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1. Review of the pharmacoeconomics of early treatment of multiple sclerosis using interferon beta

Author

Castrop F, Haslinger B, Hemmer B, and Buck D

Subjects
Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571, Neurology. Diseases of the nervous system, RC346-429
Abstract

Florian Castrop, Bernhard Haslinger, Bernhard Hemmer, Dorothea Buck Department of Neurology, Technische Universität München, Munich, Germany Abstract: Multiple sclerosis (MS) is a common neurological disease with increasing incidence and prevalence. Onset of disease is most frequently in young adulthood when productivity is usually highest; it is of chronic nature and, in the majority of patients, it will result in accumulation of disability. Due to loss of productivity in patients and caregivers as well as high expenses for medical treatment, MS is considered a disease with high economic burden for patients and society. Several drugs have been approved for treatment of MS. While treatment ameliorates the course of the disease, it is very costly; therefore, pharmacoeconomics, evaluating costs and effects of disease-modifying treatment in MS, has become an important issue. Here, we review the economic impact and treatment strategies of MS and discuss recent studies on pharmacoeconomics of early treatment with interferon beta. Keywords: MS, pharmacoeconomics, disease-modifying therapy, interferon beta, CIS

Published
2013

2. Update on immunopathogenesis and immunotherapy in multiple sclerosis

Author

Selter RC and Hemmer B

Subjects
Multiple sclerosis, immunopathogenesis, disease-modifying therapy, Immunologic diseases. Allergy, RC581-607
Abstract

Rebecca C Selter,1 Bernhard Hemmer1–3 1Department of Neurology, Klinikum Rechts der Isar, Technische Universität München, Munich, Germany; 2Munich Cluster for Systems Neurology (SyNergy), Munich, Germany; 3Competence Network on Multiple Sklerosis, Munich, Germany Abstract: Multiple sclerosis is a chronic inflammatory demyelinating disease of the central nervous system. Both genetic and environmental factors are believed to contribute to the pathogenesis of the disease. Histopathological findings suggest that multiple sclerosis is an immune-mediated disease, involving both the cellular and humoral immune systems. Within the last 20 years, several disease-modifying therapies for the treatment of multiple sclerosis were established. Moreover, promising new substances are currently being tested in clinical trials and will likely broaden the therapeutic opportunities available within the upcoming years. Keywords: multiple sclerosis, immunopathogenesis, disease-modifying therapy

Published
2013

3. MRI plaque imaging reveals high-risk carotid plaques especially in diabetic patients irrespective of the degree of stenosis

Author

Holzer K, Liebig T, Winkler C, Feurer R, Sepp D, Pelisek Jaroslav, Bockelbrink Angelina, Heider P, Saam T, Esposito L, Pauly O, Sadikovic S, Hemmer B, and Poppert H

Subjects
Medical technology, R855-855.5
Abstract

Abstract Background Plaque imaging based on magnetic resonance imaging (MRI) represents a new modality for risk assessment in atherosclerosis. It allows classification of carotid plaques in high-risk and low-risk lesion types (I-VIII). Type 2 diabetes mellitus (DM 2) represents a known risk factor for atherosclerosis, but its specific influence on plaque vulnerability is not fully understood. This study investigates whether MRI-plaque imaging can reveal differences in carotid plaque features of diabetic patients compared to nondiabetics. Methods 191 patients with moderate to high-grade carotid artery stenosis were enrolled after written informed consent was obtained. Each patient underwent MRI-plaque imaging using a 1.5-T scanner with phased-array carotid coils. The carotid plaques were classified as lesion types I-VIII according to the MRI-modified AHA criteria. For 36 patients histology data was available. Results Eleven patients were excluded because of insufficient MR-image quality. DM 2 was diagnosed in 51 patients (28.3%). Concordance between histology and MRI-classification was 91.7% (33/36) and showed a Cohen's kappa value of 0.81 with a 95% CI of 0.98-1.15. MRI-defined high-risk lesion types were overrepresented in diabetic patients (n = 29; 56.8%). Multiple logistic regression analysis revealed association between DM 2 and MRI-defined high-risk lesion types (OR 2.59; 95% CI [1.15-5.81]), independent of the degree of stenosis. Conclusion DM 2 seems to represent a predictor for the development of vulnerable carotid plaques irrespective of the degree of stenosis and other risk factors. MRI-plaque imaging represents a new tool for risk stratification of diabetic patients. See Commentary: http://www.biomedcentral.com/1741-7015/8/78/abstract

Published
2010
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7. Treatment of MOG antibody associated disorders: results of an international survey

Author

Whittam, D. H., Karthikeayan, V., Gibbons, E., Kneen, R., Chandratre, S., Ciccarelli, O., Hacohen, Y., de Seze, J., Deiva, K., Hintzen, R. Q., Wildemann, B., Jarius, S., Kleiter, I., Rostasy, K., Huppke, P., Hemmer, B., Paul, F., Aktas, O., Pröbstel, A. K., Arrambide, G., Tintore, M., Amato, M. P., Nosadini, M., Mancardi, M. M., Capobianco, M., Illes, Z., Siva, A., Altintas, A., Akman-Demir, G., Pandit, L., Apiwattankul, M., Hor, J. Y., Viswanathan, S., Qiu, W., Kim, H. J., Nakashima, I., Fujihara, K., Ramanathan, S., Dale, R. C., Boggild, M., Broadley, S., Lana-Peixoto, M. A., Sato, D. K., Tenembaum, S., Cabre, P., Wingerchuk, D. M., Weinshenker, B. G., Greenberg, B., Matiello, M., Klawiter, E. C., Bennett, J. L., Wallach, A. I., Kister, I., Banwell, B. L., Traboulsee, A., Pohl, D., Palace, J., Leite, M. I., Levy, M., Marignier, R., Solomon, T., Lim, M., Huda, S., and Jacob, A.

Published
2020
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10. Retinal ganglion cell loss is associated with future disability worsening in early relapsing remitting multiple sclerosis

Author

Wauschkuhn, J., Solorza Buenrostro, G., Aly, L., Asseyer, S., Wicklein, R., Hartberger, J.M., Ruprecht, K., Mühlau, M., Schmitz-Hübsch, T., Chien, C., Berthele, A., Brandt, A.U., Korn, T., Paul, F., Hemmer, B., Zimmermann, H.G., and Knier, B.

