Differential diagnosis of demyelinating diseases: what's new?

ABSTRACT

Background: Acquired demyelinating disorders lead to overlapping visual, pyramidal, sensory, autonomic, and cerebellar deficits and may lead to severe disability. Early diagnosis and start of treatment are fundamental towards preventing further attacks and halting disability. Objective: In this paper we provide an updated overview of the differential diagnoses of acquired demyelinating disorders. Methods: We performed a critical targeted review of the diagnoses of the most prevalent demyelinating disorders: multiple sclerosis (MS), neuromyelitis optica spectrum disorders (NMOSD) and myelin oligodendrocyte glycoprotein antibody disease (MOGAD). Results: We discuss the workup, diagnostic criteria and new biomarkers currently being used for the diagnosis of these disease entities taking into account the particularities of the Brazilian population and healthcare system. Conclusion: A comprehensive analysis of medical history, physical examination, biomedical and imaging data should be performed to obtain differential diagnosis. Diagnostic criteria should be mindfully employed considering ethnic and environmental particularities of each patient.

RESUMO

Antecedentes: Doenças desmielinizantes adquiridas levam a déficits visuais, piramidais, sensitivos, autonômicos e cerebelares que se sobrepõem e podem conduzir a grave incapacidade. O diagnóstico e o início de tratamento precoces são fundamentais para a prevenção de surtos e ocorrência de incapacidade. Objetivo: Neste artigo, apresentamos uma visão geral atualizada sobre o diagnóstico diferencial de doenças desmielinizantes adquiridas. Métodos: Realizamos uma revisão crítica sobre o diagnóstico das doenças desmielinizantes mais prevalentes: esclerose múltipla (EM), doença do espectro neuromielite óptica (NMOSD) e doença associada ao anticorpo contra a glicoproteína da mielina do oligodendrócito (MOGAD). Resultados: Discutimos a investigação, os critérios diagnósticos e os novos biomarcadores atualmente empregados para o diagnóstico dessas doenças, levando em conta as particularidades da população e sistema de saúde brasileiros. Conclusão: Uma análise minuciosa do histórico médico, exame neurológico e exames biomédicos e de imagem deve ser realizada para se fazer um diagnóstico diferencial de doença desmielinizante. Critérios diagnósticos devem ser empregados cautelosamente considerando-se particularidades étnicas e ambientais de cada paciente.

Keywords:

Multiple Sclerosis - Neuromyelitis Optica - Myelin-Oligodendrocyte Glycoprotein - Diagnosis

Palavras-chave:

Esclerose Múltipla - Neuromielite Óptica - Glicoproteína Mielina-Oligodendrócito - Diagnóstico

Author’s contributions:

ABAGRG: wrote the review; TA: wrote and critically appraised the review.

