The Open Immunology Journal




ISSN: 1874-2262 ― Volume 10, 2020
REVIEW ARTICLE

Biomarkers of Multiple Sclerosis



Daina Pastare1, 2, *, Mohamed Ridha Bennour1, Elīna Polunosika2, Guntis Karelis2, 3
1 Department of Neurology and Neurosurgery, Riga Stradins University, Riga, Latvia
2 Department of Neurology and Neurosurgery, Riga East University Hospital “Gailezers”, Riga, Latvia
3 Department of Infectology and Dermatology, Riga Stradins University, Riga, Latvia

Abstract

The search for an ideal multiple sclerosis biomarker with good diagnostic value, prognostic reference and an impact on clinical outcome has yet to be realized and is still ongoing. The aim of this review is to establish an overview of the frequent biomarkers for multiple sclerosis that exist to date. The review summarizes the results obtained from electronic databases, as well as thorough manual searches. In this review the sources and methods of biomarkers extraction are described; in addition to the description of each biomarker, determination of the prognostic, diagnostic, disease monitoring and treatment response values besides clinical impact they might possess. We divided the biomarkers into three categories according to the achievement method: laboratory markers, genetic-immunogenetic markers and imaging markers. We have found two biomarkers at the time being considered the gold standard for MS diagnostics. Unfortunately, there does not exist a single solitary marker being able to present reliable diagnostic value, prognostic value, high sensitivity and specificity as well as clinical impact. We need more studies to find the best biomarker for MS.

Keywords: Multiple sclerosis, Imaging, Genetic-immunogenetic, Biomarkers, Magnetic resonance, Laboratory.


Article Information


Identifiers and Pagination:

Year: 2019
Volume: 9
First Page: 1
Last Page: 13
Publisher Id: TOIJ-9-1
DOI: 10.2174/1874226201909010001

Article History:

Received Date: 01/04/2019
Revision Received Date: 23/10/2019
Acceptance Date: 25/10/2019
Electronic publication date: 20/12/2019
Collection year: 2019

© 2019 Pastare et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: (https://creativecommons.org/licenses/by/4.0/legalcode). This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


* Address correspondence to this author at the Department of Neurology and Neurosurgery, Riga Stradins University; Riga East University Hospital “Gailezers”, 2 Hipokrata Str., LV-1038 Riga, Latvia; Tel: +37167042531;
E-mail: daina.pastare@gmail.com






1. INTRODUCTION

Multiple Sclerosis (MS) is one of the most common causes of neurological diseases among adolescents and young adults [1Rosati G. The prevalence of multiple sclerosis in the world: An update. Neurol Sci 2001; 22(2): 117-39.
[http://dx.doi.org/10.1007/s100720170011] [PMID: 11603614]
]. MS is an immune-mediated inflammatory disease, which assaults myelinated axons in the Central Nervous System (CNS), thereby breaking the myelin sheaths and the axons in variable degrees [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. The cause of MS is still, after a century of studies, unknown; however, it is likely that many factors act in concurrence to trigger the disease. The general consensus is that MS manifests when an environmental agent (e.g., viral, bacterial infections, smoking, diet, vitamin-D deficiency or an exposure to chemicals) acts together with a genetic susceptibility to immune dysfunction [3Ghasemi N, Razavi S, Nikzad E. Multiple sclerosis: Pathogenesis, symptoms, diagnoses and cell-based therapy. Cell J 2017; 19(1): 1-10.
[PMID: 28367411]
].

While the etiology of MS is yet to be entirely uncovered, it is generally accepted that the first step in the disease progression is the breakdown of the blood-brain barrier (BBB). This breakdown of the BBB then allows autoreactive autoimmune and a cohort of inflammatory cells to enter the CNS leading to a cascade of myriad neurodegenerative events eventually manifesting as typical plaque lesions as well as clinical symptoms seen in MS [4Frohman EM, Racke MK, Raine CS. Multiple sclerosis-the plaque and its pathogenesis. N Engl J Med 2006; 354(9): 942-55.
[http://dx.doi.org/10.1056/NEJMra052130] [PMID: 16510748]
].

The clinical course can vary from patient to patient in many diversifying manners, which demonstrates the complexity of the pathophysiology. The clinical picture is ever-elusive as the mechanisms of axonal neurodegeneration, inflammatory demyelination, gliosis and re-myelination repair fuse to form different clinical pictures for each patient [5Mahad DH, Trapp BD, Lassmann H. Pathological mechanisms in progressive multiple sclerosis. Lancet Neurol 2015; 14(2): 183-93.
[http://dx.doi.org/10.1016/S1474-4422(14)70256-X] [PMID: 25772897]
]. The disease onset and progression are influenced by idiosyncratic factors. Identifying the biomarkers of these factors serves as an essential first step in determining the clinical impact they might have on the disease prognosis and treatment [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. We will review the materials from which the biomarkers are extracted focusing mainly on the serum, cerebrospinal fluid, imaging and genetic-immunogenetic biomarkers. The focus will be on describing the biomarkers and identifying the benefits as well as the clinical relevance of each biomarker.

2. MATERIALS AND METHODS

This review is based on the scientific articles found in validated sources such as PubMed, The National Centre for Biotechnology Information (NCBI) and the published books. It is comprised of publications dating from 2000 up to the present day, which deal with MS and biomarkers in general.

3. RESULTS AND ANALYSIS

3.1. Definition of a Biomarker

The Biomarkers, EndpointS and other Tools (BEST) from the National Institutes of Health (NIH) defines a biomarker as a “defined characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention, including therapeutic interventions.” The types of biomarkers are molecular, histologic, radiographic, or physiologic characteristics. “A biomarker is not an assessment of how an individual feels, functions, or survives.” BEST offers seven biomarker categories - susceptibility/risk, diagnostic, monitoring, prognostic, predictive, pharmacodynamic/response, and safety [6US Food & Drug Administration Available From: https://www.fda.gov/drugs/cder-biomarker-qualification-program/about-biomarkers-and-qualification]. It is slightly different from the World Health Organization definition who defined a biomarker as “any substance, structure, or process that can be measured in the body or its products and influence or predict the incidence of outcome or disease” [7Strimbu K, Tavel JA. What are biomarkers? Curr Opin HIV AIDS 2010; 5(6): 463-6.
[http://dx.doi.org/10.1097/COH.0b013e32833ed177] [PMID: 20978388]
].

3.2. Materials of the Biomarkers Extraction

The biomarkers can be extracted from blood, tears, urine, saliva, Cerebrospinal Fluid (CSF), genes, immunity factors and additionally interpreted via imaging techniques [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. The methods used vary depending on the substance or object of measurement focus. Blood is the easiest and most available source in terms of infection control, excluding saliva, tears and urine. The limitations of samples gathered from blood come from concomitant conditions affecting serums substrate levels such as kidney functions, liver functions and infections [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. Additionally, circadian rhythm has been shown to cause fluctuations in serum biomarker level [8Perry MG, Kirwan JR, Jessop DS, Hunt LP. Overnight variations in cortisol, interleukin 6, tumour necrosis factor alpha and other cytokines in people with rheumatoid arthritis. Ann Rheum Dis 2009; 68(1): 63-8.
[http://dx.doi.org/10.1136/ard.2007.086561] [PMID: 18375536]
, 9Wipfler P, Heikkinen A, Harrer A, et al. Circadian rhythmicity of inflammatory serum parameters: A neglected issue in the search of biomarkers in multiple sclerosis. J Neurol 2013; 260(1): 221-7.
[http://dx.doi.org/10.1007/s00415-012-6622-3] [PMID: 22875099]
]. Cerebrospinal Fluid (CSF) is unbeatable in providing biomarkers, as its connection to the CNS is indisputable. Neither CSF is affected by liver or kidney functions [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. The downside in the CSF is the invasiveness of the sample collection procedure and the reported fluctuations in the circadian rhythm. It has been hypothesized that a sample collection during morning hours after night fasting is the most optimal time [10Grady SP, Nishino S, Czeisler CA, Hepner D, Scammell TE. Diurnal variation in CSF orexin-A in healthy male subjects. Sleep 2006; 29(3): 295-7.
[http://dx.doi.org/10.1093/sleep/29.3.295] [PMID: 16553014]
, 11Poceta JS, Parsons L, Engelland S, Kripke DF. Circadian rhythm of CSF monoamines and hypocretin-1 in restless legs syndrome and Parkinson’s disease. Sleep Med 2009; 10(1): 129-33.
[http://dx.doi.org/10.1016/j.sleep.2007.11.002] [PMID: 18207455]
].

To extract biomarkers, excretory sources - urine, saliva and tears are analysed. Urine is the easiest to collect, usually 24-hour urine collection is taken. Only bacterial infections may distort a sample biomarker levels [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. Saliva is used mainly for soluble Human Leukocyte Antigen (HLA) type II [12Minagar A, Adamashvili I, Kelley RE, Gonzalez-Toledo E, McLarty J, Smith SJ. Saliva soluble HLA as a potential marker of response to interferon-β 1a in multiple sclerosis: A preliminary study. J Neuroinflammation 2007; 4(1): 16.
[http://dx.doi.org/10.1186/1742-2094-4-16] [PMID: 17601341]
]. Oligoclonal Bands (OCBs) have been measured from tears, with similar results to those of CSF [13Calais G, Forzy G, Crinquette C, et al. Tear analysis in clinically isolated syndrome as new multiple sclerosis criterion. Mult Scler 2010; 16(1): 87-92.
[http://dx.doi.org/10.1177/1352458509352195] [PMID: 20028709]
]. Within imaging techniques, magnetic resonance imaging (MRI) is still considered as the golden standard when it comes to biomarkers in MS [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. However, there are more novel and advanced imaging techniques being developed that will be dealt with further below.

3.3. Methods and Techniques of the Biomarkers Extraction

3.3.1. Enzyme-Linked Immunosorbent Assay

Enzyme-Linked Immunosorbent Assay (ELISA) as a solid-phase technique may be classified into two main types: (1) competitive assays using either an antigen-enzyme conjugate or an antibody-enzyme conjugate, and (2) non-competitive assays using a double antibody “sandwich” technique where the second antibody has an indicator enzyme conjugated to it [14Reen DJ. Enzyme-linked immunosorbent assay (ELISA).Basic Protein and Peptide Protocols 1994; 461-6. Internet [cited 2018 Jan 17] http://link.springer.com/10.1385/0-89603 -268-X:461
[http://dx.doi.org/10.1385/0-89603-268-X:461]
]. ELISA can be performed with every substance that yields antibodies or antigens.

3.3.2. Polymerase Chain Reaction

Polymerase Chain Reaction (PCR) provides the researcher with the ability to detect genetic information. MS has a significant genetic component, which can be detected using PCR (such as HLA-DRB1). Basic components of the method are primers (short DNA fragments sequences complementary to the target area), as well as a DNA polymerase, which enhances the replication. Quantitative PCR methods include competitive, non-competitive, and real-time PCR [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
].

3.3.3. Immunofluorescence

Immunofluorescence is a technique that uses the specificity of antibodies to their antigen to target fluorescent dyes to specific biomolecule targets within a cell, and therefore allows visualization of the target molecule distribution through the sample. The specific region an antibody recognizes on an antigen is called an epitope. There are two types of immunofluorescence direct and indirect, which refers to the use of one or two antibodies respectively. This is a very specific method that enables the possibility to detect singular haptens, antibodies and proteins of different sizes in vivo [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
].

3.3.4. Flow Cytometry

This is a laser- or impedance-based method where target cells are obtained via cell culture or tissue sample and then suspended in the tubes or microtiter plates. The samples are then dyed by fluorescent-labelled antibodies detecting biomarkers in the form of surface antigens, DNA and RNA variations, protein expression, enzymes, intracellular antigens and then passed through a focused light source (laser) where sensors detect the types of light that are refracted or emitted from the cells. The data is then compiled to build a comprehensive picture of the sample [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
].

3.3.5. Western Blotting

The term refers to a protein detection method, where samples are taken from tissues or cells and then undergo cell lysis to extract proteins. The mixture of proteins is then separated based on molecular weight and then by type through gel electrophoresis. There are also colorimetric and fluorescent detection techniques in conjunction with electrophoresis that have been developed [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
, 15Mahmood T, Yang PC. Western blot: technique, theory, and trouble shooting. N Am J Med Sci 2012; 4(9): 429-34.
[http://dx.doi.org/10.4103/1947-2714.100998] [PMID: 23050259]
].

3.3.6. Isoelectric Focusing

Isoelectric Focusing (IEF) is a technique of impeccable resolution and high sensitivity, which gives it greater discrimination between different biomarkers, immunoglobulins and proteins. As with western blotting, the basic principle behind IEF is gel electrophoresis, however in IEF the proteins move towards their isoelectric PH points [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
, 16Cornell FN. Isoelectric focusing, blotting and probing methods for detection and identification of monoclonal proteins. Clin Biochem Rev 2009; 30(3): 123-30.
[PMID: 19841695]
].

3.3.7. Omics Technologies

“Omics” refers to new arising technologies that make it possible to do empirical analysis and identification of biomarkers in several planes of cell biology, such as DNA, RNA, lipids, proteins, metabolites and epigenetic modifications [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. The omics can be categorized further in: epigenomics: investigates the possible effect that changes in chromatin structure can have in MS prevalence [17Baranzini SE, Mudge J, van Velkinburgh JC, et al. Genome, epigenome and RNA sequences of monozygotic twins discordant for multiple sclerosis. Nature 2010; 464(7293): 1351-6.
[http://dx.doi.org/10.1038/nature08990] [PMID: 20428171]
]; proteomics: delves into protein distribution.; genomics: investigates the entire DNA sequence; transcriptomics: investigates RNA sequences. There are two main types in use, next generation sequencing and microarrays [18Sánchez-Pla A, Reverter F, Ruíz de Villa MC, Comabella M. Transcriptomics: mRNA and alternative splicing. J Neuroimmunol 2012; 248(1-2): 23-31.
[http://dx.doi.org/10.1016/j.jneuroim.2012.04.008] [PMID: 22626445]
]; lipodomics: investigates specific CNS lipid epitopes and cellular lipid pathways [19Quintana FJ, Yeste A, Weiner HL, Covacu R. Lipids and lipid-reactive antibodies as biomarkers for multiple sclerosis. J Neuroimmunol 2012; 248(1-2): 53-7.
[http://dx.doi.org/10.1016/j.jneuroim.2012.01.002] [PMID: 22579051]
]; metabolomics: investigates the significance of metabolic pathways in MS pathogenesis.

3.4. Classification of MS Biomarkers

Various articles divide the biomarkers into different groupings, for example, Paul et al. recommends a three-group classification of MS biomarkers - diagnostic, disease activity, and treatment response biomarker [20Paul A, Comabella M, Gandhi R. Biomarkers in multiple sclerosis. Cold Spring Harb Perspect Med 2019; 9(3)a029058
[http://dx.doi.org/10.1101/cshperspect.a029058] [PMID: 29500303]
]. In this paper, we classify the biomarkers in three distinct categories: laboratory markers - this encompasses bodily fluids; imaging markers - biomarkers achieved by imaging technologies; genetic-immunogenetic markers - biomarkers related to genetics and immunogenetic. These three categories include risk, diagnostic, monitoring, prognostic, predictive, response and safety biomarkers. Further we will provide a more detailed review of each biomarker.

3.4.1. Laboratory biomarkers

3.4.1.1. Biomarkers of Immunological Activation

These biomarkers can be extracted from all bodily fluids. However, the best results are usually achieved from the serum or CSF samples depending on the biomarker. Due to the nature of immunological biomarkers, immunofluorescence or ELISA is the golden standard method for the evaluation.

