844
DOI 10.1002/prca.201400171
Proteomics Clin. Appl. 2015, 9, 844–847
How can proteomics elucidate the complexity of multiple sclerosis?
Alessandro S. Farias and Leonilda M. B. Santos Neuroimmunomodulation Group and Neuroimmunology Unit, Department of Genetics, Evolution and Bioagents, ˜ Paulo, Brazil University of Campinas, Campinas, Sao Multiple sclerosis affects more than 2.5 million people worldwide. Although multiple sclerosis was described almost 150 years ago, there are many knowledge gaps regarding its etiology, diagnosis, prognosis, and pathogenesis. Multiple sclerosis is an inflammatory, demyelinating, neurodegenerative disease of the CNS. During the last several decades, experimental models of multiple sclerosis have contributed to our understanding of the inflammatory disease mechanisms and have aided drug testing and development. However, little is known about the neurodegenerative mechanisms that operate during the evolution of the disease. Currently, all therapeutic approaches are primarily based on the inflammatory aspect of the disease. During the last decade, proteomics has emerged as a promising tool for revealing molecular pathways as well as identifying and quantifying differentially expressed proteins. Therefore, proteomics may be used for the discovery of biomarkers, potential drug targets, and new regulatory mechanisms. To date, a considerable number of proteomics studies have been conducted on samples from experimental models and patients with multiple sclerosis. These data form a solid base for further careful analysis and validation.
Received: October 30, 2014 Revised: April 28, 2015 Accepted: May 11, 2015
Keywords: Experimental autoimmune encephalomyelitis / Inflammation / Multiple sclerosis / Neurodegeneration / Proteomics
Multiple sclerosis is a complex disease in many aspects. JeanMartin Charcot described multiple sclerosis almost 150 years ago (1868); however, its etiology is still unknown, although it is unlikely that multiple sclerosis is associated with a unique causative event. Familial aggregation studies have demonstrated that the disease clusters in families. During the 1970s, an association was first found with the human leucocyte antigen DR2 isotype, and this association was refined in recent years using DNA-based typing methods to the DRB1*1501 [1–3]. Recently, large-scale collaborative genome-wide studies have enabled the discovery of many nonhuman leucocyte antigen susceptibility variants associated with multiple sclerosis [4]. These variants are mostly associated with immunological processes and are frequently associated with other Correspondence: Dr. Alessandro S Farias, Departamento de ´ ˜ e Bioagentes, Instituto de Biologia-UNICAMP, Genetica, Evoluc¸ao Campinas, SP, CEP 13083-970, Brazil E-mail: [email protected] Fax: +55-19-35216185 Abbreviations: CSF, cerebrospinal fluid; EAE, experimental autoimmune encephalomyelitis C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
autoimmune diseases [5–7]. However, the analysis of these data has revealed only a moderate effect on the multiple sclerosis odds ratio at best [8, 9]. Nonetheless, the fact that the disease frequency varies worldwide and the high discordance rate observed among monozygotic twins indicates a potential environmental influence on multiple sclerosis development [10,11]. During the last several decades, many environmental factors (e.g. sunlight exposure, diet, infections, and lifestyle) have been associated with multiple sclerosis risk to some extent. However, none of these factors alone have shown a high odds ratio [2, 12]. Thus, genetic and epidemiological studies have indicated that the disease must be a result of a complex genetic predisposition combined with an environmental trigger [7, 13, 14]. Multiple sclerosis is considered to be a demyelinating autoimmune disease. Similar to the majority of autoimmune pathologies, multiple sclerosis is more common in women. Most of the patients (85%) present with a relapse-remitting clinical manifestation of the disease, and immunomodulatory or immunosuppressive therapies are effective in partially controlling the clinical manifestations of the disease [14, 15]. In parallel, there is an important neurodegenerative aspect of the www.clinical.proteomics-journal.com
Proteomics Clin. Appl. 2015, 9, 844–847
How can proteomics elucidate the complexity of multiple sclerosis?