Subjects
Function and Dysfunction of the Nervous System
Abstract

BACKGROUND: Thinning of the retinal combined ganglion cell and inner plexiform layer (GCIP) as measured by optical coherence tomography (OCT) is a common finding in patients with multiple sclerosis. This study aimed to investigate whether a single retinal OCT analysis allows prediction of future disease activity after a first demyelinating event. METHODS: Observational cohort study including 201 patients with recently diagnosed clinically isolated syndrome or relapsing remitting multiple sclerosis from two German tertiary referral centers. Individuals underwent neurological examination, MRI and OCT at baseline and at yearly follow-up visits. RESULTS: Patients were included at a median disease duration of 2.0 months. During a median follow-up of 59 (interquartile range 43 - 71) months, 82% of patients had ongoing disease activity as demonstrated by failing the no evidence of disease activity (NEDA)-3 criteria and 19% presented with confirmed disability worsening. A GCIP threshold ≤ 77 μm at baseline identified patients with a high risk for NEDA-3 failure (hazard ratio 1.7 [95% CI 1.1 - 2.8], p=0.04) and GCIP measures ≤ 69 μm predicted disability worsening (hazard ratio 2.2 (95% CI, 1.2 - 4.3); p=0.01). Higher rates of annualized GCIP loss increased the risk for disability worsening (hazard ratio 2.5 per 1 μm/year increase of GCIP loss, p=0.03). CONCLUSIONS: Ganglion cell thickness as measured by OCT after the initial manifestation of multiple sclerosis may allow early risk stratification as to future disease activity and progression.

Published
2023

11. Epidemiology of amyotrophic lateral sclerosis in Southern Germany

Author

Rosenbohm, Angela, Peter, Raphael S., Erhardt, Siegfried, Lulé, Dorothée, Rothenbacher, Dietrich, Ludolph, Albert C., Nagel, Gabriele, Andres, F., Arnold, G., Asshauer, I., Baezner, H., Baier, H., Beattie, J., Becker, T., Behne, F., Bengel, D., Boertlein, A., Bracknies, V., Broer, R., Burkhard, A., Connemann, B., Dempewolf, S., Dettmers, C., Dieterich, M., Etzersdorfer, E., Freund, W., Gersner, T., Gold, H.-J., Hacke, W., Hamann, G., Hecht, M., Heimbach, B., Hemmer, B., Hendrich, C., Herting, B., Huber, R., Huber-Hartmann, K., Hülser, P.-J., Jüttler, E., Kammerer-Ciernioch, J., Kaspar, A., Kern, R., Kimmig, H., Klebe, S., Kloetzsch, C., Klopstock, T., Kohler, A., Kuethmann, A., Lewis, D., Lichy, C., Lindner, A., Mäurer, M., Maier-Janson, W., Metrikat, J., Meudt, O., Meyer, A., Müller vom Hagen, J., Naegele, A., Naumann, M., Neher, K.-D., Neuhaus, O., Neusch, C., Niehaus, L., Opherk, C., Raape, J., Ratzka, P., Rettenmayr, C., Riepe, M. W., Rothmeier, J., Sabolek, M., Schabet, M., Schell, C., Schlipf, T., Schmauss, M., Schoels, L., Schuetz, K., Schweigert, B., Sommer, N., Sperber, W., Steber, C., Steber, R., Stroick, M., Synofzik, M., Trottenberg, T., Tumani, H., Wahl, C., Weber, F., Weiler, M., Weiller, C., Wessig, C., Winkler, A., and The ALS Registry Study Group

Published
2017
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12. ECTRIMS/EAN guideline on the pharmacological treatment of people with multiple sclerosis

Author

Montalban, X., Gold, R., Thompson, A. J., Otero‐Romero, S., Amato, M. P., Chandraratna, D., Clanet, M., Comi, G., Derfuss, T., Fazekas, F., Hartung, H. P., Havrdova, E., Hemmer, B., Kappos, L., Liblau, R., Lubetzki, C., Marcus, E., Miller, D. H., Olsson, T., Pilling, S., Selmaj, K., Siva, A., Sorensen, P. S., Sormani, M. P., Thalheim, C., Wiendl, H., and Zipp, F.

Published
2018
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15. Artificial intelligence extension of the OSCAR-IB criteria