3.4.1.2. Oligoclonal Band Immunoglobulin G and Immunoglobulin M in the Cerebrospinal Fluid

Oligoclonal bands are IgG class antibodies that are synthesized intrathecally and are evidence of inflammatory events in the central nervous system [21Pryce G, Baker D. Oligoclonal bands in multiple sclerosis; Functional significance and therapeutic implications. Does the specificity matter? Mult Scler Relat Disord 2018; 25: 131-7.
[http://dx.doi.org/10.1016/j.msard.2018.07.030] [PMID: 30071507]
, 22Trbojevic-Cepe M. Detection of oligoclonal ig bands: Clinical significance and trends in methodological improvement. EJIFCC 2004; 15(3): 86-94.
[PMID: 29988915]
]. Advancement risk to Clinically Definite Multiple Sclerosis (CDMS) was discovered to double when Oligoclonal Band (OCB) immunoglobulin G (IgG) was affirmed in the CSF of patients with Clinically Isolated Syndrome (CIS) [23Tintore M, Rovira A, Rio J, Tur C, Pelayo R, Nos C, et al. Do oligoclonal bands add information to MRI in first attacks of multiple sclerosis? Neurology 2008; 70(Issue 13, Part 2): 1079-83.
[http://dx.doi.org/10.1212/01.wnl.0000280576.73609.c6]
]. Other studies also found consistency with positive OCB IgG finding relation into CDMS progression [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
, 24Nilsson P, Larsson E-M, Maly-Sundgren P, Perfekt R, Sandberg-Wollheim M. Predicting the outcome of optic neuritis: Evaluation of risk factors after 30 years of follow-up. J Neurol 2005; 252(4): 396-402.
[http://dx.doi.org/10.1007/s00415-005-0655-9] [PMID: 15778816]
]. Karussis' [25Karussis D. The diagnosis of multiple sclerosis and the various related demyelinating syndromes: a critical review. J Autoimmun 2014; 48-49: 134-42.
[http://dx.doi.org/10.1016/j.jaut.2014.01.022] [PMID: 24524923]
] study reveals that more than 2 ”OCBs in the CSF have a positive predictive value of 97%, a negative predictive value of 84%, a sensitivity of 91%, and a specificity of 94% for developing relapsing remitting MS after a CIS.” They talk about that presence of OCBs within 3 months of CIS nearly doubled the risk of a second clinical attack over 50 months. The diagnostic value of OCB IgG is undisputed in its sensitivity (>90%), however what it gains in sensitivity it lacks in specificity and OCB IgG can be found in other inflammatory disorders of the CNS (~35%) [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. In the revised McDonald criterions OCB seems to Disseminate In Time (DIT) and allows for patients with clinical isolated syndrome making a diagnosis of multiple sclerosis. Mantero et al, in his study reported that “OCBs reassume now a more relevant role in the MS workup and OCBs can be viewed as substitution for the DIT requirement. Its prognostic value remains undiscussed.” [26Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 2018; 17(2): 162-73.
[http://dx.doi.org/10.1016/S1474-4422(17)30470-2] [PMID: 29275977]
]. OCBs are the best biological markers to predict conversion to MS, the above-mentioned study says.

OCB Immunoglobulin M (IgM) in the CSF has not gained the same consideration by researchers as IgG, as it has been found to correlate badly with MS progression [27Mandrioli J, Sola P, Bedin R, Gambini M, Merelli E. A multifactorial prognostic index in multiple sclerosis. Cerebrospinal fluid IgM oligoclonal bands and clinical features to predict the evolution of the disease. J Neurol 2008; 255(7): 1023-31.
[http://dx.doi.org/10.1007/s00415-008-0827-5] [PMID: 18535872]
]. Another study revealed that the data offered no support for the concept that the presence of OCB IgM in the CSF might predict an unfavourable course in MS [28Schneider R, Euler B, Rauer S. Intrathecal IgM-synthesis does not correlate with the risk of relapse in patients with a primary demyelinating event. Eur J Neurol 2007; 14(8): 907-11.
[http://dx.doi.org/10.1111/j.1468-1331.2007.01871.x] [PMID: 17662013]
]. One study however has found data which successfully corroborate that OCB IgM against myelin lipids can predict an aggressive MS course and demonstrate that OCB IgM that do not recognize myelin lipids represent a more benign disease course with a transient immune response [29Villar L, García-Barragán N, Espiño M, et al. Influence of oligoclonal IgM specificity in multiple sclerosis disease course. Mult Scler 2008; 14(2): 183-7.
[http://dx.doi.org/10.1177/1352458507082046] [PMID: 17942517]
].

OCBs are extracted from the CSF then evaluated by immunofluorescence and cross-referenced with imaging techniques to determine correlation disease activity.

3.4.1.3. Measles-Rubella-Zoster Endothecal Reaction

Compared to OCB IgG the Measles-Rubella-Zoster (MRZ) IgG reaction showed improved specificity for MS diagnosis as well as prognostic value for progression from CIS to CDMS [30Brettschneider J, Tumani H, Kiechle U, et al. IgG antibodies against measles, rubella, and varicella zoster virus predict conversion to multiple sclerosis in clinically isolated syndrome. PLoS One 2009; 4(11)e7638
[http://dx.doi.org/10.1371/journal.pone.0007638] [PMID: 19890384]
]. Brettschneider et al. in their study found that MRZR and MRZS could be used as a predictive marker to patients with CIS together with lesions in MRI [31Brettschneider J, Tumani H, Kiechle U, et al. IgG antibodies against measles, rubella, and varicella zoster virus predict conversion to multiple sclerosis in clinically isolated syndrome. PLoS One 2009; 4(11)e7638
[http://dx.doi.org/10.1371/journal.pone.0007638] [PMID: 19890384]
]. They indicate that CIS patients having two or more T2-hyperintense lesions in MRI and a positive MRZS are at highest risk to develop MS and should therefore be candidates for an early beginning of an immunomodulatory therapy. Positive predictive value (PPV) could be increased to 91% by combination of MRZS with MRI (>2 lesions) or by combination of MRZS with MRI (>2 lesions) and OCBs. However, this finding was rarely evaluated systematically because of lack of CSF approved assays that would allow a routine application, which is not restricted to special laboratories. In the studies, positive MRZ reaction patients with MS and negative OCBs have been found [32Jarius S, Eichhorn P, Franciotta D, et al. The MRZ reaction as a highly specific marker of multiple sclerosis: Re-evaluation and structured review of the literature. J Neurol 2017; 264(3): 453-66.
[http://dx.doi.org/10.1007/s00415-016-8360-4] [PMID: 28005176]
]. In the recent study Hottenrott et al. found MRZ reaction -2 specificity to MS and suggests that this could be a useful diagnostic biomarker for distinguishing from other inflammatory neurological diseases [33Hottenrott T, Dersch R, Berger B, et al. The MRZ reaction helps to distinguish rheumatologic disorders with central nervous involvement from multiple sclerosis. BMC Neurol 2018; 18(1): 14.
[http://dx.doi.org/10.1186/s12883-018-1018-3] [PMID: 29386006]
]. They found that MRZR is less frequent in other inflammatory CNS diseases than in MS. Additionally, the MRZ reaction implies a immune response that is mostly B-cell mediated [34Meinl E, Krumbholz M, Hohlfeld R. B lineage cells in the inflammatory central nervous system environment: Migration, maintenance, local antibody production, and therapeutic modulation. Ann Neurol 2006; 59(6): 880-92.
[http://dx.doi.org/10.1002/ana.20890] [PMID: 16718690]
]. This can guide the therapeutically choice towards a suitable immunomodulating agent [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. The IgG for MRZ reaction were isolated from the CSF of the patients and then evaluated via ELISA.

3.4.1.4. Epstein-Barr Virus Reaction

Epstein-Barr Virus (EBV) causes infectious mononucleosis and increases the risk of developing MS. EBV may also contribute to MS pathogenesis indirectly by activating silent human endogenous retrovirus-W [35Guan Y, Jakimovski D, Ramanathan M, Weinstock-Guttman B, Zivadinov R. The role of Epstein-Barr virus in multiple sclerosis: from molecular pathophysiology to in vivo imaging. Neural Regen Res 2019; 14(3): 373-86.
[http://dx.doi.org/10.4103/1673-5374.245462] [PMID: 30539801]
]. High level of IgG antibodies against the Epstein-Barr Viral (EBV) protein epitopes BRRF2 and EBNA-1 in the CSF and serum samples of MS patients has been reported [36Cepok S, Zhou D, Srivastava R, et al. Identification of Epstein-Barr virus proteins as putative targets of the immune response in multiple sclerosis. J Clin Invest 2005; 115(5): 1352-60.
[http://dx.doi.org/10.1172/JCI200523661] [PMID: 15841210]
]. Another study also managed to isolate exceedingly specific T-cells for epitope EBNA-1 from MS patients [37Lünemann JD, Edwards N, Muraro PA, et al. Increased frequency and broadened specificity of latent EBV nuclear antigen-1-specific T cells in multiple sclerosis. Brain 2006; 129(Pt 6): 1493-506.
[http://dx.doi.org/10.1093/brain/awl067] [PMID: 16569670]
]. Furthermore one study showed breach of the Blood-brain Barrier (BBB) endothelial cells with subsequent entry of autoreactive T-cells leading to immune cell adherence which is a decisive step in MS pathogenesis [38Casiraghi C, Dorovini-Zis K, Horwitz MS. Epstein-Barr virus infection of human brain microvessel endothelial cells: A novel role in multiple sclerosis. J Neuroimmunol 2011; 230(1-2): 173-7.
[http://dx.doi.org/10.1016/j.jneuroim.2010.08.003] [PMID: 20826008]
]. Thus EBV antibodies may be associated with increased inflammatory activity in MS patients [39Buljevac D, van Doornum GJ, Flach HZ, et al. Epstein-Barr virus and disease activity in multiple sclerosis. J Neurol Neurosurg Psychiatry 2005; 76(10): 1377-81.
[http://dx.doi.org/10.1136/jnnp.2004.048504] [PMID: 16170080]
] and its potential interaction with both genetic and other environmental factors to increase susceptibility and disease severity of MS [35Guan Y, Jakimovski D, Ramanathan M, Weinstock-Guttman B, Zivadinov R. The role of Epstein-Barr virus in multiple sclerosis: from molecular pathophysiology to in vivo imaging. Neural Regen Res 2019; 14(3): 373-86.
[http://dx.doi.org/10.4103/1673-5374.245462] [PMID: 30539801]
]. In studies, we don`t find that EBV could be used as a biomarker in MS, it is more like a risk factor. Anti-EBV IgG, IgM and Anti-EBNA-1 IgG are extracted from the blood and CSF by ELISA, in turn EBV DNA by PCR.

3.4.1.5. Kappa Free and Lambda Free Light Chains in Cerebrospinal Fluid

Kappa free and Lambda free light chains are B lymphocytes produced proteins during the process of antibody synthesis [40Brebner JA, Stockley RA. Polyclonal free light chains: A biomarker of inflammatory disease or treatment target? F1000 Med Rep 2013; 5: 4.
[http://dx.doi.org/10.3410/M5-4] [PMID: 23413370]
]. Those can be detected in the blood and CSF. Increased amounts of Kappa Free Light Chains (kFLC) in the CSF of MS patients has been frequently reported [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. When compared with OCBs IgG, kFLC showed better sensitivity (96%) while the specificity was lower (86%) for MS patients [41Presslauer S, Milosavljevic D, Brücke T, Bayer P, Hübl W. Elevated levels of kappa free light chains in CSF support the diagnosis of multiple sclerosis. J Neurol 2008; 255(10): 1508-14.
[http://dx.doi.org/10.1007/s00415-008-0954-z] [PMID: 18685917]
]. Villar et al., found that high kFLC in the CSF accurately predicts CIS conversion to MS [42Villar LM, Espiño M, Costa-Frossard L, Muriel A, Jiménez J, Alvarez-Cermeño JC. High levels of cerebrospinal fluid free kappa chains predict conversion to multiple sclerosis. Clin Chim Acta 2012; 413(23-24): 1813-6.
[http://dx.doi.org/10.1016/j.cca.2012.07.007] [PMID: 22814197]
]. Nazarov et al. showed an association between kFLC and the degree of irreversible disability in MS patients. The authors showed that MS patients with high level of kFLC reached disability faster than patients who had low kFLC level, suggesting that it can be a good prognostic marker in MS [43Lo Sasso B, Agnello L, Bivona G, Bellia C, Ciaccio M. Cerebrospinal fluid analysis in multiple sclerosis diagnosis: An update. Medicina (Kaunas) 2019; 55(6): 245.
[http://dx.doi.org/10.3390/medicina55060245] [PMID: 31167509]
]. Lambda Free Light Chain (λFLC) was found to be sensitive in detection of intrathecal immunoglobulin synthesis for inflammatory CNS disorders [44Arneth B, Birklein F. High sensitivity of free lambda and free kappa light chains for detection of intrathecal immunoglobulin synthesis in cerebrospinal fluid. Acta Neurol Scand 2009; 119(1): 39-44.
[http://dx.doi.org/10.1111/j.1600-0404.2008.01058.x] [PMID: 18573131]
]. At present, Kappa free and Lambda free light chains clinical utilization is limited by analytical factors, the absence of reference values and clinically-validated cut-off [43Lo Sasso B, Agnello L, Bivona G, Bellia C, Ciaccio M. Cerebrospinal fluid analysis in multiple sclerosis diagnosis: An update. Medicina (Kaunas) 2019; 55(6): 245.
[http://dx.doi.org/10.3390/medicina55060245] [PMID: 31167509]
]. Kappa free and Lambda free light chains extracted by ELISA.

3.4.1.6. Antibodies Against Myelin Basic Protein and Myelin Oligodendrocyte Glycoprotein

Myelin Oligodendrocyte Glycoproteins (MOG) and Myelin Basic Proteins (MBP) are glycoproteins expressed on the outer membrane of myelin, involved in maintaining myelin structure, and found within the central nervous system. A meta-study found that MOG and MBP prognostic and diagnostic relevance in MS is decidedly controversial. Much of the controversy can be associated with the methodical variation between studies [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. Berger et al., 2003 found that MOG and MBP antibodies would serve as good predictive values for CIS conversion in to CDMS [25Karussis D. The diagnosis of multiple sclerosis and the various related demyelinating syndromes: a critical review. J Autoimmun 2014; 48-49: 134-42.
[http://dx.doi.org/10.1016/j.jaut.2014.01.022] [PMID: 24524923]
, 45Berger T, Rubner P, Schautzer F, et al. Antimyelin antibodies as a predictor of clinically definite multiple sclerosis after a first demyelinating event. N Engl J Med 2003; 349(2): 139-45.
[http://dx.doi.org/10.1056/NEJMoa022328] [PMID: 12853586]
]. Controversially, Kuhle et al., 2007 found that there was no correlation between anti-MOG and anti-MBP IgM or IgG antibodies and progression to CDMS [46Kuhle J, Pohl C, Mehling M, et al. Lack of association between antimyelin antibodies and progression to multiple sclerosis. N Engl J Med 2007; 356(4): 371-8.
[http://dx.doi.org/10.1056/NEJMoa063602] [PMID: 17251533]
]. In the latest studies, it has been found that Anti-MOG positive patients with MS may have a higher risk of progressive disease, high relapses rates and need for escalated therapy. MS patients with positive Anti-MOG observed severe spinal cord and brainstem involvement. Anti-MOG has its own disease phenotype and more related studies are needed. In studies, it is recommended to determine Anti-MOG at the disease onset and in the later stages of the disease because it can fluctuate and indicate on the disease course [47Spadaro M, Gerdes LA, Krumbholz M, et al. Autoantibodies to MOG in a distinct subgroup of adult multiple sclerosis. Neurol Neuroimmunol Neuroinflamm 2016; 3(5)e257
[http://dx.doi.org/10.1212/NXI.0000000000000257] [PMID: 27458601]
]. At the time, Anti-MOG is a biomarker of MOG-associated encephalomyelitis [43Lo Sasso B, Agnello L, Bivona G, Bellia C, Ciaccio M. Cerebrospinal fluid analysis in multiple sclerosis diagnosis: An update. Medicina (Kaunas) 2019; 55(6): 245.
[http://dx.doi.org/10.3390/medicina55060245] [PMID: 31167509]
]. Paul et al. not found utility measuring MBP level in the CSF [20Paul A, Comabella M, Gandhi R. Biomarkers in multiple sclerosis. Cold Spring Harb Perspect Med 2019; 9(3)a029058
[http://dx.doi.org/10.1101/cshperspect.a029058] [PMID: 29500303]
]. We need more studies about Anti-MOG and MS; thus maybe in the future it could be looked upon as the disease predictive biomarker. Anti-MOG is extracted by flow cytometry.

