Current approaches for research of multiple sclerosis biomarkers

Abstract

Current data concerning features of multiple sclerosis (MS) etiology, pathogenesis, clinical course and treatment of disease indicate the necessity of personalized approach to the management of MS patients. These features are the variety of possible etiological factors and mechanisms that trigger the development of MS, different courses of disease, and significant differences in treatment efficiency. Phenotypic and pathogenetic heterogeneity of MS requires, on the one hand, the stratification of patients into groups with different treatment depending on a number of criteria including genetic characteristics, disease course, stage of the pathological process, and forms of the disease. On the other hand, it requires the use of modern methods for assessment of individual  risk of developing MS, its early diagnosis, evaluation and prognosis of the disease course and the treatment efficiency. This approach is based on the identification and determination of biomarkers of MS including the use of systems biology technology platforms such as genomics, proteomics, metabolomics and bioinformatics. Research and practical use of biomarkers of MS in clinical and laboratory practice requires the use of a wide range of modern medical and biological, mathematical and physicochemical methods. The group of "classical" methods used to study MS biomarkers includes physicochemical and immunological methods aimed at the selection and identification of single molecular biomarkers, as well as methods of molecular genetic analysis. This group of methods includes ELISA, western blotting, isoelectric focusing, immunohistochemical methods, flow cytometry, spectrophotometric and nephelometric methods. These techniques make it possible to carry out both qualitative and quantitative assay of molecular biomarkers. The group of "classical methods" can also include methods based on polymerase chain reaction (including multiplex and allele-specific PCR) and genome sequencing techniques (including full genome resequencing, targeted resequencing of the genome). The results obtained with these techniques became the basis for the further development of screening technologies. Disadvantages of the "classical" methods are associated not only with their resolution or other technical limitations but also to the fact that the range of pathological processes in MS may vary significantly from patient to patient and single biomarkers suitable for one group of patients may be inappropriate for another group of patients. Due to the complexity of MS the reflection of pathological changes may be determined not by single biomarkers but by isolated biomarkers panel from different compartments. The solution of this problem seems to be possible due to the development of microarray methods including biochips technology. Biochips are used for screening of MS patients and allow determining the rare MS-associated gene variants that have a significant impact on the development of the disease. In conjunction with the "classical" methods, microarrays allowed to apply systems biology approaches (i.e. genomics, transcriptomics, proteomics, metabolomics, epigenomics) in the study of MS biomarkers. Addition of bioinformatics methods to "classical" and microarray laboratory methods allows not only to find new biomarkers but to identify complex patterns of biomarkers while single biomarkers informative value is not sufficient. To date, the use of genome-wide association study (GWAS) revealed more than a hundred genetic variants associated with the development of MS, while the total number of investigated genetic variants including the candidate ones exceeded two hundred. GWAS is used to identify correlations of genetic variants with the disease, including the identification of variants associated with a risk of developing MS, but cannot answer the question of the causal links between specific genes polymorphism and the pathogenesis of MS. Current studies of biomarkers of disease severity, progression, pathogenetic type and treatment efficacy are based on transcriptomics, proteomics and metabolomics technologies. Transcriptomics includes genome-wide research of RNA sequences based on the results obtained with comparative genomic hybridization on biochips, massive parallel RNA sequencing, and measuring the amount of mRNA by real-time PCR. This technology is actively used in studies of gene expression profile of peripheral blood mononuclear cells from MS patients aimed at identifying molecular markers of disease status suitable for clinical use. Proteomics is a large-scale expression and protein distribution studies in patients with MS based on the results obtained via microarray and mass spectrometry, liquid and gas chromatography methods. In recent years, a growing number of MS proteomic studies using 2DE-MS method (two-dimensional electrophoresis coupled with mass spectrometry). Metabolomics studies of low-molecular-weight metabolic profiles based on the results obtained by mass spectrometry, liquid and gas chromatography, nuclear magnetic resonance. However, unlike other «-omics»-technologies, in metabolomics microarray-techniques are not used. Conclusion. Search, verification and clinical application of biomarkers for multiple sclerosis are one of the most challenging medical and biological problems. Its solution requires an interdisciplinary approach, organization of large-scale research and engagement of new research methods. In recent years, a significant amount of data received allowed to reveal hundreds of candidate biomarkers. Some of these biomarkers have significant potential for the monitoring of disease activity and assessment of therapy efficiency. However, the verification is required for a widespread clinical application; it implies further large-scale studies in different countries. The development of personalized medicine in Ukraine, the application of its principles to the management of multiple sclerosis patients, along with the use of advanced "classic" biomarker research methods requires the introduction of modern methods including the use of new-generation biochips, genomics technologies, proteomics and metabolomics.