Author

Petzold, A., Albrecht, P., Balcer, L., Bekkers, E., Brandt, A. U., Calabresi, P. A., Deborah, O. G., Graves, J. S., Green, A., Keane, P. A., Nij Bijvank, J. A., Sander, J. W., Paul, F., Saidha, S., Villoslada, P., Wagner, S. K., Yeh, E. A., Aktas, O., Antel, J., Asgari, N., Audo, I., Avasarala, J., Avril, D., Bagnato, F. R., Banwell, B., Bar-Or, A., Behbehani, R., Manterola, A. B., Bennett, J., Benson, L., Bernard, J., Bremond-Gignac, D., Britze, J., Burton, J., Calkwood, J., Carroll, W., Chandratheva, A., Cohen, J., Comi, G., Cordano, C., Costa, S., Costello, F., Courtney, A., Cruz-Herranz, A., Cutter, G., Crabb, D., Delott, L., De Seze, J., Diem, R., Dollfuss, H., El Ayoubi, N. K., Fasser, C., Finke, C., Fischer, D., Fitzgerald, K., Fonseca, P., Frederiksen, J. L., Frohman, E., Frohman, T., Fujihara, K., Cuellar, I. G., Galetta, S., Garcia-Martin, E., Giovannoni, G., Glebauskiene, B., Suarez, I. G., Jensen, G. P., Hamann, S., Hartung, H. -P., Havla, J., Hemmer, B., Huang, S. -C., Imitola, J., Jasinskas, V., Jiang, H., Kafieh, R., Kappos, L., Kardon, R., Keegan, D., Kildebeck, E., Kim, U. S., Klistorner, S., Knier, B., Kolbe, S., Korn, T., Krupp, L., Lagreze, W., Leocani, L., Levin, N., Liskova, P., Preiningerova, J. L., Lorenz, B., May, E., Miller, D., Mikolajczak, J., Said, S. M., Montalban, X., Morrow, M., Mowry, E., Murta, J., Navas, C., Nolan, R., Nowomiejska, K., Oertel, F. C., Oh, J., Oreja-Guevara, C., Orssaud, C., Osborne, B., Outteryck, O., Paiva, C., Palace, J., Papadopoulou, A., Patsopoulos, N., Pontikos, N., Preising, M., Prince, J., Reich, D., Rejdak, R., Ringelstein, M., Rodriguez de Antonio, L., Sahel, J. -A., Sanchez-Dalmau, B., Sastre-Garriga, J., Schippling, S., Schuman, J., Shindler, K., Shin, R., Shuey, N., Soelberg, K., Specovius, S., Suppiej, A., Thompson, A., Toosy, A., Torres, R., Touitou, V., Trauzettel-Klosinski, S., van der Walt, A., Vermersch, P., Vidal-Jordana, A., Waldman, A. T., Waters, C., Wheeler, R., White, O., Wilhelm, H., Winges, K. M., Wiegerinck, N., Wiehe, L., Wisnewski, T., Wong, S., Wurfel, J., Yaghi, S., You, Y., Yu, Z., Yu-Wai-Man, P., Zemaitien≐, R., Zimmermann, H., Albrecht P., Petzold A., Balcer, L., Bekkers, E., Brandt, A. U., Calabresi, P. A., Deborah, O. G., Graves, J. S., Green, A., Keane, P. A., Nij Bijvank, J. A., Sander, J. W., Paul, F., Saidha, S., Villoslada, P., Wagner, S. K., Yeh, E. A., Aktas, O., Antel, J., Asgari, N., Audo, I., Avasarala, J., Avril, D., Bagnato, F. R., Banwell, B., Bar-Or, A., Behbehani, R., Manterola, A. B., Bennett, J., Benson, L., Bernard, J., Bremond-Gignac, D., Britze, J., Burton, J., Calkwood, J., Carroll, W., Chandratheva, A., Cohen, J., Comi, G., Cordano, C., Costa, S., Costello, F., Courtney, A., Cruz-Herranz, A., Cutter, G., Crabb, D., Delott, L., De Seze, J., Diem, R., Dollfuss, H., El Ayoubi, N. K., Fasser, C., Finke, C., Fischer, D., Fitzgerald, K., Fonseca, P., Frederiksen, J. L., Frohman, E., Frohman, T., Fujihara, K., Cuellar, I. G., Galetta, S., Garcia-Martin, E., Giovannoni, G., Glebauskiene, B., Suarez, I. G., P. , Jensen, G., Hamann, S., Hartung, H. -P., Havla, J., Hemmer, B., Huang, S. -C., Imitola, J., Jasinskas, V., Jiang, H., Kafieh, R., Kappos, L., Kardon, R., Keegan, D., Kildebeck, E., Kim, U. S., Klistorner, S., Knier, B., Kolbe, S., Korn, T., Krupp, L., Lagreze, W., Leocani, L., Levin, N., Liskova, P., Preiningerova, J. L., Lorenz, B., May, E., Miller, D., Mikolajczak, J., Said, S. M., Montalban, X., Morrow, M., Mowry, E., Murta, J., Navas, C., Nolan, R., Nowomiejska, K., Oertel, F. C., Oh, J., Oreja-Guevara, C., Orssaud, C., Osborne, B., Outteryck, O., Paiva, C., Palace, J., Papadopoulou, A., Patsopoulos, N., Pontikos, N., Preising, M., Prince, J., Reich, D., Rejdak, R., Ringelstein, M., Rodriguez de Antonio, L., Sahel, J. -A., Sanchez-Dalmau, B., Sastre-Garriga, J., Schippling, S., Schuman, J., Shindler, K., Shin, R., Shuey, N., Soelberg, K., Specovius, S., Suppiej, A., Thompson, A., Toosy, A., Torres, R., Touitou, V., Trauzettel-Klosinski, S., van der Walt, A., Vermersch, P., Vidal-Jordana, A., Waldman, A. T., Waters, C., Wheeler, R., White, O., Wilhelm, H., Winges, K. M., Wiegerinck, N., Wiehe, L., Wisnewski, T., Wong, S., Wurfel, J., Yaghi, S., You, Y., Yu, Z., Yu-Wai-Man, P., Zemaitien≐, R., and Zimmermann, H.

Subjects
0301 basic medicine, Big Data, medicine.medical_specialty, Neurology, media_common.quotation_subject, Big data, MEDLINE, Reviews, Socio-culturale, Neurosciences. Biological psychiatry. Neuropsychiatry, Review, Public domain, Retina, Cohort Studies, 03 medical and health sciences, Annotation, 0302 clinical medicine, Artificial Intelligence, medicine, Humans, Quality (business), RC346-429, Tomography, media_common, Image pattern recognition, business.industry, General Neuroscience, Nervous System Diseases, Tomography, Optical Coherence, Algorithms, 030104 developmental biology, Optical Coherence, Imaging technology, RC0321, Neurology. Diseases of the nervous system, Neurology (clinical), Artificial intelligence, sense organs, business, 030217 neurology & neurosurgery, RC321-571
Abstract

Artificial intelligence (AI)‐based diagnostic algorithms have achieved ambitious aims through automated image pattern recognition. For neurological disorders, this includes neurodegeneration and inflammation. Scalable imaging technology for big data in neurology is optical coherence tomography (OCT). We highlight that OCT changes observed in the retina, as a window to the brain, are small, requiring rigorous quality control pipelines. There are existing tools for this purpose. Firstly, there are human‐led validated consensus quality control criteria (OSCAR‐IB) for OCT. Secondly, these criteria are embedded into OCT reporting guidelines (APOSTEL). The use of the described annotation of failed OCT scans advances machine learning. This is illustrated through the present review of the advantages and disadvantages of AI‐based applications to OCT data. The neurological conditions reviewed here for the use of big data include Alzheimer disease, stroke, multiple sclerosis (MS), Parkinson disease, and epilepsy. It is noted that while big data is relevant for AI, ownership is complex. For this reason, we also reached out to involve representatives from patient organizations and the public domain in addition to clinical and research centers. The evidence reviewed can be grouped in a five‐point expansion of the OSCAR‐IB criteria to embrace AI (OSCAR‐AI). The review concludes by specific recommendations on how this can be achieved practically and in compliance with existing guidelines.

Published
2021

17. Myelin-oligodendrocyte glycoprotein antibody-associated disease

Author

Marignier, R. Hacohen, Y. Cobo-Calvo, A. Pröbstel, A.-K. Aktas, O. Alexopoulos, H. Amato, M.-P. Asgari, N. Banwell, B. Bennett, J. Brilot, F. Capobianco, M. Chitnis, T. Ciccarelli, O. Deiva, K. De Sèze, J. Fujihara, K. Jacob, A. Kim, H.J. Kleiter, I. Lassmann, H. Leite, M.-I. Linington, C. Meinl, E. Palace, J. Paul, F. Petzold, A. Pittock, S. Reindl, M. Sato, D.K. Selmaj, K. Siva, A. Stankoff, B. Tintore, M. Traboulsee, A. Waters, P. Waubant, E. Weinshenker, B. Derfuss, T. Vukusic, S. Hemmer, B.