3.4.1.7. Cytokines

Active demyelination causes an inflammatory response which releases a multitude of cytokines that can serve as the biomarkers of MS disease activity [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. Proinflammatory cytokines in the periphery mainly come from T- and B-cells. While in Relapsing Remitting MS (RRMS) the B-cells appear to be primarily accountable for intrathecal generation of cytokines, monocytes adapt a more immunoregulatory aspect in the CSF [48Romme Christensen J, Börnsen L, Hesse D, et al. Cellular sources of dysregulated cytokines in relapsing-remitting multiple sclerosis. J Neuroinflammation [Internet] 2012. Dec [cited 2018 Jan 27]; 9(1). Available from: http://jneuroinflammation.biomedcentral.com/articles/10.1186/1742-2094-9-215]. IL-6 acts as a connecting link between T-cell and B-cell immune response along with the Th-17 response triggering factor. The IL-6 levels in the serum correlated notably with relapse frequency [49Chen Y-C, Yang X, Miao L, et al. Serum level of interleukin-6 in Chinese patients with multiple sclerosis. J Neuroimmunol 2012; 249(1-2): 109-11.
[http://dx.doi.org/10.1016/j.jneuroim.2012.04.015] [PMID: 22633195]
].

Recent research has indicated that a Single Nucleotide Polymorphism (SNP) at -592 position of the main anti-inflammatory cytokine IL-10, produced by several immune cells, affects the regulation of the CNS autoimmunity in MS patients among others [50Karimabad MN, Arababadi MK, Hakimizadeh E, et al. Is the IL-10 promoter polymorphism at position -592 associated with immune system-related diseases? Inflammation 2013; 36(1): 35-41.
[http://dx.doi.org/10.1007/s10753-012-9517-7] [PMID: 22886309]
]. Additionally, two studies have shown MS patients to overexpress IL-15 in the CSF and serum [51Schneider R, Mohebiany AN, Ifergan I, et al. B cell-derived IL-15 enhances CD8 T cell cytotoxicity and is increased in multiple sclerosis patients. J Immunol 2011; 187(8): 4119-28.
[http://dx.doi.org/10.4049/jimmunol.1100885] [PMID: 21911607]
, 52Rentzos M, Cambouri C, Rombos A, et al. IL-15 is elevated in serum and cerebrospinal fluid of patients with multiple sclerosis. J Neurol Sci 2006; 241(1-2): 25-9.
[http://dx.doi.org/10.1016/j.jns.2005.10.003] [PMID: 16316662]
]. Dimisianos et al. [53Dimisianos N, Rodi M, Kalavrizioti D, Georgiou V, Papathanasopoulos P, Mouzaki A. Cytokines as biomarkers of treatment response to IFNb in relapsing-remitting multiple sclerosis 2014; 1-8.] in their study about “Cytokines as biomarkers of treatment response to IFNb in relapsing-remitting multiple sclerosis” found that IL-17A could be a treatment response biomarker. According to the above-mentioned study, high serum baseline level of IL-17A has a good treatment response to IFNb. They express the view that it is associated with IFNb effect on the IL-17A reduction. In their study, they found that a patient with EDSS < 3 and disease duration of 10 years without treatment, has low level of all serum proinflammatory cytokines and few gadolinium enhancement lesion on MRI and low level of inflammatory cells in the CSF.

Mouzaki et al. [54Mouzaki A, Rodi M, Dimisianos N, et al. Immune parameters that distinguish multiple sclerosis patients from patients with other neurological disorders at presentation. PLoS One 2015; 10(8)e0135434
[http://dx.doi.org/10.1371/journal.pone.0135434] [PMID: 26317430]
] in their study investigated signature cytokines in MS patient that can distinguish from other inflammatory CNS diseases. They found the parameter distinguishing multiple sclerosis patient from other CNS inflammatory diseases - IgG intrathecal synthesis, IgG index and IL-4 level in the CSF. They did not find statistically significant differences between age and sex in MS and other inflammatory diseases. Cytokines level are higher in the serum than in the CSF, with one exception of CSF IL-6 levels. The cytokines could be extracted by ELISA.

3.4.1.8. Chemokines

CXCL13 is a chemokine that activates B-cells and T-helper cells through interaction with CXCR5 receptors towards demyelination lesions [55Kowarik MC, Cepok S, Sellner J, Grummel V, Weber MS, Korn T, et al. CXCL13 is the major determinant for B cell recruitment to the CSF during neuroinflammation. J Neuroinflammation [Internet] 2012. Dec [cited 2018 Jan 27]; 9(1). Available from: http://jneuroinflammation.biomedcentral.com/articles/10.1186/1742-2094-9-93, 56Sellebjerg F, Börnsen L, Khademi M, et al. Increased cerebrospinal fluid concentrations of the chemokine CXCL13 in active MS. Neurology 2009; 73(23): 2003-10.
[http://dx.doi.org/10.1212/WNL.0b013e3181c5b457] [PMID: 19996075]
]. Increased level of CXCL13 has been found in both CIS and CDMS patients [56Sellebjerg F, Börnsen L, Khademi M, et al. Increased cerebrospinal fluid concentrations of the chemokine CXCL13 in active MS. Neurology 2009; 73(23): 2003-10.
[http://dx.doi.org/10.1212/WNL.0b013e3181c5b457] [PMID: 19996075]
] while Khademi et al. came to the conclusion that CXCL13 at higher level is predicted CIS conversation to MS [57Khademi M, Kockum I, Andersson ML, et al. Cerebrospinal fluid CXCL13 in multiple sclerosis: A suggestive prognostic marker for the disease course. Mult Scler 2011; 17(3): 335-43.
[http://dx.doi.org/10.1177/1352458510389102] [PMID: 21135023]
]. Karussis reveals that CXCL13 could be the best positive predictive value to CIS conversion to CDMS combining it with MRI [25Karussis D. The diagnosis of multiple sclerosis and the various related demyelinating syndromes: a critical review. J Autoimmun 2014; 48-49: 134-42.
[http://dx.doi.org/10.1016/j.jaut.2014.01.022] [PMID: 24524923]
]. Ferraro et al. in their study found correlation between CXCL13 level in the CSF and cell count, total protein, IgG index, and OCBs patient with CIS and they are at level that could be a good positive predictive value and specificity for MS diagnosis [58Ferraro D, Galli V, Vitetta F, et al. Cerebrospinal fluid CXCL13 in clinically isolated syndrome patients: Association with oligoclonal IgM bands and prediction of Multiple Sclerosis diagnosis. J Neuroimmunol 2015; 283: 64-9.
[http://dx.doi.org/10.1016/j.jneuroim.2015.04.011] [PMID: 26004159]
]. Another chemokine, CXCL12 has shown to possess a protective aspect versus CNS inflammation in Experimental Autoimmune Encephalomyelitis (EAE), however the data are still in experimental stages [59Miljković D, Stanojević Z, Momcilović M, Odoardi F, Flügel A, Mostarica-Stojković M. CXCL12 expression within the CNS contributes to the resistance against experimental autoimmune encephalomyelitis in Albino Oxford rats. Immunobiology 2011; 216(9): 979-87.
[http://dx.doi.org/10.1016/j.imbio.2011.03.013] [PMID: 21601937]
]. CXCL13 from the CSF extracted by ELISA.

3.4.1.9. Adhesion Molecules and Osteopontin

The elevated level of soluble intercellular adhesion molecules (sICAMs) in the CSF are caused by proinflammatory cytokines. Increased MS activity has been reported in conjunction with elevated ICAM-1 molecule levels [60Acar G, İdiman F, Kirkali G, et al. Intrathecal sICAM-1 production in multiple sclerosis-correlation with triple dose Gd-DTPA MRI enhancement and IgG index. J Neurol 2005; 252(2): 146-50.
[http://dx.doi.org/10.1007/s00415-005-0618-1] [PMID: 15729518]
]. Osteopontin is a phosphoprotein derived from macrophages which amplifies IL-12 and INF-γ levels while diminishing the levels of neuroprotective IL-10 [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. Osteopontin levels in the serum and CSF have been reportedly elevated in an active MS relapse episode [61Braitch M, Nunan R, Niepel G, Edwards LJ, Constantinescu CS. Increased osteopontin levels in the cerebrospinal fluid of patients with multiple sclerosis. Arch Neurol [Internet] 2008. May 1 [cited 2018 Jan 30]; 65(5). Available from: http://archneur.jamanetwork.com/article.aspx?doi=10.1001/archneur.65.5.633
[http://dx.doi.org/10.1001/archneur.65.5.633]
]. ELISA is used as an extraction method.

3.4.1.10. Neurofilament Light Chain

The Neurofilament Light Chain (NfL) is a major structural protein that occurs exclusively in neurons, myelinated axons. NfL chains level increases in axonal damage. It shows axonal damage in MS patients in the early stage of MS. It may be increased in patients with other neurodegenerative diseases too, like Alzheimer`s disease. It can be determined in the blood and in the cerebrospinal fluid, last studies have shown that the blood NfL measured with a highly Sensitive Single Molecule Array (SIMOA) are strongly correlated with NfL in the CSF of patients with MS [62Disanto G, Barro C, Benkert P, et al. Swiss Multiple Sclerosis Cohort Study Group. Serum Neurofilament light: A biomarker of neuronal damage in multiple sclerosis. Ann Neurol 2017; 81(6): 857-70.
[http://dx.doi.org/10.1002/ana.24954] [PMID: 28512753]
, 63Barro C, Benkert P, Disanto G, et al. Serum neurofilament light chain as a predictor of disease worsening and brain and spinal cord atrophy in multiple sclerosis 2018; 30.]. That allows to take a blood sample and detect NfL in an easier way. NfL chains level increases in all stages of MS and correlates with clinical expression and MRI findings. Moreover, it is a promising marker in the future as the disease activity, predictive marker and treatment response marker. It is confirmed also by Karussis [25Karussis D. The diagnosis of multiple sclerosis and the various related demyelinating syndromes: a critical review. J Autoimmun 2014; 48-49: 134-42.
[http://dx.doi.org/10.1016/j.jaut.2014.01.022] [PMID: 24524923]
] in his study. Where it says that NfL are potential CSF biomarkers for disease progression, as their presence at high levels may reflect acute axonal damage and imply a prognostic value for conversion from CIS to CDMS. But we need more long-term cohorts to understand how it works in long term [64Barro C, Leocani L, Leppert D, Comi G, Kappos L, Kuhle J. Fluid biomarker and electrophysiological outcome measures for progressive MS trials. Mult Scler 2017; 23(12): 1600-13.
[http://dx.doi.org/10.1177/1352458517732844] [PMID: 29041870]
-66Novakova L, Zetterberg H, Sundström P, et al. Monitoring disease activity in multiple sclerosis using serum neurofilament light protein. Neurology 2017; 89(22): 2230-7.
[http://dx.doi.org/10.1212/WNL.0000000000004683] [PMID: 29079686]
].

3.4.1.11. Vascular Endothelial Growth Factor-A

The Vascular Endothelial Growth Factor-A (VEGF-A) possesses neuroprotective properties [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
], VEGF-A is extracted by flow cytometry. Reduced m-RNA expression of VEGF-A in monocytes of the serum from patients with Secondary Progressive MS (SPMS) in comparison to RRMS patients were found to have, thus setting VEGF-A up as possible biomarker for RRMS progression to SPMS [67Iacobaeus E, Amoudruz P, Ström M, et al. The expression of VEGF-A is down regulated in peripheral blood mononuclear cells of patients with secondary progressive multiple sclerosis. PLoS One 2011; 6(5)e19138
[http://dx.doi.org/10.1371/journal.pone.0019138] [PMID: 21573104]
].

3.4.1.12. Vitamin D

Vitamin D is derived from cholesterol, and has an immunomodulatory function controlling the transcription of a lot of genes relating to immunity. Vitamin D levels measured by a high-performance liquid chromatography. Many epidemiological studies have found correlation with latitude from the equator and level of sun exposure and higher relative MS occurrence risk. Vitamin D can be considered a neuroprotective agent as it activates many neurotrophic factors and suppresses Th-1 immune response in many ways [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. Another study found that vitamin D intake has a protective effect on MS risk [68Munger KL, Zhang SM, O’Reilly E, et al. Vitamin D intake and incidence of multiple sclerosis. Neurology 2004; 62(1): 60-5.
[http://dx.doi.org/10.1212/01.WNL.0000101723.79681.38] [PMID: 14718698]
]. Ramagopalan et al [69Ramagopalan SV, Maugeri NJ, Handunnetthi L, et al. Expression of the multiple sclerosis-associated MHC class II Allele HLA-DRB1*1501 is regulated by vitamin D. PLoS Genet 2009; 5(2)e1000369
[http://dx.doi.org/10.1371/journal.pgen.1000369] [PMID: 19197344]
] found a direct link between vitamin D and HLA-DRB1*15 gene expression. They found a VDRE on the HLA-DRB1*15 gene promoter and showed VDR binding in vitro (EMSA) and ex-vivo (ChiP). The authors proposed that a lack of vitamin D in utero or early childhood can affect the expression of HLA-DRB1 in the thymus, impacting on central deletion. For MS, in HLA-DRB1*15 bearing individuals, a lack of vitamin D during early life could allow auto reactive T cells to escape thyme deletion and thus increase autoimmune disease risk. To note, antigen presentation in the thymus of VDR knock-out mice is impaired. As we know natural killer T cells have an important role in immune regulation and Vitamin D regulates T cell response but not T cell development. Yu et al. [70Yu S, Cantorna MT. The vitamin D receptor is required for iNKT cell development. Proc Natl Acad Sci USA 2008; 105(13): 5207-12.
[http://dx.doi.org/10.1073/pnas.0711558105] [PMID: 18364394]
] in their study found that VDR has an important role on V14 invariant NKT (iNKT) cells development and if VDR are absent it is results an iNKT cells diminished in the thymus and the periphery. Mowry et al. in their study found that low D vitamin level has association with MS activity in the MRI - new lesions and gadolinium-enhancing lesions on the brain MRI [71Mowry EM, Waubant E, McCulloch CE, et al. Vitamin D status predicts new brain magnetic resonance imaging activity in multiple sclerosis. Ann Neurol 2012; 72(2): 234-40.
[http://dx.doi.org/10.1002/ana.23591] [PMID: 22926855]
]. In another study, Mowry et al. found that vitamin D could reduce neurodegeneration after CIS and could reduce long-term disability in MS patients [72Mowry EM, Pelletier D, Gao Z, Howell MD, Zamvil SS, Waubant E. Vitamin D in clinically isolated syndrome: Evidence for possible neuroprotection. Eur J Neurol 2016; 23(2): 327-32.
[http://dx.doi.org/10.1111/ene.12844] [PMID: 26518224]
]. Vitamin D with its neuroprotective feature can be used as a part of the treatment and maybe in the future it could be as a predictive biomarker. In this case, we need more studies.

3.4.1.13. B-cells

A study investigated the difference in inflammatory response between CIS and different stage MS patients and found that mature B-cell as well as plasma-blast levels were elevated in the CSF of both CIS and RRMS patients, correlating positively with increased disease activity [73Kuenz B, Lutterotti A, Ehling R, et al. Cerebrospinal fluid B cells correlate with early brain inflammation in multiple sclerosis. PLoS One 2008; 3(7)e2559
[http://dx.doi.org/10.1371/journal.pone.0002559] [PMID: 18596942]
]. Intrathecal production of centroblasts, a B-cell subset found exclusively in secondary lymphoid organs, in the CSF of MS patients has also been reported [74Corcione A, Casazza S, Ferretti E, et al. Recapitulation of B cell differentiation in the central nervous system of patients with multiple sclerosis. Proc Natl Acad Sci USA 2004; 101(30): 11064-9.
[http://dx.doi.org/10.1073/pnas.0402455101] [PMID: 15263096]
]. B cells have a significant role in MS pathogenesis and the latest studies are focused with the B cells role in the treatment [75Claes N, Fraussen J, Stinissen P, Hupperts R, Somers V. B cells are multifunctional players in multiple sclerosis pathogenesis: Insights from therapeutic interventions. Front Immunol 2015; 6: 642.
[http://dx.doi.org/10.3389/fimmu.2015.00642] [PMID: 26734009]
].

