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Noteboom S, Seiler M, Chien C, Rane RP, Barkhof F, Strijbis EMM, Paul F, Schoonheim MM, Ritter K. Evaluation of machine learning-based classification of clinical impairment and prediction of clinical worsening in multiple sclerosis. J Neurol 2024:10.1007/s00415-024-12507-w. [PMID: 38909341 DOI: 10.1007/s00415-024-12507-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/29/2024] [Revised: 06/01/2024] [Accepted: 06/09/2024] [Indexed: 06/24/2024]
Abstract
BACKGROUND Robust predictive models of clinical impairment and worsening in multiple sclerosis (MS) are needed to identify patients at risk and optimize treatment strategies. OBJECTIVE To evaluate whether machine learning (ML) methods can classify clinical impairment and predict worsening in people with MS (pwMS) and, if so, which combination of clinical and magnetic resonance imaging (MRI) features and ML algorithm is optimal. METHODS We used baseline clinical and structural MRI data from two MS cohorts (Berlin: n = 125, Amsterdam: n = 330) to evaluate the capability of five ML models in classifying clinical impairment at baseline and predicting future clinical worsening over a follow-up of 2 and 5 years. Clinical worsening was defined by increases in the Expanded Disability Status Scale (EDSS), Timed 25-Foot Walk Test (T25FW), 9-Hole Peg Test (9HPT), or Symbol Digit Modalities Test (SDMT). Different combinations of clinical and volumetric MRI measures were systematically assessed in predicting clinical outcomes. ML models were evaluated using Monte Carlo cross-validation, area under the curve (AUC), and permutation testing to assess significance. RESULTS The ML models significantly determined clinical impairment at baseline for the Amsterdam cohort, but did not reach significance for predicting clinical worsening over a follow-up of 2 and 5 years. High disability (EDSS ≥ 4) was best determined by a support vector machine (SVM) classifier using clinical and global MRI volumes (AUC = 0.83 ± 0.07, p = 0.015). Impaired cognition (SDMT Z-score ≤ -1.5) was best determined by a SVM using regional MRI volumes (thalamus, ventricles, lesions, and hippocampus), reaching an AUC of 0.73 ± 0.04 (p = 0.008). CONCLUSION ML models could aid in classifying pwMS with clinical impairment and identify relevant biomarkers, but prediction of clinical worsening is an unmet need.
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Affiliation(s)
- Samantha Noteboom
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.
| | - Moritz Seiler
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Claudia Chien
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Experimental and Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Roshan P Rane
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Frederik Barkhof
- MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Centre for Medical Image Computing, Queen Square Institute of Neurology, University College London, London, UK
| | - Eva M M Strijbis
- MS Center Amsterdam, Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Friedemann Paul
- Experimental and Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Menno M Schoonheim
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Kerstin Ritter
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
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Hechenberger S, Helmlinger B, Tinauer C, Jauk E, Ropele S, Heschl B, Wurth S, Damulina A, Eppinger S, Demjaha R, Khalil M, Enzinger C, Pinter D. Evaluation of a self-administered iPad ®-based processing speed assessment for people with multiple sclerosis in a clinical routine setting. J Neurol 2024; 271:3268-3278. [PMID: 38441609 PMCID: PMC11136781 DOI: 10.1007/s00415-024-12274-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 02/21/2024] [Accepted: 02/23/2024] [Indexed: 05/30/2024]
Abstract
BACKGROUND Limited resources often hinder regular cognitive assessment of people with multiple sclerosis (pwMS) in standard clinical care. A self-administered iPad®-based cognitive screening-tool (Processing Speed Test; PST) might mitigate this problem. OBJECTIVE To evaluate the PST in clinical routine. METHODS We investigated the feasibility of the PST in both a quiet and a waiting room setting. We assessed the validity of the PST in comparison with the established Symbol Digit Modalities Test (SDMT). We explored associations between processing speed assessments and the Brief International Cognitive Assessment for MS (BICAMS), magnetic resonance imaging (MRI) parameters, and psychological factors. Additionally, we explored the ability of the PST to detect impairment in processing speed compared to the SDMT. RESULTS The PST was feasible in the waiting room setting. PST and SDMT correlated comparably with the BICAMS, MRI parameters, and psychological variables. Of 172 pwMS, 50 (30.8%) showed cognitive impairment according to the BICAMS; respective values were 47 (27.3%) for the SDMT and 9 (5.2%) for the PST. CONCLUSIONS The PST performed in a waiting room setting correlates strongly with established cognitive tests. It thus may be used to assess processing speed in a resource-efficient manner and complement cognitive assessment in clinical routine. Despite comparable validity of the PST and SDMT, we identified more pwMS with impaired processing speed using normative data of the SDMT compared to the PST and advise caution, that the common cut-off score of - 1.5 SD from the current PST is not appropriate in Europe.
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Affiliation(s)
- Stefanie Hechenberger
- Research Unit for Neuronal Plasticity and Repair, Medical University of Graz, Graz, Austria
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Birgit Helmlinger
- Research Unit for Neuronal Plasticity and Repair, Medical University of Graz, Graz, Austria
- Department of Neurology, Medical University of Graz, Graz, Austria
| | | | - Emanuel Jauk
- Department of Medical Psychology, Psychosomatics, and Psychotherapy, Medical University of Graz, Graz, Austria
- Clinical Psychology and Behavioral Neuroscience, Technische Universität Dresden, Dresden, Germany
| | - Stefan Ropele
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Bettina Heschl
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Sebastian Wurth
- Department of Neurology, Medical University of Graz, Graz, Austria
- Division of Neuroradiology and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Anna Damulina
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Sebastian Eppinger
- Department of Neurology, Medical University of Graz, Graz, Austria
- Division of Neuroradiology and Interventional Radiology, Department of Radiology, Medical University of Graz, Graz, Austria
| | - Rina Demjaha
- Department of Neurology, Medical University of Graz, Graz, Austria
- Neurology Biomarker Research Unit, Medical University of Graz, Graz, Austria
| | - Michael Khalil
- Department of Neurology, Medical University of Graz, Graz, Austria
- Neurology Biomarker Research Unit, Medical University of Graz, Graz, Austria
| | - Christian Enzinger
- Research Unit for Neuronal Plasticity and Repair, Medical University of Graz, Graz, Austria
- Department of Neurology, Medical University of Graz, Graz, Austria
| | - Daniela Pinter
- Research Unit for Neuronal Plasticity and Repair, Medical University of Graz, Graz, Austria.
- Department of Neurology, Medical University of Graz, Graz, Austria.
- Head of Research Unit for Neuronal Plasticity and Repair, Department of Neurology, Medical University of Graz, Auenbruggerplatz 22, 8036, Graz, Austria.
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3
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Komnenić D, Phillips OR, Joshi SH, Chien C, Schmitz-Hübsch T, Asseyer S, Paul F, Finke C. Superficial white matter integrity in neuromyelitis optica spectrum disorder and multiple sclerosis. Mult Scler J Exp Transl Clin 2024; 10:20552173231226107. [PMID: 38269006 PMCID: PMC10807332 DOI: 10.1177/20552173231226107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 12/26/2023] [Indexed: 01/26/2024] Open
Abstract
Background Superficial white matter (SWM) is a particularly vulnerable area of white matter adjacent to cerebral cortex that was shown to be a sensitive marker of disease severity in several neurological and psychiatric disorders, including multiple sclerosis (MS), but has not been studied in neuromyelitis optica spectrum disorder (NMOSD). Objective To compare the integrity of SWM between MS patients, NMOSD patients and healthy controls, and explore the correlation of SWM integrity with cognitive performance and overall disability. Methods Forty NMOSD patients, 48 MS patients and 52 healthy controls were included in the study. Mean diffusivity (MD) values obtained by diffusion tensor imaging were used as a measure of SWM integrity. Cognitive performance and overall disability were assessed with standardized tests. Results Superficial white matter MD was increased in MS patients compared to healthy controls. Higher MD was associated with poorer spatial memory (most prominently in right temporal and right limbic lobe) and poorer information processing speed in MS patients. After adjusting for age, no significant differences of SWM MD were observed between NMOSD patients and healthy controls. Conclusion Integrity of SWM is compromised in MS, but not in NMOSD, and can serve as a sensitive marker of disease severity.
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Affiliation(s)
- Darko Komnenić
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
- Humboldt-Universität zu Berlin, Berlin School of Mind and Brain, Berlin, Germany
| | - Owen Robert Phillips
- Division of Child and Adolescent Psychiatry, Department of Psychiatry, Stanford University School of Medicine, Stanford, CA, USA
| | - Shantanu H Joshi
- Department of Neurology, Department of Bioengineering, University of California Los Angeles, Los Angeles, CA, USA
| | - Claudia Chien
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin & Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Experimental and Clinical Research Center, Berlin, Germany
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NeuroCure Clinical Research Center, Berlin, Germany
- Department of Psychiatry and Neurosciences, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Tanja Schmitz-Hübsch
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin & Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Experimental and Clinical Research Center, Berlin, Germany
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NeuroCure Clinical Research Center, Berlin, Germany
| | - Susanna Asseyer
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin & Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Experimental and Clinical Research Center, Berlin, Germany
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, NeuroCure Clinical Research Center, Berlin, Germany
| | - Friedemann Paul
- Charité–Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin & Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Experimental and Clinical Research Center, Berlin, Germany
- Max Delbrück Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany
- Department of Neurology, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
| | - Carsten Finke
- Humboldt-Universität zu Berlin, Berlin School of Mind and Brain, Berlin, Germany
- Department of Neurology, Charité–Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
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4
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Balloff C, Bandlow C, Bernhard M, Brandenburger T, Bludau P, Elben S, Feldt T, Hartmann CJ, Heinen E, Ingwersen J, Jansen C, Jensen BEO, Kindgen-Milles D, Luedde T, Penner IK, Slink I, Stramm K, Telke AK, Timm J, Vetterkind L, Vollmer C, Wolff G, Schnitzler A, Meuth SG, Groiss SJ, Albrecht P. Prevalence and prognostic value of neurological affections in hospitalized patients with moderate to severe COVID-19 based on objective assessments. Sci Rep 2023; 13:19619. [PMID: 37949882 PMCID: PMC10638293 DOI: 10.1038/s41598-023-46124-w] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2023] [Accepted: 10/27/2023] [Indexed: 11/12/2023] Open
Abstract
Neurological manifestations of coronavirus disease 2019 (COVID-19) have been frequently described. In this prospective study of hospitalized COVID-19 patients without a history of neurological conditions, we aimed to analyze their prevalence and prognostic value based on established, standardized and objective methods. Patients were investigated using a multimodal electrophysiological approach, accompanied by neuropsychological and neurological examinations. Prevalence rates of central (CNS) and peripheral (PNS) nervous system affections were calculated and the relationship between neurological affections and mortality was analyzed using Firth logistic regression models. 184 patients without a history of neurological diseases could be enrolled. High rates of PNS affections were observed (66% of 138 patients receiving electrophysiological PNS examination). CNS affections were less common but still highly prevalent (33% of 139 examined patients). 63% of patients who underwent neuropsychological testing (n = 155) presented cognitive impairment. Logistic regression models revealed pathology in somatosensory evoked potentials as an independent risk factor of mortality (Odds Ratio: 6.10 [1.01-65.13], p = 0.049). We conclude that hospitalized patients with moderate to severe COVID-19 display high rates of PNS and CNS affection, which can be objectively assessed by electrophysiological examination. Electrophysiological assessment may have a prognostic value and could thus be helpful to identify patients at risk for deterioration.
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Affiliation(s)
- Carolin Balloff
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
- Department of Neurology, Kliniken Maria Hilf GmbH, 41063, Moenchengladbach, Germany
| | - Carolina Bandlow
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Michael Bernhard
- Emergency Department, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Timo Brandenburger
- Department of Anesthesiology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Patricia Bludau
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Saskia Elben
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Torsten Feldt
- Department of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Christian J Hartmann
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Elisa Heinen
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Jens Ingwersen
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Corinna Jansen
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Björn-Erik O Jensen
- Department of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Detlef Kindgen-Milles
- Department of Anesthesiology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Tom Luedde
- Department of Gastroenterology, Hepatology and Infectious Diseases, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Iris-Katharina Penner
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, 3010, Bern, Switzerland
| | - Isabel Slink
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Kim Stramm
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Ann-Kathrin Telke
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Jörg Timm
- Department of Virology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Lana Vetterkind
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Christian Vollmer
- Department of Anesthesiology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Georg Wolff
- Department of Cardiology, Pulmonology, and Vascular Medicine, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Alfons Schnitzler
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Sven G Meuth
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
| | - Stefan J Groiss
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
- Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany
- Neurocenter Duesseldorf, 40211, Duesseldorf, Germany
| | - Philipp Albrecht
- Department of Neurology, Medical Faculty, Heinrich-Heine-University, 40225, Duesseldorf, Germany.
- Department of Neurology, Kliniken Maria Hilf GmbH, 41063, Moenchengladbach, Germany.
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Renner A, Bätge SJ, Filser M, Lau S, Pöttgen J, Penner IK. Non-pharmacological randomized intervention trial for the management of neuropsychological symptoms in outpatients with progressive multiple sclerosis. APPLIED NEUROPSYCHOLOGY. ADULT 2023:1-13. [PMID: 37652158 DOI: 10.1080/23279095.2023.2233648] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/02/2023]
Abstract
PURPOSE Despite typically more pronounced cognitive and mental health issues in progressive disease courses of multiple sclerosis (PMS), rehabilitation research in this subgroup is rare. The efficacy of two non-pharmacological interventions with positive results from prior investigations was therefore examined in PMS specifically. METHODS Persons with PMS (pwPMS) received either computerized cognitive training (BrainStim), standardized cognitive-behavioral group sessions (Metacognitive Training [MaTiMS]), or a combination of both in an ambulatory setting. Neuropsychological assessment was conducted before and after the four-week intervention. RESULTS 37 participants (13 with primary/24 with secondary PMS, meanage = 52.87, SDage = 7.11, meanEDSS = 4.02, SDEDSS = 1.35) entered analyses. The BrainStim group improved in immediate and delayed verbal memory, recognition, verbal working memory, and perceived cognitive deficits while experiencing increased anxiety post-intervention. MaTiMS participants reported high program satisfaction and less cognitive difficulties at retest. The Combination group performed better in immediate and delayed verbal memory, and in information processing speed after training. Descriptive data further indicated positive effects on anxiety and depression in the MaTiMS and Combination group. CONCLUSIONS While objective cognitive performance improved when explicitly trained, psychoeducative sessions contributed to subjective mental health. The combination of both approaches is thus suggested, considering the specific needs of pwPMS treated in an ambulatory setting.