Abstract

Myelin-oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a recently identified autoimmune disorder that presents in both adults and children as CNS demyelination. Although there are clinical phenotypic overlaps between MOGAD, multiple sclerosis, and aquaporin-4 antibody-associated neuromyelitis optica spectrum disorder (NMOSD) cumulative biological, clinical, and pathological evidence discriminates between these conditions. Patients should not be diagnosed with multiple sclerosis or NMOSD if they have anti-MOG antibodies in their serum. However, many questions related to the clinical characterisation of MOGAD and pathogenetic role of MOG antibodies are still unanswered. Furthermore, therapy is mainly based on standard protocols for aquaporin-4 antibody-associated NMOSD and multiple sclerosis, and more evidence is needed regarding how and when to treat patients with MOGAD. © 2021 Elsevier Ltd

Published
2021

22. Multiple sclerosis genomic map implicates peripheral immune cells and microglia in susceptibility

Author

Patsopoulos, NA, Baranzini, SE, Santaniello, A, Shoostari, P, Cotsapas, C, Wong, G, Beecham, AH, James, T, Replogle, J, Vlachos, IS, McCabe, C, Pers, TH, Brandes, A, White, C, Keenan, B, Cimpean, M, Winn, P, Panteliadis, IP, Robbins, A, Andlauer, TFM, Zarzycki, O, Dubois, B, Goris, A, Sondergaard, HB, Sellebjerg, F, Sorensen, PS, Ullum, H, Thorner, LW, Saarela, J, Cournu-Rebeix, I, Damotte, V, Fontaine, B, Guillot-Noel, L, Lathrop, M, Vukusic, S, Berthele, A, Pongratz, V, Gasperi, C, Graetz, C, Grummel, V, Hemmer, B, Hoshi, M, Knier, B, Korn, T, Lill, CM, Luessi, F, Muhlau, M, Zipp, F, Dardiotis, E, Agliardi, C, Amoroso, A, Barizzone, N, Benedetti, MD, Bernardinelli, L, Cavalla, P, Clarelli, F, Comi, G, Cusi, D, Esposito, F, Ferre, L, Galimberti, D, Guaschino, C, Leone, MA, Martinelli, V, Moiola, L, Salvetti, M, Sorosina, M, Vecchio, D, Zauli, A, Santoro, S, Mancini, N, Zuccala, M, Mescheriakova, J, van Duijn, C, Bos, SD, Celius, EG, Spurkland, A, Comabella, M, Montalban, X, Alfredsson, L, Bomfim, IL, Gomez-Cabrero, D, Hillert, J, Jagodic, M, Linden, M, Piehl, F, Jelcic, I, Martin, R, Sospedra, M, Baker, A, Ban, M, Hawkins, C, Hysi, P, Kalra, S, Karpe, F, Khadake, J, Lachance, G, Molyneux, P, Neville, M, Thorpe, J, Bradshaw, E, Caillier, SJ, Calabresi, P, Cree, BAC, Cross, A, Davis, M, de Bakker, PWI, Delgado, S, Dembele, M, Edwards, K, Fitzgerald, K, Frohlich, IY, Gourraud, PA, Haines, JL, Hakonarson, H, Kimbrough, D, Isobe, N, Konidari, I, Lathi, E, Lee, MH, Li, T, An, D, Zimmer, A, Madireddy, L, Manrique, CP, Mitrovic, M, Olah, M, Patrick, E, Pericak-Vance, MA, Piccio, L, Schaefer, C, Weiner, H, Lage, K, Scott, RJ, Lechner-Scott, J, Leal, R, Moscato, P, Booth, DR, Stewart, GJ, Vucic, S, Pame, G, BamettO, M, Mason, D, GriffithS, L, Broadley, S, Tajouri, L, Baxter, A, Slee, M, Taylor, BV, Charlesworth, J, Kilpatrick, TJ, Rubio, J, Jokubaitis, V, Wiley, J, Butzkueven, H, Leslie, S, Motyer, A, Stankovich, J, Carroll, WM, Kermode, AG, Edrin, M, Barclay, M, Peyrin-Biroulet, L, Chamaillard, M, Colombe, JF, Cottone, M, Croft, A, D'Inca, R, Halfvarson, J, Hanigan, K, Henderson, P, Hugot, JP, Karban, A, Kennedy, NA, Khan, MA, Lemann, M, Levine, A, Massey, D, Milla, M, Motoey, GW, Ng, SME, Oikonomnou, J, Peeters, H, Proctor, DD, Rahier, JF, Roberts, R, Rutgeerts, P, Seibold, F, Stronati, L, Taylor, KM, Torkvist, L, Ublick, K, Van Limbergen, J, Van Gossum, A, Vatn, MH, Zhang, H, Zhang, W, Donnelly, P, Barroso, I, Blackwe, JM, Bramon, E, Brown, MA, Casas, JP, Corvin, A, Deloukas, P, Duncanson, A, Jankowski, J, Markus, HS, Mathew, CG, Palmer, CNA, Plomin, R, Rautanen, A, Sawcer, SJ, Trembath, RC, Viswanathan, AC, Wood, NW, Spencer, CCA, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Pirinen, M, Pearson, R, Strange, A, Sul, Z, Vukcevic, DA, Langford, C, Hunt, SE, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, SJ, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, McCann, OT, Liddle, J, Potter, SC, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Compston, A, Hafler, D, Harbo, HF, Hauser, SL, Stewart, G, D'Alfonso, S, Hadjigeorgiou, G, Taylor, B, Barcellos, LF, Booth, D, Hintzen, R, Kockum, I, Martinelli-Boneschi, F, McCauley, JL, Oksenberg, JR, Oturai, A, Sawcer, S, Ivinson, AJ, Olsson, T, De Jager, PL, Patsopoulos, Na, Baranzini, Se, Santaniello, A, Shoostari, P, Cotsapas, C, Wong, G, Beecham, Ah, James, T, Replogle, J, Vlachos, I, Mccabe, C, Pers, Th, Brandes, A, White, C, Keenan, B, Cimpean, M, Winn, P, Panteliadis, Ip, Robbins, A, Andlauer, Tfm, Zarzycki, O, Dubois, B, Goris, A, Sondergaard, Hb, Sellebjerg, F, Sorensen, P, Ullum, H, Thorner, Lw, Saarela, J, Cournu-Rebeix, I, Damotte, V, Fontaine, B, Guillot-Noel, L, Lathrop, M, Vukusic, S, Berthele, A, Pongratz, V, Gasperi, C, Graetz, C, Grummel, V, Hemmer, B, Hoshi, M, Knier, B, Korn, T, Lill, Cm, Luessi, F, Muhlau, M, Zipp, F, Dardiotis, E, Agliardi, C, Amoroso, A, Barizzone, N, Benedetti, Md, Bernardinelli, L, Cavalla, P, Clarelli, F, Comi, G, Cusi, D, Esposito, F, Ferre, L, Galimberti, D, Guaschino, C, Leone, Ma, Martinelli, V, Moiola, L, Salvetti, M, Sorosina, M, Vecchio, D, Zauli, A, Santoro, S, Mancini, N, Zuccala, M, Mescheriakova, J, van Duijn, C, Bos, Sd, Celius, Eg, Spurkland, A, Comabella, M, Montalban, X, Alfredsson, L, Bomfim, Il, Gomez-Cabrero, D, Hillert, J, Jagodic, M, Linden, M, Piehl, F, Jelcic, I, Martin, R, Sospedra, M, Baker, A, Ban, M, Hawkins, C, Hysi, P, Kalra, S, Karpe, F, Khadake, J, Lachance, G, Molyneux, P, Neville, M, Thorpe, J, Bradshaw, E, Caillier, Sj, Calabresi, P, Cree, Bac, Cross, A, Davis, M, de Bakker, Pwi, Delgado, S, Dembele, M, Edwards, K, Fitzgerald, K, Frohlich, Iy, Gourraud, Pa, Haines, Jl, Hakonarson, H, Kimbrough, D, Isobe, N, Konidari, I, Lathi, E, Lee, Mh, Li, T, An, D, Zimmer, A, Madireddy, L, Manrique, Cp, Mitrovic, M, Olah, M, Patrick, E, Pericak-Vance, Ma, Piccio, L, Schaefer, C, Weiner, H, Lage, K, Scott, Rj, Lechner-Scott, J, Leal, R, Moscato, P, Booth, Dr, Stewart, Gj, Vucic, S, Pame, G, Bametto, M, Mason, D, Griffiths, L, Broadley, S, Tajouri, L, Baxter, A, Slee, M, Taylor, Bv, Charlesworth, J, Kilpatrick, Tj, Rubio, J, Jokubaitis, V, Wiley, J, Butzkueven, H, Leslie, S, Motyer, A, Stankovich, J, Carroll, Wm, Kermode, Ag, Edrin, M, Barclay, M, Peyrin-Biroulet, L, Chamaillard, M, Colombe, Jf, Cottone, M, Croft, A, D'Inca, R, Halfvarson, J, Hanigan, K, Henderson, P, Hugot, Jp, Karban, A, Kennedy, Na, Khan, Ma, Lemann, M, Levine, A, Massey, D, Milla, M, Motoey, Gw, Ng, Sme, Oikonomnou, J, Peeters, H, Proctor, Dd, Rahier, Jf, Roberts, R, Rutgeerts, P, Seibold, F, Stronati, L, Taylor, Km, Torkvist, L, Ublick, K, Van Limbergen, J, Van Gossum, A, Vatn, Mh, Zhang, H, Zhang, W, Donnelly, P, Barroso, I, Blackwe, Jm, Bramon, E, Brown, Ma, Casas, Jp, Corvin, A, Deloukas, P, Duncanson, A, Jankowski, J, Markus, H, Mathew, Cg, Palmer, Cna, Plomin, R, Rautanen, A, Sawcer, Sj, Trembath, Rc, Viswanathan, Ac, Wood, Nw, Spencer, Cca, Band, G, Bellenguez, C, Freeman, C, Hellenthal, G, Giannoulatou, E, Pirinen, M, Pearson, R, Strange, A, Sul, Z, Vukcevic, Da, Langford, C, Hunt, Se, Edkins, S, Gwilliam, R, Blackburn, H, Bumpstead, Sj, Dronov, S, Gillman, M, Gray, E, Hammond, N, Jayakumar, A, Mccann, Ot, Liddle, J, Potter, Sc, Ravindrarajah, R, Ricketts, M, Waller, M, Weston, P, Widaa, S, Whittaker, P, Compston, A, Hafler, D, Harbo, Hf, Hauser, Sl, Stewart, G, D'Alfonso, S, Hadjigeorgiou, G, Taylor, B, Barcellos, Lf, Booth, D, Hintzen, R, Kockum, I, Martinelli-Boneschi, F, Mccauley, Jl, Oksenberg, Jr, Oturai, A, Sawcer, S, Ivinson, Aj, Olsson, T, De Jager, Pl, Neurology, and Immunology