3.4.1.14. T-cells

T-cells use the CXCR3 cytokine receptor to enter the CNS. CXCR3 however has a weak specificity value for MS because of its prominence in other inflammatory disorders [76Liu L, Callahan MK, Huang D, Ransohoff RM. Chemokine receptor CXCR3: An unexpected enigma.Current Topics in Developmental Biology 2005; 149-81.http://linkinghub.elsevier.com/retrieve/pii/S0070215305680064 Internet [cited 2018 Mar 13]]. The T-cells and specifically CD4(+) CD28(-) cells were shown to migrate and accumulate in the CNS lesions of MS. The migration occurred in response to a chemotactic gradient of fractalkine, where they then demonstrated cytotoxic effects in the target tissue contributing to the inflammatory process of MS [77Broux B, Pannemans K, Zhang X, et al. CX(3)CR1 drives cytotoxic CD4(+)CD28(-) T cells into the brain of multiple sclerosis patients. J Autoimmun 2012; 38(1): 10-9.
[http://dx.doi.org/10.1016/j.jaut.2011.11.006] [PMID: 22123179]
]. T cells have a phenotypic and transcription signature of myelin-reactive T cells in MS patients and may act as MS progression and pathogenesis [78Cao Y, Goods BA, Raddassi K, et al. Functional inflammatory profiles distinguish myelin-reactive T cells from Patients with Multiple Sclerosis. Science Translational Medicine 2015; 7(287): 287ra74-287ra74.], but to use it as a biomarker is still debatable.

3.4.1.15. Natural Killer Cells

Natural Killer (NK) cell surface antigen CD-56 was found to exist in high levels in the RRMS patients at remission. A recent study has successfully linked NK cell-mediated negative immunoregulation of activated T cells in MS [79Bielekova B, Catalfamo M, Reichert-Scrivner S, et al. Regulatory CD56(bright) natural killer cells mediate immunomodulatory effects of IL-2Ralpha-targeted therapy (daclizumab) in multiple sclerosis. Proc Natl Acad Sci USA 2006; 103(15): 5941-6.
[http://dx.doi.org/10.1073/pnas.0601335103] [PMID: 16585503]
].

3.4.1.16. T-cell Receptor Excision Circles

They are intracellular side products of T-cell receptor remodelling. The presence of T-cell Receptor Excision Circles (TRECs) inside a T-cell has been found to be a good indicator of T-cell naivety. This comes in useful when measuring the functional state of the thyroid gland, which can be evaluated by the percentage of naive T-cells circulating in peripheral blood. Decreased levels of TRECs in MS patients have been observed indicating deteriorated thyroid function in the disease. Naive T-cells were found to be increasingly decreased in patients with Primary Progressive Multiple Sclerosis (PPMS), opposed to RRMS [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
].

3.4.1.17. Lipocalin 2

Lipocalins are proteins which transport tiny hydrophobic molecules and are thereby involved in many processes of the immune system. The gene encoding Lipocalin 2 was found upregulated in relapses of Experimental Autoimmune Encephalomyelitis (EAE) mouse model of MS, primarily arising from neutrophils infiltrating the choroid plexus, as well as astrocytes in affected regions. Additionally, increased levels of lipocalin 2 from the CSF were found in two separate MS cohorts. Marques et al. in their study found that lipocalin 2 levels in the cerebrospinal fluid coincided with the active phases of the disease. The increase of lipocalin 2 in the cerebrospinal fluid was reverted by immunomodulatory therapy. They mention that lipocalin 2 could be a diagnostic or monitoring biomarker [80Marques F, Mesquita SD, Sousa JC, Coppola G, Gao F, Geschwind DH, et al. Lipocalin 2 is present in the EAE brain and is modulated by natalizumab. Front Cell Neurosci [Internet] 2012. [cited 2018 Mar 30]; 6. Available from: http://journal.frontiersin.org/article/10.3389/fncel. 2012.00033/abstract
[http://dx.doi.org/10.3389/fncel.2012.00033]
].

3.4.1.18. Matrix Metalloproteinase Proteins

In primary progressive MS serum and CSF Matrix Metalloproteinase Protein (MMP) levels are constantly increased, specifically MMP-9 which were elevated even in patients with RRMS [81Avolio C, Ruggieri M, Giuliani F, et al. Serum MMP-2 and MMP-9 are elevated in different multiple sclerosis subtypes. J Neuroimmunol 2003; 136(1-2): 46-53.
[http://dx.doi.org/10.1016/S0165-5728(03)00006-7] [PMID: 12620642]
]. Autoimmune CCR2(+) CCR5(+) CCR6(-) Th1 cells play a crucial role in the pathogenesis of MS. The CCR2(+) CCR5(+) T cells constitute a unique population selectively enriched in the cerebrospinal fluid of MS patients during relapse. CCR2(+) CCR5(+) T cells exhibited a distinct ability to produce matrix metalloproteinase-9 and osteopontin, which are involved in the CNS pathology of MS [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
, 82Sato W, Tomita A, Ichikawa D, et al. CCR2(+)CCR5(+) T cells produce matrix metalloproteinase-9 and osteopontin in the pathogenesis of multiple sclerosis. J Immunol 2012; 189(10): 5057-65.
[http://dx.doi.org/10.4049/jimmunol.1202026] [PMID: 23071279]
].

3.4.1.19. Ninjurin - 1

Ninjurin - 1 expression by endothelial cells of the blood brain barrier (BBB) and myeloid antigen-presenting cells (APCs) has an essential role in the transmigration and localization of the APCs inside the CNS, as proven by proteomic screening of human BBB cells. These APCs along with activated microglia are thought to be pivotal in the initiation of the Central Nervous System (CNS) - targeted immune response in MS and EAE. Ninjurin - 1 levels were found to be increased in active demyelinating lesions, while Ninjurin - 1 neutralization was shown to decrease migration of APCs across the BBB. Finally, complete blockade of Ninjurin - 1 reduced clinical MS activity and histopathological indices of EAE as well as decreased infiltration of macrophages, dendritic cells and APCs into the central nervous system [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
, 83Ifergan I, Kebir H, Terouz S, et al. Role of Ninjurin-1 in the migration of myeloid cells to central nervous system inflammatory lesions. Ann Neurol 2011; 70(5): 751-63.
[http://dx.doi.org/10.1002/ana.22519] [PMID: 22162058]
].

3.4.2. Imaging Biomarkers

3.4.2.1. Magnetic Resonance Imaging

Magnetic Resonance Imaging (MRI) is an essential tool for MS diagnostics, as well as for monitoring treatment and disease activity. MRI gives the clinician a vast array of neuroinflammatory biomarkers to work with. However, typical MRI approach methods lack in proper correlation with MS disability advancement and signs of neurodegeneration [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. MRI has great opportunities with different sequences.

T1 lesions with contrast enhancement: biomarkers of acute neuroinflammation. T1 lesions are thought as the gold standard for the blood brain barrier disruption imaging. Several recent studies have indicated that the same diagnosis could be reached in several instances without contrast enhancement, but with combinations of T1, T2 and T2-weighted FLAIR imaging characteristics alone [84Shinohara RT, Goldsmith J, Mateen FJ, Crainiceanu C, Reich DS. Predicting breakdown of the blood-brain barrier in multiple sclerosis without contrast agents. AJNR Am J Neuroradiol 2012; 33(8): 1586-90.
[http://dx.doi.org/10.3174/ajnr.A2997] [PMID: 22442041]
].

MS lesions typically appear in areas of high signal on T2 weighted MRI. However, a proportion of these lesions, when viewed on T1 weighted MRI, appear hypointense compared with the surrounding white matter. Hyperintense T2-weighted lesions, which reflect a multitude of mechanisms such as inflammation, demyelination, axonal damage and edema. The diagnostic significance is high, but the correlation with disability is moderate [85Brex PA, Ciccarelli O, O’Riordan JI, Sailer M, Thompson AJ, Miller DH. A longitudinal study of abnormalities on MRI and disability from multiple sclerosis. N Engl J Med 2002; 346(3): 158-64.
[http://dx.doi.org/10.1056/NEJMoa011341] [PMID: 11796849]
]. Hypointense T1-weighted lesions (also known as black holes), while they are considered as moderate biomarkers for axonal damage, their correlation with MS disability is debatable [86Brex PA, Parker GJ, Leary SM, et al. Lesion heterogeneity in multiple sclerosis: a study of the relations between appearances on T1 weighted images, T1 relaxation times, and metabolite concentrations. J Neurol Neurosurg Psychiatry 2000; 68(5): 627-32.
[http://dx.doi.org/10.1136/jnnp.68.5.627] [PMID: 10766895]
, 87Sahraian MA, Radue E-W, Haller S, Kappos L. Black holes in multiple sclerosis: definition, evolution, and clinical correlations. Acta Neurol Scand 2010; 122(1): 1-8.
[http://dx.doi.org/10.1111/j.1600-0404.2009.01221.x] [PMID: 20003089]
]. Karussis' [25Karussis D. The diagnosis of multiple sclerosis and the various related demyelinating syndromes: a critical review. J Autoimmun 2014; 48-49: 134-42.
[http://dx.doi.org/10.1016/j.jaut.2014.01.022] [PMID: 24524923]
] study revealed that the presence of at least one cortical lesion in CIS may help identify a high-risk patient with conversion to clinically definite MS.

The most broadly used whole brain atrophy biomarker is the brain parenchymal fraction. When untreated MS patients were compared with a healthy control group the brain atrophy rates were found to be much higher among the former [88De Stefano N, Giorgio A, Battaglini M, et al. Assessing brain atrophy rates in a large population of untreated multiple sclerosis subtypes. Neurology 2010; 74(23): 1868-76.
[http://dx.doi.org/10.1212/WNL.0b013e3181e24136] [PMID: 20530323]
]. The worsening rate at initial diagnosis has been proposed as a prognostic biomarker for disability progression [89Fisher E, Rudick RA, Simon JH, et al. Eight-year follow-up study of brain atrophy in patients with MS. Neurology 2002; 59(9): 1412-20.
[http://dx.doi.org/10.1212/01.WNL.0000036271.49066.06] [PMID: 12427893]
]. Sormani et el. found that the brain atrophy correlated with the disease disability and treatment efficacy [90Sormani MP, Arnold DL, De Stefano N. Treatment effect on brain atrophy correlates with treatment effect on disability in multiple sclerosis. Ann Neurol 2014; 75(1): 43-9.
[http://dx.doi.org/10.1002/ana.24018] [PMID: 24006277]
].

Recent longitudinal study found that the grey matter atrophy rates could serve as reliable biomarkers in all forms of MS. Double inversion recovery techniques displayed the grey matter demyelination, axonal damage and atrophy, with increased decline rates in SPMS [91Fisher E, Lee J-C, Nakamura K, Rudick RA. Gray matter atrophy in multiple sclerosis: a longitudinal study. Ann Neurol 2008; 64(3): 255-65.
[http://dx.doi.org/10.1002/ana.21436] [PMID: 18661561]
]. Another study found that increased decline rates of the grey matter atrophy in clinically isolated syndrome patients correlated well with aggressive conversion to RRMS, thus validating the grey matter as prospective biomarker [92Dalton CM, Chard DT, Davies GR, et al. Early development of multiple sclerosis is associated with progressive grey matter atrophy in patients presenting with clinically isolated syndromes. Brain 2004; 127(Pt 5): 1101-7.
[http://dx.doi.org/10.1093/brain/awh126] [PMID: 14998914]
]. The studies disclose the correlation between the grey matter atrophy and clinical disability, cognitive dysfunction that may be useful predictive marker for severity of the disease [91Fisher E, Lee J-C, Nakamura K, Rudick RA. Gray matter atrophy in multiple sclerosis: a longitudinal study. Ann Neurol 2008; 64(3): 255-65.
[http://dx.doi.org/10.1002/ana.21436] [PMID: 18661561]
, 93Geurts JJ, Calabrese M, Fisher E, Rudick RA. Measurement and clinical effect of grey matter pathology in multiple sclerosis. Lancet Neurol 2012; 11(12): 1082-92.
[http://dx.doi.org/10.1016/S1474-4422(12)70230-2] [PMID: 23153407]
, 94Calabrese M, Agosta F, Rinaldi F, et al. Cortical lesions and atrophy associated with cognitive impairment in relapsing-remitting multiple sclerosis. Arch Neurol 2009; 66(9): 1144-50.
[http://dx.doi.org/10.1001/archneurol.2009.174] [PMID: 19752305]
].

The spinal cord atrophy biomarkers focusing on upper cervical cord area imaging techniques have shown apparent atrophy in progressive forms of MS, which have correlated well with disability progression. Upper cervical cord area atrophy in the early stages of RRMS has been regarded as bad prognostic biomarker of future disability [95Rashid W, Davies GR, Chard DT, et al. Increasing cord atrophy in early relapsing-remitting multiple sclerosis: A 3 year study. J Neurol Neurosurg Psychiatry 2006; 77(1): 51-5.
[http://dx.doi.org/10.1136/jnnp.2005.068338] [PMID: 16361592]
].

3.4.2.2. Contrast Magnetization Transfer Ratio

Magnetization Transfer Ratio (MTR) is a sensitive parameter to quantify the integrity of myelinated white matter in patients with multiple sclerosis. This is a novel MRI method that is based on the interaction between protons, free water and macromolecules. In the absence of axonal loss, acute MRI lesions, which display improvement, similarly increase in MTR. MTR therefore might prove a viable outcome measure to assess the effect of remyelinating agents [96van den Elskamp IJ, Knol DL, Vrenken H, et al. Lesional magnetization transfer ratio: A feasible outcome for remyelinating treatment trials in multiple sclerosis. Mult Scler 2010; 16(6): 660-9.
[http://dx.doi.org/10.1177/1352458510364630] [PMID: 20350960]
]. Another study suggests that MTR should be used mainly as an axonal damage biomarker. As seen by their results, regarding optic nerve MTR reduction after optic neuritis showed good correlation with Retinal Nerve Fibre Layer (RNFL) thickness [97Klistorner A, Chaganti J, Garrick R, Moffat K, Yiannikas C. Magnetisation transfer ratio in optic neuritis is associated with axonal loss, but not with demyelination. Neuroimage 2011; 56(1): 21-6.
[http://dx.doi.org/10.1016/j.neuroimage.2011.02.041] [PMID: 21338694]
]. Yet, decisive assessment of treatment outcomes on re-myelination has been shown [98Brown RA, Narayanan S, Arnold DL. Segmentation of magnetization transfer ratio lesions for longitudinal analysis of demyelination and remyelination in multiple sclerosis. Neuroimage 2013; 66: 103-9.
[http://dx.doi.org/10.1016/j.neuroimage.2012.10.059] [PMID: 23110887]
]. MTR has been an effective monitoring tool for pathology in MS.

3.4.2.3. Diffusion Weighted Imaging and Diffusion Tensor Imaging Techniques

Diffusion Weighted Imaging (DWI) method is grounded on the mobility and spatial distribution of water molecules, while Diffusion Tensor Imaging (DTI) measures movement in different directions in the space. DTI method gives four measures, Axial Diffusivity (AD), Radial Diffusivity (RD), Mean Diffusivity (MD) and Fractional Anisotropy (FA) [2Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
]. Axial diffusivity indicates loss of axons, radial diffusivity is related to demyelination, mean diffusivity is average diffusion and fractional anisotropy integrate AD and RD [99Aung WY, Mar S, Benzinger TL. Diffusion tensor MRI as a biomarker in axonal and myelin damage. Imaging Med 2013; 5(5): 427-40.
[http://dx.doi.org/10.2217/iim.13.49] [PMID: 24795779]
, 100Klawiter EC, Schmidt RE, Trinkaus K, et al. Radial diffusivity predicts demyelination in ex vivo multiple sclerosis spinal cords. Neuroimage 2011; 55(4): 1454-60.
[http://dx.doi.org/10.1016/j.neuroimage.2011.01.007] [PMID: 21238597]
].