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Affiliation(s)
- Alina Renner
- Cogito Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany
| | - Sharon Jean Bätge
- Cogito Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany
| | - Melanie Filser
- Cogito Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany
| | - Stephanie Lau
- Institute of Neuroimmunology and Multiple Sclerosis (INIMS), Center for Molecular Neurobiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Jana Pöttgen
- Institute of Neuroimmunology and Multiple Sclerosis (INIMS), Center for Molecular Neurobiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
- Department of Neurology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Iris-Katharina Penner
- Cogito Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany
- Department of Neurology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
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Maier PM, Iggena D, Meyer T, Finke C, Ploner CJ. Memory-guided navigation in amyotrophic lateral sclerosis. J Neurol 2023:10.1007/s00415-023-11753-8. [PMID: 37154895 DOI: 10.1007/s00415-023-11753-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 04/28/2023] [Accepted: 04/29/2023] [Indexed: 05/10/2023]
Abstract
BACKGROUND Previous studies have yielded inconsistent results about hippocampal involvement in non-demented patients with amyotrophic lateral sclerosis (ALS). We hypothesized that testing of memory-guided spatial navigation i.e., a highly hippocampus-dependent behaviour, might reveal behavioural correlates of hippocampal dysfunction in non-demented ALS patients. METHODS We conducted a prospective study of spatial cognition in 43 non-demented ALS outpatients (11f, 32 m, mean age 60.0 years, mean disease duration 27.0 months, mean ALSFRS-R score 40.0) and 43 healthy controls (14f, 29 m, mean age 57.0 years). Participants were tested with a virtual memory-guided navigation task derived from animal research ("starmaze") that has previously been used in studies of hippocampal function. Participants were further tested with neuropsychological tests of visuospatial memory (SPART, 10/36 Spatial Recall Test), fluency (5PT, five-point test) and orientation (PTSOT, Perspective Taking/Spatial Orientation Test). RESULTS Patients successfully learned and navigated the starmaze from memory, both in conditions that forced memory of landmarks (success: patients 50.7%, controls 47.7%, p = 0.786) and memory of path sequences (success: patients 96.5%, controls 94.0%, p = 0.937). Measures of navigational efficacy (latency, path error and navigational uncertainty) did not differ between groups (p ≥ 0.546). Likewise, SPART, 5PT and PTSOT scores did not differ between groups (p ≥ 0.238). CONCLUSIONS This study found no behavioural correlate for hippocampal dysfunction in non-demented ALS patients. These findings support the view that the individual cognitive phenotype of ALS may relate to distinct disease subtypes rather than being a variable expression of the same underlying condition.
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Affiliation(s)
- Patrizia M Maier
- Department of Neurology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Faculty of Philosophy, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Deetje Iggena
- Department of Neurology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Faculty of Philosophy, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Thomas Meyer
- Department of Neurology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
| | - Carsten Finke
- Department of Neurology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany
- Faculty of Philosophy, Berlin School of Mind and Brain, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Christoph J Ploner
- Department of Neurology, Charité - Universitätsmedizin Berlin, Augustenburger Platz 1, 13353, Berlin, Germany.
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7
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Hümmert MW, Stern C, Paul F, Duchow A, Bellmann-Strobl J, Ayzenberg I, Schwake C, Kleiter I, Hellwig K, Jarius S, Wildemann B, Senel M, Berthele A, Giglhuber K, Luessi F, Grothe M, Klotz L, Schülke R, Gingele S, Faiss JH, Walter A, Warnke C, Then Bergh F, Aktas O, Ringelstein M, Stellmann JP, Häußler V, Havla J, Pellkofer H, Kümpfel T, Kopp B, Trebst C. Cognition in patients with neuromyelitis optica spectrum disorders: A prospective multicentre study of 217 patients (CogniNMO-Study). Mult Scler 2023:13524585231151212. [PMID: 36786424 DOI: 10.1177/13524585231151212] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/15/2023]
Abstract
BACKGROUND There is limited and inconsistent information on the prevalence of cognitive impairment in neuromyelitis optica spectrum disorders (NMOSD). OBJECTIVE To assess cognitive performance and changes over time in NMOSD. METHODS This study included data from 217 aquaporin-4-IgG-seropositive (80%) and double-seronegative NMOSD patients. Cognitive functions measured by Symbol Digit Modalities Test (SDMT), Paced Auditory Serial-Addition Task (PASAT), and/or Multiple Sclerosis Inventory Cognition (MuSIC) were standardized against normative data (N = 157). Intraindividual cognitive performance at 1- and 2-year follow-up was analyzed. Cognitive test scores were correlated with demographic and clinical variables and assessed with a multiple linear regression model. RESULTS NMOSD patients were impaired in SDMT (p = 0.007), MuSIC semantic fluency (p < 0.001), and MuSIC congruent speed (p < 0.001). No significant cognitive deterioration was found at follow-up. SDMT scores were related to motor and visual disability (pBon < 0.05). No differences were found between aquaporin-4-IgG-seropositive and double-seronegative NMOSD. CONCLUSIONS A subset of NMOSD patients shows impairment in visual processing speed and in semantic fluency regardless of serostatus, without noticeable changes during a 2-year observation period. Neuropsychological measurements should be adapted to physical and visual disabilities.
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Affiliation(s)
- Martin W Hümmert
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Carlotta Stern
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Friedemann Paul
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, and Max Delbrück Center for Molecular Medicine, Berlin, Germany/Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany/ Department of Neurology, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Ankelien Duchow
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, and Max Delbrück Center for Molecular Medicine, Berlin, Germany/Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Judith Bellmann-Strobl
- NeuroCure Clinical Research Center, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin Institute of Health, and Max Delbrück Center for Molecular Medicine, Berlin, Germany/Experimental and Clinical Research Center, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
| | - Ilya Ayzenberg
- Department of Neurology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Carolin Schwake
- Department of Neurology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Ingo Kleiter
- Department of Neurology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany/Marianne-Strauß-Klinik, Behandlungszentrum Kempfenhausen für Multiple Sklerose Kranke, Berg, Germany
| | - Kerstin Hellwig
- Department of Neurology, St. Josef Hospital, Ruhr University Bochum, Bochum, Germany
| | - Sven Jarius
- Molecular Neuroimmunology Group, Department of Neurology, University of Heidelberg, Heidelberg, Germany
| | - Brigitte Wildemann
- Molecular Neuroimmunology Group, Department of Neurology, University of Heidelberg, Heidelberg, Germany
| | - Makbule Senel
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Achim Berthele
- Department of Neurology, School of Medicine, Technical University Munich, Klinikum rechts der Isar, Munich, Germany
| | - Katrin Giglhuber
- Department of Neurology, School of Medicine, Technical University Munich, Klinikum rechts der Isar, Munich, Germany
| | - Felix Luessi
- Department of Neurology, University Medical Center, Johannes Gutenberg University of Mainz, Mainz, Germany
| | - Matthias Grothe
- Department of Neurology, University Medicine of Greifswald, Greifswald, Germany
| | - Luisa Klotz
- Department of Neurology, University of Münster, Münster, Germany
| | - Rasmus Schülke
- Department of Psychiatry, Social Psychiatry and Psychotherapy, Hannover Medical School, Hannover, Germany
| | - Stefan Gingele
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Jürgen H Faiss
- Department of Neurology, Asklepios Expert Clinic Teupitz, Teupitz, Germany
| | - Annette Walter
- Department of Neurology, Herford Hospital, Herford, Germany
| | - Clemens Warnke
- Department of Neurology, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
| | | | - Orhan Aktas
- Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Marius Ringelstein
- Department of Neurology, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany/Department of Neurology, Center for Neurology and Neuropsychiatry, LVR-Klinikum, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Jan-Patrick Stellmann
- Department of Neurology and Institute of Neuroimmunology and Multiple Sclerosis (INIMS), University Medical Center Hamburg-Eppendorf, Hamburg, Germany/Aix-Marseille Univ, CNRS, CRMBM, UMR 7339, Marseille, France/APHM, Hopital de la Timone, CEMEREM, Marseille, France
| | - Vivien Häußler
- Department of Neurology and Institute of Neuroimmunology and Multiple Sclerosis (INIMS), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - Joachim Havla
- Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany/Data Integration for Future Medicine Consortium, LMU Hospital, Ludwig-Maximilians Universität München, Munich, Germany
| | - Hannah Pellkofer
- Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Tania Kümpfel
- Institute of Clinical Neuroimmunology, LMU Hospital, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Bruno Kopp
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Corinna Trebst
- Department of Neurology, Hannover Medical School, Hannover, Germany.,Department of Neurology, Hannover Medical School, Carl-Neuberg-Str. 1, Hannover 30625, Germany
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Grothe M, Jochem K, Strauss S, Langner S, Kirsch M, Hoffeld K, Penner IK, Nagels G, Klepzig K, Domin M, Lotze M. Performance in information processing speed is associated with parietal white matter tract integrity in multiple sclerosis. Front Neurol 2022; 13:982964. [DOI: 10.3389/fneur.2022.982964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 09/20/2022] [Indexed: 11/06/2022] Open
Abstract
BackgroundThe Symbol Digit Modalities Test (SDMT) is most frequently used to test processing speed in patients with multiple sclerosis (MS). Functional imaging studies emphasize the importance of frontal and parietal areas for task performance, but the influence of frontoparietal tracts has not been thoroughly studied. We were interested in tract-specific characteristics and their association with processing speed in MS patients.MethodsDiffusion tensor imaging was obtained in 100 MS patients and 24 healthy matched controls to compare seed-based tract characteristics descending from the superior parietal lobule [Brodman area 7A (BA7A)], atlas-based tract characteristics from the superior longitudinal fasciculus (SLF), and control tract characteristics from the corticospinal tract (CST) and their respective association with ability on the SDMT.ResultsPatients had decreased performance on the SDMT and decreased white matter volume (each p < 0.05). The mean fractional anisotropy (FA) for the BA7A tract and CST (p < 0.05), but not the SLF, differed between MS patients and controls. Furthermore, only the FA of the SLF was positively associated with SDMT performance even after exclusion of the lesions within the tract (r = 0.25, p < 0.05). However, only disease disability and total white matter volume were associated with information processing speed in a linear regression model.ConclusionsProcessing speed in MS is associated with the structural integrity of frontoparietal white matter tracts.
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9
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Brummer T, Muthuraman M, Steffen F, Uphaus T, Minch L, Person M, Zipp F, Groppa S, Bittner S, Fleischer V. Improved prediction of early cognitive impairment in multiple sclerosis combining blood and imaging biomarkers. Brain Commun 2022; 4:fcac153. [PMID: 35813883 PMCID: PMC9263885 DOI: 10.1093/braincomms/fcac153] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 02/28/2022] [Accepted: 06/17/2022] [Indexed: 12/30/2022] Open
Abstract
Disability in multiple sclerosis is generally classified by sensory and motor symptoms, yet cognitive impairment has been identified as a frequent manifestation already in the early disease stages. Imaging- and more recently blood-based biomarkers have become increasingly important for understanding cognitive decline associated with multiple sclerosis. Thus, we sought to determine the prognostic utility of serum neurofilament light chain levels alone and in combination with MRI markers by examining their ability to predict cognitive impairment in early multiple sclerosis. A comprehensive and detailed assessment of 152 early multiple sclerosis patients (Expanded Disability Status Scale: 1.3 ± 1.2, mean age: 33.0 ± 10.0 years) was performed, which included serum neurofilament light chain measurement, MRI markers (i.e. T2-hyperintense lesion volume and grey matter volume) acquisition and completion of a set of cognitive tests (Symbol Digits Modalities Test, Paced Auditory Serial Addition Test, Verbal Learning and Memory Test) and mood questionnaires (Hospital Anxiety and Depression scale, Fatigue Scale for Motor and Cognitive Functions). Support vector regression, a branch of unsupervised machine learning, was applied to test serum neurofilament light chain and combination models of biomarkers for the prediction of neuropsychological test performance. The support vector regression results were validated in a replication cohort of 101 early multiple sclerosis patients (Expanded Disability Status Scale: 1.1 ± 1.2, mean age: 34.4 ± 10.6 years). Higher serum neurofilament light chain levels were associated with worse Symbol Digits Modalities Test scores after adjusting for age, sex Expanded Disability Status Scale, disease duration and disease-modifying therapy (B = −0.561; SE = 0.192; P = 0.004; 95% CI = −0.940 to −0.182). Besides this association, serum neurofilament light chain levels were not linked to any other cognitive or mood measures (all P-values > 0.05). The tripartite combination of serum neurofilament light chain levels, lesion volume and grey matter volume showed a cross-validated accuracy of 88.7% (90.8% in the replication cohort) in predicting Symbol Digits Modalities Test performance in the support vector regression approach, and outperformed each single biomarker (accuracy range: 68.6–75.6% and 68.9–77.8% in the replication cohort), as well as the dual biomarker combinations (accuracy range: 71.8–82.3% and 72.6–85.6% in the replication cohort). Taken together, early neuro-axonal loss reflects worse information processing speed, the key deficit underlying cognitive dysfunction in multiple sclerosis. Our findings demonstrate that combining blood and imaging measures improves the accuracy of predicting cognitive impairment, highlighting the clinical utility of cross-modal biomarkers in multiple sclerosis.
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Affiliation(s)
- Tobias Brummer
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz , Langenbeckstr, 1, Mainz 55131 , Germany
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz , Langenbeckstr, 1, Mainz 55131 , Germany
| | - Falk Steffen
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz , Langenbeckstr, 1, Mainz 55131 , Germany
| | - Timo Uphaus
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz , Langenbeckstr, 1, Mainz 55131 , Germany
| | - Lena Minch
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz , Langenbeckstr, 1, Mainz 55131 , Germany
| | - Maren Person
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz , Langenbeckstr, 1, Mainz 55131 , Germany
| | - Frauke Zipp
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz , Langenbeckstr, 1, Mainz 55131 , Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz , Langenbeckstr, 1, Mainz 55131 , Germany
| | - Stefan Bittner
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz , Langenbeckstr, 1, Mainz 55131 , Germany
| | - Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN) and Immunotherapy (FZI), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz , Langenbeckstr, 1, Mainz 55131 , Germany
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10
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Balloff C, Penner IK, Ma M, Georgiades I, Scala L, Troullinakis N, Graf J, Kremer D, Aktas O, Hartung HP, Meuth SG, Schnitzler A, Groiss SJ, Albrecht P. The degree of cortical plasticity correlates with cognitive performance in patients with Multiple Sclerosis. Brain Stimul 2022; 15:403-413. [PMID: 35182811 DOI: 10.1016/j.brs.2022.02.007] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 02/14/2022] [Accepted: 02/14/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Cortical reorganization and plasticity may compensate for structural damage in Multiple Sclerosis (MS). It is important to establish sensitive methods to measure these compensatory mechanisms, as they may be of prognostic value. OBJECTIVE To investigate the association between the degree of cortical plasticity and cognitive performance and to compare plasticity between MS patients and healthy controls (HCs). METHODS The amplitudes of the motor evoked potential (MEP) pre and post quadripulse stimulation (QPS) applied over the contralateral motor cortex served as measure of the degree of cortical plasticity in 63 patients with relapsing-remitting MS (RRMS) and 55 matched HCs. The main outcomes were the correlation coefficients between the difference of MEP amplitudes post and pre QPS and the Symbol Digit Modalities Test (SDMT) and Brief Visuospatial Memory Test-Revised (BVMT-R), and the QPSxgroup interaction in a mixed model predicting the MEP amplitude. RESULTS SDMT and BVMT-R correlated significantly with QPS-induced cortical plasticity in RRMS patients. Plasticity was significantly reduced in patients with cognitive impairment compared to patients with preserved cognitive function and the degree of plasticity differentiated between both patient groups. Interestingly, the overall RRMS patient cohort did not show reduced plasticity compared to HCs. CONCLUSIONS We provide first evidence that QPS-induced plasticity may inform about the global synaptic plasticity in RRMS which correlates with cognitive performance as well as clinical disability. Larger longitudinal studies on patients with MS are needed to investigate the relevance and prognostic value of this measure for disease progression and recovery.