Publication History

Received: 16 March 2022

Accepted: 29 April 2022

Article published online:
06 February 2023

• References

• 1 Koch-Henriksen N, Sørensen PS. The changing demographic pattern of multiple sclerosis epidemiology. Lancet Neurol 2010; 9 (05) 520-532 https://doi.org/10.1016/S1474-4422(10)70064-8
• 2 Pereira ABCNG, Lacativa MCS, Pereira FFCC, Alvarenga RMP. Prevalence of multiple sclerosis in Brazil: a systematic review. Mult Scler Relat Disord 2015; 4 (06) 572-579 https://doi.org/10.1016/j.msard.2015.08.004
• 3 Alvarenga MP, Schimidt S, Alvarenga RP. Epidemiology of neuromyelitis optica in Latin America. Mult Scler J Exp Transl Clin 2017; 3 (03) 2055217317730098-2055217317730098 https://doi.org/10.1177/2055217317730098
• 4 Lana-Peixoto MA, Talim NC, Pedrosa D, Macedo JM, Santiago-Amaral J. Prevalence of neuromyelitis optica spectrum disorder in Belo Horizonte, Southeast Brazil. Mult Scler Relat Disord 2021; 50: 102807 https://doi.org/10.1016/j.msard.2021.102807
• 5 Pandit L, Asgari N, Apiwattanakul M, Palace J, Paul F, Leite MI. et al. Demographic and clinical features of neuromyelitis optica: a review. Mult Scler 2015; 21 (07) 845-853 https://doi.org/10.1177/1352458515572406
• 6 Hegen H, Reindl M. Recent developments in MOG-IgG associated neurological disorders. Ther Adv Neurol Disord 2020; 13: 1756286420945135-1756286420945135 https://doi.org/10.1177/1756286420945135
• 7 Dos Passos GR, Oliveira LM, Costa BK, Apostolos-Pereira SL, Callegaro D, Fujihara K. et al. MOG-IgG-Associated optic neuritis, encephalitis, and myelitis: lessons learned from neuromyelitis optica spectrum disorder. Front Neurol 2018; Apr 4; 9: 217 https://doi.org/10.3389/fneur.2018.00217
• 8 Papais-Alvarenga RM, Neri VC, Araújo ACRA, Silva EB, Alvarenga MP, Pereira ABCNG. et al. Lower frequency of antibodies to MOG in Brazilian patients with demyelinating diseases: an ethnicity influence?. Mult Scler Relat Disord 2018; 25: P87-P94 https://doi.org/10.1016/j.msard.2018.07.026
• 9 Thompson AJ, Banwell BL, Barkhof F, Carroll WM, Coetzee T, Comi G. et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 2018; 17 (02) P162-P173 https://doi.org/10.1016/S1474-4422(17)30470-2
• 10 Wingerchuk DM, Banwell B, Bennett JL, Cabre P, Carroll W, Chitnis T. et al. International consensus diagnostic criteria for neuromyelitis optica spectrum disorders. Neurology 2015; 85 (02) 177-189 https://doi.org/10.1212/WNL.2022s1092022s1091729
• 11 Yeh EA, Nakashima I. Live-cell based assays are the gold standard for anti-MOG-Ab testing. Neurology 2019; 92 (11) 501-502 https://doi.org/10.1212/WNL.2022s1092022s1097077
• 12 Alonso R, Gonzalez-Moron D, Garcea O. Optical coherence tomography as a biomarker of neurodegeneration in multiple sclerosis: a review. Mult Scler Relat Disord 2018; 22: P77-P82 https://doi.org/10.1016/j.msard.2018.03.007
• 13 Toledo J, Sepulcre J, Salinas-Alaman A, García-Layana A, Murie-Fernandez M, Bejarano B. et al. Retinal nerve fiber layer atrophy is associated with physical and cognitive disability in multiple sclerosis. Mult Scler 2008; 14 (07) 906-912 https://doi.org/10.1177/1352458508090221
• 14 Garcia-Martin E, Ara JR, Martin J, Almarcegui C, Dolz I, Vilades E. et al. Retinal and optic nerve degeneration in patients with multiple sclerosis followed up for 5 years. Ophthalmology 2017; 124 (05) P688-P696 https://doi.org/10.1016/j.ophtha.2017.01.005
• 15 Lambe J, Fitzgerald KC, Murphy OC, Filippatou AG, Sotirchos ES, Kalaitzidis G. et al. Association of spectral-domain OCT with long-term disability worsening in multiple sclerosis. Neurology 2021; 96 (16) e2058-e2069 https://doi.org/10.1212/WNL.2022s1090000011788
• 16 Narayan RN, McCreary M, Conger D, Wang C, Greenberg BM. Unique characteristics of optical coherence tomography (OCT) results and visual acuity testing in myelin oligodendrocyte glycoprotein (MOG) antibody positive pediatric patients. Mult Scler Relat Disord 2019; 28: 86-90 https://doi.org/10.1016/j.msard.2018.11.026
• 17 Chen JJ, Sotirchos ES, Henderson AD, Vasileiou ES, Flanagan EP, Bhatti MT. et al. OCT retinal nerve fiber layer thickness differentiates acute optic neuritis from MOG antibody-associated disease and multiple sclerosis. Mult Scler Relat Disord 2022; 58: 103525-103525 https://doi.org/10.1016/j.msard.2022.103525
• 18 Khalil M, Teunissen CE, Otto M, Piehl F, Sormani MP, Gattringer T. et al. Neurofilaments as biomarkers in neurological disorders. Nat Rev Neurol 2018; 14 (10) 577-589 https://doi.org/10.1038/s41582-018-0058-z
• 19 Håkansson I, Tisell A, Cassel P, Blennow K, Zetterberg H, Lundberg P. et al. Neurofilament light chain in cerebrospinal fluid and prediction of disease activity in clinically isolated syndrome and relapsing-remitting multiple sclerosis. Eur J Neurol 2017; 24 (05) 703-712 https://doi.org/10.1111/ene.13274
• 20 Kuhle J, Kropshofer H, Haering DA, Kundu U, Meinert R, Barro C. et al. Blood neurofilament light chain as a biomarker of MS disease activity and treatment response. Neurology 2019; 92 (10) e1007-e1015 https://doi.org/10.1212/WNL.2022s1092022s1097032
• 21 Disanto G, Barro C, Benkert P, Naegelin Y, Schädelin S, Giardiello A. et al. Serum neurofilament light: a biomarker of neuronal damage in multiple sclerosis. Ann Neurol 2017; 81 (06) 857-870 https://doi.org/10.1002/ana.24954
• 22 Siller N, Kuhle J, Muthuraman M, Barro C, Uphaus T, Groppa S. et al. Serum neurofilament light chain is a biomarker of acute and chronic neuronal damage in early multiple sclerosis. Mult Scler 2019; 25 (05) 678-686 https://doi.org/10.1177/1352458518765666
• 23 Benkert P, Meier S, Schaedelin S, Manouchehrinia A, Yaldizli Ö, Maceski A. et al. Serum neurofilament light chain for individual prognostication of disease activity in people with multiple sclerosis: a retrospective modelling and validation study. Lancet Neurol 2022; 21 (03) P246-P257 https://doi.org/10.1016/S1474-4422(22)00009-6
• 24 Watanabe M, Nakamura Y, Michalak Z, Isobe N, Barro C, Leppert D. et al. Serum GFAP and neurofilament light as biomarkers of disease activity and disability in NMOSD. Neurology 2019; 93 (13) e1299-e1311 https://doi.org/10.1212/WNL.2022s1092022s1098160
• 25 Chang X, Huang W, Wang L, ZhangBao J, Zhou L, Lu C. et al. Serum neurofilament light and GFAP are associated with disease severity in inflammatory disorders with aquaporin-4 or myelin oligodendrocyte glycoprotein antibodies. Front Immunol 2021; 12: 647618-647618 https://doi.org/10.3389/fimmu.2021.647618
• 26 Aktas O, Smith MA, Rees WA, Bennett JL, She D, Katz E. et al. Serum glial fibrillary acidic protein: a neuromyelitis optica spectrum disorder biomarker. Ann Neurol 2021; 89 (05) 895-910 https://doi.org/10.1002/ana.26067