Differential Gene Expression Patterns in Blood and Cerebrospinal Fluid of Multiple Sclerosis and Neuro-Behçet Disease

Increased T-bet/GATA-3 and ROR-γt /Foxp3 Ratios in Cerebrospinal Fluid as Potential Criteria for Definite Neuro-Behçet’s Disease

When the central nervous system (CNS) is the primary affected site in an initial attack of Behçet’s disease (BD), the differential diagnosis is particularly challenging. Some cases remain unclassified or qualified as probable neuro-Behçet’s disease (NBD). Several cytokines are involved in the immunopathogenesis of this disease; however, studies establishing the differential cytokine pattern between probable and definite NBD are scarce. Twenty-eight parenchymal NBD patients, diagnosed according to the International Consensus Recommendation (ICR) criteria and classified into definite (D-NBD; n = 17) and probable (P-NBD; n = 11), were sampled at their first neurological symptoms, and compared with healthy control subjects (n = 20). Oligoclonal bands (OCB) of IgG were detected by isoelectric focusing on agarose, and immunoblotting of matched serum and cerebrospinal fluid (CSF) sample pairs. T cell cytokines (INF-γ, IL-4, IL-17, and IL-10) and transcription factors related to Th1, Th2, Th17, and T regulatory populations (respectively T-bet, GATA-3, ROR-γt, and Foxp3) were studied by quantitative RT-PCR in peripheral blood mononuclear cells (PBMCs) and CSF cells. Inflammatory cytokines such as IL-6, TNF-α, and IL-1β were also analyzed. CSF OCB pattern 2 was present in only 1 out of 28 neuro-Behçet’s patients who belonged to the P-NBD group. Two D-NBD patients had OCB in CSF showing pattern 4. In the D-NBD CSF samples, IL-17 and IL-10 expressions were significantly elevated compared to P-NBD. Moreover, D-NBD patients had increased levels of T-bet/GATA-3 and ROR-γt/Foxp3 ratios compared to P-NBD. Furthermore, a significant increase of CSF IL-6 in D-NBD, compared to P-NBD and the controls, was found. In addition to the increased IL-6 level, the data obtained suggest the existence in D-NBD patients of a significantly disrupted balance between Th17 effector and T regulatory cells, as reflected by the enhanced ROR-γt/Foxp3 ratio. This could be considered as an additional criterion for definite neuro-Behçet’s disease.

Alteration of interleukin-10-producing Type 1 regulatory cells in autoimmune diseases

PURPOSE OF REVIEW

This review highlights findings describing the role of interleukin (IL)-10-producing Type 1 regulatory T (Tr1) cells in controlling autoimmune diseases and possible approaches to restore their function and number.

RECENT FINDINGS

Reduced frequency and/or function of cell subsets playing a role in Tr1 cell induction (e.g., DC-10 and Bregs), was found in patients with autoimmunity and may impact on Tr1 cell frequency.

SUMMARY

IL-10 is a pleiotropic cytokine with fundamental anti-inflammatory functions acting as negative regulator of immune responses. IL-10 is critically involved in the induction and functions of Tr1 cells, a subset of memory CD4+ T cells induced in the periphery to suppress immune responses to a variety of antigens (Ags), including self-, allogeneic, and dietary Ags. Alterations in IL-10-related pathways and/or in the frequency and activities of Tr1 cells have been associated to several autoimmune diseases. We will give an overview of the alterations of IL-10 and IL-10-producing Tr1 cells in Multiple Sclerosis, Type 1 Diabetes, and Celiac Disease, in which similarities in the role of these tolerogenic mechanisms are present. Current and future approaches to overcome Tr1 cell defects and restore tolerance in these diseases will also be discussed.

Posttranslational modifications of proteins are key features in the identification of CSF biomarkers of multiple sclerosis

Background

Multiple sclerosis is an inflammatory and degenerative disease of the central nervous system (CNS) characterized by demyelination and concomitant axonal loss. The lack of a single specific test, and the similarity to other inflammatory diseases of the central nervous system, makes it difficult to have a clear diagnosis of multiple sclerosis. Therefore, laboratory tests that allows a clear and definite diagnosis, as well as to predict the different clinical courses of the disease are of utmost importance. Herein, we compared the cerebrospinal fluid (CSF) proteome of patients with multiple sclerosis (in the relapse–remitting phase of the disease) and other diseases of the CNS (inflammatory and non-inflammatory) aiming at identifying reliable biomarkers of multiple sclerosis.

Methods

CSF samples from the discovery group were resolved by 2D-gel electrophoresis followed by identification of the protein spots by mass spectrometry. The results were analyzed using univariate (Student’s t test) and multivariate (Hierarchical Cluster Analysis, Principal Component Analysis, Linear Discriminant Analysis) statistical and numerical techniques, to identify a set of protein spots that were differentially expressed in CSF samples from patients with multiple sclerosis when compared with other two groups. Validation of the results was performed in samples from a different set of patients using quantitative (e.g., ELISA) and semi-quantitative (e.g., Western Blot) experimental approaches.

Results

Analysis of the 2D-gels showed 13 protein spots that were differentially expressed in the three groups of patients: Alpha-1-antichymotrypsin, Prostaglandin-H2-isomerase, Retinol binding protein 4, Transthyretin (TTR), Apolipoprotein E, Gelsolin, Angiotensinogen, Agrin, Serum albumin, Myosin-15, Apolipoprotein B-100 and EF-hand calcium-binding domain—containing protein. ELISA experiments allowed validating part of the results obtained in the proteomics analysis and showed that some of the alterations in the CSF proteome are also mirrored in serum samples from multiple sclerosis patients. CSF of multiple sclerosis patients was characterized by TTR oligomerization, thus highlighting the importance of analyzing posttranslational modifications of the proteome in the identification of novel biomarkers of the disease.

Conclusions

The model built based on the results obtained upon analysis of the 2D-gels and in the validation phase attained an accuracy of about 80% in distinguishing multiple sclerosis patients and the other two groups.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02404-2.