In hyperintense T2-weighted lesions we can observe an increase in MD and decrease in FA. This type of phenomena can be seen in Normal Appearing White Matter (NAWM) areas in regular MRI, likewise for Normal Appearing Grey Matter (NAGM) areas, more notably on progressive forms of MS [101Bozzali M, Cercignani M, Sormani MP, Comi G, Filippi M. Quantification of brain gray matter damage in different MS phenotypes by use of diffusion tensor MR imaging. AJNR Am J Neuroradiol 2002; 23(6): 985-8.
[PMID: 12063230]
]. Early MS stages show corpus callosum changes in DTI, while regular MRI lesions are still not even present [102Wahl M, Hübers A, Lauterbach-Soon B, et al. Motor callosal disconnection in early relapsing-remitting multiple sclerosis. Hum Brain Mapp 2011; 32(6): 846-55.
[http://dx.doi.org/10.1002/hbm.21071] [PMID: 21495114]
]. MD changes could be used as a dependable biomarker for MS relapse as they precede typical MRI blood brain barrier damage by a minimum of 5 months [103Liu Y, Mitchell PJ, Kilpatrick TJ, et al. Diffusion tensor imaging of acute inflammatory lesion evolution in multiple sclerosis. J Clin Neurosci 2012; 19(12): 1689-94.
[http://dx.doi.org/10.1016/j.jocn.2012.03.022] [PMID: 23084347]
]. Corpus callosum DTI changes in secondary progressive MS have been reported as a bad prognostic biomarker of eventual disability [104Tian W, Zhu T, Zhong J, et al. Progressive decline in fractional anisotropy on serial DTI examinations of the corpus callosum: a putative marker of disease activity and progression in SPMS. Neuroradiology 2012; 54(4): 287-97.
[http://dx.doi.org/10.1007/s00234-011-0885-8] [PMID: 21567135]
].

3.4.2.4. Magnetic Resonance Spectroscopy

In Magnetic Resonance Spectroscopy (MRS) it is possible to measure cellular metabolism in the CNS, which is important in MS and can`t be detected with standard MRI. In MRS usually detect N-acetyl aspartate, choline, creatine, myoinositol, glutamate, glutamine and lactate, which are in the brain and the spinal cord, in small amounts. Neuronal dysfunction is related to a low level of N-acetyl aspartate. Different studies show different points of view - NAA deficits do not correlate significantly with EDSS others found NAA correlation with EDSS. Reduction of N-acetyl aspartate level indicates reduction of oedema at active lessons in the CNS. During active demyelination, the level of choline is elevated; it could be detected up to 12 months prior to the white matter lesion formation. Glutamate converted to glutamine and Gamma-Amino Butyric Acid (GABA). In studies, it was found that the GABA levels are reduced in the hippocampus and sensorimotor cortex for patients with SPMS. MRS takes a longer time to do compared to routine MRI, and MRS has a reduced spatial resolution. Due to the mentioned characteristics, it is not suitable for the clinical practice [105Akbar N, Rudko DA, Parmar K. Magnetic Resonance Imaging of Multiple Sclerosis. Sci J Mult Scler 2017; 1(1): 008-020.].

3.4.2.5. Optical Coherence Tomography

Optical Coherence Tomography (OCT) is a non-invasive method of RNFL thickness estimation. It is done by means of infrared light emission through the pupil and detecting the reflection from retina. RNFL thickness reduction, aka thinning, can be used as a biomarker for axonal loss, which correlates well with the brain atrophy levels as was discussed above [106Grazioli E, Zivadinov R, Weinstock-Guttman B, et al. Retinal nerve fiber layer thickness is associated with brain MRI outcomes in multiple sclerosis. J Neurol Sci 2008; 268(1-2): 12-7.
[http://dx.doi.org/10.1016/j.jns.2007.10.020] [PMID: 18054962]
]. Another study has suggested the use of RNFL thickness as a biomarker for MS disease progression when used in conjunction with MRI techniques [107Herrero R, Garcia-Martin E, Almarcegui C, et al. Progressive degeneration of the retinal nerve fiber layer in patients with multiple sclerosis. Invest Ophthalmol Vis Sci 2012; 53(13): 8344-9.
[http://dx.doi.org/10.1167/iovs.12-10362] [PMID: 23154461]
]. In the last studies, was found thicker RNFL associated with the disease activity in MS, and increased risk of disability. OCT could be used as predictor biomarker of the disease progression [108Saidha S, Sotirchos ES, Ibrahim MA, et al. Microcystic macular oedema, thickness of the inner nuclear layer of the retina, and disease characteristics in multiple sclerosis: a retrospective study. Lancet Neurol 2012; 11(11): 963-72.
[http://dx.doi.org/10.1016/S1474-4422(12)70213-2] [PMID: 23041237]
, 109Martinez-Lapiscina EH, Arnow S, Wilson JA, et al. Retinal thickness measured with optical coherence tomography and risk of disability worsening in multiple sclerosis: a cohort study. Lancet Neurol 2016; 15(6): 574-84.
[http://dx.doi.org/10.1016/S1474-4422(16)00068-5] [PMID: 27011339]
].

3.4.3. Genetic - Immunogenetic Biomarkers

3.4.3.1. Human Leukocyte Antigen

Genetic risk in human leukocyte antigen (HLA) class II antigen polymorphisms seem to be a decisive factor in attributing the genetic burden for MS. Initial studies have found positive interaction between DRB1*1501-DRB5*0101-DQA1*0102-DQB1*0602 haplotypes and disease occurrence. Numerous late researches done in MS cohorts have come to the conclusion that HLA-DRB1*1501 is the allele primarily responsible for the genetic risk in MS [110Schmidt H, Williamson D, Ashley-Koch A. HLA-DR15 haplotype and multiple sclerosis: a HuGE review. Am J Epidemiol 2007; 165(10): 1097-109.
[http://dx.doi.org/10.1093/aje/kwk118] [PMID: 17329717]
-112Bozikas VP, Anagnostouli MC, Petrikis P, et al. Familial bipolar disorder and multiple sclerosis: a three-generation HLA family study. Prog Neuropsychopharmacol Biol Psychiatry 2003; 27(5): 835-9.
[http://dx.doi.org/10.1016/S0278-5846(03)00116-7] [PMID: 12921917]
]. Furthemore, HLA-DRB1*1501 expression is regulated up to a degree by vitamin D through interaction at a genomic level, which explains the known connection in latitude and MS prevalence. Moreover, the coexistence of some alleles likely precipitates augmentation of the comprehensive risk by epistatic mechanisms [113Lincoln MR, Ramagopalan SV, Chao MJ, et al. Epistasis among HLA-DRB1, HLA-DQA1, and HLA-DQB1 loci determines multiple sclerosis susceptibility. Proc Natl Acad Sci USA 2009; 106(18): 7542-7.
[http://dx.doi.org/10.1073/pnas.0812664106] [PMID: 19380721]
]. Additionally, there has been documentation of association with different HLA loci in other studies, like DR3 and DR4 haplotypes [114Marrosu MG, Sardu C, Cocco E, et al. Bias in parental transmission of the HLA-DR3 allele in Sardinian multiple sclerosis. Neurology 2004; 63(6): 1084-6.
[http://dx.doi.org/10.1212/01.WNL.0000138493.04890.7C] [PMID: 15452304]
] and DRB1*04 Hutterite families [115Dyment DA, Cader MZ, Datta A, et al. A first stage genome-wide screen for regions shared identical-by-descent in Hutterite families with multiple sclerosis. Am J Med Genet B Neuropsychiatr Genet 2008; 147B(4): 467-72.
[http://dx.doi.org/10.1002/ajmg.b.30620] [PMID: 18081025]
], which further demonstrate the diversity of MS disease. Haplotype DRB1*1303-DQA1*05-DQB1*030 was found to have a positive association with MS among some Jewish sub-populations.

Confirmatory correlation of HLA-DRB1*1501 allele with OCB in the CSF of MS patients has been found by observations in Asian cohort and was confirmed by successive research efforts [116Kikuchi S, Fukazawa T, Niino M, et al. HLA-related subpopulations of MS in Japanese with and without oligoclonal IgG bands. Human leukocyte antigen. Neurology 2003; 60(4): 647-51.
[http://dx.doi.org/10.1212/01.WNL.0000048202.09147.9E] [PMID: 12601107]
].

Clinical and imaging correlations of HLA-DRB1*15 alleles were found with early onset MS [117Van der Walt A, Stankovich J, Bahlo M, et al. Heterogeneity at the HLA-DRB1 allelic variation locus does not influence multiple sclerosis disease severity, brain atrophy or cognition. Mult Scler 2011; 17(3): 344-52.
[http://dx.doi.org/10.1177/1352458510389101] [PMID: 21149397]
]. One study observed MS patients and found those with positive HLA-DRB1*1501 to have larger T1 lesion burden in MRI and lowest brain atrophy scores [118Zivadinov R, Uxa L, Bratina A, Bosco A, Srinivasaraghavan B, Minagar A, et al. HLA-DRB1*1501, -DQB1*0301, -DQB1*0302, -DQB1*0602, and -DQB1*0603 Alleles are associated with more severe disease outcome on mri in patients with multiple sclerosis [Internet]. In: International Review of Neurobiology. Elsevier; 2007 [cited 2018 Apr 3]. p. 521–535. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0074774207790232]. Another study reported HLA-DRB1*15 positive MS patients to have larger white matter lesions, lower brain atrophy scores as well as declined cognitive function and decreased N-acetyl-aspartate (NAA) levels alongside with NAWM [119Okuda DT, Srinivasan R, Oksenberg JR, et al. Genotype-Phenotype correlations in multiple sclerosis: HLA genes influence disease severity inferred by 1HMR spectroscopy and MRI measures. Brain 2009; 132(Pt 1): 250-9.
[http://dx.doi.org/10.1093/brain/awn301] [PMID: 19022862]
]. Correlation with RRMS and SPMS is still to be fully confirmed [120Stankovich J, Butzkueven H, Marriott M, et al. HLA-DRB1 associations with disease susceptibility and clinical course in Australians with multiple sclerosis. Tissue Antigens 2009; 74(1): 17-21.
[http://dx.doi.org/10.1111/j.1399-0039.2009.01262.x] [PMID: 19392788]
, 121Cournu-Rebeix I, Génin E, Leray E, et al. HLA-DRB1*15 allele influences the later course of relapsing remitting multiple sclerosis. Genes Immun 2008; 9(6): 570-4.
[http://dx.doi.org/10.1038/gene.2008.52] [PMID: 18615093]
].

3.4.3.2. Transducer of ERBB2-1 and Apolipoprotein E

Transducer of ERBB2-1 (TOB-1) gene plays an important role versus T-cell replication by holding autoreactive cells in an inert state. Decreased TOB-1 expression gives rise to a more intensified immune response, with increased Th1 and Th17 cells and further decreased T-regulatory cells. TOB-1 polymorphisms express an autonomous factor affecting the advancement from CIS to CDMS [122Corvol J-C, Pelletier D, Henry RG, et al. Abrogation of T cell quiescence characterizes patients at high risk for multiple sclerosis after the initial neurological event. Proc Natl Acad Sci USA 2008; 105(33): 11839-44.
[http://dx.doi.org/10.1073/pnas.0805065105] [PMID: 18689680]
]. Apolipoprotein E (ApoE) is a protein found mainly in astrocytes, with the function of regulating lipid homeostasis. MS patients found carrying the ε4 allele of ApoE have been attributed on having higher risk of developing psychic disorders. ApoE role as a biomarker for MS showed promising future prospect for a high specificity and sensitivity in animal models of EAE, further study is however required [123Zhang H-L, Wu J, Zhu J. The immune-modulatory role of apolipoprotein E with emphasis on multiple sclerosis and experimental autoimmune encephalomyelitis. Clin Dev Immunol 2010; 2010186813
[http://dx.doi.org/10.1155/2010/186813] [PMID: 20613949]
].

4. DISCUSSION

Multiple sclerosis is a diverse disease with many different forms manifested in a wide variety of ways from patient to patient. Though it is the most common neurodegenerative disorder among adolescents and young adults, there still are many unanswered questions revolving around it, despite extensive research spanning multiple decades. From the etiology to pathogenesis to effective diagnostic methods MS continues to elude humanity’s best efforts in unveiling its secrets. This leads inevitably to a great amount of potential theories and findings in each area, as seen in the above analysis. The biomarkers described above represent the most existing biomarkers for MS. We divided the biomarkers into three subgroups - laboratorial, imaging and genetic-immunogenetic biomarkers, which include risk, diagnostic, monitoring, prognostic, predictive, response and safety biomarkers. Very important task is to find the best biomarker for MS.

The laboratorial biomarkers are by far the most diverse and extensive subgroup of all available biomarkers. They could be affected by circadian fluctuation but, unfortunately, there are not enough studies where circadian fluctuation would have proven its essential role. There are some recommendations on when certain samples should be collected from the CSF or serum. Additionally, the research findings on the effects of circadian rhythm on biomarker levels were hesitantly inconclusive at times due to lack of proper guidelines. Therefore, it is only logical to deem the creation of a standard “time” which should be upheld by future measurements. This would create solid reliable results, which would not be hampered by diversity or fluctuations of circadian rhythm, thus removing the problem. Further studies are required.

We have lot of biomarkers in MS but the highest diagnostic value in laboratorial biomarkers was seen in OCBs, CSF MRZ reaction, NfL and kFLC. The OCBs was found by multiple studies to be a reliable biomarker for transition from CIS to CDMS and is associated with aggressive disease course, with an undisputed sensitivity of above 90 percent. However, it was found to lack specificity (~35%). On the other hand, OCBs are the gold standard in MS diagnosis and it is used as a diagnostic biomarker in MS. In the revised McDonald Diagnostic Criteria of 2017 OCBs are recognized as a dissemination of lesions in time [26Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 2018; 17(2): 162-73.
[http://dx.doi.org/10.1016/S1474-4422(17)30470-2] [PMID: 29275977]
]. We should reconsider MS diagnosis if OCBs are negative; therefore we should be careful and must exclude MS mimics. OCB is detected in the CSF and blood by immunofluorescence. In the CSF sample, should be two or more OCB detected, but in the blood sample - should not. It is simple to use in daily clinical practice. MRZ reaction boasted higher overall specificity as well as predictive value in conversion from CIS to CDMS. MRZ reaction could be used as diagnostic biomarker in MS and as a measure for distinguishing other inflammatory neurological diseases from MS [32Jarius S, Eichhorn P, Franciotta D, et al. The MRZ reaction as a highly specific marker of multiple sclerosis: Re-evaluation and structured review of the literature. J Neurol 2017; 264(3): 453-66.
[http://dx.doi.org/10.1007/s00415-016-8360-4] [PMID: 28005176]
, 33Hottenrott T, Dersch R, Berger B, et al. The MRZ reaction helps to distinguish rheumatologic disorders with central nervous involvement from multiple sclerosis. BMC Neurol 2018; 18(1): 14.
[http://dx.doi.org/10.1186/s12883-018-1018-3] [PMID: 29386006]
, 124Hottenrott T, Dersch R, Berger B, Rauer S, Huzly D, Stich O. The MRZ reaction in primary progressive multiple sclerosis. Fluids Barriers CNS 2017; 14(1): 2.
[http://dx.doi.org/10.1186/s12987-016-0049-7] [PMID: 28166789]
]. MRZ reaction is detected in the CSF by ELISA and it could be used in the clinical practice. But we should keep in mind that only positive MRZ reaction does not prove an MS diagnosis. MRZ reaction could be helpful in situations when OCBs are negative. NfL is a recently founded promising MS biomarker. NfL could be used as the disease activity and treatment response biomarker [125Martin SJ, McGlasson S, Hunt D, Overell J. Cerebrospinal fluid neurofilament light chain in multiple sclerosis and its subtypes: a meta-analysis of case-control studies. J Neurol Neurosurg Psychiatry 2019; 90(9): 1059-67.
[http://dx.doi.org/10.1136/jnnp-2018-319190] [PMID: 31123141]
, 126Kuhle J, Kropshofer H, Haering DA, et al. Blood neurofilament light chain as a biomarker of MS disease activity and treatment response. Neurology 2019; 92(10): e1007-15.
[http://dx.doi.org/10.1212/WNL.0000000000007032] [PMID: 30737333]
]. In the future, we need more studies about NfL, their commitment to co-morbidities and standardized measurement. NfL level is also high in other neurodegenerative diseases; that is the reason why we need more studies about NfL in the future. At the time in the clinical practice, it`s not used as routine measurement, it needs special technique (SIMONA) to detect the NfL in the blood. The kFLC has a 96 per cent sensitivity and an 86 per cent specificity for MS. It has also been found to be a reliable predictive biomarker for CIS conversion into MS and as a prognostic biomarker to MS, to prevent faster disability and escalate therapy. In clinical practice, it is not used, at the time, as a routine test, this is because of its limited analytical factors. More studies on this are needed. These are all biomarkers of immunological activation and while many of the biomarkers in this subgroup possess some predictive value as well as specificity or sensitivity; they are not adequate on their own. Therefore, for a reliable and accurate diagnosis multiple biomarkers should be evaluated simultaneously. At present, we don`t have one single biomarker to detect an MS diagnosis; OCBs are very promising. We should be careful with MS mimics and other inflammatory neurological diseases.