Subjects
0301 basic medicine, Multiple Sclerosis, Quantitative Trait Loci, Inheritance Patterns, Cell Cycle Proteins, Genome-wide association study, Biology, Major histocompatibility complex, Polymorphism, Single Nucleotide, Major Histocompatibility Complex, Transcriptome, 03 medical and health sciences, 0302 clinical medicine, Immune system, Gene Frequency, Autoimmune Process, medicine, Humans, RNA-Seq, X chromosome, Genetics, Chromosomes, Human, X, Multidisciplinary, Microglia, Multiple sclerosis, GTPase-Activating Proteins, Chromosome Mapping, Genomics, medicine.disease, 3. Good health, 030104 developmental biology, medicine.anatomical_structure, Genetic Loci, Case-Control Studies, biology.protein, Genome-Wide Association Study, 030217 neurology & neurosurgery
Abstract

Genetic roots of multiple sclerosis The genetics underlying who develops multiple sclerosis (MS) have been difficult to work out. Examining more than 47,000 cases and 68,000 controls with multiple genome-wide association studies, the International Multiple Sclerosis Genetics Consortium identified more than 200 risk loci in MS (see the Perspective by Briggs). Focusing on the best candidate genes, including a model of the major histocompatibility complex region, the authors identified statistically independent effects at the genome level. Gene expression studies detected that every major immune cell type is enriched for MS susceptibility genes and that MS risk variants are enriched in brain-resident immune cells, especially microglia. Up to 48% of the genetic contribution of MS can be explained through this analysis. Science , this issue p. eaav7188 ; see also p. 1383