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Affiliation(s)
- Carolin Balloff
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
| | - Iris-Katharina Penner
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany; Cogito Center for Applied Neurocognition and Neuropsychological Research, 40225, Düsseldorf, Germany; Department of Neurology, Inselspital, University Hospital Bern, 3010, Bern, Switzerland
| | - Meng Ma
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
| | - Iason Georgiades
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
| | - Lina Scala
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
| | - Nina Troullinakis
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
| | - Jonas Graf
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
| | - David Kremer
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
| | - Orhan Aktas
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
| | - Hans-Peter Hartung
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany; Brain and Mind Center, University of Sydney, NSW, 2006, Australia; Department of Neurology, Medical University of Vienna, 1090, Vienna, Austria
| | - Sven Günther Meuth
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
| | - Alfons Schnitzler
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
| | - Stefan Jun Groiss
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany; Institute of Clinical Neuroscience and Medical Psychology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany.
| | - Philipp Albrecht
- Department of Neurology, Medical Faculty, Heinrich-Heine University, 40225, Duesseldorf, Germany
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11
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Hechenberger S, Helmlinger B, Ropele S, Pirpamer L, Bachmaier G, Damulina A, Pichler A, Khalil M, Enzinger C, Pinter D. Information processing speed as a prognostic marker of physical impairment and progression in patients with multiple sclerosis. Mult Scler Relat Disord 2022; 57:103353. [PMID: 35158430 DOI: 10.1016/j.msard.2021.103353] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 10/22/2021] [Accepted: 10/25/2021] [Indexed: 12/30/2022]
Abstract
BACKGROUND Prediction of disability progression in patients with MS (pwMS) is challenging. So far, scarce evidence exists suggesting knowledge about how cognitive performance may potentially improve prediction of physical impairment and disability progression in MS. Therefore, we wanted to assess the prognostic value of cognitive performance regarding physical impairment and disability progression in pwMS. METHODS 85 patients (64% female; 60% relapse-remitting MS; mean age=36.78 ± 9.63 years) underwent clinical, neuropsychological (Brief Repeatable Battery for Neuropsychological Test (BRB-N)) and brain MRI (T1-weighted and T2-weighted FLAIR images) assessment at baseline and after an average of 7 years (SD=3.75) at follow-up. We assessed physical impairment and annualized disability progression (disability progression divided by follow-up duration) using the Expanded Disability Status Scale (EDSS). To compare patients with no or mild physical impairment (EDSS≤2.5) and patients with moderate to severe physical impairment (EDSS≥3.0), we used an EDSS score ≥3.0 as cut-off. Silent progression was defined by an EDSS worsening of at least 0.5 in the absence of relapses and inflammation in relapsing-remitting MS. RESULTS In hierarchical regression models (method "STEPWISE", forward) performance in information processing speed was a significant and independent predictor of physical impairment (EDSS≥3.0) at follow-up (model R²=0.671, b=-1.46, OR=0.23, p=0.001) and annualized disability progression (adjusted model R²=0.257, β=-0.26, 95% CI: -0.066, -0.008, p=0.012), in addition to demographics (age, education, individual follow-up time), clinical (EDSS, disease duration, clinical phenotype, annualized-relapse-rate) and MRI measures (brain volumes and T2-lesion load). In a MANCOVA controlled for age, disease duration and individual follow-up time, worse baseline performance in information processing speed was found in patients with higher EDSS at follow-up (m=-1.91, SD=1.18, p<0.001) and silent progression (m=-2.19, SD=1.01, p=0.038). CONCLUSION Performance in information processing speed might help to identify patients at risk for physical impairment. Therefore, neuropsychological assessment should be integrated in clinical standard care to support disease management in pwMS.
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Affiliation(s)
- Stefanie Hechenberger
- Medical University of Graz, Department of Neurology, Research Unit for Neuronal Plasticity and Repair, Graz, Austria
| | - Birgit Helmlinger
- Medical University of Graz, Department of Neurology, Research Unit for Neuronal Plasticity and Repair, Graz, Austria
| | - Stefan Ropele
- Medical University of Graz, Department of Neurology, Graz, Austria
| | - Lukas Pirpamer
- Medical University of Graz, Department of Neurology, Graz, Austria
| | - Gerhard Bachmaier
- Medical University of Graz, Institute for Medical Informatics, Statistics and Documentation, Graz, Austria
| | - Anna Damulina
- Medical University of Graz, Department of Neurology, Graz, Austria
| | | | - Michael Khalil
- Medical University of Graz, Department of Neurology, Graz, Austria
| | - Christian Enzinger
- Medical University of Graz, Department of Neurology, Research Unit for Neuronal Plasticity and Repair, Graz, Austria; Medical University of Graz, Department of Neurology, Graz, Austria; Medical University of Graz, Division of Neuroradiology, Vascular And Interventional Radiology, Department of Radiology, Graz, Austria
| | - Daniela Pinter
- Medical University of Graz, Department of Neurology, Research Unit for Neuronal Plasticity and Repair, Graz, Austria.
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12
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Rivera D, Usuga DR, Mendoza EMF, Arelis AA, Barajas BVR, Islas MÁM, Krch D, Lequerica AH, Arango-Lasprilla JC. Validation of the Norma Latina neuropsychological assessment battery in individuals with multiple sclerosis in Mexico. Mult Scler Relat Disord 2022; 59:103685. [DOI: 10.1016/j.msard.2022.103685] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Revised: 01/23/2022] [Accepted: 02/11/2022] [Indexed: 10/19/2022]
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13
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Ciolac D, Gonzalez-Escamilla G, Radetz A, Fleischer V, Person M, Johnen A, Landmeyer NC, Krämer J, Muthuraman M, Meuth SG, Groppa S. Sex-specific signatures of intrinsic hippocampal networks and regional integrity underlying cognitive status in multiple sclerosis. Brain Commun 2021; 3:fcab198. [PMID: 34514402 PMCID: PMC8417841 DOI: 10.1093/braincomms/fcab198] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/27/2021] [Accepted: 07/15/2021] [Indexed: 11/24/2022] Open
Abstract
The hippocampus is an anatomically compartmentalized structure embedded in highly wired networks that are essential for cognitive functions. The hippocampal vulnerability has been postulated in acute and chronic neuroinflammation in multiple sclerosis, while the patterns of occurring inflammation, neurodegeneration or compensation have not yet been described. Besides focal damage to hippocampal tissue, network disruption is an important contributor to cognitive decline in multiple sclerosis patients. We postulate sex-specific trajectories in hippocampal network reorganization and regional integrity and address their relationship to markers of neuroinflammation, cognitive/memory performance and clinical severity. In a large cohort of multiple sclerosis patients (n = 476; 337 females, age 35 ± 10 years, disease duration 16 ± 14 months) and healthy subjects (n = 110, 54 females; age 34 ± 15 years), we utilized MRI at baseline and at 2-year follow-up to quantify regional hippocampal volumetry and reconstruct single-subject hippocampal networks. Through graph analytical tools we assessed the clustered topology of the hippocampal networks. Mixed-effects analyses served to model sex-based differences in hippocampal network and subfield integrity between multiple sclerosis patients and healthy subjects at both time points and longitudinally. Afterwards, hippocampal network and subfield integrity were related to clinical and radiological variables in dependency of sex attribution. We found a more clustered network architecture in both female and male patients compared to their healthy counterparts. At both time points, female patients displayed a more clustered network topology in comparison to male patients. Over time, multiple sclerosis patients developed an even more clustered network architecture, though with a greater magnitude in females. We detected reduced regional volumes in most of the addressed hippocampal subfields in both female and male patients compared to healthy subjects. Compared to male patients, females displayed lower volumes of para- and presubiculum but higher volumes of the molecular layer. Longitudinally, volumetric alterations were more pronounced in female patients, which showed a more extensive regional tissue loss. Despite a comparable cognitive/memory performance between female and male patients over the follow-up period, we identified a strong interrelation between hippocampal network properties and cognitive/memory performance only in female patients. Our findings evidence a more clustered hippocampal network topology in female patients with a more extensive subfield volume loss over time. A stronger relation between cognitive/memory performance and the network topology in female patients suggests greater entrainment of the brain’s reserve. These results may serve to adapt sex-targeted neuropsychological interventions.
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Affiliation(s)
- Dumitru Ciolac
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany.,Department of Neurology, Institute of Emergency Medicine, Chisinau 2004, Moldova.,Laboratory of Neurobiology and Medical Genetics, Nicolae Testemitanu State University of Medicine and Pharmacy, Chisinau 2004, Moldova
| | - Gabriel Gonzalez-Escamilla
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Angela Radetz
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Vinzenz Fleischer
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Maren Person
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Andreas Johnen
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, Münster 48149, Germany
| | - Nils C Landmeyer
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, Münster 48149, Germany
| | - Julia Krämer
- Department of Neurology with Institute of Translational Neurology, University Hospital of Münster, Münster 48149, Germany
| | - Muthuraman Muthuraman
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
| | - Sven G Meuth
- Department of Neurology, Heinrich Heine University, Düsseldorf 40225, Germany
| | - Sergiu Groppa
- Department of Neurology, Focus Program Translational Neuroscience (FTN), Rhine-Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz 55131, Germany
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14
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Sousa C, Rigueiro-Neves M, Passos AM, Ferreira A, Sá MJ. Assessment of cognitive functions in patients with multiple sclerosis applying the normative values of the Rao's brief repeatable battery in the Portuguese population. BMC Neurol 2021; 21:170. [PMID: 33882847 PMCID: PMC8059237 DOI: 10.1186/s12883-021-02193-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 03/23/2021] [Indexed: 11/18/2022] Open
Abstract
Background The Brief Repeatable Battery of Neuropsychological Tests (BRBN-T) is one of the most sensitive and used measures for detecting cognitive impairment in Multiple Sclerosis (MS). Objective The aim of this study was to adapt and validate this battery to the Portuguese population of MS patients. Methods The Portuguese version of the BRBN-T was applied to a stratified control national sample of 326 individuals considering sex, age, educational level and geographic location and also a clinical sample of 115 MS patients from several national hospitals. Through the exploration of its psychometrics properties, the Portuguese BRBN-T norms were produced. Results The normative data is presented as a regression-based formula to adjust test scores for gender, education and age, and the results reveal the BRBN-T has the ability to differentiate between MS patients and healthy participant’s cognitive performance. Conclusion This study demonstrated in our clinical population a good ability to detect cognitive impairment. Its clearly contributed to reinforcing the neuropsychological assessment in Portugal in patients with MS, by providing a new set of instruments, which can be used in the clinical practice, and in future studies. Moreover, it will allow a rigorous and precise support in relation to neuropsychological assessment for future longitudinal studies and clinical trials.
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Affiliation(s)
- Claudia Sousa
- MS Clinic, Department of Neurology, Centro Hospitalar Universitário São João Porto, Alameda Prof. Hernâni Monteiro, Porto, Portugal. .,Neuropsychological Unit, Department of Psychology, Centro Hospitalar Universitário São João Porto, Alameda Prof. Hernâni Monteiro, 4200 - 319, Porto, Portugal.
| | | | | | - Aristides Ferreira
- BRU-IUL, Instituto Universitário de Lisboa (ISCTE-IUL), Lisbon, Portugal
| | - Maria José Sá
- MS Clinic, Department of Neurology, Centro Hospitalar Universitário São João Porto, Alameda Prof. Hernâni Monteiro, Porto, Portugal.,Faculty of Health Sciences, University Fernando Pessoa, Porto, Portugal
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15
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Grothe M, Opolka M, Berneiser J, Dressel A. Testing social cognition in multiple sclerosis: Difference between emotion recognition and theory of mind and its influence on quality of life. Brain Behav 2021; 11:e01925. [PMID: 33135386 PMCID: PMC7821581 DOI: 10.1002/brb3.1925] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 10/02/2020] [Accepted: 10/11/2020] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Deficits in social cognition can occur in multiple sclerosis (MS) patients, and different methods are utilized for its assessment. The aim of this study was to compare two tests of social cognition in a cohort of multiple sclerosis patients with respect to other clinical variables. Additionally, the impact of social cognition on quality of life was investigated. METHODS In total, 50 patients were included in the study. Two tests of social cognition, emotion recognition and theory of mind, were performed and controlled for disease disability, depression, fatigue, and cognition in a multiple linear regression. Assessment of quality of life was also conducted. RESULTS Accuracy on emotion recognition was better compared to theory of mind (86.5 ± 9.5% and 63.6 ± 10.1%, respectively). Cognition was associated with both social cognition tasks, accounting for more variance in the emotion recognition task. Quality of life was not related to social cognition. CONCLUSION Studies on social cognition in MS have to keep in mind the higher degree of cognitive influence of emotion recognition compared to theory of mind.
