Markers for different glial cell responses in multiple sclerosis: clinical and pathological correlations

Disease progression in multiple sclerosis occurs within the interface of glial activation and gliosis. This study aimed to investigate the relationship between biomarkers of different glial cell responses: (i) to disease dynamics and the clinical subtypes of multiple sclerosis; (ii) to disability; and (iii) to cross‐validate these findings in a post‐mortem study. To address the first goal, 51 patients with multiple sclerosis [20 relapsing remitting (RR), 21 secondary progressive (SP) and 10 primary progressive (PP)] and 51 neurological control patients were included. Disability was assessed using the ambulation index (AI), the Expanded Disability Status Scale score (EDSS) and the 9‐hole PEG test (9HPT). Patients underwent lumbar puncture within 7 days of clinical assessment. Post‐mortem brain tissue (12 multiple sclerosis and eight control patients) was classified histologically and adjacent sites were homogenized for protein analysis. S100B, ferritin and glial‐fibrillary acidic protein (GFAP) were quantified in CSF and brain‐tissue homogenate by ELISA (enzyme‐linked immunosorbent assay) techniques developed in‐house. There was a significant trend for increasing S100B levels from PP to SP to RR multiple sclerosis (P 6.5) had significantly higher CSF GFAP levels than less disabled multiple sclerosis or control patients (P < 0.01 and P < 0.001, respectively). There was a correlation between GFAP levels and ambulation in SP multiple sclerosis (r = 0.57, P < 0.01), and between S100B level and the 9HPT in PP multiple sclerosis patients (r = –0.85, P < 0.01). The post‐mortem study showed significantly higher S100B levels in the acute than in the subacute plaques (P < 0.01), whilst ferritin levels were elevated in all multiple sclerosis lesion stages. Both GFAP and S100B levels were significantly higher in the cortex of multiple sclerosis than in control brain homogenate (P < 0.001 and P < 0.05, respectively). We found that S100B is a good marker for the relapsing phase of the disease (confirmed by post‐mortem observation) as opposed to ferritin, which is elevated throughout the entire course. GFAP correlated with disability scales and may therefore be a marker for irreversible damage. The results of this study have broad implications for finding new and sensitive outcome measures for treatment trials that aim to delay the development of disability. They may also be considered in future classifications of multiple sclerosis patients

Seizure-related complication rate in a residential population with epilepsy and intellectual disability (ECOMRAID-trial)

Introduction: The aim of the ECOMRAID trial (Epileptic seizure related Complication RAte in residential population of persons with epilepsy and Intellectual Disability) was to study seizure-related complications (status epilepticus, respiratory complications, or other severe complications) in people with epilepsy and intellectual disability living in a residential setting. The results of the present study are a prerequisite for performing a prospective study into the effectiveness of nocturnal surveillance patients with high risk for Sudden unexpected death in epilepsy (SUDEP).Material and methods: A retrospective study was conducted in three general residential care institutions and one residential specialized epilepsy clinic. In this 5-year cohort, we collected the following data: age (at inclusion and in case of death), sex, type of residential care, different types of complications, rescue/ emergency medication administration, transfers to another department (internal midcare / monitoring unit or general hospital) and a self-designed SUDEP risk score. Our primary research questions were to assess the number of patients who experienced seizure-related complications and their individual complication rates. The secondary research questions were to document the relationship of these complications with the SUDEP risk score, with the type of residential living, and with the frequency of interventions by caregivers.Results: We included 370 patients (1790 patient-years) and in 135 of them, we found 717 seizure-related complications. The following complication rates were found: all complications: at 36%, status epilepticus: at 13%, respiratory complications: at 5%, and other complications at 26%. In residential care institutions, we found fewer patients with complications compared to the specialized epilepsy clinic (all complications 24% vs 42%, OR 0.44, p < 0.01; status epilepticus 5% vs 17%, OR 0.27, p < 0.01; other: complications 19% vs 30%, OR 0.56, p < 0.05). In residential care institutions, we found more "other complications" than in the specialized epilepsy clinic (89% vs 71%, OR 3.13, p < 0.0001). The annual frequency of all complications together was higher in residential care institutions (range 0 to 21 vs 0 to 10, p < 0.05). Rescue medication was given to 75% of the patients, but more often in the specialized epilepsy clinic (median 2.6 vs 0.5 times/patient/year, p < 0.001). In the specialized epilepsy clinic, more patients were transferred to a midcare / monitoring unit or general hospital (56% vs 9%, OR 13.44, p < 0.0001) with higher yearly frequencies (median 0.2 vs 0.0, p < 0.001). There were no reported cases of SUDEP. The median SUDEP risk score was higher in the specialized epilepsy clinic (5 vs 4, p < 0.05) and was weakly correlated with the status epilepticus (q = 0.20, p < 0.001) and (total) complication rate (q = 0.18, p < 0.001).Conclusion: We found seizure-related complications in more than one-third of the patients with epilepsy and intellectual disability living in a residential setting over a period of 5 years. The data also quantify seizure-related complications in patients with epilepsy and intellectual disability.(c) 2022 Published by Elsevier Inc