Published
2019

24. Correction to: A nonsynonymous mutation in PLCG2 reduces the risk of Alzheimer’s disease, dementia with Lewy bodies and frontotemporal dementia, and increases the likelihood of longevity (Acta Neuropathologica, (2019), 138, 2, (237-250), 10.1007/s00401-019-02026-8)

Author

van der Lee, S. J., Conway, O. J., Jansen, I., Carrasquillo, M. M., Kleineidam, L., van den Akker, E., Hernandez, I., van Eijk, K. R., Stringa, N., Chen, J. A., Zettergren, A., Andlauer, T. F. M., Diez-Fairen, M., Simon-Sanchez, J., Lleo, A., Zetterberg, H., Nygaard, M., Blauwendraat, C., Savage, J. E., Mengel-From, J., Moreno-Grau, S., Wagner, M., Fortea, J., Keogh, M. J., Blennow, K., Skoog, I., Friese, M. A., Pletnikova, O., Zulaica, M., Lage, C., de Rojas, I., Riedel-Heller, S., Illan-Gala, I., Wei, W., Jeune, B., Orellana, A., Then Bergh, F., Wang, X., Hulsman, M., Beker, N., Tesi, N., Morris, C. M., Indakoetxea, B., Collij, L. E., Scherer, M., Morenas-Rodriguez, E., Ironside, J. W., van Berckel, B. N. M., Alcolea, D., Wiendl, H., Strickland, S. L., Pastor, P., Rodriguez Rodriguez, E., Mead, S., Synofzik, M., van Swieten, J. C., Leber, I., Ferrari, R., Hernandez, D. G., Nalls, M. A., Rohrer, J. D., Ramasamy, A., Kwok, J. B. J., Dobson-Stone, C., Schofield, P. R., Halliday, G. M., Hodges, J. R., Piguet, O., Bartley, L., Thompson, E., Borroni, B., Padovani, A., Cruchaga, C., Cairns, N. J., Benussi, L., Binetti, G., Ghidoni, R., Forloni, G., Albani, D., Galimberti, D., Fenoglio, C., Serpente, M., Scarpini, E., Blesa, R., Landqvist Waldo, M., Nilsson, K., Nilsson, C., Mackenzie, I. R. A., Hsiung, G. -Y. R., Mann, D. M. A., Grafman, J., Attems, J., Griffiths, T. D., Mckeith, I. G., Thomas, A. J., Pietrini, P., Huey, E. D., Wassermann, E. M., Baborie, A., Jaros, E., Tierney, M. C., Razquin, C., Ortega-Cubero, S., Alonso, E., Perneczky, R., Diehl-Schmid, J., Alexopoulos, P., Kurz, A., Rainero, I., Rubino, E., Pinessi, L., Rogaeva, E., St George-Hyslop, P., Rossi, G., Tagliavini, F., Giaccone, G., Rowe, J. B., Schlachetzki, J. C. M., Uphill, J., Collinge, J., Danek, A., Van Deerlin, V. M., Grossman, M., Trojanowski, J. Q., van der Zee, J., Van Broeckhoven, C., Cappa, S. F., Hannequin, D., Golfier, V., Vercelletto, M., Brice, A., Nacmias, B., Sorbi, S., Bagnoli, S., Piaceri, I., Nielsen, J. E., Hjermind, L. E., Riemenschneider, M., Mayhaus, M., Ibach, B., Gasparoni, G., Pichler, S., Gu, W., Rossor, M. N., Fox, N. C., Warren, J. D., Spillantini, M. G., Morris, H. R., Rizzu, P., Snowden, J. S., Rollinson, S., Richardson, A., Gerhard, A., Bruni, A. C., Maletta, R., Frangipane, F., Cupidi, C., Bernardi, L., Anfossi, M., Gallo, M., Conidi, M. E., Smirne, N., Baker, M., Josephs, K. A., Parisi, J. E., Seeley, W. W., Miller, B. L., Karydas, A. M., Rosen, H., Dopper, E. G. P., Seelaar, H., Logroscino, G., Capozzo, R., Novelli, V., Puca, A. A., Franceschi, M., Postiglione, A., Milan, G., Sorrentino, P., Kristiansen, M., Chiang, H. -H., Graff, C., Pasquier, F., Rollin, A., Deramecourt, V., Lebouvier, T., Kapogiannis, D., Ferrucci, L., Pickering-Brown, S., Singleton, A. B., Hardy, J., Momeni, P., Boeve, B. F., Petersen, R. C., Ferman, T. J., van Gerpen, J. A., Reinders, M. J. T., Uitti, R. J., Tarraga, L., Maier, W., Dols-Icardo, O., Kawalia, A., Dalmasso, M. C., Boada, M., Zettl, U. K., van Schoor, N. M., Beekman, M., Allen, M., Masliah, E., de Munain, A. L., Pantelyat, A., Wszolek, Z. K., Ross, O. A., Dickson, D. W., Graff-Radford, N. R., Knopman, D., Rademakers, R., Lemstra, A. W., Pijnenburg, Y. A. L., Scheltens, P., Gasser, T., Chinnery, P. F., Hemmer, B., Huisman, M. A., Troncoso, J., Moreno, F., Nohr, E. A., Sorensen, T. I. A., Heutink, P., Sanchez-Juan, P., Posthuma, D., Coppola, G., Varpetian, A., Foroud, T. M., Levey, A. I., Kukull, W. A., Mendez, M. F., Ringman, J., Chui, H., Cotman, C., Decarli, C., Geschwind, D. H., Clarimon, J., Christensen, K., Ertekin-Taner, N., Scholz, S. W., Ramirez, A., Ruiz, A., Slagboom, E., van der Flier, W. M., Holstege, H., Neurology, Epidemiology and Data Science, Human genetics, APH - Societal Participation & Health, APH - Aging & Later Life, Amsterdam Neuroscience - Complex Trait Genetics, APH - Personalized Medicine, and APH - Methodology

Subjects
education
Abstract

The IPDGC (The International Parkinson Disease Genomics Consortium) and EADB (Alzheimer Disease European DNA biobank) are listed correctly as an author to the article, however, they were incorrectly listed more than once.