Vitamin D works as a neuroprotector such as Th-1 immune response suppression and a genetic aspect with inhibitory function near the notorious HLA-DRB1*1501 through VDRE. Its levels have shown MS occurrence risk to increase with a distance from the equator by epidemiological correlation studies. Vitamin D level is associated with the MRI activity - higher vitamin D level is associate with lower risk of new lesions in the MRI, while low vitamin D level is strongly associated with new T2 lesions in the brain MRI [71Mowry EM, Waubant E, McCulloch CE, et al. Vitamin D status predicts new brain magnetic resonance imaging activity in multiple sclerosis. Ann Neurol 2012; 72(2): 234-40.
[http://dx.doi.org/10.1002/ana.23591] [PMID: 22926855]
]. We don’t have a specific level of vitamin D supplementation to reduce the risk for MS and MS clinical activity [127Sintzel MB, Rametta M, Reder AT. Vitamin D and Multiple Sclerosis: A Comprehensive Review. Neurol Ther 2018; 7(1): 59-85.
[http://dx.doi.org/10.1007/s40120-017-0086-4] [PMID: 29243029]
]. We need more studies researching vitamin D and maybe in the future we could use vitamin D as predictive biomarker and could predict disease clinical activity and reduce long-term disability in MS patients. Now we use vitamin D in routine clinical practice as dietary supplement. It is easy to be used and detected in the blood.

Cellular subpopulations are extremely diverse, widely disseminated and play an essential role in the pathogenesis, they are present in all stages of MS disease. This also applies to many other inflammatory disorders. Therefore, their specificity tends to be lacking. The B-cell, T-cell and TRECs can all be considered good biomarkers for disease activity, progression between different MS stages and thereby also prognosis up to a degree. Lipocalin 2 has shown similar promise in EAE models, but further study is warranted. Before the mystery around the pathogenesis of multiple sclerosis becomes clearer and the revelations that will be brought forth with it, these biomarkers will likely remain as measurements of MS disease activity. Ninjurin-1 has a major role in the development of neuroinflammatory lesions in the brain. It was found in active lesions in the brain compared with healthy population. Blocking Ninjurin-1 reduces the disease clinical activity and decreases inflammatory cells in the brain [83Ifergan I, Kebir H, Terouz S, et al. Role of Ninjurin-1 in the migration of myeloid cells to central nervous system inflammatory lesions. Ann Neurol 2011; 70(5): 751-63.
[http://dx.doi.org/10.1002/ana.22519] [PMID: 22162058]
]. This could be used as a therapeutic target in the future but not as a biomarker.

Imaging biomarkers present a unique variety of new novel techniques and time proven standardized methods. The MRI is rightfully considered the golden standard for diagnostics of neuroinflammation and neurodegeneration in MS. Contrast enhanced MRI T1 and T2 lesions are undisputable findings indicating MS disease. An MRI could detect new lesions, active lesions, number of lesions and brain atrophy. MRI gives us great options with many sequences and different programs like T1, T2 sequences, DWI, MRS but in the routine clinical practice T1 and T2 sequences are used. While DTI and MRS are not used in the routine clinical practice, those are used in the researches. Standard MRI protocol is recommended for MS. MRI is an essential tool for MS diagnostics and monitoring and it is used as one of the main monitoring and diagnostic biomarkers. OCT has been proven to correlate brain atrophy rates well and thereby with disease progression. Thickness of the retinal inner nuclear layer associated with progression of the disease activity and disability. OCT could be used as predictive biomarker of the disease progression. Thus, use of MRI techniques together with OCT would create a solid biomarker for disease diagnosis, progression and treatment response.

Genetic-immunogenetic biomarkers have been proven by multiple studies to have an unequivocal role in the genetic risk for MS disease presentation. While there are many haplotypes that correlate with disease occurrence the HLA-DRB1*1501 stands above the rest. This was further validated by the discovery of vitamin D inhibitory effect through VDRE on the HLA-DRB1*1501 coding zone. As well as the presence of OCBs in the CSF of HLA-DRB1*1501 allele positive patients. Furthermore HLA-DRB1*1501 was also reported to correlate with clinical and imaging findings. Therefore, its place as a diagnostic marker has been established. However, screening for the HLA-DRB1*15 in CIS patients or those under suspicion might be indicated.

CONCLUSION

In this review, we have seen that there are many biomarkers available with clinical relevance, and it is enough when they are used together. Nevertheless, there does not exist a single solitary biomarker being able to present a reliable diagnostic value, prognostic value, high sensitivity and specificity as well as clinical impact on its own. At the time, a biomarker plays a crucial role in the clinical practice to diagnose MS is MRI and OCBs. Recent studies have shown good results as a biomarker of the disease diagnosis can be MRZ reaction and OCT. OCT could also be used as the disease progression and treatment response biomarker. In the future, hopefully, the disease monitoring and treatment responsible biomarker could be NfL. The above mentioned, biomarkers are used together, complementing each other. In case of some negative biomarker, one should be very careful with making MS diagnosis. We need more studies about MS biomarkers in the future, to provide better disease monitoring and treatment response.

CONSENT FOR PUBLICATION

Not applicable.

FUNDING

None.

CONFLICT OF INTEREST

The authors declare no conflict of interest, financial or otherwise.

ACKNOWLEDGEMENTS

Declared none.

