Biomarkers of Multiple Sclerosis

Tear Biomarkers in Alzheimer's and Parkinson's Diseases, and Multiple Sclerosis: Implications for Diagnosis (Systematic Review)

Biological material is one of the most important aspects that allow for the correct diagnosis of the disease, and tears are an interesting subject of research because of the simplicity of collection, as the well as the relation to the components similar to other body fluids. In this review, biomarkers for Alzheimer's disease (AD), Parkinson's disease (PD), and multiple sclerosis (MS) in tears are investigated and analyzed. Records were obtained from the PubMed and Google Scholar databases in a timeline of 2015-2022. The keywords were: tear film/tear biochemistry/tear biomarkers + diseases (AD, PD, or MS). The recent original studies were analyzed, discussed, and biomarkers present in tears that can be used for the diagnosis and management of AD, PD, and MS diseases were shown. α-synTotal and α-synOligo, lactoferrin, norepinephrine, adrenaline, epinephrine, dopamine, α-2-macroglobulin, proteins involved in immune response, lipid metabolism and oxidative stress, apolipoprotein superfamily, and others were shown to be biomarkers in PD. For AD as potential biomarkers, there are: lipocalin-1, lysozyme-C, and lacritin, amyloid proteins, t-Tau, p-Tau; for MS there are: oligoclonal bands, lipids containing choline, free carnitine, acylcarnitines, and some amino acids. Information systematized in this review provides interesting data and new insight to help improve clinical outcomes for patients with neurodegenerative disorders.

Developing a clinical-environmental-genotypic prognostic index for relapsing-onset multiple sclerosis and clinically isolated syndrome

Our inability to reliably predict disease outcomes in multiple sclerosis remains an issue for clinicians and clinical trialists. This study aims to create, from available clinical, genetic and environmental factors; a clinical–environmental–genotypic prognostic index to predict the probability of new relapses and disability worsening. The analyses cohort included prospectively assessed multiple sclerosis cases (N = 253) with 2858 repeated observations measured over 10 years. N = 219 had been diagnosed as relapsing-onset, while N = 34 remained as clinically isolated syndrome by the 10th-year review. Genotype data were available for 199 genetic variants associated with multiple sclerosis risk. Penalized Cox regression models were used to select potential genetic variants and predict risk for relapses and/or worsening of disability. Multivariable Cox regression models with backward elimination were then used to construct clinical–environmental, genetic and clinical–environmental–genotypic prognostic index, respectively. Robust time-course predictions were obtained by Landmarking. To validate our models, Weibull calibration models were used, and the Chi-square statistics, Harrell’s C-index and pseudo-R² were used to compare models. The predictive performance at diagnosis was evaluated using the Kullback–Leibler and Brier (dynamic) prediction error (reduction) curves. The combined index (clinical–environmental–genotypic) predicted a quadratic time-dynamic disease course in terms of worsening (HR = 2.74, CI: 2.00–3.76; pseudo-R²=0.64; C-index = 0.76), relapses (HR = 2.16, CI: 1.74–2.68; pseudo-R² = 0.91; C-index = 0.85), or both (HR = 3.32, CI: 1.88–5.86; pseudo-R² = 0.72; C-index = 0.77). The Kullback–Leibler and Brier curves suggested that for short-term prognosis (≤5 years from diagnosis), the clinical–environmental components of disease were more relevant, whereas the genetic components reduced the prediction errors only in the long-term (≥5 years from diagnosis). The combined components performed slightly better than the individual ones, although their prognostic sensitivities were largely modulated by the clinical–environmental components. We have created a clinical–environmental–genotypic prognostic index using relevant clinical, environmental, and genetic predictors, and obtained robust dynamic predictions for the probability of developing new relapses and worsening of symptoms in multiple sclerosis. Our prognostic index provides reliable information that is relevant for long-term prognostication and may be used as a selection criterion and risk stratification tool for clinical trials. Further work to investigate component interactions is required and to validate the index in independent data sets.

Laboratory biomarkers of Multiple Sclerosis (MS)

Multiple Sclerosis (MS) is a neurological disease that affects the central nervous system (CNS). The diagnosis of the disease is quite challenging due to its variation among patients. As a result, the need to enhance diagnostic procedures, evaluate objective prognostic markers and promote effective monitoring of patients' responses to treatment has prompted the identification of many biomarkers. To present up-to-date knowledge on potential biomarkers for MS used to assess disease activity, progression, and therapeutic responses. The search for articles was conducted in various databases, namely, PubMed, Cochrane Library, and CINAHL, using an identical search strategy and terms that included "Multiple Sclerosis," "MS," "biomarkers," "potential," "magnetic resonance spectroscopy," "progress," "marker," "predict," "disability," "indicator," and "mass spectrometry." Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines were followed when scrutinizing the articles for inclusion in the study. The search process identified 75 articles that were used in this systematic review. MS biomarkers consisted of laboratory biomarkers, imaging biomarkers, and genetic and immunogenetic biomarkers. The efficacy, which leads to their potential classification, relies on numerous factors, such as sensitivity, specificity, clinical rationale, predictability, practicality, biological rationale, reproducibility, and correlations with prognosis and disability. Oligoclonal bands (OCBs) and magnetic resonance imaging (MRI) features are the most established biomarkers so far, although kappa free light chains (kFLCs), the measles-rubella-zoster (MRZ) reaction, and neurofilament light chains (NfLs) might show potential in the near future after more studies are conducted.

Comparison between cerebrospinal fluid and serum levels of myelin-associated glycoprotein, total antioxidant capacity, and 8-hydroxy-2'-deoxyguanosine in patients with multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a chronic inflammatory disease characterized by demyelinated lesions in the brain, the spinal cord, and the optic nerve. It is one of the most common neurological disorders. In this study, serum and cerebrospinal fluid (CSF) levels of total antioxidant capacity (TAC), myelin-associated glycoprotein (MAG), and 8-hydroxy-2'-deoxyguanosine (8-OHdG) were investigated to determine their effects on MS.

MATERIALS AND METHOD

In this study, 25 serum and cerebrospinal samples from MS patients as a case group and 40 serum and CSF samples from healthy participants as a control group were collected and analyzed. Concentrations of TAC, MAG, and 8-OhdG were determined in the samples using a dedicated kit and relayed using the ELISA device.

RESULTS

The mean serum antibody levels of MAG and TAC were higher in the case group than the control group, although the difference in the MAG level was not significant (P > 0.05). However, the mean serum level of -8 OHdG was lower in the case group than the control group. Moreover, the mean levels of the evaluated biomarkers in the CSF samples were higher in the case group than in the control group. Still, the difference was only significant in terms of TAC levels (P < 0.05). Receiver operating characteristics curve analysis showed that the area under the curve was 0.71 and 0.69 for 8-OhdG and TAC serum levels, respectively, and 0.73 for both TAC and CSF levels, which was not significantly different from that in other biomarkers.

CONCLUSION

Elevated TAC levels in serum and CSF samples and 8-OhdG in serum samples may be associated with MS pathogenesis. However, further investigation is needed to consider these cases as a follow-up to the therapeutic goals or treatment process.