Multiple Sclerosis: Relationships Between Cytokines, MRI Lesion Burden, Visual Evoked Potentials and Disability Scores

Vitamin D deficiency in relation with the systemic and central inflammation during multiple sclerosis

Background

During the last decade, vitamin D (VitD) has become a topic of interest in immune regulation, especially in multiple sclerosis (MS) disease. Amongst the wide range of effects reported for this vitamin on the immune system, a regulatory role on cytokines production has been described. Our aim is to analyze the status of VitD and its correlation with the circulating inflammation and the intrathecal humoral response during MS.

Methods

We analyzed samples of 318 individuals: 108 MS patients and 210 controls. Determination of 25-(OH) VitD3 level in serum was made using electrochemiluminescence method. Circulating inflammatory cytokines (IL-6, IL-8, IL-10, TNF-a, IL12p70 and IL-1b) were investigated using Cytometer Bead Array Technology. The central humoral response was characterized using CSF isofocusing test and IgG Index calculation.

Results

As expected, mean value of VitD was significantly lower in MS group (26 nmol/L) than in control group (34.75 nmol/L) (p=0.002), with a severe deficiency in 67% of MS patients. Mean value of VitD was significantly lower in MS female patients. Regarding cytokines, mean value of TNFa was significantly higher in MS patients with oligoclonal bands of IgG in the CSF. IL6 was positively correlated with IgG level in serum of MS patients.

Conclusions

Our results support the association of VitD deficiency with MS, especially in female patients of our region. However, the vitamin level seems to not correlate with inflammatory cytokines nor with disability. Interestingly, TNFa and IL6 levels were correlated with the intrathecal synthesis of IgG and the circulating IgG level, respectively.

Multiplex Analysis of Serum Cytokine Profiles in Systemic Lupus Erythematosus and Multiple Sclerosis

Changes in cytokine profiles and cytokine networks are known to be a hallmark of autoimmune diseases, including systemic lupus erythematosus (SLE) and multiple sclerosis (MS). However, cytokine profiles research studies are usually based on the analysis of a small number of cytokines and give conflicting results. In this work, we analyzed cytokine profiles of 41 analytes in patients with SLE and MS compared with healthy donors using multiplex immunoassay. The SLE group included treated patients, while the MS patients were drug-free. Levels of 11 cytokines, IL-1b, IL-1RA, IL-6, IL-9, IL-10, IL-15, MCP-1/CCL2, Fractalkine/CX3CL1, MIP-1a/CCL3, MIP-1b/CCL4, and TNFa, were increased, but sCD40L, PDGF-AA, and MDC/CCL22 levels were decreased in SLE patients. Thus, changes in the cytokine profile in SLE have been associated with the dysregulation of interleukins, TNF superfamily members, and chemokines. In the case of MS, levels of 10 cytokines, sCD40L, CCL2, CCL3, CCL22, PDGF-AA, PDGF-AB/BB, EGF, IL-8, TGF-a, and VEGF, decreased significantly compared to the control group. Therefore, cytokine network dysregulation in MS is characterized by abnormal levels of growth factors and chemokines. Cross-disorder analysis of cytokine levels in MS and SLE showed significant differences between 22 cytokines. Protein interaction network analysis showed that all significantly altered cytokines in both SLE and MS are functionally interconnected. Thus, MS and SLE may be associated with impaired functional relationships in the cytokine network. A cytokine correlation networks analysis revealed changes in correlation clusters in SLE and MS. These data expand the understanding of abnormal regulatory interactions in cytokine profiles associated with autoimmune diseases.

Computational Intelligence Technique for Prediction of Multiple Sclerosis Based on Serum Cytokines

Multiple sclerosis (MS) is a neurodegenerative disease characterized by lesions in the central nervous system (CNS). Inflammation and demyelination are the leading causes of neuronal death and brain lesions formation. The immune reactivity is believed to be essential in the neuronal damage in MS. Cytokines play important role in differentiation of Th cells and recruitment of auto-reactive B and T lymphocytes that leads to neuron demyelination and death. Several cytokines have been found to be linked with MS pathogenesis. In the present study, serum level of eight cytokines (IL-1β, IL-2, IL-4, IL-8, IL-10, IL-13, IFN-γ, and TNF-α) was analyzed in USA and Russian MS to identify predictors for the disease. Further, the model was extended to classify MS into remitting and non-remitting by including age, gender, disease duration, Expanded Disability Status Scale (EDSS) and Multiple Sclerosis Severity Score (MSSS) into the cytokines datasets in Russian cohorts. The individual serum cytokines data for the USA cohort was generated by Z score percentile method using R studio, while serum cytokines of the Russian cohort were analyzed using multiplex immunoassay. Datasets were divided into training (70%) and testing (30%). These datasets were used as an input into four machine learning models (support vector machine, decision tree, random forest, and neural networks) available in R programming language. Random forest model was identified as the best model for diagnosis of MS as it performed remarkable on all the considered criteria i.e., Gini, accuracy, specificity, AUC, and sensitivity. RF model also performed best in predicting remitting and non-remitting MS. The present study suggests that the concentration of serum cytokines could be used as prognostic markers for the prediction of MS.

Evaluating sex hormones and cytokine profile in Egyptian females with relapsing-remitting multiple sclerosis

Background

Sexual dimorphism shown in multiple sclerosis suggests an interaction between immune system and sex hormones. The objective of this study is to determine the hormonal profile and serum cytokine levels in Egyptian female patients with relapsing-remitting MS (RRMS) compared with healthy controls and their associations with disease disability.

Methods

This study was conducted on 40 female patients with RRMS and 20 age-matched controls subjected to measurements of the hormonal profile (estrogen, testosterone) and cytokine levels (interleukin 10 and 4 and tumor necrosis factor alpha) and disability assessment using Expanded Disability Status Scale (EDSS).

Results

Levels of estrogen, testosterone, interleukin 10 and 4 (IL-10 and IL-4), and tumor necrosis factor alpha (TNF-α) were higher in patients compared to control with no statistically significant difference. Estrogen levels were positively correlated with interleukin 10 and interleukin 4 levels and negatively correlated with tumor necrosis factor alpha (TNF-α), but there was no statistically significant correlation between hormonal profile or cytokine profile (IL-10, IL-4, and TNF-α) and EDSS.

Conclusions

It is suggested that estrogen has an anti-inflammatory effect on cytokine milieu; therefore, it can be tried as a treatment option in multiple sclerosis.