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Affiliation(s)
- Matthias Grothe
- Department of Neurology, University Medicine of Greifswald, Greifswald, Germany
| | - Michael Opolka
- Department of Neurology, University Medicine of Greifswald, Greifswald, Germany
| | - Julia Berneiser
- Department of Neurology, University Medicine of Greifswald, Greifswald, Germany
| | - Alexander Dressel
- Department of Neurology, University Medicine of Greifswald, Greifswald, Germany.,Department of Neurology, Carl-Thiem-Hospital Cottbus, Cottbus, Germany
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16
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Chavarro VS, Bellmann-Strobl J, Zimmermann HG, Scheel M, Chien C, Oertel FC, Weygandt M, Ruprecht K, Paul F, Finke C, Brandt AU. Visual system damage and network maladaptation are associated with cognitive performance in neuromyelitis optica spectrum disorders. Mult Scler Relat Disord 2020; 45:102406. [DOI: 10.1016/j.msard.2020.102406] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2020] [Revised: 07/07/2020] [Accepted: 07/15/2020] [Indexed: 11/16/2022]
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Landmeyer NC, Dzionsko I, Brockhoff L, Wiendl H, Domes G, Bölte J, Krämer J, Meuth SG, Johnen A. The Agony of Choice? Preserved Affective Decision Making in Early Multiple Sclerosis. Front Neurol 2020; 11:914. [PMID: 32982932 PMCID: PMC7492612 DOI: 10.3389/fneur.2020.00914] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2020] [Accepted: 07/16/2020] [Indexed: 11/13/2022] Open
Abstract
Background: Cognitive impairment (CI) is an early and frequent symptom of multiple sclerosis (MS). Likewise, affective symptoms (e.g., depression and anxiety) and alterations in the processing of emotional stimuli have been frequently reported. Thus, abilities that integrate affective and cognitive processes such as decision making (DM) based on affective feedback are potentially valuable early diagnostic markers for MS. The available research on this topic, however, is still inconclusive and suffers from methodological issues. Methods: We compared DM ability in a clinically homogeneous cohort of 24 patients with early relapsing-remitting MS (RRMS) and 59 age-matched healthy controls (HCs). A modified version of the Iowa gambling task (IGT) allowed us to control for individual differences in search strategies during the risk exploration phase. Besides standard IGT measures (netscore, obtained play money, and learning index), we also examined reaction times and post-error slowing (PES) patterns as a proxy for abnormalities in the processing of affective feedback. Results: The performance of patients did not significantly deviate from HCs in any standard parameter of the modified IGT. Furthermore, although RRMS patients reacted significantly slower than HCs overall, we found similar patterns of PES in both groups, suggesting similarly efficient processing of affective feedback. Conclusion: We conclude that there is no specific deficit in affective feedback processing in early RRMS. Previous findings of IGT impairments in this patient group may thus not represent a genuine deficit in affective DM but rather be related to sample characteristics, general CI, and/or differences in individual search strategies. Future research should explore the potential influence of lesion volumes and locations on DM ability by employing brain imaging techniques.
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Affiliation(s)
- Nils C Landmeyer
- Department of Neurology With Institute of Translational Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany
| | - Inga Dzionsko
- Department of Neurology With Institute of Translational Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany.,Department of Biological and Clinical Psychology, University of Trier, Trier, Germany
| | - Laura Brockhoff
- Department of Neurology With Institute of Translational Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany.,Department of Psychology, Westfälische-Wilhelms-University Münster, Münster, Germany
| | - Heinz Wiendl
- Department of Neurology With Institute of Translational Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany
| | - Gregor Domes
- Department of Biological and Clinical Psychology, University of Trier, Trier, Germany
| | - Jens Bölte
- Department of Psychology, Westfälische-Wilhelms-University Münster, Münster, Germany
| | - Julia Krämer
- Department of Neurology With Institute of Translational Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany
| | - Sven G Meuth
- Department of Neurology With Institute of Translational Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany
| | - Andreas Johnen
- Department of Neurology With Institute of Translational Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany
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18
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Engel S, Graetz C, Salmen A, Muthuraman M, Toenges G, Ambrosius B, Bayas A, Berthele A, Heesen C, Klotz L, Kümpfel T, Linker RA, Meuth SG, Paul F, Stangel M, Tackenberg B, Then Bergh F, Tumani H, Weber F, Wildemann B, Zettl UK, Antony G, Bittner S, Groppa S, Hemmer B, Wiendl H, Gold R, Zipp F, Lill CM, Luessi F. Is APOE ε4 associated with cognitive performance in early MS? NEUROLOGY-NEUROIMMUNOLOGY & NEUROINFLAMMATION 2020; 7:7/4/e728. [PMID: 32358224 PMCID: PMC7217661 DOI: 10.1212/nxi.0000000000000728] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/14/2019] [Accepted: 03/27/2020] [Indexed: 01/01/2023]
Abstract
Objective To assess the impact of APOE polymorphisms on cognitive performance in patients newly diagnosed with clinically isolated syndrome (CIS) or relapsing-remitting MS (RRMS). Methods This multicenter cohort study included 552 untreated patients recently diagnosed with CIS or RRMS according to the 2005 revised McDonald criteria. The single nucleotide polymorphisms rs429358 (ε4) and rs7412 (ε2) of the APOE haplotype were assessed by allelic discrimination assays. Cognitive performance was evaluated using the 3-second paced auditory serial addition test and the Multiple Sclerosis Inventory Cognition (MUSIC). Sum scores were calculated to approximate the overall cognitive performance and memory-centered cognitive functions. The impact of the APOE carrier status on cognitive performance was assessed using multiple linear regression models, also including demographic, clinical, MRI, and lifestyle factors. Results APOE ε4 homozygosity was associated with lower overall cognitive performance, whereas no relevant association was observed for APOE ε4 heterozygosity or APOE ε2 carrier status. Furthermore, higher disability levels, MRI lesion load, and depressive symptoms were associated with lower cognitive performance. Patients consuming alcohol had higher test scores than patients not consuming alcohol. Female sex, lower disability, and alcohol consumption were associated with better performance in the memory-centered subtests of MUSIC, whereas no relevant association was observed for APOE carrier status. Conclusion Along with parameters of a higher disease burden, APOE ε4 homozygosity was identified as a potential predictor of cognitive performance in this large cohort of patients with CIS and early RRMS.
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Affiliation(s)
- Sinah Engel
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Christiane Graetz
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Anke Salmen
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Muthuraman Muthuraman
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Gerrit Toenges
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Björn Ambrosius
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Antonios Bayas
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Achim Berthele
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Christoph Heesen
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Luisa Klotz
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Tania Kümpfel
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Ralf A Linker
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Sven G Meuth
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Friedemann Paul
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Martin Stangel
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Björn Tackenberg
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Florian Then Bergh
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Hayrettin Tumani
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Frank Weber
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Brigitte Wildemann
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Uwe K Zettl
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Gisela Antony
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Stefan Bittner
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Sergiu Groppa
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Bernhard Hemmer
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Heinz Wiendl
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Ralf Gold
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Frauke Zipp
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Christina M Lill
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany
| | - Felix Luessi
- From the Department of Neurology and Focus Program Translational Neuroscience (FTN) (S.E., C.G., M.M., S.B., S.G., F.Z., C.M.L., F.L.), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Germany; Department of Neurology (A.S.), Inselspital, Bern University Hospital, University of Bern, Switzerland; Department of Neurology (A.S., B.A., R.G.), St. Josef-Hospital, Ruhr-University Bochum; Institute of Medical Biostatistics (G.T.), Epidemiology and Informatics (IMBEI), University Medical Center of the Johannes Gutenberg University Mainz; Department of Neurology (A. Bayas), Klinikum Augsburg; Department of Neurology (A. Berthele, B.H.), Klinikum rechts der Isar, Technical University of Munich; Institut für Neuroimmunologie und Multiple Sklerose (C.H.), Universitätsklinikum Hamburg-Eppendorf; Clinic of Neurology (L.K., S.G.M., H.W.), University Hospital Münster, Westphalian-Wilhelms-University Münster; Institute of Clinical Neuroimmunology (T.K.), Ludwig Maximilian University of Munich; Department of Neurology (R.A.L.), University Hospital Erlangen; NeuroCure Clinical Research Center and Experimental and Clinical Research Center (F.P.), Charité - Universitätsmedizin Berlin and Max Delbrueck Center for Molecular Medicine; Department of Neurology (M.S.), Hannover Medical School; Department of Neurology (B.T.), Philipps-University Marburg; Department of Neurology (F.T.B.), University of Leipzig; Department of Neurology (H.T.), University of Ulm; Clinic of Neurology Dietenbronn (H.T.), Schwendi; Neurology (F.W.), Max-Planck-Institute of Psychiatry, Munich; Neurological Clinic (F.W.), Sana Kliniken des Landkreises Cham; Department of Neurology (B.W.), University of Heidelberg; Department. of Neurology (U.K.Z.), University of Rostock; Central Information Office (CIO) (G.A.), Philipps-University Marburg; and Genetic and Molecular Epidemiology Group (C.M.L.), Lübeck Interdisciplinary Platform for Genome Analytics, Institutes of Neurogenetics and Cardiogenetics, University of Lübeck, Germany.
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Hälbig TD, Wüstenberg T, Giess RM, Kunte H, Bellmann-Strobl J, Ruprecht K, Paul F. Emotional experience in patients with clinically isolated syndrome and early multiple sclerosis. Eur J Neurol 2020; 27:1537-1545. [PMID: 32307769 DOI: 10.1111/ene.14269] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2019] [Accepted: 04/02/2020] [Indexed: 01/07/2023]
Abstract
BACKGROUND AND PURPOSE Evidence suggests that there are changes in the processing of emotional information (EP) in people with multiple sclerosis (MS). It is unclear which functional domains of EP are affected, whether these changes are secondary to other MS-related neuropsychological or psychiatric symptoms and if EP changes are present in early MS. The aim of the study was to investigate EP in patients with early MS (clinically isolated syndrome and early relapsing/remitting MS) and healthy controls (HCs). METHODS A total of 29 patients without neuropsychological or psychiatric deficits and 29 matched HCs were presented with pictures from the International Affective Picture System with negative, positive or neutral content. Participants rated the induced emotion regarding valence and arousal using nine-level Likert scales. A speeded recognition test assessed memory for the emotional stimuli and for the emotional modulation of response time. A subgroup of participants was tested during a magnetic resonance imaging (MRI) session. RESULTS Patients in the MRI subgroup rated the experience induced by pictures with positive or negative emotional content significantly more weakly than HCs. Further, these patients were significantly less aroused when watching the pictures from the International Affective Picture System. There were no effects in the non-MRI subgroup or effects on emotional memory or response times. CONCLUSIONS Emotional processing changes may be present in early MS in the form of flattened emotional experience on both the valence and arousal dimensions. These changes do not appear to be secondary to neuropsychological or psychiatric deficits. The fact that emotional flattening was only found in the MRI setting suggests that EP changes may be unmasked within stressful environments and points to the potential yet underestimated impact of the MRI setting on behavioral outcomes.
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Affiliation(s)
- T D Hälbig
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - T Wüstenberg
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - R M Giess
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - H Kunte
- Faculty of Natural Sciences, MSB, Medical School Berlin, Berlin, Germany
| | - J Bellmann-Strobl
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - K Ruprecht
- Department of Neurology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - F Paul
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany.,Experimental and Clinical Research Center, Max Delbrueck Center for Molecular Medicine and Charité - Universitätsmedizin Berlin, Berlin, Germany
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20
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Renner A, Baetge SJ, Filser M, Ullrich S, Lassek C, Penner I. Characterizing cognitive deficits and potential predictors in multiple sclerosis: A large nationwide study applying Brief International Cognitive Assessment for Multiple Sclerosis in standard clinical care. J Neuropsychol 2020; 14:347-369. [DOI: 10.1111/jnp.12202] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2019] [Revised: 01/10/2020] [Indexed: 01/21/2023]
Affiliation(s)
- Alina Renner
- Cogito Center for Applied Neurocognition and Neuropsychological Research Düsseldorf Germany
| | - Sharon J. Baetge
- Cogito Center for Applied Neurocognition and Neuropsychological Research Düsseldorf Germany
| | - Melanie Filser
- Cogito Center for Applied Neurocognition and Neuropsychological Research Düsseldorf Germany
| | | | | | - Iris‐Katharina Penner
- Cogito Center for Applied Neurocognition and Neuropsychological Research Düsseldorf Germany
- Department of Neurology Medical Faculty Heinrich‐Heine University Düsseldorf Düsseldorf Germany
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21
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Bogdanova MD, Mikadze YV, Bembeeva RT, Volkova EY. [Methodological issues of cognitive impairment studies in pediatric multiple sclerosis patients]. Zh Nevrol Psikhiatr Im S S Korsakova 2020; 119:105-111. [PMID: 31626226 DOI: 10.17116/jnevro2019119091105] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The article provides a review of the characteristics of cognitive impairment in multiple sclerosis (MS) and methods for its assessment in children. The features of the most frequently used neuropsychological batteries, with consideration of specifics of cognitive impairment in MS, and data on assessment of a state of cognitive functions obtained using neuropsychological tests are presented. The authors also discuss the issue of a long-term impact of the disease on a state of cognitive functions. Clinical factors, which can lead to cognitive impairment (type of multiple sclerosis, age at manifestation, number of relapses), are described.
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Affiliation(s)
- M D Bogdanova
- Lomonosov Moscow State University, Moscow, Russia; Sechenov First Moscow State Medical University, Moscow, Russia
| | - Yu V Mikadze
- Lomonosov Moscow State University, Moscow, Russia; Pirogov Russian National Research Medical University, Moscow, Russia
| | - R Ts Bembeeva
- Pirogov Russian National Research Medical University, Moscow, Russia
| | - E Yu Volkova
- Russian Pediatric Clinical Hospital, Pirogov Russian National Research Medical University, Moscow, Russia
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22
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Ehling R, Amprosi M, Kremmel B, Bsteh G, Eberharter K, Zehentner M, Steiger R, Tuovinen N, Gizewski ER, Benke T, Berger T, Spöttl C, Brenneis C, Scherfler C. Second language learning induces grey matter volume increase in people with multiple sclerosis. PLoS One 2019; 14:e0226525. [PMID: 31869402 PMCID: PMC6927643 DOI: 10.1371/journal.pone.0226525] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2019] [Accepted: 11/29/2019] [Indexed: 11/25/2022] Open
Abstract
Background Grey matter volume (GMV) decline is a frequent finding in multiple sclerosis (MS), the most common chronic neurological disease in young adults. Increases of GMV were detected in language related brain regions following second language (L2) learning in healthy adults. Effects of L2 learning in people with MS (pwMS) have not been investigated so far. Methods This study prospectively evaluated the potential of an eight-week L2 training on grey matter plasticity measured by 3T-MRI, L2 proficiency and health-related quality of life (HRQoL) in people with relapsing-remitting MS (pwMS, n = 11) and healthy, sex- and age-matched controls (HCs; n = 12). Results Categorical voxel-based analysis revealed significantly less GMV bilaterally of the insula extending to the temporal pole in pwMS at baseline. Following L2 training, significant increases of GMV were evident in the right hippocampus, parahippocampus and putamen of pwMS and in the left insula of HCs. L2 training resulted in significant improvements of listening comprehension, speaking fluency and vocabulary knowledge in both pwMS and HCs. GMV increases of right hippocampus and parahippocampus significantly correlated with vocabulary knowledge gain and L2 learning was associated with a significant increase of HRQoL in pwMS. Conclusion Our findings demonstrate distinct patterns of GMV increases of language related brain regions in pwMS and HCs and indicate disease-related compensatory cortical and subcortical plasticity to acquire L2 proficiency in pwMS.
