Abrogation of T cell quiescence characterizes patients at high risk for multiple sclerosis after the initial neurological event

An analytical review on the use of artificial intelligence and machine learning in diagnosis, prediction, and risk factor analysis of multiple sclerosis

Medical research offers potential for disease prediction, like Multiple Sclerosis (MS). This neurological disorder damages nerve cell sheaths, with treatments focusing on symptom relief. Manual MS detection is time-consuming and error prone. Though MS lesion detection has been studied, limited attention has been paid to clinical analysis and computational risk factor prediction. Artificial intelligence (AI) techniques and Machine Learning (ML) methods offer accurate and effective alternatives to mapping MS progression. However, there are challenges in accessing clinical data and interdisciplinary collaboration. By analyzing 103 papers, we recognize the trends, strengths and weaknesses of AI, ML, and statistical methods applied to MS diagnosis. AI/ML-based approaches are suggested to identify MS risk factors, select significant MS features, and improve the diagnostic accuracy, such as Rule-based Fuzzy Logic (RBFL), Adaptive Fuzzy Inference System (ANFIS), Artificial Neural Network methods (ANN), Support Vector Machine (SVM), and Bayesian Networks (BNs). Meanwhile, applications of the Expanded Disability Status Scale (EDSS) and Magnetic Resonance Imaging (MRI) can enhance MS diagnostic accuracy. By examining established risk factors like obesity, smoking, and education, some research tackled the issue of disease progression. The performance metrics varied across different aspects of MS studies: Diagnosis: Sensitivity ranged from 60 % to 98 %, specificity from 60 % to 98 %, and accuracy from 61 % to 97 %. Prediction: Sensitivity ranged from 76 % to 98 %, specificity from 65 % to 98 %, and accuracy from 62 % to 99 %. Segmentation: Accuracy ranged up to 96.7 %. Classification: Sensitivity ranged from 78 % to 97.34 %, specificity from 65 % to 99.32 %, and accuracy from 71 % to 97.94 %. Furthermore, the literature shows that combining techniques can improve efficiency, exploiting their strengths for better overall performance.

Dysregulated lipid metabolism networks modulate T-cell function in people with relapsing-remitting multiple sclerosis

Altered cholesterol, oxysterol, sphingolipid, and fatty acid concentrations are reported in blood, cerebrospinal fluid, and brain tissue of people with relapsing-remitting multiple sclerosis (RRMS) and are linked to disease progression and treatment responses. CD4 + T cells are pathogenic in RRMS, and defective T-cell function could be mediated in part by liver X receptors (LXRs)-nuclear receptors that regulate lipid homeostasis and immunity. RNA-sequencing and pathway analysis identified that genes within the 'lipid metabolism' and 'signalling of nuclear receptors' pathways were dysregulated in CD4 + T cells isolated from RRMS patients compared with healthy donors. While LXRB and genes associated with cholesterol metabolism were upregulated, other T-cell LXR-target genes, including genes involved in cellular lipid uptake (inducible degrader of the LDL receptor, IDOL), and the rate-limiting enzyme for glycosphingolipid biosynthesis (UDP-glucosylceramide synthase, UGCG) were downregulated in T cells from patients with RRMS compared to healthy donors. Correspondingly, plasma membrane glycosphingolipids were reduced, and cholesterol levels increased in RRMS CD4 + T cells, an effect partially recapitulated in healthy T cells by in vitro culture with T-cell receptor stimulation in the presence of serum from RRMS patients. Notably, stimulation with LXR-agonist GW3965 normalized membrane cholesterol levels, and reduced proliferation and IL17 cytokine production in RRMS CD4 + T-cells. Thus, LXR-mediated lipid metabolism pathways were dysregulated in T cells from patients with RRMS and could contribute to RRMS pathogenesis. Therapies that modify lipid metabolism could help restore immune cell function.

A systematic review of the application of machine-learning algorithms in multiple sclerosis

INTRODUCTION

The applications of artificial intelligence, and in particular automatic learning or "machine learning" (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years.

OBJECTIVE

We present a systematic review of the application of ML algorithms in MS.

MATERIALS AND METHODS

We used the PubMed search engine, which allows free access to the MEDLINE medical database, to identify studies including the keywords "machine learning" and "multiple sclerosis." We excluded review articles, studies written in languages other than English or Spanish, and studies that were mainly technical and did not specifically apply to MS. The final selection included 76 articles, and 38 were rejected.