Correspondence concerning this and other Viewpoint articles can be accessed on the journals’ home page at: http://viewpoint.proteomics-journal.de Correspondence for posting on these pages is welcome and can also be submitted at this site.
disease [16], which was first considered to be a consequence of the inflammatory response. However, recent studies have shown that the neurodegenerative process occurs even in the early stages of the disease [17, 18]. Moreover, some studies have provided evidence suggesting that axonal and neuronal impairment could be an independent contributor to the progression of multiple sclerosis [19–22]. However, more precise neuropathological observations have revealed that inflammation is always present during the entire course of the disease [23]. This observation does not support the concept of a neurodegenerative component occurring in the absence of inflammation. However, during the progressive stage of the disease or in the absence of gadolinium enhancement, the inflammation differs in terms of cells and humoral factors from the classical inflammation found in active plaques [23]. Recently, it has become clear that there is inflammation and tissue damage throughout the entire CNS (white matter, apparently normal white matter and gray matter) [24]. The complexity of multiple sclerosis pathology has implications for its diagnosis. The most recent diagnostic criteria are based on MRI evidence of CNS lesions disseminated temporally and spatially. Although helpful, cerebrospinal fluid (CSF) parameters are not strictly necessary for the diagnosis of multiple sclerosis [25]. The majority of patients present with increased immunoglobulin concentrations, and approximately 90% present oligoclonal bands exclusively detected by the separation of CFS proteins in electrophoresis gel or by IEF followed by immunoblotting [26]. However, these features can be found in other neurological and/or inflammatory conditions [27–30]. In terms of prognosis, a large number of features (early onset age, gender, ethnic origin, specific symptoms, number of attacks, and progression during the first years) may predict the evolution of the disease. Currently, a single laboratory test has not been established for the diagnosis or prognosis of multiple sclerosis [31]. Furthermore, very little is known about the neurodegenerative mechanisms of the disease. The absence of information about the neurodegenerative aspects of multiple sclerosis hinders the development of therapeutic approaches. The majority of the knowledge about the inflammatory mechanisms of multiple sclerosis has been obtained from studies using experimental models. Experimental autoimmune encephalomyelitis (EAE) can be induced in susceptible animals by active immunization with neuroantigens or by adoptive transfer of preactivated encephalitogenic T cells [32]. EAE can have a broad clinical evolution depending on C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
845
the species, strain, or neuroantigen used [33]. Since its development in 1933 [34], EAE has been helpful not only for understanding the inflammatory mechanisms of multiple sclerosis but also for the development and testing of therapeutic strategies. Most of the currently approved therapies for multiple sclerosis were developed or tested in EAE models [35]. However, some approaches that were successful for the treatment of EAE showed poor outcomes for the treatment of multiple sclerosis [36]. Nevertheless, the following points must be considered. (i) EAE is normally induced in isogenic animals. Therefore, it does not reflect the genetic variability found in humans. (ii) Laboratory animals are housed and maintained under pathogen-free conditions, which eliminates the influence of environmental factors (infections, microbiota composition, food intake, weather, temperature, solar incidence, and social behavior) during disease evolution or therapeutic approaches. (iii) Much of the data that have contributed to our understanding of the pathophysiology of EAE were originally derived from knockout animals. (iv) Studies conducted in animal models are normally performed with acute diseases, which compromise our knowledge of the disease mechanisms and the effects of “chronic” treatments. (v) We estimate that the etiology of multiple sclerosis begins years, if not decades, before the first clinical manifestations. In contrast, EAE has a rapid clinical evolution. Nevertheless, EAE has been unequivocally important for understanding