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Affiliation(s)
- Rainer Ehling
- Department of Neurology, Clinic for Rehabilitation Münster, Münster, Austria
- Karl Landsteiner Institut für Interdisziplinäre Forschung am Reha Zentrum Münster, Münster, Austria
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
- * E-mail:
| | - Matthias Amprosi
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Benjamin Kremmel
- Language Testing Research Group Innsbruck, Department for Subject Specific Education, University of Innsbruck, Innsbruck, Austria
| | - Gabriel Bsteh
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Kathrin Eberharter
- Language Testing Research Group Innsbruck, Department for Subject Specific Education, University of Innsbruck, Innsbruck, Austria
| | - Matthias Zehentner
- Language Testing Research Group Innsbruck, Department for Subject Specific Education, University of Innsbruck, Innsbruck, Austria
| | - Ruth Steiger
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria
- Neuroimaging Research Core Facility, Medical University Innsbruck, Innsbruck, Austria
| | - Noora Tuovinen
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Elke R. Gizewski
- Department of Neuroradiology, Medical University of Innsbruck, Innsbruck, Austria
- Neuroimaging Research Core Facility, Medical University Innsbruck, Innsbruck, Austria
| | - Thomas Benke
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Thomas Berger
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Carol Spöttl
- Language Testing Research Group Innsbruck, Department for Subject Specific Education, University of Innsbruck, Innsbruck, Austria
| | - Christian Brenneis
- Department of Neurology, Clinic for Rehabilitation Münster, Münster, Austria
- Karl Landsteiner Institut für Interdisziplinäre Forschung am Reha Zentrum Münster, Münster, Austria
| | - Christoph Scherfler
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
- Neuroimaging Research Core Facility, Medical University Innsbruck, Innsbruck, Austria
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Baetge SJ, Filser M, Renner A, Ullrich S, Lassek C, Penner IK. On the validity of single tests, two-test combinations and the full Brief International Cognitive Assessment for Multiple Sclerosis (BICAMS) in detecting patients with cognitive impairment. Mult Scler 2019; 26:1919-1928. [DOI: 10.1177/1352458519887897] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background: The international standard to screen for cognitive impairment in multiple sclerosis (MS) is BICAMS (Brief International Cognitive Assessment for MS). However, with an application time of approximately 20 minutes, the battery might be too time consuming from a pragmatic perspective of a routine examination. Objectives: To examine the relative sensitivity and specificity of a BICAMS short version and its validity compared to the total battery. Methods: The German BICAMS version was applied comprising the Symbol Digit Modalities Test (SDMT), the Brief Visuospatial Memory Test–Revised (BVMT-R) and the Rey Auditory Verbal Learning Test (RAVLT; German VLMT). Single tests and two-test combinations were compared regarding conformity with the total battery. Results: Examining 1320 MS patients, the two-test combination of SDMT-BVMT-R was the most sensitive (92.7%) to impairment and showed the strongest agreement with the total battery (κ = 0.95). Performing binary logistic regression analyses, this combination was also validated by its association with employment status. Conclusion: Application of the total BICAMS battery should be the goal to strive for. However, in time-restricted clinical settings, the combined application of SDMT and BVMT-R is a recommendable alternative with an application time of 10 minutes, while single tests alone are not sufficiently sensitive.
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Affiliation(s)
- Sharon Jean Baetge
- COGITO Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany
| | - Melanie Filser
- COGITO Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany
| | - Alina Renner
- COGITO Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany
| | | | | | - Iris-Katharina Penner
- COGITO Center for Applied Neurocognition and Neuropsychological Research, Düsseldorf, Germany/Department of Neurology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany
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Kober SE, Pinter D, Enzinger C, Damulina A, Duckstein H, Fuchs S, Neuper C, Wood G. Self-regulation of brain activity and its effect on cognitive function in patients with multiple sclerosis - First insights from an interventional study using neurofeedback. Clin Neurophysiol 2019; 130:2124-2131. [PMID: 31546180 DOI: 10.1016/j.clinph.2019.08.025] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Revised: 07/26/2019] [Accepted: 08/19/2019] [Indexed: 11/15/2022]
Abstract
OBJECTIVE To investigate the effects of EEG-based neurofeedback training, in which one can learn to self-regulate one's own brain activity, on cognitive function in patients with multiple sclerosis (pwMS). METHODS Fourteen pwMS performed ten neurofeedback training sessions within 3-4 weeks at home using a tele-rehabilitation system. The aim of the neurofeedback training was to increase voluntarily the sensorimotor rhythm (SMR, 12-15 Hz) in the EEG over central brain areas by receiving visual real-time feedback thereof. Cognitive function was assessed before and after all neurofeedback training sessions using a comprehensive standardized neuropsychological test battery. RESULTS Half of the pwMS (N = 7) showed cognitive improvements in long-term memory and executive functions after neurofeedback training. These patients successfully learned to self-regulate their own brain activity by means of neurofeedback training. The other half of pwMS (N = 7) did neither show any cognitive changes when comparing the pre- and post-assessment nor were they able to modulate their own brain activity in the desired direction during neurofeedback training. CONCLUSIONS Data from this interventional study provide first preliminary evidence that successful self-regulation of one's own brain activity may be associated with cognitive improvements in pwMS. SIGNIFICANCE These promising results should stimulate further studies. Neurofeedback might be a promising and alternative tool for future cognitive rehabilitation.
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Affiliation(s)
- Silvia Erika Kober
- University of Graz, Institute of Psychology, Graz, Austria; BioTechMed-Graz, Graz, Austria.
| | - Daniela Pinter
- Medical University of Graz, Department of Neurology, Graz, Austria.
| | - Christian Enzinger
- Medical University of Graz, Department of Neurology, Graz, Austria; Medical University of Graz, Division of Neuroradiology, Vascular and Interventional Radiology, Department of Radiology, Graz, Austria.
| | - Anna Damulina
- Medical University of Graz, Department of Neurology, Graz, Austria.
| | | | - Siegrid Fuchs
- Medical University of Graz, Department of Neurology, Graz, Austria.
| | - Christa Neuper
- University of Graz, Institute of Psychology, Graz, Austria; BioTechMed-Graz, Graz, Austria; Graz University of Technology, Laboratory of Brain-Computer Interfaces, Institute of Neural Engineering, Graz, Austria.
| | - Guilherme Wood
- University of Graz, Institute of Psychology, Graz, Austria; BioTechMed-Graz, Graz, Austria.
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Keune PM, Hansen S, Sauder T, Jaruszowic S, Kehm C, Keune J, Weber E, Schönenberg M, Oschmann P. Frontal brain activity and cognitive processing speed in multiple sclerosis: An exploration of EEG neurofeedback training. NEUROIMAGE-CLINICAL 2019; 22:101716. [PMID: 30798167 PMCID: PMC6384325 DOI: 10.1016/j.nicl.2019.101716] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Revised: 01/22/2019] [Accepted: 02/10/2019] [Indexed: 12/20/2022]
Abstract
Background Cognitive deficits including impaired information processing speed as assessed by the Symbol Digit Modalities Test (SDMT) are common in multiple sclerosis (MS). Oscillatory markers of processing speed may be extracted from magnetoencephalographic (MEG) and electroencephalographic (EEG) resting-state recordings. In this context, an increased proportion of frontal slow-wave (theta, 4–8 Hz) to fast-wave (beta, 13–30 Hz) EEG activity was indicative of impaired SDMT performance. Such an increased theta/beta ratio may reflect oscillatory slowing associated with deficits in attention control. Therapeutic approaches that consider atypical oscillatory activity in MS remain sparse. Objectives In a cross-sectional design, we examined the relation between SDMT performance, the EEG theta/beta ratio and its components. We also explored longitudinally, whether EEG neurofeedback could be used to induce a putatively adaptive alteration in these EEG parameters, toward a pattern indicative of improved processing speed. Methods N = 58 MS patients (RRMS/SPMS/PPMS N: 18/35/3, 2 cases excluded) participated in a neuropsychological examination and a resting-state EEG recording. Subsequently, N = 10 patients received neurofeedback training for two weeks in a hospitalized setting. The purpose was to reduce the frontal theta/beta ratio through operant conditioning. Results In the cross-sectional examination, patients with slow SDMT speed displayed an increased theta/beta ratio, relative to those with normal speed. This involved increased frontal theta power, whereas beta power was equal across groups. The theta/beta ratio remained stable during neurofeedback across sessions of the two-week training period. In an exploratory secondary analysis, within sessions a reduction in the theta/beta ratio during active training blocks relative pre/post session resting-states was observed, driven by reduced theta power. Conclusions These findings provide support for utilizing frontal EEG theta activity as an inverse marker of processing speed in MS. Across sessions, there was no support for successful operant conditioning of the theta/beta ratio during the two-week training period. The observed state-specific shift within sessions, involving a transient reduction in theta activity, nevertheless may provide a rationale for a further investigation of neurofeedback as a treatment approach in MS. Frontal EEG slow-wave/fast-wave activity (theta/beta ratio) was increased in MS patients with slow cognitive processing speed The association involved a significant increase in theta activity, while beta did not vary with processing speed The frontal theta/beta ratio remained stable across sessions during a neurofeedback intervention Within sessions the theta/beta ratio was reduced during active training, relative to rest, driven by reduced theta activity Frontal theta may be a marker of processing speed and a further exploration of neurofeedback training may be feasible in MS
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Affiliation(s)
- Philipp M Keune
- Department of Neurology, Klinikum Bayreuth GmbH, Bayreuth, Germany; Department of Physiological Psychology, University of Bamberg, Germany.
| | - Sascha Hansen
- Department of Neurology, Klinikum Bayreuth GmbH, Bayreuth, Germany; Department of Physiological Psychology, University of Bamberg, Germany
| | - Torsten Sauder
- Department of Neurology, Klinikum Bayreuth GmbH, Bayreuth, Germany
| | - Sonja Jaruszowic
- Department of Neurology, Klinikum Bayreuth GmbH, Bayreuth, Germany; Department of Physiological Psychology, University of Bamberg, Germany
| | - Christina Kehm
- Department of Physiological Psychology, University of Bamberg, Germany
| | - Jana Keune
- Department of Neurology, Klinikum Bayreuth GmbH, Bayreuth, Germany
| | - Emily Weber
- Department of Neurology, Klinikum Bayreuth GmbH, Bayreuth, Germany
| | | | - Patrick Oschmann
- Department of Neurology, Klinikum Bayreuth GmbH, Bayreuth, Germany
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Johnen A, Bürkner PC, Landmeyer NC, Ambrosius B, Calabrese P, Motte J, Hessler N, Antony G, König IR, Klotz L, Hoshi MM, Aly L, Groppa S, Luessi F, Paul F, Tackenberg B, Bergh FT, Kümpfel T, Tumani H, Stangel M, Weber F, Bayas A, Wildemann B, Heesen C, Zettl UK, Zipp F, Hemmer B, Meuth SG, Gold R, Wiendl H, Salmen A. Can we predict cognitive decline after initial diagnosis of multiple sclerosis? Results from the German National early MS cohort (KKNMS). J Neurol 2018; 266:386-397. [PMID: 30515631 PMCID: PMC6373354 DOI: 10.1007/s00415-018-9142-y] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2018] [Revised: 11/14/2018] [Accepted: 11/26/2018] [Indexed: 02/05/2023]
Abstract
BACKGROUND Cognitive impairment (CI) affects approximately one-third of the patients with early multiple sclerosis (MS) and clinically isolated syndrome (CIS). Little is known about factors predicting CI and progression after initial diagnosis. METHODS Neuropsychological screening data from baseline and 1-year follow-up of a prospective multicenter cohort study (NationMS) involving 1123 patients with newly diagnosed MS or CIS were analyzed. Employing linear multilevel models, we investigated whether demographic, clinical and conventional MRI markers at baseline were predictive for CI and longitudinal cognitive changes. RESULTS At baseline, 22% of patients had CI (impairment in ≥2 cognitive domains) with highest frequencies and severity in processing speed and executive functions. Demographics (fewer years of academic education, higher age, male sex), clinical (EDSS, depressive symptoms) but no conventional MRI characteristics were linked to baseline CI. At follow-up, only 14% of patients showed CI suggesting effects of retesting. Neither baseline characteristics nor initiation of treatment between baseline and follow-up was able to predict cognitive changes within the follow-up period of 1 year. CONCLUSIONS Identification of risk factors for short-term cognitive change in newly diagnosed MS or CIS is insufficient using only demographic, clinical and conventional MRI data. Change-sensitive, re-test reliable cognitive tests and more sophisticated predictors need to be employed in future clinical trials and cohort studies of early-stage MS to improve prediction.
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Affiliation(s)
- Andreas Johnen
- Department of Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany.