Ictal autonomic changes as a tool for seizure detection:a systematic review

\u3cp\u3ePurpose: Adequate epileptic seizure detection may have the potential to minimize seizure-related complications and improve treatment evaluation. Autonomic changes often precede ictal electroencephalographic discharges and therefore provide a promising tool for timely seizure detection. We reviewed the literature for seizure detection algorithms using autonomic nervous system parameters. Methods: The PubMed and Embase databases were systematically searched for original human studies that validate an algorithm for automatic seizure detection based on autonomic function alterations. Studies on neonates only and pilot studies without performance data were excluded. Algorithm performance was compared for studies with a similar design (retrospective vs. prospective) reporting both sensitivity and false alarm rate (FAR). Quality assessment was performed using QUADAS-2 and recently reported quality standards on reporting seizure detection algorithms. Results: Twenty-one out of 638 studies were included in the analysis. Fifteen studies presented a single-modality algorithm based on heart rate variability (n = 10), heart rate (n = 4), or QRS morphology (n = 1), while six studies assessed multimodal algorithms using various combinations of HR, corrected QT interval, oxygen saturation, electrodermal activity, and accelerometry. Most studies had small sample sizes and a short follow-up period. Only two studies performed a prospective validation. A tendency for a lower FAR was found for retrospectively validated algorithms using multimodal autonomic parameters compared to those using single modalities (mean sensitivity per participant 71–100% vs. 64–96%, and mean FAR per participant 0.0–2.4/h vs. 0.7–5.4/h). Conclusions: The overall quality of studies on seizure detection using autonomic parameters is low. Unimodal autonomic algorithms cannot reach acceptable performance as false alarm rates are still too high. Larger prospective studies are needed to validate multimodal automatic seizure detection.\u3c/p\u3

Subgroup classification in patients with psychogenic non-epileptic seizures

Introduction In this open non-controlled clinical cohort study, the applicability of a theoretical model for the diagnosis of psychogenic non-epileptic seizures (PNES) was studied in order to define a general psychological profile and to specify possible subgroups. Methods Forty PNES patients were assessed with a PNES "test battery" consisting of eleven psychological instruments, e.g., a trauma checklist, the global cognitive level, mental flexibility, speed of information processing, personality factors, dissociation, daily hassles and stress and coping factors. Results The total PNES group was characterized by multiple trauma, personality vulnerability (in a lesser extent, neuropsychological vulnerabilities), no increased dissociation, many complaints about daily hassles that may trigger seizures and negative coping strategies that may contribute to prolongation of the seizures. Using factor analysis, specific subgroups were revealed: a ‘psychotrauma subgroup’, a ‘high vulnerability somatizing subgroup’ (with high and low cognitive levels) and a ‘high vulnerability sensitive personality problem subgroup’. Conclusion Using a theoretical model in PNES diagnosis, PNES seem to be a symptom of distinct underlying etiological factors with different accents in the model. Hence, describing a general profile seems to conceal specific subgroups with subsequent treatment implications. This study identified three factors, representing two dimensions of the model, that are essential for subgroup classification: psychological etiology (psychotrauma or not), vulnerability, e.g., the somatization tendency, and sensitive personality problems/characteristics (‘novelty seeking’). For treatment, this means that interventions could be tailored to the main underlying etiological problem. Also, further research could focus on differentiating subgroups with subsequent treatment indications and possible different prognoses

A paced visual serial addition test for fMRI

\u3cp\u3eBackground and purpose: The Paced Auditory Serial Attention Task (PASAT) is an attention and information processing task used in patients with diffuse brain disorders, like cerebral trauma and multiple sclerosis (MS). Based on the PASAT we used a adapted version of the test to assess several cognitive functions with fMRI. In this study we investigated the activation pattern on a group and individual level and upon parametric stimulation. Methods: Nine young, healthy, right-handed subjects (mean age 24 years) were studied. The test contrasts an adding-and-memory stage with a control stage in a block design, at two different speeds. Group average maps (random effects analysis, p=0.05) were created to identify the brain areas subserving this task. For each area found active in the group map, the percentage of individuals showing activation in that same anatomical area was calculated. Results: Group activation was localized in the superior and inferior parietal lobe bilaterally, the superior frontal gyrus bilaterally, the left medial frontal gyrus, the left inferior frontal gyrus and adjacent part of the insula, the anterior part of the cingulate gyrus and some cerebellar areas. For the main activated areas, 78-100% of the individual subjects showed activation in that same area. Contrasting the low speed with the high speed condition yielded activation with a considerable individual variation. Conclusion: The group mean activated areas were located mainly in the frontal and parietal lobes and those areas were also activated in the majority of the subjects, indicating limited inter-individual variation, rendering this test suitable for clinical applications in a variety of neurological disorders.\u3c/p\u3

Chronic antiepileptic drug use and functional network efficiency:a functional magnetic resonance imaging study