the neuroinflammatory mechanisms of multiple sclerosis. Moreover, recent studies using different proteomics approaches have noted early neurodegenerative signatures during the evolution of EAE [37], which seems to be, at least in part, in agreement with the findings in CSF from multiple sclerosis patients [38]. Proteomics analyses are a powerful tool for global proteome analyses and protein identification [39]. Recently, with mass spectrometry, it has also become possible to reliably quantify differentially expressed proteins by SRM [40]. Thus, combined proteomics technologies are suitable for identifying and analyzing regulation within molecular pathways. Assuming that multiple sclerosis is a pathway disorder, proteomics is one of the most appropriate approaches for understanding and establishing biomarkers. Due to the inflammatory and neurodegenerative aspects of multiple sclerosis, it is not likely that one single biomarker could be used to separate multiple sclerosis from other neurological and/or inflammatory diseases. Recently, we reviewed the last 10 years of proteomics studies in multiple sclerosis or EAE [38]. Although no definitive conclusions could be achieved from the existing data, interesting observations can be highlighted. Many of the regulated proteins in these studies are related to structural and metabolic pathways and are not directly related to the immune response [38]. Although the studies were performed with different techniques and samples, many differentially regulated proteins have appeared in different studies in both experimental models and multiple sclerosis samples [38]. Although a considerable number of studies have been performed, the focus is usually on only one clinical www.clinical.proteomics-journal.com
846
A. S. Farias and L. M. B. Santos
manifestation of the disease or on a small number of enrolled patients. Yet, the majority of the studies were performed in patients under disease-modifying therapies, which might contaminate serum or CSF proteome. More importantly, these protein candidates need to be validated, and their penetrance should be evaluated. Nevertheless, a panel of potential biomarkers could be established using these “preliminary” data to facilitate the diagnosis and/or prognosis of the disease. Moreover, a more careful examination of the regulated pathways could reveal new therapeutic targets. Interestingly, a recent study using presymptomatic and postsymptomatic sera demonstrated that some proteins were differentially regulated in presymptomatic multiple sclerosis samples compared with the control samples [41]. These data suggest that there are abnormalities even before the onset of symptoms. More importantly, these results reveal that the risk of developing the disease may be predicted years before the onset. For many decades, we assumed that multiple sclerosis was primarily an inflammatory disease and that its etiology was related to the autoimmune process. Recently, the possibility of a primarily neurodegenerative etiology has emerged [19–21]. Can proteomics help to identify the initiating factors involved in multiple sclerosis development? It is likely that only the existence of a unique genetic signature (e.g. a specific mutation) or an etiological agent (environmental factor) could irrefutably answer this question. Despite the large number of epidemiological studies and the existence of an International Multiple Sclerosis Genetics Consortium, these unique genetic signatures or etiological agent have not yet been identified. Thus, although this is an intriguing question, it might not be the most important question at the moment. Currently, a substantial therapeutic arsenal is available for combatting the inflammatory aspect of the disease. However, there is no single drug that can manage the neurodegenerative events. Therefore, new therapeutic strategies must be developed to treat the progression of neurodegeneration. Moreover, earlier and more precise diagnoses would most likely improve the results of current and future therapies. In summary, the current knowledge base regarding multiple sclerosis has many gaps that have yet to be filled. Without question, proteomics is one strategy that could be applied toward the elucidation of the molecular aspects of the disease. Fortunately, a large amount of data have been generated in proteomic studies performed during the last decade. These data represent a solid basis for further studies. The authors have declared no conflict of interest.