| | - Paul-Christian Bürkner
- Department of Statistics, Faculty of Psychology, Westfälische-Wilhelms-University, Münster, Germany
| | - Nils C Landmeyer
- Department of Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany
| | - Björn Ambrosius
- Department of Neurology, St. Josef-Hospital, Ruhr-University Bochum, Bochum, Germany
| | - Pasquale Calabrese
- Department of Neuropsychology and Behavioral Neurology, University of Basel, Basel, Switzerland
| | - Jeremias Motte
- Department of Neurology, St. Josef-Hospital, Ruhr-University Bochum, Bochum, Germany
| | - Nicole Hessler
- Institute of Medical Biometry and Statistics, University of Lübeck, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Gisela Antony
- Central Information Office (CIO), Philipps-University Marburg, Marburg, Germany
| | - Inke R König
- Institute of Medical Biometry and Statistics, University of Lübeck, University Hospital Schleswig-Holstein, Campus Lübeck, Lübeck, Germany
| | - Luisa Klotz
- Department of Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany
| | - Muna-Miriam Hoshi
- Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Lilian Aly
- Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Sergiu Groppa
- Department of Neurology and Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Felix Luessi
- Department of Neurology and Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Friedemann Paul
- NeuroCure Clinical Research Center and Experimental and Clinical Research Center, Charité, University Medicine Berlin and Max Delbrueck Center for Molecular Medicine, Berlin, Germany
| | - Björn Tackenberg
- Department of Neurology, Philipps-University Marburg, Marburg, Germany
| | | | - Tania Kümpfel
- Institute of Clinical Neuroimmunology, Ludwig Maximilian University of Munich, Munich, Germany
| | - Hayrettin Tumani
- Department of Neurology, University of Ulm, Ulm, Germany
- Clinic of Neurology Dietenbronn, Schwendi, Germany
| | - Martin Stangel
- Department of Neurology, Hannover Medical School, Hannover, Germany
| | - Frank Weber
- Neurology, Max-Planck-Institute of Psychiatry, Munich, Germany
- Neurological Clinic, Sana Kliniken des Landkreises Cham, Cham, Germany
| | - Antonios Bayas
- Department of Neurology, Klinikum Augsburg, Augsburg, Germany
| | | | - Christoph Heesen
- Institut für Neuroimmunologie und Multiple Sklerose, Universitätsklinikum Hamburg-Eppendorf, Hamburg, Germany
| | - Uwe K Zettl
- Department of Neurology, Neuroimmunological Section, University of Rostock, Rostock, Germany
| | - Frauke Zipp
- Department of Neurology and Focus Program Translational Neuroscience (FTN), Rhine Main Neuroscience Network (rmn2), University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Bernhard Hemmer
- Department of Neurology, Klinikum rechts der Isar, Technical University of Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Sven G Meuth
- Department of Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany
| | - Ralf Gold
- Department of Neurology, St. Josef-Hospital, Ruhr-University Bochum, Bochum, Germany
| | - Heinz Wiendl
- Department of Neurology, University Hospital Münster, Westfälische-Wilhelms-University Münster, Münster, Germany
| | - Anke Salmen
- Department of Neurology, St. Josef-Hospital, Ruhr-University Bochum, Bochum, Germany
- Department of Neurology, Inselspital Bern, Bern University Hospital and University of Bern, Bern, Switzerland
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Cognitive impairment and quality of life of people with epilepsy and neurocysticercosis in Zambia. Epilepsy Behav 2018; 80:354-359. [PMID: 29221763 DOI: 10.1016/j.yebeh.2017.10.042] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/04/2017] [Revised: 10/29/2017] [Accepted: 10/29/2017] [Indexed: 12/17/2022]
Abstract
Cognitive impairment and quality of life (Qol) are important to assess the burden of epilepsy and neurocysticercosis (NCC), which are common but neglected in Sub-Saharan Africa (SSA). The aims of this study were to assess cognitive performance and Qol of people with epilepsy (PWE) in Zambia and to explore differences in PWE with and without NCC. In this community based, cross-sectional case-control-study, 47 PWE and 50 healthy controls completed five neuropsychological tests (Mini Mental State Examination (MMSE), Digit Span, Selective Reminding Test (SRT), Spatial Recall Test (SPART), Test Battery of Attentional Performance (TAP)) and a World Health Organization (WHO) questionnaire of Qol. Comparisons were made between PWE (n=47) and healthy controls (n=50) and between PWE with NCC (n=28) and without NCC (n=19), respectively, using Analysis of Covariance (ANCOVA) and Linear Models (LMs) while correcting for confounders such as age, sex, and schooling years, and adjusting for multiplicity. Working memory, spatial memory, verbal memory, verbal learning, orientation, speech and language reception, visuoconstructive ability, and attentional performance were significantly reduced in PWE compared with healthy controls (ANCOVA and LM, p<0.05). Quality of life of PWE was significantly lower in three domains (psychological, social, environmental) and in overall Qol compared with healthy controls (ANCOVA, p<0.05). There were no significant differences between PWE with NCC and PWE without NCC detected by ANCOVA. Using LM, significant differences between the groups were detected in four tests, indicating worse performance of PWE without NCC in MMSE, Digit Span, SPART, and lower physical Qol. Epilepsy was found to be associated with cognitive impairment and reduced Qol. People with epilepsy due to NCC had similar cognitive impairment and Qol compared with PWE due to other causes. Further studies should investigate the role of different conditions of NCC and the role of seizures on cognition and Qol.
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Information processing deficits as a driving force for memory impairment in MS: A cross--sectional study of memory functions and MRI in early and late stage MS. Mult Scler Relat Disord 2017; 18:119-127. [PMID: 29141793 DOI: 10.1016/j.msard.2017.09.026] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2017] [Revised: 09/08/2017] [Accepted: 09/23/2017] [Indexed: 11/21/2022]
Abstract
BACKGROUND Memory impairment (MI) is a common symptom of MS. Previous studies were conflicting in respect to the possible existence of early MI and the role of hippocampal atrophy. The objective of this study was to investigate MI and structural MRI correlates in homogenous groups of early and late MS, controlling for a potential information-processing speed (IPS) deficit, and utilizing multiple memory test paradigms. METHODS 152 individually matched subjects were recruited: early MS (EMS, N = 25, disease duration 1.0 ± 0.8 years), late MS (LMS, N = 52, 16.5 ± 5.2 years), and corresponding controls. Five memory tests were utilized to account for differences in learning material (verbal, visual), encoding (incidental, intentional), and retrieval (free recall, recognition, recurring recognition). Performance was related to IPS, memory-specific (hippocampal volumes), and unspecific MRI measures (T1/T2LL, brain volume, cortical thickness). RESULTS Memory was impaired across all tests in LMS, but not in EMS. LMS-patients were also significantly impaired in IPS which was correlated with several memory scores. Regression analyses revealed IPS and cortical thickness as predictors for visual MI, and IPS, sex, and left hippocampal volume as predictors for verbal MI. CONCLUSION Additionally to direct destructions in memory specific tracts such as the hippocampus, memory decline in MS may also be related to a general factor comprising slowed information-processing and global tissue loss.
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Hansen S, Muenssinger J, Kronhofmann S, Lautenbacher S, Oschmann P, Keune PM. Cognitive screening in Multiple Sclerosis: the Five-Point Test as a substitute for the PASAT in measuring executive function. Clin Neuropsychol 2016; 31:179-192. [PMID: 27707354 DOI: 10.1080/13854046.2016.1241894] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
OBJECTIVE The Paced Auditory Serial Addition Test (PASAT) is frequently employed to measure executive functions in patients with Multiple Sclerosis (MS). In the past, the PASAT has often been criticized because of its stressful and demanding requirements. Continuous utilization might also reduce its validity. The Five-Point Test (FPT) by Regard, Strauss, and Knapp ((1982) Children's production on verbal and non-verbal fluency tasks. Perceptual and Motor Skills, 55, 839-844.) is a short test of figural fluency which might serve as a substitute. METHOD 116 patients diagnosed with MS were tested with a short version of the Brief Repeatable Battery (BRB) by Rao and the Cognitive Function Study Group of the National Multiple Sclerosis Society including the PASAT, as well as the FPT. A factor analysis was computed and the frequency of cognitive impairment was calculated for both the original short version of the BRB and the alternative version (involving the FPT). RESULTS In the factor analysis, PASAT and FPT loaded highest on the same factor (two factors were extracted). The estimation of the frequency of cognitive impairment showed that replacing the PASAT with the FPT did not considerably alter the proportion of patients identified as cognitively impaired. CONCLUSIONS The FPT proved to be a viable alternative to the PASAT in this study. It may be recommended as a possible replacement in neuropsychological screening of MS-patients with the advantage of avoiding the indicated limitations of the PASAT.
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Affiliation(s)
- Sascha Hansen
- a Department of Neurology , Klinikum Bayreuth GmbH, Betriebsstätte Hohe Warte , Bayreuth , Germany.,b Department of Physiological Psychology , Otto-Friedrich-University , Bamberg , Germany
| | - Jana Muenssinger
- a Department of Neurology , Klinikum Bayreuth GmbH, Betriebsstätte Hohe Warte , Bayreuth , Germany
| | - Simona Kronhofmann
- a Department of Neurology , Klinikum Bayreuth GmbH, Betriebsstätte Hohe Warte , Bayreuth , Germany
| | - Stefan Lautenbacher
- b Department of Physiological Psychology , Otto-Friedrich-University , Bamberg , Germany
| | - Patrick Oschmann
- a Department of Neurology , Klinikum Bayreuth GmbH, Betriebsstätte Hohe Warte , Bayreuth , Germany
| | - Philipp M Keune
- a Department of Neurology , Klinikum Bayreuth GmbH, Betriebsstätte Hohe Warte , Bayreuth , Germany.,b Department of Physiological Psychology , Otto-Friedrich-University , Bamberg , Germany
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Adamski N, Adler M, Opwis K, Penner IK. A pilot study on the benefit of cognitive rehabilitation in Parkinson's disease. Ther Adv Neurol Disord 2016; 9:153-64. [PMID: 27134671 DOI: 10.1177/1756285616628765] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
PURPOSE Patients with Parkinson's disease (PD) show inefficiencies in cognitive performance including working memory functions. Since these problems impact on quality of life and overall well-being, the current study was aimed at improving patients' situations by evaluating the computerized cognitive training tool, BrainStim. METHOD A total of 19 healthy controls (HCs) and six patients with PD were included in the study. While all PD patients received cognitive training, the HC sample was subdivided into 12 subjects with training (HC-T) and 10 subjects without (HC-NT). Participants underwent a double baseline assessment, a post-training assessment, and a 3-month follow up on neuropsychological tests and self-report measures on fatigue and depression. Training was administered between the second baseline and postassessment. It comprised 16 supervised sessions according to a standardized training protocol over 4 weeks. RESULTS Significant improvements in verbal and visuospatial short-term and long-term memory were found in both training groups. In addition, the HC-T improved on mental speed, and verbal and visuospatial working memory. Both training groups showed stable results for all short-term visuospatial measures after 3 months. Further, the HC-T showed stable results for working memory, verbal, and visuospatial short-term and long-term memory. CONCLUSIONS The efficacy of the applied computerized cognitive training tool BrainStim could be verified in patients with PD and healthy age-matched controls. The preliminary findings highlighted the suitability of a specific cognitive intervention to improve cognitive inefficiencies in patients with PD as well as in healthy older people. Further research on cognitive training in combination with PD drug therapy is needed to better understand the mutual interaction and to offer optimal therapeutic approaches to patients.
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Affiliation(s)
- Natalia Adamski
- Department of Cognitive Psychology and Methodology, University of Basel, Switzerland
| | - Matthias Adler
- Department of Cognitive Psychology and Methodology, University of Basel, Switzerland
| | - Klaus Opwis
- Department of Cognitive Psychology and Methodology, University of Basel, Switzerland
| | - Iris-Katharina Penner
- COGITO Center for Applied Neurocognition and Neuropsychological Research and Neurology Department, University Hospital, Merowingerplatz 1, 40225 Düsseldorf, Germany
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31
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Hubacher M, Kappos L, Weier K, Stöcklin M, Opwis K, Penner IK. Case-Based fMRI Analysis after Cognitive Rehabilitation in MS: A Novel Approach. Front Neurol 2015; 6:78. [PMID: 25904893 PMCID: PMC4389546 DOI: 10.3389/fneur.2015.00078] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2015] [Accepted: 03/23/2015] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Cognitive decline in multiple sclerosis (MS) negatively impacts patients' everyday functioning and quality of life. Since symptomatic pharmacological treatment is not yet available alternative treatment strategies such as cognitive rehabilitation are of particular interest. OBJECTIVES To analyse the ways in which MS patients respond to cognitive training, by combining behavioral and fMRI data in a case-based triangulation approach. METHODS Ten relapsing-remitting (RR) MS patients aged between 39 and 58 years and between 1 and 8 years post MS diagnosis were included. EDSS ranged from 1 to 3.5. Participants had normal to high intelligence levels. Six patients were assigned to the training group (TG) and four to the control group (CG) without intervention. The TG received a 4-week computerized working memory (WM) training, consisting of 16 training sessions of 45 min duration each. Before and after the training a neuropsychological examination and fMRI investigation by using an N-back task of different complexity was applied. RESULTS Patients in the TG responded differently to cognitive training. Four participants did not meet the triangulation criteria for being treatment responders. The two responders showed two distinct changes regarding activation patterns after training: (I) decreased brain activation associated with increased processing speed and (II) increased brain activation associated with higher processing speed and WM performance. CONCLUSION The occurrence of different and opposed response patterns after the same training indicates a risk in applying classical group statistics. Different and especially opposed patterns within the same sample may distort results of classical statistical comparisons. Thus, underlying processes may not be discovered and lead to misinterpretation of results.
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Affiliation(s)
- Martina Hubacher
- Department of Cognitive Psychology and Methodology, University of Basel , Basel , Switzerland
| | - Ludwig Kappos
- Department of Neurology, University Hospital Basel , Basel , Switzerland
| | - Katrin Weier
- Department of Neurology, University Hospital Basel , Basel , Switzerland
| | - Markus Stöcklin
- Department of Cognitive Psychology and Methodology, University of Basel , Basel , Switzerland
| | - Klaus Opwis
- Department of Cognitive Psychology and Methodology, University of Basel , Basel , Switzerland
| | - Iris-Katharina Penner
- Department of Cognitive Psychology and Methodology, University of Basel , Basel , Switzerland
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Cognitive functions after spinal tap in patients with normal pressure hydrocephalus. J Neurol 2014; 261:2344-50. [PMID: 25239390 DOI: 10.1007/s00415-014-7489-2] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2014] [Revised: 08/28/2014] [Accepted: 08/30/2014] [Indexed: 10/24/2022]
Abstract
Normal pressure hydrocephalus (NPH) is characterised by gait disturbance, urinary incontinence and dementia. Even though dementia is a cardinal symptom of NPH, there is few data available concerning cognitive functioning. The aim of this observational case-control study was to evaluate the use of neuropsychological (NPSY) tests prior and after spinal tap test, which might be helpful for diagnosis, treatment and as a prognostic factor for shunt surgery. 15 patients with NPH and 18 controls were examined with eleven different tests covering all neuropsychological domains on two consecutive days. The second examination in NPH patients was 1 day after a spinal tap of 30-50 ml cerebrospinal fluid. A significant difference between NPH and controls in the change between baseline and 1 day after spinal tap was only observed in MMSE. In the domains of visuo-constructive function and attention, controls performed slightly better at day one compared to baseline, which could be interpreted as a learning effect, but after adjusting for multiple testing none of the P values were significant. In contrast to other reports, the MMSE seems to provide a sensitive evaluation of the response to spinal tap in NPH patients and might therefore be included into the routine work up of NPH patients. All other NPSY tests showed less prominent changes within 1 day after spinal tap.
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Erlanger DM, Kaushik T, Caruso LS, Benedict RHB, Foley FW, Wilken J, Cadavid D, Deluca J. Reliability of a cognitive endpoint for use in a multiple sclerosis pharmaceutical trial. J Neurol Sci 2014; 340:123-9. [PMID: 24656433 DOI: 10.1016/j.jns.2014.03.009] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2013] [Revised: 03/04/2014] [Accepted: 03/05/2014] [Indexed: 10/25/2022]
Abstract
OBJECTIVE Determine reliability and basic psychometric properties of a composite cognitive endpoint, MS-COG, for monitoring change in cognitive function in MS drug trials. BACKGROUND 50% of MS patients have cognitive impairment that impacts ability to work and quality of life. We selected neuropsychological tests based on sensitivity to MS cognitive impairment, availability of alternate forms, cross-cultural utility, and feasibility for multicenter trials, and assessed the reliability and validity of a composite endpoint, MS-COG. DESIGN/METHODS Administered SRT, BVMT-R, PASAT, and SDMT to 60 MS patients at 4 US centers twice over 45days, along with symptom inventories by patients and informants. RESULTS The MS-COG had test-retest reliability of 0.91. Processing Speed and Memory indices had reliabilities of 0.89 and 0.86, with modest practice effects. Reliability was high for the RR MS and SP MS subgroups as well, with correlations of .90 and .93, respectively for MS-COG. Overall, 42% of subjects obtained MS-COG scores in the impaired range, with SP MS subjects performing 0.8 SD below RR MS subjects. Impairment correlated well (r=0.37 to 0.40) with informant reports but was inconsistent with patient report, with the least reliable assessments by those with greater symptom severity. CONCLUSIONS The MS-COG is a reliable, repeatable measure of MS cognitive functioning that is sensitive to cognitive impairment in SP MS and RR MS patients and feasible for multicenter clinical trials. Further development is warranted.
