does not correlate with fatigue. Rather, distinctive clusters of lesions and atrophy at different locations, mostly bifrontal or in subcortical structures, correlate specifically with fatigue. Regardless of the difficulties in pinpointing the immunogenesis of MS-fatigue, an important role of autoimmunity is strongly supported by an indirect route: A growing amount of data shows that the highly effective immunotherapeutics which have been introduced to MS-treatment over the last years effectively and sustainably stabilize and ameliorate fatigue in parallel to their dampening effects on the neuroinflammatory process. This review summarizes the existing data on the relation between inflammation, patterns of CNS-lesions and the effects of immunotherapeutics on MS-fatigue.

Clinical and imaging assessment of cognitive dysfunction in multiple sclerosis.

In patients with multiple sclerosis (MS), grey matter damage is widespread and might underlie many of the clinical symptoms, especially cognitive impairment. This relation between grey matter damage and cognitive impairment has been lent support by findings from clinical and MRI studies. However, many aspects of cognitive impairment in patients with MS still need to be characterised. Standardised neuropsychological tests that are easy to administer and sensitive to disease-related abnormalities are needed to gain a better understanding of the factors affecting cognitive performance in patients with MS than exists at present. Imaging measures of the grey matter are necessary, but not sufficient to fully characterise cognitive decline in MS. Imaging measures of both lesioned and normal-appearing white matter lend support to the hypothesis of the existence of an underlying disconnection syndrome that causes clinical symptoms to trigger. Findings on cortical reorganisation support the contribution of brain plasticity and cognitive reserve in limiting cognitive deficits. The development of clinical and imaging biomarkers that can monitor disease development and treatment response is crucial to allow early identification of patients with MS who are at risk of cognitive impairment.

Cerebellar abnormalities contribute to disability including cognitive impairment in multiple sclerosis.

The cerebellum is known to be involved not only in motor but also cognitive and affective processes. Structural changes in the cerebellum in relation to cognitive dysfunction are an emerging topic in the field of neuro-psychiatric disorders. In Multiple Sclerosis (MS) cerebellar motor and cognitive dysfunction occur in parallel, early in the onset of the disease, and the cerebellum is one of the predilection sites of atrophy. This study is aimed at determining the relationship between cerebellar volumes, clinical cerebellar signs, cognitive functioning and fatigue in MS. Cerebellar volumetry was conducted using T1-weighted MPRAGE magnetic resonance imaging of 172 MS patients. All patients underwent a clinical and brief neuropsychological assessment (information processing speed, working memory), including fatigue testing. Patients with and without cerebellar signs differed significantly regarding normalized cerebellar total volume (nTCV), normalized brain volume (nBV) and whole brain T2 lesion volume (LV). Patients with cerebellar dysfunction likewise performed worse in cognitive tests. A regression analysis indicated that age and nTCV explained 26.3% of the variance in SDMT (symbol digit modalities test) performance. However, only age, T2 LV and nBV remained predictors in the full model (r(2) = 0.36). The full model for the prediction of PASAT (Paced Auditory Serial Addition Test) scores (r(2) = 0.23) included age, cerebellar and T2 LV. In the case of fatigue, only age and nBV (r(2) = 0.17) emerged as significant predictors. These data support the view that cerebellar abnormalities contribute to disability, including cognitive impairment in MS. However, this contribution does not seem to be independent of, and may even be dominated by wider spread MS pathology as reflected by nBV and T2 LV.

Evaluation of a new approach for semi-automatic segmentation of the cerebellum in patients with multiple sclerosis.

Cerebellar dysfunction is an important contributor to disability in patients with multiple sclerosis (MS), however, few in vivo studies focused on cerebellar volume loss so far. This relates to technical challenges regarding the segmentation of the cerebellum. In this study, we evaluated the semi-automatic ECCET software for performing cerebellar volumetry using high-resolution 3D T1-MR scans in patients with MS and healthy volunteers. We performed test-retest as well as inter-observer reliability testing of cerebellar segmentation and compared the ECCET results with a fully automatic cerebellar segmentation using the FreeSurfer software pipeline in 15 MS patients. In a pilot matched-pair analysis with another data set from 15 relapsing-remitting MS patients and 15 age- and sex-matched healthy controls (HC), we assessed the feasibility of the ECCET approach to detect MS-related cerebellar volume differences. For total normalized cerebellar volume as well as grey and white matter volumes, intrarater (intraclass correlation coefficient (ICC) = 0.99, 95 % CI = 0.98-0.99) and interobserver agreement (ICC = 0.98, 95 % CI = 0.74-0.99) were strong. Comparison between ECCET and FreeSurfer results likewise yielded a good intraclass correlation (ICC = 0.86, 95 % CI = 0.58-0.95). Compared to HC, MS patients had significantly reduced normalized total brain, total cerebellar, and grey matter volumes (p ≤ 0.05). ECCET is a suitable tool for cerebellar segmentation showing excellent test-retest and inter-observer reliability. Our matched-pair analysis between MS patients and healthy volunteers suggests that the method is sensitive and reliable in detecting cerebellar atrophy in MS.