CONCLUSIONS

After the review process, we established 4 main applications of ML in MS: 1) classifying MS subtypes; 2) distinguishing patients with MS from healthy controls and individuals with other diseases; 3) predicting progression and response to therapeutic interventions; and 4) other applications. Results found to date have shown that ML algorithms may offer great support for health professionals both in clinical settings and in research into MS.

GPX4 aggravates experimental autoimmune encephalomyelitis by inhibiting the functions of CD4+ T cells

Multiple sclerosis (MS) is a common autoimmunity disease of the central nervous system (CNS) that mostly happens in young adults. The chronic clinical features of MS include inflammatory demyelination, infiltration of immune cells, and secretion of inflammatory cytokines, which have been proved to be associated with CD4⁺ T cells. Ferroptosis is a newly discovered programmed cell death mediated by the massive lipid peroxidation and more sensitive to CD4⁺ T cells. However, the effect of ferroptosis of CD4⁺ T cells on the occurrence and progression of MS retains unclear. Here, the experimental autoimmune encephalomyelitis (EAE) model was used to investigate the role of GPX4, a leading inhibitor of ferroptosis, which plays in the function of CD4⁺ T cells. Our results showed that GPX4 was highly expressed in CD4⁺ T cells of MS patients based on existing databases. Strikingly, conditional knockout of GPX4 in CD4^cre mice (cKO mice) significantly alleviated the average symptom scores and immunopathology of EAE. The infiltration of immune cells, including CD4⁺ T and CD8⁺ T cells, and the generation of GM-CSF, TNF-α, and IL-17A, were remarkably reduced in the CNS from cKO mice compared with WT mice. These findings further revealed the vital role of GPX4 in the expansion and function of CD4⁺ T cells. Moreover, GPX4-deficient CD4⁺ T cells were susceptible to ferroptosis in EAE model. Overall, this study provided novel insights into therapeutic strategies targeting GPX4 in CD4⁺ T cells for inhibiting CNS inflammation and treating MS.

Identification of ferroptosis-related gene signatures associated with multiple sclerosis using weighted gene co-expression network analysis

Multiple sclerosis (MS) is a chronic inflammatory disease of central nervous system leading to demyelination followed by neurological symptoms. Ferroptosis is a newly discovered pathogenic hallmark important for the progression of MS. However, the gene markers of ferroptosis in MS are still uncertain. In this study, mRNA expression profiles and clinical data of MS samples were retrieved from Gene Expression Omnibus database. Weighted gene co-expression network analysis and receiver operating characteristic curve analysis were utilized to identify ferroptosis-related gene (FRG) signatures of MS. Gene set enrichment analysis and gene set variation analysis were performed to explore the biological functions of single FRG signature. HMOX1, LPCAT3 and RPL8 were firstly identified as FRG signatures of MS with the predictive capacity confirmed. Gene set enrichment analysis and gene set variation analyses revealed that metabolism-related, immune and inflammation-related, microglia-related, oxidation-related, and mitochondria-related biological functions were enriched, providing implications of the mechanisms underlying ferroptosis in MS. This study presented a systematic analysis of FRG in MS and explored the potential ferroptosis targets for new interventional strategies in MS.

From the prodromal stage of multiple sclerosis to disease prevention

A prodrome is an early set of signs or symptoms that indicate the onset of a disease before more typical symptoms develop. Prodromal stages are well recognized in some neurological and immune-mediated diseases such as Parkinson disease, schizophrenia, type 1 diabetes mellitus and rheumatoid arthritis. Emerging evidence indicates that a prodromal stage exists in multiple sclerosis (MS), raising the possibility of intervention at this stage to delay or prevent the development of classical MS. However, much remains unclear about the prodromal stage of MS and considerable research is needed to fully characterize the prodrome and develop standardized criteria to reliably identify individuals with prodromal MS who are at high risk of progressing to a diagnosis of MS. In this Roadmap, we draw on work in other diseases to propose a disease framework for MS that incorporates the prodromal stage, and set out key steps and considerations needed in future research to fully characterize the MS prodrome, identify early disease markers and develop standardized criteria that will enable reliable identification of individuals with prodromal MS, thereby facilitating trials of interventions to slow or stop progression beyond the prodrome.