References [1] Ramagopalan, S. V., Dobson, R., Meier, U. C., Giovannoni, G., Multiple sclerosis: risk factors, prodromes, and potential causal pathways. Lancet Neurol. 2010, 9, 727–739. [2] vonGlehn, F., Brandao, C. O., Farias, A. S., Santos, L. M. B., Young perspectives for old diseases – Multiple Sclerosis: An Overview, Bentham Science Publishers 2014, 1, 223–250. C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
Proteomics Clin. Appl. 2015, 9, 844–847
[3] Haines, J. L., Ter-Minassian, M., Bazyk, A., Gusella, J. F. et al., A complete genomic screen for multiple sclerosis underscores a role for the major histocompatability complex. The Multiple Sclerosis Genetics Group. Nat. Genet. 1996, 13, 469– 471. [4] International Multiple Sclerosis Genetics Consortium, Network-based multiple sclerosis pathway analysis with GWAS data from 15000 cases and 30000 controls. Am. J. Hum. Genet. 2013, 92, 854–865. [5] International Multiple Sclerosis Genetics Consortium (IMSGC), Beecham, A. H., Patsopoulos, N. A., Xifara, D. K. et al., Analysis of immune-related loci identifies 48 new susceptibility variants for multiple sclerosis. Nat. Genet. 2013, 45, 1353–1360. [6] International Multiple Sclerosis Genetics Consortium, Wellcome Trust Case Control Consortium 2, Sawcer, S., Hellenthal, G. et al., Genetic risk and a primary role for cellmediated immune mechanisms in multiple sclerosis. Nature 2011, 476, 214–219. [7] Sawcer, S., Franklin, R. J. M., Ban, M., Multiple sclerosis genetics. Lancet Neurol. 2014, 13, 700–709. [8] Baranzini, S. E., Nickles, D., Genetics of multiple sclerosis: swimming in an ocean of data. Curr. Opin. Neurol. 2012, 25, 239–245. [9] Westerlind, H., Ramanujam, R., Uvehag, D., Kuja-Halkola, R. et al., Modest familial risks for multiple sclerosis: a registrybased study of the population of Sweden. Brain 2014, 137, 770–778. [10] Belbasis, L., Bellou, V., Evangelou, E., Ioannidis, J. P. A., Tzoulaki, I., Environmental risk factors and multiple sclerosis: an umbrella review of systematic reviews and metaanalyses. Lancet Neurol. 2015, 14, 263–273. [11] Baranzini, S. E., Mudge, J., vanVelkinburgh, J. C., Khankhanian, P. et al., Genome, epigenome and RNA sequences of monozygotic twins discordant for multiple sclerosis. Nature 2010, 464, 1351–1356. [12] Sajedi, S. A., Abdollahi, F., Geomagnetic disturbances may be environmental risk factor for multiple sclerosis: an ecological study of 111 locations in 24 countries. BMC Neurol. 2012, 12(100), 1–18. [13] Hafler, D. A., Slavik, J. M., Anderson, D. E., O’Connor, K. C. et al., Multiple sclerosis. Immunol. Rev. 2005, 204, 208–231. [14] Hauser, S. L., Oksenberg, J. R., The neurobiology of multiple sclerosis: genes, inflammation, and neurodegeneration. Neuron 2006, 52, 61–76. [15] Steinman, L., Immunology of relapse and remission in multiple sclerosis. Annu. Rev. Immunol. 2014, 32, 257–281. [16] Lassmann, H., Mechanisms of neurodegeneration shared between multiple sclerosis and Alzheimer’s disease. J. Neural Transm. 2011, 118, 747–752. [17] Lucchinetti, C. F., Popescu, B. F. G., Bunyan, R. F., Moll, N. M. et al., Inflammatory cortical demyelination in early multiple sclerosis. N. Engl. J. Med. 2011, 365, 2188–2197. ˜ C. O., Ruocco, H. H., Farias, A. S., Oliveira, C. et al., [18] Brandao, Intrathecal immunoglobulin G synthesis and brain injury by quantitative MRI in multiple sclerosis. Neuroimmunomodulation 2006, 13, 89–95. www.clinical.proteomics-journal.com
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How can proteomics elucidate the complexity of multiple sclerosis?
[19] Friese, M. A., Schattling, B., Fugger, L., Mechanisms of neurodegeneration and axonal dysfunction in multiple sclerosis. Nat. Rev. Neurol. 2014, 10, 225–238.
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central nervous system in systemic lupus erythematosus. J. Neurol. 1992, 239, 460–464.
[20] Filippi, M., Rocca, M. A., Multiple sclerosis: new measures to monitor the disease. Lancet Neurol. 2013, 12, 12–13.
[31] Harris, V. K., Sadiq, S. A., Biomarkers of therapeutic response in multiple sclerosis: current status. Mol. Diagn. Ther. 2014, 1–13.