REFERENCES

[1] Rosati G. The prevalence of multiple sclerosis in the world: An update. Neurol Sci 2001; 22(2): 117-39.
[http://dx.doi.org/10.1007/s100720170011] [PMID: 11603614]
[2] Katsavos S, Anagnostouli M. Biomarkers in multiple sclerosis: An up-to-date overview. Mult Scler Int 2013; 2013340508
[http://dx.doi.org/10.1155/2013/340508] [PMID: 23401777]
[3] Ghasemi N, Razavi S, Nikzad E. Multiple sclerosis: Pathogenesis, symptoms, diagnoses and cell-based therapy. Cell J 2017; 19(1): 1-10.
[PMID: 28367411]
[4] Frohman EM, Racke MK, Raine CS. Multiple sclerosis-the plaque and its pathogenesis. N Engl J Med 2006; 354(9): 942-55.
[http://dx.doi.org/10.1056/NEJMra052130] [PMID: 16510748]
[5] Mahad DH, Trapp BD, Lassmann H. Pathological mechanisms in progressive multiple sclerosis. Lancet Neurol 2015; 14(2): 183-93.
[http://dx.doi.org/10.1016/S1474-4422(14)70256-X] [PMID: 25772897]
[6] US Food & Drug Administration Available From: https://www.fda.gov/drugs/cder-biomarker-qualification-program/about-biomarkers-and-qualification
[7] Strimbu K, Tavel JA. What are biomarkers? Curr Opin HIV AIDS 2010; 5(6): 463-6.
[http://dx.doi.org/10.1097/COH.0b013e32833ed177] [PMID: 20978388]
[8] Perry MG, Kirwan JR, Jessop DS, Hunt LP. Overnight variations in cortisol, interleukin 6, tumour necrosis factor alpha and other cytokines in people with rheumatoid arthritis. Ann Rheum Dis 2009; 68(1): 63-8.
[http://dx.doi.org/10.1136/ard.2007.086561] [PMID: 18375536]
[9] Wipfler P, Heikkinen A, Harrer A, et al. Circadian rhythmicity of inflammatory serum parameters: A neglected issue in the search of biomarkers in multiple sclerosis. J Neurol 2013; 260(1): 221-7.
[http://dx.doi.org/10.1007/s00415-012-6622-3] [PMID: 22875099]
[10] Grady SP, Nishino S, Czeisler CA, Hepner D, Scammell TE. Diurnal variation in CSF orexin-A in healthy male subjects. Sleep 2006; 29(3): 295-7.
[http://dx.doi.org/10.1093/sleep/29.3.295] [PMID: 16553014]
[11] Poceta JS, Parsons L, Engelland S, Kripke DF. Circadian rhythm of CSF monoamines and hypocretin-1 in restless legs syndrome and Parkinson’s disease. Sleep Med 2009; 10(1): 129-33.
[http://dx.doi.org/10.1016/j.sleep.2007.11.002] [PMID: 18207455]
[12] Minagar A, Adamashvili I, Kelley RE, Gonzalez-Toledo E, McLarty J, Smith SJ. Saliva soluble HLA as a potential marker of response to interferon-β 1a in multiple sclerosis: A preliminary study. J Neuroinflammation 2007; 4(1): 16.
[http://dx.doi.org/10.1186/1742-2094-4-16] [PMID: 17601341]
[13] Calais G, Forzy G, Crinquette C, et al. Tear analysis in clinically isolated syndrome as new multiple sclerosis criterion. Mult Scler 2010; 16(1): 87-92.
[http://dx.doi.org/10.1177/1352458509352195] [PMID: 20028709]
[14] Reen DJ. Enzyme-linked immunosorbent assay (ELISA).Basic Protein and Peptide Protocols 1994; 461-6. Internet [cited 2018 Jan 17] http://link.springer.com/10.1385/0-89603 -268-X:461
[http://dx.doi.org/10.1385/0-89603-268-X:461]
[15] Mahmood T, Yang PC. Western blot: technique, theory, and trouble shooting. N Am J Med Sci 2012; 4(9): 429-34.
[http://dx.doi.org/10.4103/1947-2714.100998] [PMID: 23050259]
[16] Cornell FN. Isoelectric focusing, blotting and probing methods for detection and identification of monoclonal proteins. Clin Biochem Rev 2009; 30(3): 123-30.
[PMID: 19841695]
[17] Baranzini SE, Mudge J, van Velkinburgh JC, et al. Genome, epigenome and RNA sequences of monozygotic twins discordant for multiple sclerosis. Nature 2010; 464(7293): 1351-6.
[http://dx.doi.org/10.1038/nature08990] [PMID: 20428171]
[18] Sánchez-Pla A, Reverter F, Ruíz de Villa MC, Comabella M. Transcriptomics: mRNA and alternative splicing. J Neuroimmunol 2012; 248(1-2): 23-31.
[http://dx.doi.org/10.1016/j.jneuroim.2012.04.008] [PMID: 22626445]
[19] Quintana FJ, Yeste A, Weiner HL, Covacu R. Lipids and lipid-reactive antibodies as biomarkers for multiple sclerosis. J Neuroimmunol 2012; 248(1-2): 53-7.
[http://dx.doi.org/10.1016/j.jneuroim.2012.01.002] [PMID: 22579051]
[20] Paul A, Comabella M, Gandhi R. Biomarkers in multiple sclerosis. Cold Spring Harb Perspect Med 2019; 9(3)a029058
[http://dx.doi.org/10.1101/cshperspect.a029058] [PMID: 29500303]
[21] Pryce G, Baker D. Oligoclonal bands in multiple sclerosis; Functional significance and therapeutic implications. Does the specificity matter? Mult Scler Relat Disord 2018; 25: 131-7.
[http://dx.doi.org/10.1016/j.msard.2018.07.030] [PMID: 30071507]
[22] Trbojevic-Cepe M. Detection of oligoclonal ig bands: Clinical significance and trends in methodological improvement. EJIFCC 2004; 15(3): 86-94.
[PMID: 29988915]
[23] Tintore M, Rovira A, Rio J, Tur C, Pelayo R, Nos C, et al. Do oligoclonal bands add information to MRI in first attacks of multiple sclerosis? Neurology 2008; 70(Issue 13, Part 2): 1079-83.
[http://dx.doi.org/10.1212/01.wnl.0000280576.73609.c6]
[24] Nilsson P, Larsson E-M, Maly-Sundgren P, Perfekt R, Sandberg-Wollheim M. Predicting the outcome of optic neuritis: Evaluation of risk factors after 30 years of follow-up. J Neurol 2005; 252(4): 396-402.
[http://dx.doi.org/10.1007/s00415-005-0655-9] [PMID: 15778816]
[25] Karussis D. The diagnosis of multiple sclerosis and the various related demyelinating syndromes: a critical review. J Autoimmun 2014; 48-49: 134-42.
[http://dx.doi.org/10.1016/j.jaut.2014.01.022] [PMID: 24524923]
[26] Thompson AJ, Banwell BL, Barkhof F, et al. Diagnosis of multiple sclerosis: 2017 revisions of the McDonald criteria. Lancet Neurol 2018; 17(2): 162-73.
[http://dx.doi.org/10.1016/S1474-4422(17)30470-2] [PMID: 29275977]
[27] Mandrioli J, Sola P, Bedin R, Gambini M, Merelli E. A multifactorial prognostic index in multiple sclerosis. Cerebrospinal fluid IgM oligoclonal bands and clinical features to predict the evolution of the disease. J Neurol 2008; 255(7): 1023-31.
[http://dx.doi.org/10.1007/s00415-008-0827-5] [PMID: 18535872]
[28] Schneider R, Euler B, Rauer S. Intrathecal IgM-synthesis does not correlate with the risk of relapse in patients with a primary demyelinating event. Eur J Neurol 2007; 14(8): 907-11.
[http://dx.doi.org/10.1111/j.1468-1331.2007.01871.x] [PMID: 17662013]
[29] Villar L, García-Barragán N, Espiño M, et al. Influence of oligoclonal IgM specificity in multiple sclerosis disease course. Mult Scler 2008; 14(2): 183-7.
[http://dx.doi.org/10.1177/1352458507082046] [PMID: 17942517]
[30] Brettschneider J, Tumani H, Kiechle U, et al. IgG antibodies against measles, rubella, and varicella zoster virus predict conversion to multiple sclerosis in clinically isolated syndrome. PLoS One 2009; 4(11)e7638
[http://dx.doi.org/10.1371/journal.pone.0007638] [PMID: 19890384]
[31] Brettschneider J, Tumani H, Kiechle U, et al. IgG antibodies against measles, rubella, and varicella zoster virus predict conversion to multiple sclerosis in clinically isolated syndrome. PLoS One 2009; 4(11)e7638
[http://dx.doi.org/10.1371/journal.pone.0007638] [PMID: 19890384]
[32] Jarius S, Eichhorn P, Franciotta D, et al. The MRZ reaction as a highly specific marker of multiple sclerosis: Re-evaluation and structured review of the literature. J Neurol 2017; 264(3): 453-66.
[http://dx.doi.org/10.1007/s00415-016-8360-4] [PMID: 28005176]
[33] Hottenrott T, Dersch R, Berger B, et al. The MRZ reaction helps to distinguish rheumatologic disorders with central nervous involvement from multiple sclerosis. BMC Neurol 2018; 18(1): 14.
[http://dx.doi.org/10.1186/s12883-018-1018-3] [PMID: 29386006]
[34] Meinl E, Krumbholz M, Hohlfeld R. B lineage cells in the inflammatory central nervous system environment: Migration, maintenance, local antibody production, and therapeutic modulation. Ann Neurol 2006; 59(6): 880-92.
[http://dx.doi.org/10.1002/ana.20890] [PMID: 16718690]
[35] Guan Y, Jakimovski D, Ramanathan M, Weinstock-Guttman B, Zivadinov R. The role of Epstein-Barr virus in multiple sclerosis: from molecular pathophysiology to in vivo imaging. Neural Regen Res 2019; 14(3): 373-86.
[http://dx.doi.org/10.4103/1673-5374.245462] [PMID: 30539801]
[36] Cepok S, Zhou D, Srivastava R, et al. Identification of Epstein-Barr virus proteins as putative targets of the immune response in multiple sclerosis. J Clin Invest 2005; 115(5): 1352-60.
[http://dx.doi.org/10.1172/JCI200523661] [PMID: 15841210]
[37] Lünemann JD, Edwards N, Muraro PA, et al. Increased frequency and broadened specificity of latent EBV nuclear antigen-1-specific T cells in multiple sclerosis. Brain 2006; 129(Pt 6): 1493-506.
[http://dx.doi.org/10.1093/brain/awl067] [PMID: 16569670]
[38] Casiraghi C, Dorovini-Zis K, Horwitz MS. Epstein-Barr virus infection of human brain microvessel endothelial cells: A novel role in multiple sclerosis. J Neuroimmunol 2011; 230(1-2): 173-7.
[http://dx.doi.org/10.1016/j.jneuroim.2010.08.003] [PMID: 20826008]
[39] Buljevac D, van Doornum GJ, Flach HZ, et al. Epstein-Barr virus and disease activity in multiple sclerosis. J Neurol Neurosurg Psychiatry 2005; 76(10): 1377-81.
[http://dx.doi.org/10.1136/jnnp.2004.048504] [PMID: 16170080]
[40] Brebner JA, Stockley RA. Polyclonal free light chains: A biomarker of inflammatory disease or treatment target? F1000 Med Rep 2013; 5: 4.
[http://dx.doi.org/10.3410/M5-4] [PMID: 23413370]
[41] Presslauer S, Milosavljevic D, Brücke T, Bayer P, Hübl W. Elevated levels of kappa free light chains in CSF support the diagnosis of multiple sclerosis. J Neurol 2008; 255(10): 1508-14.
[http://dx.doi.org/10.1007/s00415-008-0954-z] [PMID: 18685917]
[42] Villar LM, Espiño M, Costa-Frossard L, Muriel A, Jiménez J, Alvarez-Cermeño JC. High levels of cerebrospinal fluid free kappa chains predict conversion to multiple sclerosis. Clin Chim Acta 2012; 413(23-24): 1813-6.
[http://dx.doi.org/10.1016/j.cca.2012.07.007] [PMID: 22814197]
[43] Lo Sasso B, Agnello L, Bivona G, Bellia C, Ciaccio M. Cerebrospinal fluid analysis in multiple sclerosis diagnosis: An update. Medicina (Kaunas) 2019; 55(6): 245.
[http://dx.doi.org/10.3390/medicina55060245] [PMID: 31167509]
[44] Arneth B, Birklein F. High sensitivity of free lambda and free kappa light chains for detection of intrathecal immunoglobulin synthesis in cerebrospinal fluid. Acta Neurol Scand 2009; 119(1): 39-44.
[http://dx.doi.org/10.1111/j.1600-0404.2008.01058.x] [PMID: 18573131]
[45] Berger T, Rubner P, Schautzer F, et al. Antimyelin antibodies as a predictor of clinically definite multiple sclerosis after a first demyelinating event. N Engl J Med 2003; 349(2): 139-45.
[http://dx.doi.org/10.1056/NEJMoa022328] [PMID: 12853586]
[46] Kuhle J, Pohl C, Mehling M, et al. Lack of association between antimyelin antibodies and progression to multiple sclerosis. N Engl J Med 2007; 356(4): 371-8.
[http://dx.doi.org/10.1056/NEJMoa063602] [PMID: 17251533]
[47] Spadaro M, Gerdes LA, Krumbholz M, et al. Autoantibodies to MOG in a distinct subgroup of adult multiple sclerosis. Neurol Neuroimmunol Neuroinflamm 2016; 3(5)e257
[http://dx.doi.org/10.1212/NXI.0000000000000257] [PMID: 27458601]
[48] Romme Christensen J, Börnsen L, Hesse D, et al. Cellular sources of dysregulated cytokines in relapsing-remitting multiple sclerosis. J Neuroinflammation [Internet] 2012. Dec [cited 2018 Jan 27]; 9(1). Available from: http://jneuroinflammation.biomedcentral.com/articles/10.1186/1742-2094-9-215
[49] Chen Y-C, Yang X, Miao L, et al. Serum level of interleukin-6 in Chinese patients with multiple sclerosis. J Neuroimmunol 2012; 249(1-2): 109-11.
[http://dx.doi.org/10.1016/j.jneuroim.2012.04.015] [PMID: 22633195]
[50] Karimabad MN, Arababadi MK, Hakimizadeh E, et al. Is the IL-10 promoter polymorphism at position -592 associated with immune system-related diseases? Inflammation 2013; 36(1): 35-41.
[http://dx.doi.org/10.1007/s10753-012-9517-7] [PMID: 22886309]
[51] Schneider R, Mohebiany AN, Ifergan I, et al. B cell-derived IL-15 enhances CD8 T cell cytotoxicity and is increased in multiple sclerosis patients. J Immunol 2011; 187(8): 4119-28.
[http://dx.doi.org/10.4049/jimmunol.1100885] [PMID: 21911607]
[52] Rentzos M, Cambouri C, Rombos A, et al. IL-15 is elevated in serum and cerebrospinal fluid of patients with multiple sclerosis. J Neurol Sci 2006; 241(1-2): 25-9.
[http://dx.doi.org/10.1016/j.jns.2005.10.003] [PMID: 16316662]
[53] Dimisianos N, Rodi M, Kalavrizioti D, Georgiou V, Papathanasopoulos P, Mouzaki A. Cytokines as biomarkers of treatment response to IFNb in relapsing-remitting multiple sclerosis 2014; 1-8.
[54] Mouzaki A, Rodi M, Dimisianos N, et al. Immune parameters that distinguish multiple sclerosis patients from patients with other neurological disorders at presentation. PLoS One 2015; 10(8)e0135434
[http://dx.doi.org/10.1371/journal.pone.0135434] [PMID: 26317430]
[55] Kowarik MC, Cepok S, Sellner J, Grummel V, Weber MS, Korn T, et al. CXCL13 is the major determinant for B cell recruitment to the CSF during neuroinflammation. J Neuroinflammation [Internet] 2012. Dec [cited 2018 Jan 27]; 9(1). Available from: http://jneuroinflammation.biomedcentral.com/articles/10.1186/1742-2094-9-93
[56] Sellebjerg F, Börnsen L, Khademi M, et al. Increased cerebrospinal fluid concentrations of the chemokine CXCL13 in active MS. Neurology 2009; 73(23): 2003-10.
[http://dx.doi.org/10.1212/WNL.0b013e3181c5b457] [PMID: 19996075]
[57] Khademi M, Kockum I, Andersson ML, et al. Cerebrospinal fluid CXCL13 in multiple sclerosis: A suggestive prognostic marker for the disease course. Mult Scler 2011; 17(3): 335-43.
[http://dx.doi.org/10.1177/1352458510389102] [PMID: 21135023]
[58] Ferraro D, Galli V, Vitetta F, et al. Cerebrospinal fluid CXCL13 in clinically isolated syndrome patients: Association with oligoclonal IgM bands and prediction of Multiple Sclerosis diagnosis. J Neuroimmunol 2015; 283: 64-9.
[http://dx.doi.org/10.1016/j.jneuroim.2015.04.011] [PMID: 26004159]
[59] Miljković D, Stanojević Z, Momcilović M, Odoardi F, Flügel A, Mostarica-Stojković M. CXCL12 expression within the CNS contributes to the resistance against experimental autoimmune encephalomyelitis in Albino Oxford rats. Immunobiology 2011; 216(9): 979-87.
[http://dx.doi.org/10.1016/j.imbio.2011.03.013] [PMID: 21601937]
[60] Acar G, İdiman F, Kirkali G, et al. Intrathecal sICAM-1 production in multiple sclerosis-correlation with triple dose Gd-DTPA MRI enhancement and IgG index. J Neurol 2005; 252(2): 146-50.
[http://dx.doi.org/10.1007/s00415-005-0618-1] [PMID: 15729518]
[61] Braitch M, Nunan R, Niepel G, Edwards LJ, Constantinescu CS. Increased osteopontin levels in the cerebrospinal fluid of patients with multiple sclerosis. Arch Neurol [Internet] 2008. May 1 [cited 2018 Jan 30]; 65(5). Available from: http://archneur.jamanetwork.com/article.aspx?doi=10.1001/archneur.65.5.633
[http://dx.doi.org/10.1001/archneur.65.5.633]
[62] Disanto G, Barro C, Benkert P, et al. Swiss Multiple Sclerosis Cohort Study Group. Serum Neurofilament light: A biomarker of neuronal damage in multiple sclerosis. Ann Neurol 2017; 81(6): 857-70.
[http://dx.doi.org/10.1002/ana.24954] [PMID: 28512753]
[63] Barro C, Benkert P, Disanto G, et al. Serum neurofilament light chain as a predictor of disease worsening and brain and spinal cord atrophy in multiple sclerosis 2018; 30.
[64] Barro C, Leocani L, Leppert D, Comi G, Kappos L, Kuhle J. Fluid biomarker and electrophysiological outcome measures for progressive MS trials. Mult Scler 2017; 23(12): 1600-13.
[http://dx.doi.org/10.1177/1352458517732844] [PMID: 29041870]
[65] Siller N, Kuhle J, Muthuraman M, et al. Serum neurofilament light chain is a biomarker of acute and chronic neuronal damage in early multiple sclerosis. Mult Scler J 2018; 1-9.
[PMID: 29542376]
[66] Novakova L, Zetterberg H, Sundström P, et al. Monitoring disease activity in multiple sclerosis using serum neurofilament light protein. Neurology 2017; 89(22): 2230-7.
[http://dx.doi.org/10.1212/WNL.0000000000004683] [PMID: 29079686]
[67] Iacobaeus E, Amoudruz P, Ström M, et al. The expression of VEGF-A is down regulated in peripheral blood mononuclear cells of patients with secondary progressive multiple sclerosis. PLoS One 2011; 6(5)e19138
[http://dx.doi.org/10.1371/journal.pone.0019138] [PMID: 21573104]
[68] Munger KL, Zhang SM, O’Reilly E, et al. Vitamin D intake and incidence of multiple sclerosis. Neurology 2004; 62(1): 60-5.
[http://dx.doi.org/10.1212/01.WNL.0000101723.79681.38] [PMID: 14718698]
[69] Ramagopalan SV, Maugeri NJ, Handunnetthi L, et al. Expression of the multiple sclerosis-associated MHC class II Allele HLA-DRB1*1501 is regulated by vitamin D. PLoS Genet 2009; 5(2)e1000369
[http://dx.doi.org/10.1371/journal.pgen.1000369] [PMID: 19197344]
[70] Yu S, Cantorna MT. The vitamin D receptor is required for iNKT cell development. Proc Natl Acad Sci USA 2008; 105(13): 5207-12.
[http://dx.doi.org/10.1073/pnas.0711558105] [PMID: 18364394]
[71] Mowry EM, Waubant E, McCulloch CE, et al. Vitamin D status predicts new brain magnetic resonance imaging activity in multiple sclerosis. Ann Neurol 2012; 72(2): 234-40.
[http://dx.doi.org/10.1002/ana.23591] [PMID: 22926855]
[72] Mowry EM, Pelletier D, Gao Z, Howell MD, Zamvil SS, Waubant E. Vitamin D in clinically isolated syndrome: Evidence for possible neuroprotection. Eur J Neurol 2016; 23(2): 327-32.
[http://dx.doi.org/10.1111/ene.12844] [PMID: 26518224]
[73] Kuenz B, Lutterotti A, Ehling R, et al. Cerebrospinal fluid B cells correlate with early brain inflammation in multiple sclerosis. PLoS One 2008; 3(7)e2559
[http://dx.doi.org/10.1371/journal.pone.0002559] [PMID: 18596942]
[74] Corcione A, Casazza S, Ferretti E, et al. Recapitulation of B cell differentiation in the central nervous system of patients with multiple sclerosis. Proc Natl Acad Sci USA 2004; 101(30): 11064-9.
[http://dx.doi.org/10.1073/pnas.0402455101] [PMID: 15263096]
[75] Claes N, Fraussen J, Stinissen P, Hupperts R, Somers V. B cells are multifunctional players in multiple sclerosis pathogenesis: Insights from therapeutic interventions. Front Immunol 2015; 6: 642.
[http://dx.doi.org/10.3389/fimmu.2015.00642] [PMID: 26734009]
[76] Liu L, Callahan MK, Huang D, Ransohoff RM. Chemokine receptor CXCR3: An unexpected enigma.Current Topics in Developmental Biology 2005; 149-81.http://linkinghub.elsevier.com/retrieve/pii/S0070215305680064 Internet [cited 2018 Mar 13]
[77] Broux B, Pannemans K, Zhang X, et al. CX(3)CR1 drives cytotoxic CD4(+)CD28(-) T cells into the brain of multiple sclerosis patients. J Autoimmun 2012; 38(1): 10-9.
[http://dx.doi.org/10.1016/j.jaut.2011.11.006] [PMID: 22123179]
[78] Cao Y, Goods BA, Raddassi K, et al. Functional inflammatory profiles distinguish myelin-reactive T cells from Patients with Multiple Sclerosis. Science Translational Medicine 2015; 7(287): 287ra74-287ra74.
[79] Bielekova B, Catalfamo M, Reichert-Scrivner S, et al. Regulatory CD56(bright) natural killer cells mediate immunomodulatory effects of IL-2Ralpha-targeted therapy (daclizumab) in multiple sclerosis. Proc Natl Acad Sci USA 2006; 103(15): 5941-6.
[http://dx.doi.org/10.1073/pnas.0601335103] [PMID: 16585503]
[80] Marques F, Mesquita SD, Sousa JC, Coppola G, Gao F, Geschwind DH, et al. Lipocalin 2 is present in the EAE brain and is modulated by natalizumab. Front Cell Neurosci [Internet] 2012. [cited 2018 Mar 30]; 6. Available from: http://journal.frontiersin.org/article/10.3389/fncel. 2012.00033/abstract
[http://dx.doi.org/10.3389/fncel.2012.00033]
[81] Avolio C, Ruggieri M, Giuliani F, et al. Serum MMP-2 and MMP-9 are elevated in different multiple sclerosis subtypes. J Neuroimmunol 2003; 136(1-2): 46-53.
[http://dx.doi.org/10.1016/S0165-5728(03)00006-7] [PMID: 12620642]
[82] Sato W, Tomita A, Ichikawa D, et al. CCR2(+)CCR5(+) T cells produce matrix metalloproteinase-9 and osteopontin in the pathogenesis of multiple sclerosis. J Immunol 2012; 189(10): 5057-65.
[http://dx.doi.org/10.4049/jimmunol.1202026] [PMID: 23071279]
[83] Ifergan I, Kebir H, Terouz S, et al. Role of Ninjurin-1 in the migration of myeloid cells to central nervous system inflammatory lesions. Ann Neurol 2011; 70(5): 751-63.
[http://dx.doi.org/10.1002/ana.22519] [PMID: 22162058]
[84] Shinohara RT, Goldsmith J, Mateen FJ, Crainiceanu C, Reich DS. Predicting breakdown of the blood-brain barrier in multiple sclerosis without contrast agents. AJNR Am J Neuroradiol 2012; 33(8): 1586-90.
[http://dx.doi.org/10.3174/ajnr.A2997] [PMID: 22442041]
[85] Brex PA, Ciccarelli O, O’Riordan JI, Sailer M, Thompson AJ, Miller DH. A longitudinal study of abnormalities on MRI and disability from multiple sclerosis. N Engl J Med 2002; 346(3): 158-64.
[http://dx.doi.org/10.1056/NEJMoa011341] [PMID: 11796849]
[86] Brex PA, Parker GJ, Leary SM, et al. Lesion heterogeneity in multiple sclerosis: a study of the relations between appearances on T1 weighted images, T1 relaxation times, and metabolite concentrations. J Neurol Neurosurg Psychiatry 2000; 68(5): 627-32.
[http://dx.doi.org/10.1136/jnnp.68.5.627] [PMID: 10766895]
[87] Sahraian MA, Radue E-W, Haller S, Kappos L. Black holes in multiple sclerosis: definition, evolution, and clinical correlations. Acta Neurol Scand 2010; 122(1): 1-8.
[http://dx.doi.org/10.1111/j.1600-0404.2009.01221.x] [PMID: 20003089]
[88] De Stefano N, Giorgio A, Battaglini M, et al. Assessing brain atrophy rates in a large population of untreated multiple sclerosis subtypes. Neurology 2010; 74(23): 1868-76.
[http://dx.doi.org/10.1212/WNL.0b013e3181e24136] [PMID: 20530323]
[89] Fisher E, Rudick RA, Simon JH, et al. Eight-year follow-up study of brain atrophy in patients with MS. Neurology 2002; 59(9): 1412-20.
[http://dx.doi.org/10.1212/01.WNL.0000036271.49066.06] [PMID: 12427893]
[90] Sormani MP, Arnold DL, De Stefano N. Treatment effect on brain atrophy correlates with treatment effect on disability in multiple sclerosis. Ann Neurol 2014; 75(1): 43-9.
[http://dx.doi.org/10.1002/ana.24018] [PMID: 24006277]
[91] Fisher E, Lee J-C, Nakamura K, Rudick RA. Gray matter atrophy in multiple sclerosis: a longitudinal study. Ann Neurol 2008; 64(3): 255-65.
[http://dx.doi.org/10.1002/ana.21436] [PMID: 18661561]
[92] Dalton CM, Chard DT, Davies GR, et al. Early development of multiple sclerosis is associated with progressive grey matter atrophy in patients presenting with clinically isolated syndromes. Brain 2004; 127(Pt 5): 1101-7.
[http://dx.doi.org/10.1093/brain/awh126] [PMID: 14998914]
[93] Geurts JJ, Calabrese M, Fisher E, Rudick RA. Measurement and clinical effect of grey matter pathology in multiple sclerosis. Lancet Neurol 2012; 11(12): 1082-92.
[http://dx.doi.org/10.1016/S1474-4422(12)70230-2] [PMID: 23153407]
[94] Calabrese M, Agosta F, Rinaldi F, et al. Cortical lesions and atrophy associated with cognitive impairment in relapsing-remitting multiple sclerosis. Arch Neurol 2009; 66(9): 1144-50.
[http://dx.doi.org/10.1001/archneurol.2009.174] [PMID: 19752305]
[95] Rashid W, Davies GR, Chard DT, et al. Increasing cord atrophy in early relapsing-remitting multiple sclerosis: A 3 year study. J Neurol Neurosurg Psychiatry 2006; 77(1): 51-5.
[http://dx.doi.org/10.1136/jnnp.2005.068338] [PMID: 16361592]
[96] van den Elskamp IJ, Knol DL, Vrenken H, et al. Lesional magnetization transfer ratio: A feasible outcome for remyelinating treatment trials in multiple sclerosis. Mult Scler 2010; 16(6): 660-9.
[http://dx.doi.org/10.1177/1352458510364630] [PMID: 20350960]
[97] Klistorner A, Chaganti J, Garrick R, Moffat K, Yiannikas C. Magnetisation transfer ratio in optic neuritis is associated with axonal loss, but not with demyelination. Neuroimage 2011; 56(1): 21-6.
[http://dx.doi.org/10.1016/j.neuroimage.2011.02.041] [PMID: 21338694]
[98] Brown RA, Narayanan S, Arnold DL. Segmentation of magnetization transfer ratio lesions for longitudinal analysis of demyelination and remyelination in multiple sclerosis. Neuroimage 2013; 66: 103-9.
[http://dx.doi.org/10.1016/j.neuroimage.2012.10.059] [PMID: 23110887]
[99] Aung WY, Mar S, Benzinger TL. Diffusion tensor MRI as a biomarker in axonal and myelin damage. Imaging Med 2013; 5(5): 427-40.
[http://dx.doi.org/10.2217/iim.13.49] [PMID: 24795779]
[100] Klawiter EC, Schmidt RE, Trinkaus K, et al. Radial diffusivity predicts demyelination in ex vivo multiple sclerosis spinal cords. Neuroimage 2011; 55(4): 1454-60.
[http://dx.doi.org/10.1016/j.neuroimage.2011.01.007] [PMID: 21238597]
[101] Bozzali M, Cercignani M, Sormani MP, Comi G, Filippi M. Quantification of brain gray matter damage in different MS phenotypes by use of diffusion tensor MR imaging. AJNR Am J Neuroradiol 2002; 23(6): 985-8.
[PMID: 12063230]
[102] Wahl M, Hübers A, Lauterbach-Soon B, et al. Motor callosal disconnection in early relapsing-remitting multiple sclerosis. Hum Brain Mapp 2011; 32(6): 846-55.
[http://dx.doi.org/10.1002/hbm.21071] [PMID: 21495114]
[103] Liu Y, Mitchell PJ, Kilpatrick TJ, et al. Diffusion tensor imaging of acute inflammatory lesion evolution in multiple sclerosis. J Clin Neurosci 2012; 19(12): 1689-94.
[http://dx.doi.org/10.1016/j.jocn.2012.03.022] [PMID: 23084347]
[104] Tian W, Zhu T, Zhong J, et al. Progressive decline in fractional anisotropy on serial DTI examinations of the corpus callosum: a putative marker of disease activity and progression in SPMS. Neuroradiology 2012; 54(4): 287-97.
[http://dx.doi.org/10.1007/s00234-011-0885-8] [PMID: 21567135]
[105] Akbar N, Rudko DA, Parmar K. Magnetic Resonance Imaging of Multiple Sclerosis. Sci J Mult Scler 2017; 1(1): 008-020.
[106] Grazioli E, Zivadinov R, Weinstock-Guttman B, et al. Retinal nerve fiber layer thickness is associated with brain MRI outcomes in multiple sclerosis. J Neurol Sci 2008; 268(1-2): 12-7.
[http://dx.doi.org/10.1016/j.jns.2007.10.020] [PMID: 18054962]
[107] Herrero R, Garcia-Martin E, Almarcegui C, et al. Progressive degeneration of the retinal nerve fiber layer in patients with multiple sclerosis. Invest Ophthalmol Vis Sci 2012; 53(13): 8344-9.
[http://dx.doi.org/10.1167/iovs.12-10362] [PMID: 23154461]
[108] Saidha S, Sotirchos ES, Ibrahim MA, et al. Microcystic macular oedema, thickness of the inner nuclear layer of the retina, and disease characteristics in multiple sclerosis: a retrospective study. Lancet Neurol 2012; 11(11): 963-72.
[http://dx.doi.org/10.1016/S1474-4422(12)70213-2] [PMID: 23041237]
[109] Martinez-Lapiscina EH, Arnow S, Wilson JA, et al. Retinal thickness measured with optical coherence tomography and risk of disability worsening in multiple sclerosis: a cohort study. Lancet Neurol 2016; 15(6): 574-84.
[http://dx.doi.org/10.1016/S1474-4422(16)00068-5] [PMID: 27011339]
[110] Schmidt H, Williamson D, Ashley-Koch A. HLA-DR15 haplotype and multiple sclerosis: a HuGE review. Am J Epidemiol 2007; 165(10): 1097-109.
[http://dx.doi.org/10.1093/aje/kwk118] [PMID: 17329717]
[111] Oksenberg JR, Barcellos LF, Cree BAC, et al. Mapping multiple sclerosis susceptibility to the HLA-DR locus in African Americans. Am J Hum Genet 2004; 74(1): 160-7.
[http://dx.doi.org/10.1086/380997] [PMID: 14669136]
[112] Bozikas VP, Anagnostouli MC, Petrikis P, et al. Familial bipolar disorder and multiple sclerosis: a three-generation HLA family study. Prog Neuropsychopharmacol Biol Psychiatry 2003; 27(5): 835-9.
[http://dx.doi.org/10.1016/S0278-5846(03)00116-7] [PMID: 12921917]
[113] Lincoln MR, Ramagopalan SV, Chao MJ, et al. Epistasis among HLA-DRB1, HLA-DQA1, and HLA-DQB1 loci determines multiple sclerosis susceptibility. Proc Natl Acad Sci USA 2009; 106(18): 7542-7.
[http://dx.doi.org/10.1073/pnas.0812664106] [PMID: 19380721]
[114] Marrosu MG, Sardu C, Cocco E, et al. Bias in parental transmission of the HLA-DR3 allele in Sardinian multiple sclerosis. Neurology 2004; 63(6): 1084-6.
[http://dx.doi.org/10.1212/01.WNL.0000138493.04890.7C] [PMID: 15452304]
[115] Dyment DA, Cader MZ, Datta A, et al. A first stage genome-wide screen for regions shared identical-by-descent in Hutterite families with multiple sclerosis. Am J Med Genet B Neuropsychiatr Genet 2008; 147B(4): 467-72.
[http://dx.doi.org/10.1002/ajmg.b.30620] [PMID: 18081025]
[116] Kikuchi S, Fukazawa T, Niino M, et al. HLA-related subpopulations of MS in Japanese with and without oligoclonal IgG bands. Human leukocyte antigen. Neurology 2003; 60(4): 647-51.
[http://dx.doi.org/10.1212/01.WNL.0000048202.09147.9E] [PMID: 12601107]
[117] Van der Walt A, Stankovich J, Bahlo M, et al. Heterogeneity at the HLA-DRB1 allelic variation locus does not influence multiple sclerosis disease severity, brain atrophy or cognition. Mult Scler 2011; 17(3): 344-52.
[http://dx.doi.org/10.1177/1352458510389101] [PMID: 21149397]
[118] Zivadinov R, Uxa L, Bratina A, Bosco A, Srinivasaraghavan B, Minagar A, et al. HLA-DRB1*1501, -DQB1*0301, -DQB1*0302, -DQB1*0602, and -DQB1*0603 Alleles are associated with more severe disease outcome on mri in patients with multiple sclerosis [Internet]. In: International Review of Neurobiology. Elsevier; 2007 [cited 2018 Apr 3]. p. 521–535. Available from: http://linkinghub.elsevier.com/retrieve/pii/S0074774207790232
[119] Okuda DT, Srinivasan R, Oksenberg JR, et al. Genotype-Phenotype correlations in multiple sclerosis: HLA genes influence disease severity inferred by 1HMR spectroscopy and MRI measures. Brain 2009; 132(Pt 1): 250-9.
[http://dx.doi.org/10.1093/brain/awn301] [PMID: 19022862]
[120] Stankovich J, Butzkueven H, Marriott M, et al. HLA-DRB1 associations with disease susceptibility and clinical course in Australians with multiple sclerosis. Tissue Antigens 2009; 74(1): 17-21.
[http://dx.doi.org/10.1111/j.1399-0039.2009.01262.x] [PMID: 19392788]
[121] Cournu-Rebeix I, Génin E, Leray E, et al. HLA-DRB1*15 allele influences the later course of relapsing remitting multiple sclerosis. Genes Immun 2008; 9(6): 570-4.
[http://dx.doi.org/10.1038/gene.2008.52] [PMID: 18615093]
[122] Corvol J-C, Pelletier D, Henry RG, et al. Abrogation of T cell quiescence characterizes patients at high risk for multiple sclerosis after the initial neurological event. Proc Natl Acad Sci USA 2008; 105(33): 11839-44.
[http://dx.doi.org/10.1073/pnas.0805065105] [PMID: 18689680]
[123] Zhang H-L, Wu J, Zhu J. The immune-modulatory role of apolipoprotein E with emphasis on multiple sclerosis and experimental autoimmune encephalomyelitis. Clin Dev Immunol 2010; 2010186813
[http://dx.doi.org/10.1155/2010/186813] [PMID: 20613949]
[124] Hottenrott T, Dersch R, Berger B, Rauer S, Huzly D, Stich O. The MRZ reaction in primary progressive multiple sclerosis. Fluids Barriers CNS 2017; 14(1): 2.
[http://dx.doi.org/10.1186/s12987-016-0049-7] [PMID: 28166789]
[125] Martin SJ, McGlasson S, Hunt D, Overell J. Cerebrospinal fluid neurofilament light chain in multiple sclerosis and its subtypes: a meta-analysis of case-control studies. J Neurol Neurosurg Psychiatry 2019; 90(9): 1059-67.
[http://dx.doi.org/10.1136/jnnp-2018-319190] [PMID: 31123141]
[126] Kuhle J, Kropshofer H, Haering DA, et al. Blood neurofilament light chain as a biomarker of MS disease activity and treatment response. Neurology 2019; 92(10): e1007-15.
[http://dx.doi.org/10.1212/WNL.0000000000007032] [PMID: 30737333]
[127] Sintzel MB, Rametta M, Reder AT. Vitamin D and Multiple Sclerosis: A Comprehensive Review. Neurol Ther 2018; 7(1): 59-85.
[http://dx.doi.org/10.1007/s40120-017-0086-4] [PMID: 29243029]
Track Your Manuscript:


