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Published in: BMC Neurology 1/2022

Open Access 01-12-2022 | Multiple Sclerosis | Study protocol

Berlin Registry of Neuroimmunological entities (BERLimmun): protocol of a prospective observational study

Authors: Pia S. Sperber, Alexander U. Brandt, Hanna G. Zimmermann, Lina S. Bahr, Claudia Chien, Sophia Rekers, Anja Mähler, Chotima Böttcher, Susanna Asseyer, Ankelien Solveig Duchow, Judith Bellmann-Strobl, Klemens Ruprecht, Friedemann Paul, Tanja Schmitz-Hübsch

Published in: BMC Neurology | Issue 1/2022

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Abstract

Background

Large-scale disease overarching longitudinal data are rare in the field of neuroimmunology. However, such data could aid early disease stratification, understanding disease etiology and ultimately improve treatment decisions. The Berlin Registry of Neuroimmunological Entities (BERLimmun) is a longitudinal prospective observational study, which aims to identify diagnostic, disease activity and prognostic markers and to elucidate the underlying pathobiology of neuroimmunological diseases.

Methods

BERLimmun is a single-center prospective observational study of planned 650 patients with neuroimmunological disease entity (e.g. but not confined to: multiple sclerosis, isolated syndromes, neuromyelitis optica spectrum disorders) and 85 healthy participants with 15 years of follow-up. The protocol comprises annual in-person visits with multimodal standardized assessments of medical history, rater-based disability staging, patient-report of lifestyle, diet, general health and disease specific symptoms, tests of motor, cognitive and visual functions, structural imaging of the neuroaxis and retina and extensive sampling of biological specimen.