[21] Narayana, P. A., Doyle, T. J., Lai, D., Wolinsky, J. S., Serial proton magnetic resonance spectroscopic imaging, contrastenhanced magnetic resonance imaging, and quantitative lesion volumetry in multiple sclerosis. Ann. Neurol. 1998, 43, 56–71.
[32] Ben Nun, A., Kaushansky, N., Kawakami, N., Krishnamoorthy, G. et al., From classic to spontaneous and humanized models of multiple sclerosis: Impact on understanding pathogenesis and drug development. J. Autoimmun. 2014, 54, 33–50.
[22] Fu, L., Matthews, P. M., DeStefano, N., Worsley, K. J. et al., Imaging axonal damage of normal-appearing white matter in multiple sclerosis. Brain 1998, 121, 103–113.
[33] Robinson, A. P., Harp, C. T., Noronha, A., Miller, S. D., The experimental autoimmune encephalomyelitis (EAE) model of MS: utility for understanding disease pathophysiology and treatment. Handb. Clin. Neurol. 2014, 122, 173–189.
[23] Lassmann, H., Multiple sclerosis: is there neurodegeneration independent from inflammation? J. Neurol. Sci. 2007, 259, 3–6. [24] Kutzelnigg, A., Lassmann, H., Pathology of multiple sclerosis and related inflammatory demyelinating diseases. Handb. Clin. Neurol. 2014, 122, 15–58.
[34] Rivers, T. M., Sprunt, D. H., Berry, G. P., Observations on attempts to produce acute disseminated encephalomyelitis in monkeys. J. Exp. Med. 1933, 58, 39–53.
[25] Milo, R., Miller, A., Revised diagnostic criteria of multiple sclerosis. Autoimmun. Rev. 2014, 13, 518–524.
[35] Baxter, A. G., The origin and application of experimental autoimmune encephalomyelitis. Nat. Rev. Immunol. 2007, 7, 904–912.
[26] Link, H., Huang, Y.-M., Oligoclonal bands in multiple sclerosis cerebrospinal fluid: an update on methodology and clinical usefulness. J. Neuimmunol. 2006, 180, 17–28.
[36] Kaltsonoudis, E., Voulgari, P. V., Konitsiotis, S., Drosos, A. A., Demyelination and other neurological adverse events after anti-TNF therapy. Autoimmun. Rev. 2014, 13, 54–58.
[27] Chu, A. B., Sever, J. L., Madden, D. L., Iivanainen, M. et al., Oligoclonal IgG bands in cerebrospinal fluid in various neurological diseases. Ann. Neurol. 1983, 13, 434–439.
˜ [37] Farias, A. S., Martins-de-Souza, D., Guimaraes, L., Pradella, F. et al., Proteome analysis of spinal cord during the clinical course of monophasic experimental autoimmune encephalomyelitis. Proteomics 2012, 12, 2656–2662.
¨ ¨ [28] Hampel, H., Kotter, H. U., Padberg, F., Korschenhausen, D. A., ¨ Moller, H. J., Oligoclonal bands and blood–cerebrospinalfluid barrier dysfunction in a subset of patients with Alzheimer disease: comparison with vascular dementia, major depression, and multiple sclerosis. Alzheimer Dis. Assoc. Disord. 1999, 13, 9–19. [29] Wengert, O., Rothenfusser-Korber, E., Vollrath, B., Bohner, G. et al., Neurosarcoidosis: correlation of cerebrospinal fluid findings with diffuse leptomeningeal gadolinium enhancement on MRI and clinical disease activity. J. Neurol. Sci. 2013, 335, 124–130. [30] Miller, D. H., Buchanan, N., Barker, G., Morrissey, S. P. et al., Gadolinium-enhanced magnetic resonance imaging of the
C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
[38] Farias, A. S., Pradella, F., Schmitt, A., Santos, L. M. B., Martins-de-Souza, D., Ten years of proteomics in multiple sclerosis. Proteomics 2014, 14, 467–480. [39] Filiou, M. D., Turck, C. W., General overview: biomarkers in neuroscience research. Int. Rev. Neurobiol. 2011, 101, 1–17. [40] Martins-de-Souza, D., Alsaif, M., Ernst, A., Harris, L. W. et al., The application of selective reaction monitoring confirms dysregulation of glycolysis in a preclinical model of schizophrenia. BMC Res. Notes 2012, 5(146), 1–7. [41] Wallin, M. T., Oh, U., Nyalwidhe, J., Semmes, J. et al., Serum proteomic analysis of a pre-symptomatic multiple sclerosis cohort. Eur. J. Neurol. 2015, 22, 591–599.