Endorsements



"Open access will revolutionize 21st century knowledge work and accelerate the diffusion of ideas and evidence that support just in time learning and the evolution of thinking in a number of disciplines."


Daniel Pesut
(Indiana University School of Nursing, USA)

"It is important that students and researchers from all over the world can have easy access to relevant, high-standard and timely scientific information. This is exactly what Open Access Journals provide and this is the reason why I support this endeavor."


Jacques Descotes
(Centre Antipoison-Centre de Pharmacovigilance, France)

"Publishing research articles is the key for future scientific progress. Open Access publishing is therefore of utmost importance for wider dissemination of information, and will help serving the best interest of the scientific community."


Patrice Talaga
(UCB S.A., Belgium)

"Open access journals are a novel concept in the medical literature. They offer accessible information to a wide variety of individuals, including physicians, medical students, clinical investigators, and the general public. They are an outstanding source of medical and scientific information."


Jeffrey M. Weinberg
(St. Luke's-Roosevelt Hospital Center, USA)

"Open access journals are extremely useful for graduate students, investigators and all other interested persons to read important scientific articles and subscribe scientific journals. Indeed, the research articles span a wide range of area and of high quality. This is specially a must for researchers belonging to institutions with limited library facility and funding to subscribe scientific journals."


Debomoy K. Lahiri
(Indiana University School of Medicine, USA)

"Open access journals represent a major break-through in publishing. They provide easy access to the latest research on a wide variety of issues. Relevant and timely articles are made available in a fraction of the time taken by more conventional publishers. Articles are of uniformly high quality and written by the world's leading authorities."


Robert Looney
(Naval Postgraduate School, USA)

"Open access journals have transformed the way scientific data is published and disseminated: particularly, whilst ensuring a high quality standard and transparency in the editorial process, they have increased the access to the scientific literature by those researchers that have limited library support or that are working on small budgets."


Richard Reithinger
(Westat, USA)

"Not only do open access journals greatly improve the access to high quality information for scientists in the developing world, it also provides extra exposure for our papers."


J. Ferwerda
(University of Oxford, UK)

"Open Access 'Chemistry' Journals allow the dissemination of knowledge at your finger tips without paying for the scientific content."


Sean L. Kitson
(Almac Sciences, Northern Ireland)

"In principle, all scientific journals should have open access, as should be science itself. Open access journals are very helpful for students, researchers and the general public including people from institutions which do not have library or cannot afford to subscribe scientific journals. The articles are high standard and cover a wide area."


Hubert Wolterbeek
(Delft University of Technology, The Netherlands)

"The widest possible diffusion of information is critical for the advancement of science. In this perspective, open access journals are instrumental in fostering researches and achievements."


Alessandro Laviano
(Sapienza - University of Rome, Italy)

"Open access journals are very useful for all scientists as they can have quick information in the different fields of science."


Philippe Hernigou
(Paris University, France)

"There are many scientists who can not afford the rather expensive subscriptions to scientific journals. Open access journals offer a good alternative for free access to good quality scientific information."


Fidel Toldrá
(Instituto de Agroquimica y Tecnologia de Alimentos, Spain)

"Open access journals have become a fundamental tool for students, researchers, patients and the general public. Many people from institutions which do not have library or cannot afford to subscribe scientific journals benefit of them on a daily basis. The articles are among the best and cover most scientific areas."


M. Bendandi
(University Clinic of Navarre, Spain)

"These journals provide researchers with a platform for rapid, open access scientific communication. The articles are of high quality and broad scope."


Peter Chiba
(University of Vienna, Austria)

"Open access journals are probably one of the most important contributions to promote and diffuse science worldwide."


Jaime Sampaio
(University of Trás-os-Montes e Alto Douro, Portugal)

"Open access journals make up a new and rather revolutionary way to scientific publication. This option opens several quite interesting possibilities to disseminate openly and freely new knowledge and even to facilitate interpersonal communication among scientists."


Eduardo A. Castro
(INIFTA, Argentina)

"Open access journals are freely available online throughout the world, for you to read, download, copy, distribute, and use. The articles published in the open access journals are high quality and cover a wide range of fields."


Kenji Hashimoto
(Chiba University, Japan)

"Open Access journals offer an innovative and efficient way of publication for academics and professionals in a wide range of disciplines. The papers published are of high quality after rigorous peer review and they are Indexed in: major international databases. I read Open Access journals to keep abreast of the recent development in my field of study."


Daniel Shek
(Chinese University of Hong Kong, Hong Kong)

"It is a modern trend for publishers to establish open access journals. Researchers, faculty members, and students will be greatly benefited by the new journals of Bentham Science Publishers Ltd. in this category."


Jih Ru Hwu
(National Central University, Taiwan)


Browse Contents




Webmaster Contact: info@benthamopen.net
Copyright © 2020 Bentham Open