Published
2020

25. Aggressive multiple sclerosis (2): Treatment

Author

Arrambide, G., Iacobaeus, E., Amato, M. P., Derfuss, T., Vukusic, S., Hemmer, B., Brundin, L., Tintore, M., Berger, J., Boyko, A., Brinar, V., Brownlee, W., Ciccarelli, O., Coles, A., Correale, J., Cutter, G., Edan, G., Evangelou, N., Fernandez, O., Frederiksen, J., Gold, R., Hacohen, Y., Hartung, H. -P., Hellwig, K., Hillert, J., Imitola, J., Kalincik, T., Kappos, L., Khoury, S., Kim, H. J., Havrdova, E. K., Liblau, R., Lycke, J., Montalban, X., Muraro, P., Reingold, S., Schmierer, K., Sellebjerg, F., Sorensen, P. S., Solari, A., Sormani, M. P., Thompson, A., Trapp, B., Tremlett, H., Trojano, M., Tur, C., Uccelli, A., van Pesch, V., and Waubant, E.

Subjects
Aggressive, medicine.medical_specialty, Treatment response, relapsing–remitting, Disease, Permanent disability, multiple sclerosis, disability, highly active, treatment response, Multiple sclerosis, 03 medical and health sciences, 0302 clinical medicine, 2018 ECTRIMS Focused Workshop Group, medicine, Relapsing-remitting, 030212 general & internal medicine, Intensive care medicine, Highly active, Therapeutic window, Neurology & Neurosurgery, Disability, business.industry, 1103 Clinical Sciences, medicine.disease, ddc, Natural history, Neurology, Relapsing remitting, Neurology (clinical), business, 1109 Neurosciences, 030217 neurology & neurosurgery, Meeting Reviews
Abstract

Altres ajuts: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The workshop on which the manuscript is based was supported in its entirety by the European Committee on Treatment and Research in Multiple Sclerosis (ECTRIMS). The natural history of multiple sclerosis (MS) is highly heterogeneous. A subgroup of patients has what might be termed aggressive MS. These patients may have frequent, severe relapses with incomplete recovery and are at risk of developing greater and permanent disability at the earlier stages of the disease. Their therapeutic window of opportunity may be narrow, and while it is generally considered that they will benefit from starting early with a highly efficacious treatment, a unified definition of aggressive MS does not exist and data on its treatment are largely lacking. Based on discussions at an international focused workshop sponsored by the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), we review our current knowledge about treatment of individuals with aggressive MS. We analyse the available evidence, identify gaps in knowledge and suggest future research needed to fill those gaps. A companion paper details the difficulties in developing a consensus about what defines aggressive MS.

Published
2020

39. Plasma levels of soluble AβPPβ as a biomarker for Alzheimer's disease with dementia

Author

Alexopoulos, P. Thierjung, N. Economou, P. Werle, L. Buhl, F. Kagerbauer, S. Papanastasiou, A.D. Grimmer, T. Gourzis, P. Berthele, A. Hemmer, B. Kübler, H. Martin, J. Politis, A. Perneczky, R.

Abstract

Cost- and time-effective markers of Alzheimer's disease (AD), reliable and feasible at the population level are urgently needed. Soluble amyloid-β protein precursor β (sAβPPβ) in plasma has attracted scientific attention as a potential AD biomarker candidate. Here we report that plasma sAβPPβ levels in patients with AD dementia and typical for AD cerebrospinal fluid (CSF) biomarker profiles (N=33) are significantly lower (p

Published
2019

43. Apheresis therapies for NMOSD attacks : a retrospective study of 207 therapeutic interventions

Author

Kleiter, I., Gahlen, A., Borisow, N., Fischer, K., Wernecke, K.D., Hellwig, K., Pache, F., Ruprecht, K., Havla, J., Kümpfel, T., Aktas, O., Hartung, H.P., Ringelstein, M., Geis, C., Kleinschnitz, C., Berthele, A., Hemmer, B., Angstwurm, K., Stellmann, J.P., Schuster, S., Stangel, M., Lauda, F., Tumani, H., Mayer, C., Krumbholz, M., Zeltner, L., Ziemann, U., Linker, R., Schwab, M., Marziniak, M., Then Bergh, F., Hofstadt-van Oy, U., Neuhaus, O., Zettl, U.K., Faiss, J., Wildemann, B., Paul, F., Jarius, S., Trebst, C., and NEMOS (Neuromyelitis Optica Study Group)

Subjects
ddc:610, Function and Dysfunction of the Nervous System
Abstract

Objective: To analyze whether 1 of the 2 apheresis techniques, therapeutic plasma exchange (PE) or immunoadsorption (IA), is superior in treating neuromyelitis optica spectrum disorder (NMOSD) attacks and to identify predictive factors for complete remission (CR). Methods: This retrospective cohort study was based on the registry of the German Neuromyelitis Optica Study Group, a nationwide network established in 2008. It recruited patients with neuromyelitis optica diagnosed according to the 2006 Wingerchuk criteria or with aquaporin-4 (AQP4-ab)-antibody–seropositive NMOSD treated at 6 regional hospitals and 16 tertiary referral centers until March 2013. Besides descriptive data analysis of patient and attack characteristics, generalized estimation equation (GEE) analyses were applied to compare the effectiveness of the 2 apheresis techniques. A GEE model was generated to assess predictors of outcome. Results: Two hundred and seven attacks in 105 patients (87% AQP4-ab-antibody seropositive) were treated with at least 1 apheresis therapy. Neither PE nor IA was proven superior in the therapy of NMOSD attacks. CR was only achieved with early apheresis therapy. Strong predictors for CR were the use of apheresis therapy as first-line therapy (OR 12.27, 95% CI: 1.04–144.91, p = 0.047), time from onset of attack to start of therapy in days (OR 0.94, 95% CI: 0.89–0.99, p = 0.014), the presence of AQP4-ab-antibodies (OR 33.34, 95% CI: 1.76–631.17, p = 0.019), and monofocal attack manifestation (OR 4.71, 95% CI: 1.03–21.62, p = 0.046). Conclusions: Our findings suggest early use of an apheresis therapy in NMOSD attacks, particularly in AQP4-ab-seropositive patients. No superiority was shown for one of the 2 apheresis techniques. Classification of evidence: This study provides Class IV evidence that for patients with NMOSD, neither PE nor IA is superior in the treatment of attacks.

Published
2018

48. Volume versus surface-based cortical thickness measurements: A comparative study with healthy controls and multiple sclerosis patients

Author

Righart, R., Schmidt, P., Dahnke, R., Biberacher, V., Beer, A., Buck, D., Hemmer, B., Kirschke, J. S., Zimmer, C., Gaser, C., and Mühlau, M.