www.clinical.proteomics-journal.com
DOI 10.1002/prca.201400171
Proteomics Clin. Appl. 2015, 9, 844–847
How can proteomics elucidate the complexity of multiple sclerosis?
Alessandro S. Farias and Leonilda M. B. Santos Neuroimmunomodulation Group and Neuroimmunology Unit, Department of Genetics, Evolution and Bioagents, ˜ Paulo, Brazil University of Campinas, Campinas, Sao Multiple sclerosis affects more than 2.5 million people worldwide. Although multiple sclerosis was described almost 150 years ago, there are many knowledge gaps regarding its etiology, diagnosis, prognosis, and pathogenesis. Multiple sclerosis is an inflammatory, demyelinating, neurodegenerative disease of the CNS. During the last several decades, experimental models of multiple sclerosis have contributed to our understanding of the inflammatory disease mechanisms and have aided drug testing and development. However, little is known about the neurodegenerative mechanisms that operate during the evolution of the disease. Currently, all therapeutic approaches are primarily based on the inflammatory aspect of the disease. During the last decade, proteomics has emerged as a promising tool for revealing molecular pathways as well as identifying and quantifying differentially expressed proteins. Therefore, proteomics may be used for the discovery of biomarkers, potential drug targets, and new regulatory mechanisms. To date, a considerable number of proteomics studies have been conducted on samples from experimental models and patients with multiple sclerosis. These data form a solid base for further careful analysis and validation.
Received: October 30, 2014 Revised: April 28, 2015 Accepted: May 11, 2015
Keywords: Experimental autoimmune encephalomyelitis / Inflammation / Multiple sclerosis / Neurodegeneration / Proteomics
Multiple sclerosis is a complex disease in many aspects. JeanMartin Charcot described multiple sclerosis almost 150 years ago (1868); however, its etiology is still unknown, although it is unlikely that multiple sclerosis is associated with a unique causative event. Familial aggregation studies have demonstrated that the disease clusters in families. During the 1970s, an association was first found with the human leucocyte antigen DR2 isotype, and this association was refined in recent years using DNA-based typing methods to the DRB1*1501 [1–3]. Recently, large-scale collaborative genome-wide studies have enabled the discovery of many nonhuman leucocyte antigen susceptibility variants associated with multiple sclerosis [4]. These variants are mostly associated with immunological processes and are frequently associated with other Correspondence: Dr. Alessandro S Farias, Departamento de ´ ˜ e Bioagentes, Instituto de Biologia-UNICAMP, Genetica, Evoluc¸ao Campinas, SP, CEP 13083-970, Brazil E-mail: [email protected] Fax: +55-19-35216185 Abbreviations: CSF, cerebrospinal fluid; EAE, experimental autoimmune encephalomyelitis C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
autoimmune diseases [5–7]. However, the analysis of these data has revealed only a moderate effect on the multiple sclerosis odds ratio at best [8, 9]. Nonetheless, the fact that the disease frequency varies worldwide and the high discordance rate observed among monozygotic twins indicates a potential environmental influence on multiple sclerosis development [10,11]. During the last several decades, many environmental factors (e.g. sunlight exposure, diet, infections, and lifestyle) have been associated with multiple sclerosis risk to some extent. However, none of these factors alone have shown a high odds ratio [2, 12]. Thus, genetic and epidemiological studies have indicated that the disease must be a result of a complex genetic predisposition combined with an environmental trigger [7, 13, 14]. Multiple sclerosis is considered to be a demyelinating autoimmune disease. Similar to the majority of autoimmune pathologies, multiple sclerosis is more common in women. Most of the patients (85%) present with a relapse-remitting clinical manifestation of the disease, and immunomodulatory or immunosuppressive therapies are effective in partially controlling the clinical manifestations of the disease [14, 15]. In parallel, there is an important neurodegenerative aspect of the www.clinical.proteomics-journal.com
Proteomics Clin. Appl. 2015, 9, 844–847
How can proteomics elucidate the complexity of multiple sclerosis?