\u3cp\u3eAIM: To increase our insight in the neuronal mechanisms underlying cognitive side-effects of antiepileptic drug (AED) treatment.\u3c/p\u3e\u3cp\u3eMETHODS: The relation between functional magnetic resonance-acquired brain network measures, AED use, and cognitive function was investigated. Three groups of patients with epilepsy with a different risk profile for developing cognitive side effects were included: A low risk category (lamotrigine or levetiracetam, n = 16), an intermediate risk category (carbamazepine, oxcarbazepine, phenytoin, or valproate, n = 34) and a high risk category (topiramate, n = 5). Brain connectivity was assessed using resting state functional magnetic resonance imaging and graph theoretical network analysis. The Computerized Visual Searching Task was used to measure central information processing speed, a common cognitive side effect of AED treatment.\u3c/p\u3e\u3cp\u3eRESULTS: Central information processing speed was lower in patients taking AEDs from the intermediate and high risk categories, compared with patients from the low risk category. The effect of risk category on global efficiency was significant (P &lt; 0.05, ANCOVA), with a significantly higher global efficiency for patient from the low category compared with the high risk category (P &lt; 0.05, post-hoc test). Risk category had no significant effect on the clustering coefficient (ANCOVA, P &gt; 0.2). Also no significant associations between information processing speed and global efficiency or the clustering coefficient (linear regression analysis, P &gt; 0.15) were observed.\u3c/p\u3e\u3cp\u3eCONCLUSION: Only the four patients taking topiramate show aberrant network measures, suggesting that alterations in functional brain network organization may be only subtle and measureable in patients with more severe cognitive side effects.\u3c/p\u3

Psychogenic nonepileptic seizures in adults with epilepsy and intellectual disability:A neglected area

\u3cp\u3ePURPOSE: To describe the main characteristics of psychogenic nonepileptic seizures (PNES) in adults with epilepsy and intellectual disability (ID), and to analyse the differences regarding psychosocial functioning, epilepsy severity and ID between patients with PNES and a control group without PNES.\u3c/p\u3e\u3cp\u3eMETHODS: Medical records of adults with ID and epilepsy living at an epilepsy care facility (N = 240) were screened for PNES and evaluated by a neurologist. A control group consisting of patients with epilepsy and ID, without PNES, was matched according to age, sex and level of ID. Characteristics of PNES and epilepsy were provided by the subject's nursing staff or retrieved from patient charts, psychosocial data were collected by standardised questionnaires and level of ID was individually assessed using psychometric instruments.\u3c/p\u3e\u3cp\u3eRESULTS: The point prevalence of PNES was 7.1%. The patients with PNES (n = 15) were most often female and had a mild or moderate level of ID. Compared to controls, they showed more depressive symptoms, experienced more negative life events and had more often an ID discrepancy (ID profile with one domain particularly more impaired than another). Stress-related triggers were recognised in a large majority by the nursing staff.\u3c/p\u3e\u3cp\u3eCONCLUSION: PNES appears to be a relatively rare diagnostic entity among inpatients with both epilepsy and ID. However, the complexity of diagnosing PNES in this population, and the similarities in stress-related triggers for PNES in patients with and without ID, suggest that PNES may be underdiagnosed in the ID population. Diagnostic challenges of PNES and, as subcategory, reinforced behavioural patterns are discussed.\u3c/p\u3

Glutamate concentrations vary with antiepileptic drug use and mental slowing

\u3cp\u3eOBJECTIVE: Although antiepileptic drugs (AEDs) are effective in suppressing epileptic seizures, they also induce (cognitive) side effects, with mental slowing as a general effect. This study aimed to assess whether concentrations of MR detectable neurotransmitters, glutamate and GABA, are associated with mental slowing in patients with epilepsy taking AEDs.\u3c/p\u3e\u3cp\u3eMETHODS: Cross-sectional data were collected from patients with localization-related epilepsy using a variety of AEDs from three risk categories, i.e., AEDs with low, intermediate, and high risks of developing cognitive problems. Patients underwent 3T MR spectroscopy, including a PRESS (n=55) and MEGA-PRESS (n=43) sequence, to estimate occipital glutamate and GABA concentrations, respectively. The association was calculated between neurotransmitter concentrations and central information processing speed, which was measured using the Computerized Visual Searching Task (CVST) and compared between the different risk categories.\u3c/p\u3e\u3cp\u3eRESULTS: Combining all groups, patients with lower processing speeds had lower glutamate concentrations. Patients in the high-risk category had a lower glutamate concentration and lower processing speed compared with patients taking low-risk AEDs. Patients taking intermediate-risk AEDs also had a lower glutamate concentration compared with patients taking low-risk AEDs, but processing speed did not differ significantly between those groups. No associations were found between the GABA concentration and risk category or processing speed.\u3c/p\u3e\u3cp\u3eCONCLUSIONS: For the first time, a relation is shown between glutamate concentration and both mental slowing and AED use. It is suggested that the reduced excitatory action, reflected by lowered glutamate concentrations, may have contributed to the slowing of information processing in patients using AEDs with higher risks of cognitive side effects.\u3c/p\u3