Subjects
Central Nervous System, Adult, Male, Computer and Information Sciences, Multiple Sclerosis, Imaging Techniques, Immunology, lcsh:Medicine, Research and Analysis Methods, Pathology and Laboratory Medicine, Nervous System, Autoimmune Diseases, Diagnostic Radiology, Signs and Symptoms, Diagnostic Medicine, Medicine and Health Sciences, Image Processing, Computer-Assisted, Humans, Animal Anatomy, Gray Matter, lcsh:Science, Cerebral Cortex, Cingulate Cortex, Software Tools, Radiology and Imaging, lcsh:R, Age Factors, Biology and Life Sciences, Brain, Software Engineering, Neurodegenerative Diseases, Demyelinating Disorders, Magnetic Resonance Imaging, Frontal Lobe, Neurology, Case-Control Studies, Lesions, Engineering and Technology, Clinical Immunology, Female, lcsh:Q, Clinical Medicine, Anatomy, Zoology, Software, Research Article
Abstract

The cerebral cortex is a highly folded outer layer of grey matter tissue that plays a key role in cognitive functions. In part, alterations of the cortex during development and disease can be captured by measuring the cortical thickness across the whole brain. Available software tools differ with regard to labor intensity and computational demands. In this study, we compared the computational anatomy toolbox (CAT), a recently proposed volume-based tool, with the well-established surface-based tool FreeSurfer. We observed that overall thickness measures were highly inter-correlated, although thickness estimates were systematically lower in CAT than in FreeSurfer. Comparison of multiple sclerosis (MS) patients with age-matched healthy control subjects showed highly comparable clusters of MS-related thinning for both methods. Likewise, both methods yielded comparable clusters of age-related cortical thinning, although correlations between age and average cortical thickness were stronger for FreeSurfer. Our data suggest that, for the analysis of cortical thickness, the volume-based CAT tool can be regarded a considerable alternative to the well-established surface-based FreeSurfer tool.

Published
2017

49. Inner retinal layer thinning in radiologically isolated syndrome predicts conversion to multiple sclerosis.

Author

Aly, L., Havla, J., Lepennetier, G., Andlauer, T. F. M., Sie, C., Strauß, E.‐M., Hoshi, M.‐M., Kümpfel, T., Hiltensperger, M., Mitsdoerffer, M., Mühlau, M., Zimmer, C., Hemmer, B., Korn, T., and Knier, B.

Subjects
MULTIPLE sclerosis, OPTICAL coherence tomography, NERVE fibers, THERAPEUTIC complications, SYNDROMES
Abstract

Background and purpose: Individuals with radiologically isolated syndrome (RIS) are at increased risk of converting to multiple sclerosis (MS). Early identification of later converters is crucial for optimal treatment decisions. The purpose of this study was to assess the predictive potential of optical coherence tomography (OCT) measures in individuals with RIS regarding conversion to MS. Methods: This prospective observational cohort study included 36 individuals with RIS and 36 healthy controls recruited from two German MS centers. All individuals received baseline OCT and clinical examination and were longitudinally followed over up to 6 years. The primary outcome measure was the conversion to MS. Results: During clinical follow‐up of 46 (26–58) months (median, 25%–75% interquartile range), eight individuals with RIS converted to MS. Individuals converting to MS showed a thinning of the peripapillary retinal nerve fiber layer (pRNFL) and the common ganglion cell and inner plexiform layer (GCIP) at baseline and during follow‐up. Individuals with a pRNFL of 99 µm or lower or a GCIP of 1.99 mm3 or lower were at a 7.5‐ and 8.0‐fold risk for MS conversion, respectively, compared to individuals with higher measures. After correction for other known risk factors, Cox proportional hazards regression revealed a hazard ratio of 1.08 for conversion to MS for each 1 µm decline in pRNFL. Conclusions: Reduction of the pRNFL might be a novel and independent risk factor for conversion to MS in individuals with RIS. OCT might be useful for risk stratification and therapeutic decision‐making in individuals with RIS. [ABSTRACT FROM AUTHOR]

Published
2020
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50. Differential effects of disease modifying drugs on peripheral blood B cell subsets: A cross sectional study in multiple sclerosis patients treated with interferon-β, glatiramer acetate, dimethyl fumarate, fingolimod or natalizumab.

Author

Kemmerer, C. L., Pernpeintner, V., Ruschil, C., Abdelhak, A., Scholl, M., Ziemann, U., Krumbholz, M., Hemmer, B., and Kowarik, M. C.

Subjects
INTERFERON beta 1b, GLATIRAMER acetate, BLOOD cells, NATALIZUMAB, B cells, MULTIPLE sclerosis, PATHOLOGY, FLOW cytometry
Abstract

Background: Several disease modifying drugs (DMDs) have been approved for the treatment of multiple sclerosis (MS), however, little is known about their differential impact on peripheral blood (PB) B cell subsets. Methods: We performed a cross sectional study on PB B cells in MS patients treated with interferon-β (n = 25), glatiramer acetate (n = 19), dimethyl fumarate (n = 15), fingolimod (n = 16) or natalizumab (n = 22), untreated MS patients (n = 20), and in patients with non-inflammatory neurological diseases (n = 12). Besides analyzing routine laboratory data, flow cytometry was performed to analyze naïve B cells (CD19+CD20+CD27-IgD+), non-class switched (CD19+CD20+CD27+IgD+) and class-switched memory B cells (CD19+CD20+CD27+IgD-), double negative B cells (CD19+CD20lowCD27-IgD-) and plasmablasts (CD19+CD20lowCD27+CD38++). Results: Treatment associated changes were found for the overall B cell pool as well as for all B cell subsets. Natalizumab increased absolute numbers and percentage of all B cells mainly by expanding the memory B cell pool. Fingolimod decreased absolute numbers of all B cell subsets and the percentage of total B cells. Fingolimod, dimethyl fumarate and interferon-β treatments were associated with an increase in the fraction of naïve B cells while class switched and non-class switched memory B cells showed decreased percentages. Conclusion: Our results highlight differential effects of DMDs on the PB B cell compartment. Across the examined treatments, a decreased percentage of memory B cells was found in dimethyl fumarate, interferon-β and fingolimod treated patients which might contribute to the drugs' mode of action in MS. Further studies are necessary to decipher the exact role of B cell subsets during MS pathogenesis. [ABSTRACT FROM AUTHOR]

Published
2020
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