Discussion

The BERLimmun database allows to investigate multiple key aspects of neuroimmunological diseases, such as immunological differences between diagnoses or compared to healthy participants, interrelations between findings of functional impairment and structural change, trajectories of change for different biomarkers over time and, importantly, to study determinants of the long-term disease course. BERLimmun opens an opportunity to a better understanding and distinction of neuroimmunological diseases.
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Literature
3.
go back to reference Abbatemarco JR, Rodenbeck SJ, Day GS, Titulaer MJ, Yeshokumar AK, Clardy SL. Autoimmune neurology: the need for Comprehensive Care. Neurol Neuroimmunol Neuroinflamm. 2021;8(5). Abbatemarco JR, Rodenbeck SJ, Day GS, Titulaer MJ, Yeshokumar AK, Clardy SL. Autoimmune neurology: the need for Comprehensive Care. Neurol Neuroimmunol Neuroinflamm. 2021;8(5).
11.
go back to reference Graves JS, Oertel FC, Van der Walt A, et al. Leveraging Visual Outcome Measures to Advance Therapy Development in Neuroimmunologic Disorders. Neurol Neuroimmunol neuroinflammation. 2022;9(2). Graves JS, Oertel FC, Van der Walt A, et al. Leveraging Visual Outcome Measures to Advance Therapy Development in Neuroimmunologic Disorders. Neurol Neuroimmunol neuroinflammation. 2022;9(2).
14.
go back to reference Avasarala J, Pettigrew C, Sutton P, et al. Can a diagnosis of multiple sclerosis be made without ruling out neuromyelitis optica spectrum disorder ? Mult Scler Relat Disord. 2020;40. Avasarala J, Pettigrew C, Sutton P, et al. Can a diagnosis of multiple sclerosis be made without ruling out neuromyelitis optica spectrum disorder ? Mult Scler Relat Disord. 2020;40.
18.
go back to reference Chien C, Brandt AU, Schmidt F, et al. MRI-based methods for spinal cord atrophy evaluation: a comparison of cervical cord cross-sectional area, cervical cord volume, and full spinal cord volume in patients with aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders. Am J Neuroradiol. 2018;39(7):1362–8. doi:https://doi.org/10.3174/ajnr.A5665.CrossRef Chien C, Brandt AU, Schmidt F, et al. MRI-based methods for spinal cord atrophy evaluation: a comparison of cervical cord cross-sectional area, cervical cord volume, and full spinal cord volume in patients with aquaporin-4 antibody seropositive neuromyelitis optica spectrum disorders. Am J Neuroradiol. 2018;39(7):1362–8. doi:https://​doi.​org/​10.​3174/​ajnr.​A5665.CrossRef
26.
go back to reference Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33(11):1444–52.CrossRef Kurtzke JF. Rating neurologic impairment in multiple sclerosis: an expanded disability status scale (EDSS). Neurology. 1983;33(11):1444–52.CrossRef
38.
go back to reference Palylyk-Colwell E, Ford C. Flash glucose monitoring system for diabetes. In: Ottawa (ON); 2016:1–13. Palylyk-Colwell E, Ford C. Flash glucose monitoring system for diabetes. In: Ottawa (ON); 2016:1–13.
43.
go back to reference Hohol MJ, Orav EJ, Weiner HL. Disease steps in multiple sclerosis. Neurology. 1995;45(April 1993):251–5.CrossRef Hohol MJ, Orav EJ, Weiner HL. Disease steps in multiple sclerosis. Neurology. 1995;45(April 1993):251–5.CrossRef
46.
go back to reference Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989;46(10):1121–3.CrossRef Krupp LB, LaRocca NG, Muir-Nash J, Steinberg AD. The fatigue severity scale. Application to patients with multiple sclerosis and systemic lupus erythematosus. Arch Neurol. 1989;46(10):1121–3.CrossRef
49.
go back to reference Radbruch L, Loick G, Kiencke P, et al. Validation of the german version of the brief Pain Inventory. J Pain Symptom Manage. 1999;18(3):180–7. https://doi.org/10.1016/j.beth.2017.10.003%0Ahttp://www.ncbi.nlm.nih.gov/pubmed/8826494%0Ahttp://www.scielo.br/scielo.php?script=sci_arttext&pid=S2237-60892013000300007&lng=en&tlng=en%0Ahttps://www5.bahiana.edu.br/index.php/fisioterapia/article/view/1080 Radbruch L, Loick G, Kiencke P, et al. Validation of the german version of the brief Pain Inventory. J Pain Symptom Manage. 1999;18(3):180–7. https://​doi.​org/​10.​1016/​j.​beth.​2017.​10.​003%0Ahttp://www.ncbi.nlm.nih.gov/pubmed/8826494%0Ahttp://www.scielo.br/scielo.php?script=sci_arttext&pid=S2237-60892013000300007&lng=en&tlng=en%0Ahttps://www5.bahiana.edu.br/index.php/fisioterapia/article/view/1080
54.
57.
go back to reference Otte K, Kayser B, Mansow-Model S, et al. Accuracy and Reliability of the Kinect Version 2 for Clinical Measurement of Motor Function. Maurits NM, ed. PLoS One. 2016;11(11). Otte K, Kayser B, Mansow-Model S, et al. Accuracy and Reliability of the Kinect Version 2 for Clinical Measurement of Motor Function. Maurits NM, ed. PLoS One. 2016;11(11).
59.
go back to reference Grobelny A, Behrens JR, Mertens S, et al. Maximum walking speed in multiple sclerosis assessed with visual perceptive computing. Sakakibara M, ed. PLoS One. 2017;12(12). Grobelny A, Behrens JR, Mertens S, et al. Maximum walking speed in multiple sclerosis assessed with visual perceptive computing. Sakakibara M, ed. PLoS One. 2017;12(12).
62.
go back to reference Smith A. Symbol Digit Modalities Test (revised). Los Angeles: Western Psychological Services; 1982. 1982:1982. Smith A. Symbol Digit Modalities Test (revised). Los Angeles: Western Psychological Services; 1982. 1982:1982.
64.
go back to reference Schmidt M. Rey auditory verbal learning test: A handbook. Los Angeles: Western Psychological Services; 1996. p. 1996. Schmidt M. Rey auditory verbal learning test: A handbook. Los Angeles: Western Psychological Services; 1996. p. 1996.
65.
go back to reference Helmstaedter C, Lendt M, Lux S. Verbaler Lern-und Merkfähigkeitstest: VLMT: manual. 1st ed. Göttingen: Hogrefe Verlag; 2001. p. 2001. Helmstaedter C, Lendt M, Lux S. Verbaler Lern-und Merkfähigkeitstest: VLMT: manual. 1st ed. Göttingen: Hogrefe Verlag; 2001. p. 2001.
66.
go back to reference Benedict RHB. Benedict RHB. Brief Visuospatial Memory test – revised. Odessa: Psychological Assessment Resources, Inc; 1997. 1997:1997. Benedict RHB. Benedict RHB. Brief Visuospatial Memory test – revised. Odessa: Psychological Assessment Resources, Inc; 1997. 1997:1997.
67.
go back to reference Yadav SK, Kafieh R, Zimmermann HG, et al. Deep learning based intraretinal layer segmentation using cascaded compressed U-net. 2021.CrossRef Yadav SK, Kafieh R, Zimmermann HG, et al. Deep learning based intraretinal layer segmentation using cascaded compressed U-net. 2021.CrossRef
70.
76.
go back to reference Concato J, Shah N, Horwitz RI. Randomized controlled trials, observational studies and the hierachy of research designs. N Engl J Med. 2000:1887–1892. Concato J, Shah N, Horwitz RI. Randomized controlled trials, observational studies and the hierachy of research designs. N Engl J Med. 2000:1887–1892.
Metadata
Title
Berlin Registry of Neuroimmunological entities (BERLimmun): protocol of a prospective observational study
Authors
Pia S. Sperber
Alexander U. Brandt
Hanna G. Zimmermann
Lina S. Bahr
Claudia Chien
Sophia Rekers
Anja Mähler
Chotima Böttcher
Susanna Asseyer
Ankelien Solveig Duchow
Judith Bellmann-Strobl
Klemens Ruprecht
Friedemann Paul
Tanja Schmitz-Hübsch
Publication date
01-12-2022
Publisher
BioMed Central
Published in
BMC Neurology / Issue 1/2022
Electronic ISSN: 1471-2377
DOI
https://doi.org/10.1186/s12883-022-02986-7

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