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Affiliation(s)
- David M Erlanger
- Psychology Department, Rusk Institute of Rehabilitation Medicine.
| | | | | | | | - F W Foley
- Ferkauf Graduate School of Psychology, Yeshiva University
| | - Jeffrey Wilken
- Neuropsychology Associates of Fairfax, Georgetown University Department of Neurology
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Weier K, Penner IK, Magon S, Amann M, Naegelin Y, Andelova M, Derfuss T, Stippich C, Radue EW, Kappos L, Sprenger T. Cerebellar abnormalities contribute to disability including cognitive impairment in multiple sclerosis. PLoS One 2014; 9:e86916. [PMID: 24466290 PMCID: PMC3899307 DOI: 10.1371/journal.pone.0086916] [Citation(s) in RCA: 65] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2013] [Accepted: 12/16/2013] [Indexed: 01/11/2023] Open
Abstract
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 (r2 = 0.36). The full model for the prediction of PASAT (Paced Auditory Serial Addition Test) scores (r2 = 0.23) included age, cerebellar and T2 LV. In the case of fatigue, only age and nBV (r2 = 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.
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Affiliation(s)
- Katrin Weier
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- * E-mail:
| | - Iris K. Penner
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Cognitive Psychology and Methodology, University of Basel, Basel, Switzerland
| | - Stefano Magon
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Michael Amann
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Radiology, Division of Neuroradiology, University Hospital Basel, Basel, Switzerland
| | - Yvonne Naegelin
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Michaela Andelova
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Tobias Derfuss
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Christoph Stippich
- Department of Radiology, Division of Neuroradiology, University Hospital Basel, Basel, Switzerland
| | - Ernst-Wilhelm Radue
- Medical Image Analysis Center (MIAC) AG, University Hospital Basel, Basel, Switzerland
| | - Ludwig Kappos
- Department of Neurology, University Hospital Basel, Basel, Switzerland
| | - Till Sprenger
- Department of Neurology, University Hospital Basel, Basel, Switzerland
- Department of Radiology, Division of Neuroradiology, University Hospital Basel, Basel, Switzerland
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Wieder L, Gäde G, Pech LM, Zimmermann H, Wernecke KD, Dörr JM, Bellmann-Strobl J, Paul F, Brandt AU. Low contrast visual acuity testing is associated with cognitive performance in multiple sclerosis: a cross-sectional pilot study. BMC Neurol 2013; 13:167. [PMID: 24206900 PMCID: PMC4226200 DOI: 10.1186/1471-2377-13-167] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2013] [Accepted: 10/28/2013] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Cognitive impairment and visual deterioration are two key clinical symptoms in MS and affect 50 to 80% of patients. Little is known about the influence of cognitive impairment on visual tests recommended for MS such as low contrast sensitivity testing. Our objective was to investigate whether low contrast sensitivity testing is influenced by cognitive impairment in multiple sclerosis (MS) patients. METHODS Cross-sectional study including 89 patients with relapsing-remitting MS. All patients received cognitive evaluation using Rao's Brief Repeatable Battery of Neuropsychological Testing (BRB-N). Visual assessments included low contrast sensitivity (CS) by functional acuity contrast testing and high contrast visual acuity (VA) using ETDRS charts. Retinal morphology as visual impairment correlate was measured using retinal nerve fiber layer (RNFL) thickness by optical coherence tomography. RESULTS In combined analyses using generalized estimating equation models, Paced Auditory Serial Addition Test (PASAT) and RNFL as well as and the Symbol Digit Modalities Test (SDMT) and RNFL predicted CS. To further control for a potential influence of the anterior visual system we performed partial correlation analyses between visual function and cognitive function test results but controlling for RNFL. Even when controlling for RNFL, CS was associated with PASAT performance and SDMT performance. CONCLUSION Our data show that: a) cognitive impairment and performance in visual function tests such as low contrast sensitivity testing are associated; b) the main cognitive domains correlating with visual test performance are information processing speed and, to a lesser degree, memory; This preliminary data needs to be substantiated in further studies investigating patients with a higher cognitive burden, healthy controls and in longitudinal settings.
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Affiliation(s)
| | | | | | | | | | | | | | | | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Berlin, Germany.
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The Rao's Brief Repeatable Battery version B: normative values with age, education and gender corrections in an Italian population. Neurol Sci 2013; 35:79-82. [PMID: 24101117 DOI: 10.1007/s10072-013-1558-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2013] [Accepted: 09/26/2013] [Indexed: 10/26/2022]
Abstract
The Brief Repeatable Battery (BRB) of Neuropsychological Tests is one of the most widely used instruments to assess cognitive functioning in multiple sclerosis patients. However, to date, normative data for the Italian population are available only for the version A, which limits the use of the battery in longitudinal evaluations. We administered the BRB version B to 132 healthy subjects to obtain normative values taking into account the influences of demographic factors on the test scores and calculating corrections for these relevant factors (age, gender and education). Higher age and educational level were associated with better performance on all the tests. The World List Generation was also influenced by gender, since women performed better than men. Moreover, some tests of the version B seem to be easier than those of version A. Our data can improve the applicability of the BRB for both clinical and research purposes in longitudinal assessments.
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Papadopoulou A, Müller-Lenke N, Naegelin Y, Kalt G, Bendfeldt K, Kuster P, Stoecklin M, Gass A, Sprenger T, Radue EW, Kappos L, Penner IK. Contribution of cortical and white matter lesions to cognitive impairment in multiple sclerosis. Mult Scler 2013; 19:1290-6. [PMID: 23459568 DOI: 10.1177/1352458513475490] [Citation(s) in RCA: 86] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cortical lesions (CLs) have been reported to be a better predictor for cognitive impairment than white matter (WM) lesions in relapsing-remitting multiple sclerosis (RRMS). OBJECTIVES The objectives of this article are to investigate the contribution of CLs and WM lesions to cognitive impairment in 91 patients with MS and clinically isolated syndrome, and to test potential associations of CLs and WM lesions with fatigue and depression. METHODS Lesions were scored and segmented on 3D double inversion recovery sequences, according to their location (cortical, WM). Normalised grey matter volume was also determined. Cognitive performance was assessed with the SDMT and PASAT-3, fatigue with the FSMC and depression with the German version of the CES-D. RESULTS CL volume did not correlate with fatigue or depression, but correlated significantly with both neuropsychological outcome measures: PASAT-3 (r = -0.275, p = 0.009) and SDMT (r = -0.377, p < 0.001). Multiple regression analyses with age, WM lesions, CLs and GM volume as independent variables, however, did not reveal CL volume as a significant predictor of neuropsychological outcomes, whereas WM lesion volume significantly predicted SDMT and by trend PASAT performance. CONCLUSIONS These findings suggest a role of WM lesions in the development of cognitive deficits, especially information-processing speed, which may be higher than previously assumed. ABBREVIATIONS CES-D Center for Epidemiologic Studies Depression scale (ADS-L: Allgemeine Depressions Skala-L, German version of CES-D), CIS: clinically isolated syndrome, CL: cortical lesion, DIR: double inversion recovery, EDSS: Expanded Disability Status Scale, FSMC: fatigue scale for motor and cognitive functions, GM: grey matter, MRI: magnetic resonance imaging, MS: multiple sclerosis, PASAT-3: paced auditory serial addition test 3s, PPMS: primary progressive multiple sclerosis, RRMS: relapsing-remitting multiple sclerosis, SDMT: symbol digit modalities test, SPM: statistical parametric mapping, SPMS: secondary progressive multiple sclerosis, WM: white matter.
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Brooks JBB, Borela MCM, Fragoso YD. Assessment of cognition using the Rao's Brief Repeatable Battery of Neuropsychological Tests on a group of Brazilian patients with multiple sclerosis. ARQUIVOS DE NEURO-PSIQUIATRIA 2012; 69:887-91. [PMID: 22297873 DOI: 10.1590/s0004-282x2011000700007] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2011] [Accepted: 06/20/2011] [Indexed: 11/22/2022]
Abstract
UNLABELLED To assess the cognition of patients with multiple sclerosis (MS) using the Rao's Brief Repeatable Battery of Neuropsychological Tests (BRB-N). METHOD BRB-N was translated and adapted for control subjects. Subsequently, it was applied to a group of patients with relapsing-remitting (RR) MS. RESULTS The assessment on the healthy controls (n=47) showed that the correlation between tests on the same cognitive domain was high and that there was a five-factor solution that explained 90% of the total variance. Except for the Word List Generation subset of tests, the performance of patients with RRMS (n=39) was worse than that of the healthy controls. CONCLUSION BRB-N is a relatively simple method to assess cognition of patients with MS in the daily clinic. It does not take long to apply and does not require special skills or equipment.
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Hoffmann K, Sallen J. Spezifische Normierung des Trierer Inventars zum chronischen Stress (TICS) zur diagnostischen Anwendung im Spitzensport. ZEITSCHRIFT FUR SPORTPSYCHOLOGIE 2012. [DOI: 10.1026/1612-5010/a000074] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
Zusammenfassung: In diesem Beitrag wird das Trierer Inventar zum chronischen Stress (TICS; Schulz, Schlotz & Becker, 2004 ) vorgestellt und seine Eignung für die Anwendung im Spitzensport diskutiert. Dazu werden spezifische Normen für die Gruppe der Spitzensportler präsentiert. Das TICS misst chronischen Stress differenziert in neun Stressbereichen. Seine inhaltliche Struktur lässt sich faktorenanalytisch aus den Testwerten von Spitzensportlern replizieren. Die Skalen besitzen gute bis sehr gute interne Konsistenzen. Das Instrument kann in seiner Originalform zur Diagnostik im Spitzensport herangezogen werden. Für die Interpretation von Testergebnissen werden jedoch spezifische Normen für Spitzensportler empfohlen. Die Normstichprobe besteht aus 395 A- bis D-Kaderathleten olympischer Sportarten ab einem Alter von 16 Jahren. Berechnet wurden standardisierte Normen (T-Werte) auf der Basis der Gesamtstichprobe sowie separat für beide Geschlechter. Diese ermöglichen den Vergleich mit Testwerten von Spitzensportlern und gewährleisten eine den Besonderheiten der Zielgruppe angepasste Interpretation von Testergebnissen. Zur Interpretation werden mehrere Orientierungsmaße und ein Anwendungsbeispiel bereitgestellt.
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40
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Hubacher M, Calabrese P, Bassetti C, Carota A, Stöcklin M, Penner IK. Assessment of post-stroke fatigue: the fatigue scale for motor and cognitive functions. Eur Neurol 2012; 67:377-84. [PMID: 22614741 DOI: 10.1159/000336736] [Citation(s) in RCA: 41] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2011] [Accepted: 01/22/2012] [Indexed: 11/19/2022]
Abstract
BACKGROUND/AIMS Post-stroke fatigue (PSF) is an important but still controversial issue since knowledge on its nature is still humble. The aim of the present study was to characterize PSF beyond the subacute phase. METHODS Thirty-one stroke patients (gender: 6 female, 25 male; age range: 35-76 years; 28 patients with ischemic stroke, 3 patients with hemorrhagic stroke; mean delay after stroke: 50.65 ± 31.57 days) were recruited and assessed by measures of fatigue (Fatigue Scale for Motor and Cognitive Functions [FSMC], Fatigue Severity Scale, and Modified Fatigue Impact Scale), depression (Beck Depression Inventory Fast Screen), cognition (Brief Repeatable Battery of Neuropsychological Tests) and upper and lower extremity functions (Nine-Hole Peg Test and 25-foot walk). RESULTS Depending on the different scales, PSF prevalence ranged from 16.1 to 58.1%. Depression measures correlated significantly (r(29) ≥ 0.46; p < 0.01) with the results of all fatigue scales. Seventy-one percent of patients showed cognitive deficits in at least one cognitive domain. Cognitive fatigue measured by one subscale of the FSMC correlated most significantly with mental speed, working memory, and verbal short-term memory, while the motor subscale was associated with upper and lower extremity functions, mental speed, visual short-term memory, and working memory. A differentiation between lesion localization and fatigue severity in the motor or cognitive domain was only possible when applying the FSMC. Patients with cortical lesions scored higher on the cognitive subscale, while patients with subcortical lesions showed higher physical subscale scores. CONCLUSION The present pilot study revealed differences between lesion localization and subdomains of fatigue after stroke by applying a new fatigue scale (FSMC). The results underline the necessity for separate assessment of motor and cognitive fatigue in stroke patients.
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Affiliation(s)
- Martina Hubacher
- Department of Cognitive Psychology and Methodology, University of Basel, Basel, Switzerland
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41
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Obradovic D, Petrovic M, Antanasijevic I, Marinkovic J, Stojanovic T, Obradovic S. The Brief Repeatable Battery: psychometrics and normative values with age, education and gender corrections in a Serbian population. Neurol Sci 2012; 33:1369-74. [PMID: 22552866 DOI: 10.1007/s10072-012-1099-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2012] [Accepted: 04/12/2012] [Indexed: 10/28/2022]
Abstract
Cognitive impairment is present in up to 65 % of multiple sclerosis (MS) patients. The Brief Repeatable Battery of neuropsychological tests (BRB) is one of the most used neuropsychological tools for cognitive assessment in MS. However, relative lack of normative data limits its application in research and clinical practice. In order to obtain normative data for a Serbian population, we administered the BRB version A to 140 healthy subjects and assessed the influence of demographic factors such as gender, age, and education on the tests' scores. We also calculated corrections for these factors. Higher education was associated with better performance on all the tests. Age influenced all the tests, except the word list generation, higher age being associated with worse performance on all other tests. Women performed worse on the paced auditory serial addition test 2, no other gender differences were observed. Our data obtained for the Serbian population could further improve use of the BRB in clinical practice and for the research purposes, establishing cognitive evaluation as a part of standard neurological examination of MS patients.