Correspondence concerning this and other Viewpoint articles can be accessed on the journals’ home page at: http://viewpoint.proteomics-journal.de Correspondence for posting on these pages is welcome and can also be submitted at this site.
disease [16], which was first considered to be a consequence of the inflammatory response. However, recent studies have shown that the neurodegenerative process occurs even in the early stages of the disease [17, 18]. Moreover, some studies have provided evidence suggesting that axonal and neuronal impairment could be an independent contributor to the progression of multiple sclerosis [19–22]. However, more precise neuropathological observations have revealed that inflammation is always present during the entire course of the disease [23]. This observation does not support the concept of a neurodegenerative component occurring in the absence of inflammation. However, during the progressive stage of the disease or in the absence of gadolinium enhancement, the inflammation differs in terms of cells and humoral factors from the classical inflammation found in active plaques [23]. Recently, it has become clear that there is inflammation and tissue damage throughout the entire CNS (white matter, apparently normal white matter and gray matter) [24]. The complexity of multiple sclerosis pathology has implications for its diagnosis. The most recent diagnostic criteria are based on MRI evidence of CNS lesions disseminated temporally and spatially. Although helpful, cerebrospinal fluid (CSF) parameters are not strictly necessary for the diagnosis of multiple sclerosis [25]. The majority of patients present with increased immunoglobulin concentrations, and approximately 90% present oligoclonal bands exclusively detected by the separation of CFS proteins in electrophoresis gel or by IEF followed by immunoblotting [26]. However, these features can be found in other neurological and/or inflammatory conditions [27–30]. In terms of prognosis, a large number of features (early onset age, gender, ethnic origin, specific symptoms, number of attacks, and progression during the first years) may predict the evolution of the disease. Currently, a single laboratory test has not been established for the diagnosis or prognosis of multiple sclerosis [31]. Furthermore, very little is known about the neurodegenerative mechanisms of the disease. The absence of information about the neurodegenerative aspects of multiple sclerosis hinders the development of therapeutic approaches. The majority of the knowledge about the inflammatory mechanisms of multiple sclerosis has been obtained from studies using experimental models. Experimental autoimmune encephalomyelitis (EAE) can be induced in susceptible animals by active immunization with neuroantigens or by adoptive transfer of preactivated encephalitogenic T cells [32]. EAE can have a broad clinical evolution depending on C 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim
845
the species, strain, or neuroantigen used [33]. Since its development in 1933 [34], EAE has been helpful not only for understanding the inflammatory mechanisms of multiple sclerosis but also for the development and testing of therapeutic strategies. Most of the currently approved therapies for multiple sclerosis were developed or tested in EAE models [35]. However, some approaches that were successful for the treatment of EAE showed poor outcomes for the treatment of multiple sclerosis [36]. Nevertheless, the following points must be considered. (i) EAE is normally induced in isogenic animals. Therefore, it does not reflect the genetic variability found in humans. (ii) Laboratory animals are housed and maintained under pathogen-free conditions, which eliminates the influence of environmental factors (infections, microbiota composition, food intake, weather, temperature, solar incidence, and social behavior) during disease evolution or therapeutic approaches. (iii) Much of the data that have contributed to our understanding of the pathophysiology of EAE were originally derived from knockout animals. (iv) Studies conducted in animal models are normally performed with acute diseases, which compromise our knowledge of the disease mechanisms and the effects of “chronic” treatments. (v) We estimate that the etiology of multiple sclerosis begins years, if not decades, before the first clinical manifestations. In contrast, EAE has a rapid clinical evolution. Nevertheless, EAE has been unequivocally important for understanding the neuroinflammatory mechanisms of multiple sclerosis. Moreover, recent