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Affiliation(s)
- D Obradovic
- Clinic of Neurology, University of Defence, Faculty of Medicine of the Military Medical Academy, Crnotravska 17, 11 000, Belgrade, Serbia,
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Abstract
In this article, the nature and course of cognitive dysfunction in MS are reviewed, particularly in the context of recent advances in our understanding of the diffuse nature of neuropathology in MS, and in the context of specific factors that may confer risk or protection for the development of cognitive impairment. In addition, assessment and screening approaches of MS-related cognitive dysfunction are discussed. MS is a condition not only restricted to the adult population, and this article includes a brief description of cognition in pediatric-onset MS. Finally, promising intervention approaches to treat cognitive problems in MS are summarized.
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Affiliation(s)
- Laura J Julian
- Department of Medicine, University of California San Francisco, 3333 California Street, STE 270, San Francisco, CA 94143-0920, USA.
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43
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Jehna M, Langkammer C, Wallner-Blazek M, Neuper C, Loitfelder M, Ropele S, Fuchs S, Khalil M, Pluta-Fuerst A, Fazekas F, Enzinger C. Cognitively preserved MS patients demonstrate functional differences in processing neutral and emotional faces. Brain Imaging Behav 2011; 5:241-51. [DOI: 10.1007/s11682-011-9128-1] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
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44
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Kincses ZT, Ropele S, Jenkinson M, Khalil M, Petrovic K, Loitfelder M, Langkammer C, Aspeck E, Wallner-Blazek M, Fuchs S, Jehna M, Schmidt R, Vécsei L, Fazekas F, Enzinger C. Lesion probability mapping to explain clinical deficits and cognitive performance in multiple sclerosis. Mult Scler 2010; 17:681-9. [PMID: 21177325 DOI: 10.1177/1352458510391342] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
BACKGROUND Lesion dissemination in time and space represents a key feature and diagnostic marker of multiple sclerosis (MS). The correlation between magnetic resonance imaging (MRI) lesion load and disability is only modest, however. Strategic lesion location might at least partially account for this 'clinico-radiologic paradox'. OBJECTIVES Here we used a non-parametric permutation-based approach to map lesion location probability based on MS lesions identified on T2-weighted MRI. We studied 121 patients with clinically isolated syndrome, relapsing-remitting or secondary progressive MS and correlated these maps to assessments of neurologic and cognitive functions. RESULTS The Expanded Disability Status Scale correlated with bilateral periventricular lesion location (LL), and sensory and coordination functional system deficits correlated with lesion accumulation in distinct anatomically plausible regions, i.e. thalamus and middle cerebellar peduncule. Regarding cognitive performance, decreased verbal fluency correlated with left parietal LL comprising the putative superior longitudinal fascicle. Delayed spatial recall correlated with _amygdalar, _left frontal and parietal LL. Delayed selective reminding correlated with bilateral frontal and temporal LL. However, only part of the spectrum of cognitive and neurological problems encountered in our cohort could be explained by specific lesion location. CONCLUSIONS Lesion probability mapping supports the association of specific lesion locations with symptom development in MS, but only to limited extent.
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Affiliation(s)
- Z T Kincses
- Department of Neurology, Albert Szent-Györgyi Clinical Center, University of Szeged, Hungary
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Reuter F, Baumstarck-Barrau K, Loundou A, Pelletier J, Auquier P. Paced Auditory Serial Addition Test : données normatives dans une population française. Rev Neurol (Paris) 2010; 166:944-7. [DOI: 10.1016/j.neurol.2010.01.018] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2009] [Revised: 11/09/2009] [Accepted: 01/30/2010] [Indexed: 11/25/2022]
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46
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Khalil M, Enzinger C, Langkammer C, Petrovic K, Loitfelder M, Tscherner M, Jehna M, Bachmaier G, Wallner-Blazek M, Ropele S, Schmidt R, Fuchs S, Fazekas F. Cognitive impairment in relation to MRI metrics in patients with clinically isolated syndrome. Mult Scler 2010; 17:173-80. [DOI: 10.1177/1352458510384009] [Citation(s) in RCA: 55] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: Cognitive deficits are frequent in multiple sclerosis (MS) and have been associated with morphologic brain changes. Less information exists on their extent and relation to MRI findings in clinically isolated syndrome (CIS). It is also unclear if structural changes as detected by magnetization transfer (MT) imaging may provide an additional explanation for cognitive dysfunction. Objective: To analyse the extent of cognitive deficits and their relation to MRI metrics including MT imaging in CIS compared to relapsing-remitting MS (RRMS). Methods: Forty-four CIS and 80 RRMS patients underwent the Brief Repeatable Battery of Neuropsychological Tests (BRB-N) and a 3 T MRI scan. Results: BRB-N subtests revealed similar results in CIS and RRMS. Impaired mental processing speed was most prevalent in both groups (CIS 13.6%; RRMS 16.3%) and thus served for correlation with MRI metrics. Using stepwise linear regression analyses, the strongest predictor for decreased mental processing speed was normalized cortex volume ( p < 0.001) followed by T2-lesion load ( p < 0.05) in RRMS, whereas cortical MT ratio was the only MRI parameter associated with decreased mental processing speed in CIS ( p < 0.005). Conclusion: Cognitive dysfunction occurs in CIS in a pattern similar to RRMS, with impaired mental processing speed being most prevalent. Cortical MT-ratio changes may be an early sign for tissue changes related to impaired mental processing speed in CIS while this association shifts to increased signs of cortical atrophy and lesion load in RRMS.
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Affiliation(s)
- M Khalil
- Department of Neurology, Medical University of Graz, Austria
| | - C Enzinger
- Department of Neurology, Medical University of Graz, Austria
- Department of Radiology (Division of Neuroradiology), Medical University of Graz, Austria
| | - C Langkammer
- Department of Neurology, Medical University of Graz, Austria
| | - K Petrovic
- Department of Neurology, Medical University of Graz, Austria
| | - M Loitfelder
- Department of Neurology, Medical University of Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria
| | - M Tscherner
- Department of Neurology, Medical University of Graz, Austria
| | - M Jehna
- Department of Neurology, Medical University of Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria
| | - G Bachmaier
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, Austria
| | | | - S Ropele
- Department of Neurology, Medical University of Graz, Austria
| | - R Schmidt
- Department of Neurology, Medical University of Graz, Austria
| | - S Fuchs
- Department of Neurology, Medical University of Graz, Austria
| | - F Fazekas
- Department of Neurology, Medical University of Graz, Austria
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47
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Weinges-Evers N, Brandt AU, Bock M, Pfueller CF, Dörr J, Bellmann-Strobl J, Scherer P, Urbanek C, Boers C, Ohlraun S, Zipp F, Paul F. Correlation of self-assessed fatigue and alertness in multiple sclerosis. Mult Scler 2010; 16:1134-40. [DOI: 10.1177/1352458510374202] [Citation(s) in RCA: 69] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Background: Fatigue is the most common symptom in multiple sclerosis patients, but is difficult to measure; quantification thus relies on self-assessed questionnaires. Objective: To evaluate a battery of neuropsychological tests regarding their capacity to objectify self-reported fatigue. Methods: We assessed the correlation between age, gender, education, Kurtzke’s Expanded Disability Status Scale, depression, fatigue and neuropsychological testing using a cross-sectional approach in 110 multiple sclerosis patients. Fatigue was measured with the Fatigue Severity Scale. Cognition was measured using a series of neuropsychological tests including three subtests of the Test of Attentional Performance, the Brief Repeatable Battery of Neuropsychological Tests and the Faces Symbol Test. Results: According to the Fatigue Severity Scale 51.4% of the cohort were fatigued (scores ≥4). Age, education and depression showed a significant correlation with the Fatigue Severity Scale. Only 5.5% of the cohort exhibited cognitive impairment in the Brief Repeatable Battery of Neuropsychological Tests scores. After correction for age, education, Expanded Disability Status Scale and depression, Fatigue Severity Scale scores were an independent predictor of performance in the alertness subtest of the Test of Attentional Performance (standardized coefficient beta = 0.298, p = 0.014). Conclusion: The alertness subtest of the Test of Attentional Performance may offer an objective method of evaluating self-reported fatigue, and may therefore — in addition to the Fatigue Severity Scale — be a suitable tool for the assessment of multiple sclerosis patients complaining of fatigue.
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Affiliation(s)
- Nicholetta Weinges-Evers
- NeuroCure Clinical Research Center, Charité - University Medicine Berlin, Germany, Cecilie Vogt Clinic, Charité - University Medicine Berlin, Germany
| | - Alexander U Brandt
- NeuroCure Clinical Research Center, Charité - University Medicine Berlin, Germany, Mediber GmbH, Berlin, Germany
| | - Markus Bock
- NeuroCure Clinical Research Center, Charité - University Medicine Berlin, Germany, Cecilie Vogt Clinic, Charité - University Medicine Berlin, Germany
| | - Caspar F Pfueller
- NeuroCure Clinical Research Center, Charité - University Medicine Berlin, Germany, Cecilie Vogt Clinic, Charité - University Medicine Berlin, Germany
| | - Jan Dörr
- NeuroCure Clinical Research Center, Charité - University Medicine Berlin, Germany, Cecilie Vogt Clinic, Charité - University Medicine Berlin, Germany
| | | | - Peter Scherer
- Neurology Practice Scherer, Kantstrasse 125, 10625 Berlin, Germany
| | - Carsten Urbanek
- Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité - University Medicine Berlin, Germany
| | - Claudia Boers
- NeuroCure Clinical Research Center, Charité - University Medicine Berlin, Germany
| | - Stephanie Ohlraun
- NeuroCure Clinical Research Center, Charité - University Medicine Berlin, Germany
| | - Frauke Zipp
- Cecilie Vogt Clinic, Charité - University Medicine Berlin, Germany
| | - Friedemann Paul
- NeuroCure Clinical Research Center, Charité - University Medicine Berlin, Germany, Cecilie Vogt Clinic, Charité - University Medicine Berlin, Germany,
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48
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Urbanek C, Weinges-Evers N, Bellmann-Strobl J, Bock M, Dörr J, Hahn E, Neuhaus AH, Opgen-Rhein C, Thi Minh Tam Ta, Herges K, Pfueller CF, Radbruch H, Wernecke KD, Ohlraun S, Zipp F, Dettling M, Paul F. Attention Network Test reveals alerting network dysfunction in multiple sclerosis. Mult Scler 2009; 16:93-9. [DOI: 10.1177/1352458509350308] [Citation(s) in RCA: 56] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Attention is one of the cognitive domains typically affected in multiple sclerosis. The Attention Network Test was developed to measure the function of the three distinct attentional networks, alerting, orienting, and executive control. The Attention Network Test has been performed in various neuropsychiatric conditions, but not in multiple sclerosis. Our objective was to investigate functions of attentional networks in multiple sclerosis by means of the Attention Network Test. Patients with relapsing—remitting multiple sclerosis (n = 57) and healthy controls (n = 57) matched for age, sex, and education performed the Attention Network Test. Significant differences between patients and controls were detected in the alerting network (p = 0.003), in contrast to the orienting (p = 0.696) and the conflict (p = 0.114) network of visual attention. Mean reaction time in the Attention Network Test was significantly longer in multiple sclerosis patients than in controls (p = 0.032), Multiple sclerosis patients benefited less from alerting cues for conflict resolution compared with healthy controls. The Attention Network Test revealed specific alterations of the attention network in multiple sclerosis patients which were not explained by an overall cognitive slowing.
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Affiliation(s)
- Carsten Urbanek
- Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité University Medicine Berlin, Berlin, Germany
| | - Nicholetta Weinges-Evers
- Cecilie Vogt Clinic, Charité University Medicine Berlin, Berlin, Germany, NeuroCure Clinical Research Center, Charité University Medicine Berlin, Berlin, Germany
| | - Judith Bellmann-Strobl
- Cecilie Vogt Clinic, Charité University Medicine Berlin, Berlin, Germany, NeuroCure Clinical Research Center, Charité University Medicine Berlin, Berlin, Germany
| | - Markus Bock
- Cecilie Vogt Clinic, Charité University Medicine Berlin, Berlin, Germany, NeuroCure Clinical Research Center, Charité University Medicine Berlin, Berlin, Germany
| | - Jan Dörr
- Cecilie Vogt Clinic, Charité University Medicine Berlin, Berlin, Germany, NeuroCure Clinical Research Center, Charité University Medicine Berlin, Berlin, Germany
| | - Eric Hahn
- Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité University Medicine Berlin, Berlin, Germany
| | - Andres H Neuhaus
- Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité University Medicine Berlin, Berlin, Germany
| | - Carolin Opgen-Rhein
- Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité University Medicine Berlin, Berlin, Germany
| | - Thi Minh Tam Ta
- Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité University Medicine Berlin, Berlin, Germany
| | - Katja Herges
- Cecilie Vogt Clinic, Charité University Medicine Berlin, Berlin, Germany
| | - Caspar F Pfueller
- Cecilie Vogt Clinic, Charité University Medicine Berlin, Berlin, Germany, NeuroCure Clinical Research Center, Charité University Medicine Berlin, Berlin, Germany
| | - Helena Radbruch
- Cecilie Vogt Clinic, Charité University Medicine Berlin, Berlin, Germany
| | - Klaus D Wernecke
- Sostana GmbH and Charité University Medicine Berlin, Berlin, Germany
| | - Stephanie Ohlraun
- NeuroCure Clinical Research Center, Charité University Medicine Berlin, Berlin, Germany
| | - Frauke Zipp
- Cecilie Vogt Clinic, Charité University Medicine Berlin, Berlin, Germany
| | - Michael Dettling
- Department of Psychiatry and Psychotherapy, Campus Benjamin Franklin, Charité University Medicine Berlin, Berlin, Germany
| | - Friedemann Paul
- Cecilie Vogt Clinic, Charité University Medicine Berlin, Berlin, Germany, , NeuroCure Clinical Research Center, Charité University Medicine Berlin, Berlin, Germany
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49
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Abstract
Cognitive dysfunctions are frequent symptoms in multiple sclerosis (MS). Up to 65% of MS patients suffer from cognitive dysfunctions. Especially memory, attention and executive functions are impaired. These problems strongly affect the patients' ability to work and their quality of life (QoL). A differentiating diagnostic effort is necessary to control fatigue and depression. Screening tools alone can not provide a detailed description of all cognitive domains. Therefore, an elaborated neuropsychological diagnostics is necessary. This report provides a description of cognitive functions and its diagnostic opportunities, especially in MS patients. After displaying aspects of differential diagnostics, a recommendation for a diagnostic work schedule is given.
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Affiliation(s)
- Claudia Engel
- University of Rostock, Department of Neurology, Gehlsheimer Str. 20, 18147, Rostock, Germany.
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50
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Abstract
Cognitive screening tests in multiple sclerosis (MS) are time- and cost-saving test instruments. In the case of a positive test result (alert function) a comprehensive cognitive test procedure should be administered. This paper explains what cognitive screening in MS means and presents several screening instruments used in MS with their statistical test characteristics, e. g. sensitivity and specificity.
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