studies using different proteomics approaches have noted early neurodegenerative signatures during the evolution of EAE [37], which seems to be, at least in part, in agreement with the findings in CSF from multiple sclerosis patients [38]. Proteomics analyses are a powerful tool for global proteome analyses and protein identification [39]. Recently, with mass spectrometry, it has also become possible to reliably quantify differentially expressed proteins by SRM [40]. Thus, combined proteomics technologies are suitable for identifying and analyzing regulation within molecular pathways. Assuming that multiple sclerosis is a pathway disorder, proteomics is one of the most appropriate approaches for understanding and establishing biomarkers. Due to the inflammatory and neurodegenerative aspects of multiple sclerosis, it is not likely that one single biomarker could be used to separate multiple sclerosis from other neurological and/or inflammatory diseases. Recently, we reviewed the last 10 years of proteomics studies in multiple sclerosis or EAE [38]. Although no definitive conclusions could be achieved from the existing data, interesting observations can be highlighted. Many of the regulated proteins in these studies are related to structural and metabolic pathways and are not directly related to the immune response [38]. Although the studies were performed with different techniques and samples, many differentially regulated proteins have appeared in different studies in both experimental models and multiple sclerosis samples [38]. Although a considerable number of studies have been performed, the focus is usually on only one clinical www.clinical.proteomics-journal.com
846
A. S. Farias and L. M. B. Santos
manifestation of the disease or on a small number of enrolled patients. Yet, the majority of the studies were performed in patients under disease-modifying therapies, which might contaminate serum or CSF proteome. More importantly, these protein candidates need to be validated, and their penetrance should be evaluated. Nevertheless, a panel of potential biomarkers could be established using these “preliminary” data to facilitate the diagnosis and/or prognosis of the disease. Moreover, a more careful examination of the regulated pathways could reveal new therapeutic targets. Interestingly, a recent study using presymptomatic and postsymptomatic sera demonstrated that some proteins were differentially regulated in presymptomatic multiple sclerosis samples compared with the control samples [41]. These data suggest that there are abnormalities even before the onset of symptoms. More importantly, these results reveal that the risk of developing the disease may be predicted years before the onset. For many decades, we assumed that multiple sclerosis was primarily an inflammatory disease and that its etiology was related to the autoimmune process. Recently, the possibility of a primarily neurodegenerative etiology has emerged [19–21]. Can proteomics help to identify the initiating factors involved in multiple sclerosis development? It is likely that only the existence of a unique genetic signature (e.g. a specific mutation) or an etiological agent (environmental factor) could irrefutably answer this question. Despite the large number of epidemiological studies and the existence of an International Multiple Sclerosis Genetics Consortium, these unique genetic signatures or etiological agent have not yet been identified. Thus, although this is an intriguing question, it might not be the most important question at the moment. Currently, a substantial therapeutic arsenal is available for combatting the inflammatory aspect of the disease. However, there is no single drug that can manage the neurodegenerative events. Therefore, new therapeutic strategies must be developed to treat the progression of neurodegeneration. Moreover, earlier and more precise diagnoses would most likely improve the results of current and future therapies. In summary, the current knowledge base regarding multiple sclerosis has many gaps that have yet to be filled. Without question, proteomics is one strategy that could be applied toward the elucidation of the molecular aspects of the disease. Fortunately, a large amount of data have been generated in proteomic studies performed during the last decade. These data represent a solid basis for further studies. The authors have declared no conflict of interest.
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Proteomics Clin. Appl. 2015, 9, 844–847
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