A Scoping Review on Body Fluid Biomarkers for Prognosis and Disease Activity in Patients with Multiple Sclerosis

Multiple sclerosis (MS) is a complex demyelinating disease of the central nervous system, presenting with different clinical forms, including clinically isolated syndrome (CIS), which is a first clinical episode suggestive of demyelination. Several molecules have been proposed as prognostic biomarkers in MS. We aimed to perform a scoping review of the potential use of prognostic biomarkers in MS clinical practice. We searched MEDLINE up to 25 November 2021 for review articles assessing body fluid biomarkers for prognostic purposes, including any type of biomarkers, cell types and tissues. Original articles were obtained to confirm and detail the data reported by the review authors. We evaluated the reliability of the biomarkers based on the sample size used by various studies. Fifty-two review articles were included. We identified 110 molecules proposed as prognostic biomarkers. Only six studies had an adequate sample size to explore the risk of conversion from CIS to MS. These confirm the role of oligoclonal bands, immunoglobulin free light chain and chitinase CHI3L1 in CSF and of serum vitamin D in the prediction of conversion from CIS to clinically definite MS. Other prognostic markers are not yet explored in adequately powered samples. Serum and CSF levels of neurofilaments represent a promising biomarker.

Multiple sclerosis diagnosis and phenotype identification by multivariate classification of in vivo frontal cortex metabolite profiles

Multiple sclerosis (MS) is a heterogeneous autoimmune disease for which diagnosis continues to rely on subjective clinical judgment over a battery of tests. Proton magnetic resonance spectroscopy (¹H MRS) enables the noninvasive in vivo detection of multiple small-molecule metabolites and is therefore in principle a promising means of gathering information sufficient for multiple sclerosis diagnosis and subtype classification. Here we show that supervised classification using ¹H-MRS-visible normal-appearing frontal cortex small-molecule metabolites alone can indeed differentiate individuals with progressive MS from control (held-out validation sensitivity 79% and specificity 68%), as well as between relapsing and progressive MS phenotypes (held-out validation sensitivity 84% and specificity 74%). Post hoc assessment demonstrated the disproportionate contributions of glutamate and glutamine to identifying MS status and phenotype, respectively. Our finding establishes ¹H MRS as a viable means of characterizing progressive multiple sclerosis disease status and paves the way for continued refinement of this method as an auxiliary or mainstay of multiple sclerosis diagnostics.

TOB is an effector of the hippocampus-mediated acute stress response

Stress affects behavior and involves critical dynamic changes at multiple levels ranging from molecular pathways to neural circuits and behavior. Abnormalities at any of these levels lead to decreased stress resilience and pathological behavior. However, temporal modulation of molecular pathways underlying stress response remains poorly understood. Transducer of ErbB2.1, known as TOB, is involved in different physiological functions, including cellular stress and immediate response to stimulation. In this study, we investigated the role of TOB in psychological stress machinery at molecular, neural circuit, and behavioral levels. Interestingly, TOB protein levels increased after mice were exposed to acute stress. At the neural circuit level, functional magnetic resonance imaging (fMRI) suggested that intra-hippocampal and hippocampal-prefrontal connectivity were dysregulated in Tob knockout (Tob-KO) mice. Electrophysiological recordings in hippocampal slices showed increased postsynaptic AMPAR-mediated neurotransmission, accompanied by decreased GABA neurotransmission and subsequently altered Excitatory/Inhibitory balance after Tob deletion. At the behavioral level, Tob-KO mice show abnormal, hippocampus-dependent, contextual fear conditioning and extinction, and depression-like behaviors. On the other hand, increased anxiety observed in Tob-KO mice is hippocampus-independent. At the molecular level, we observed changes in factors involved in stress response like decreased stress-induced LCN2 expression and ERK phosphorylation, as well as increased MKP-1 expression. This study introduces TOB as an important modulator in the hippocampal stress signaling machinery. In summary, we reveal a molecular pathway and neural circuit mechanism by which Tob deletion contributes to expression of pathological stress-related behavior.

An Enhanced Multiple Sclerosis Disease Diagnosis via an Ensemble Approach

Multiple Sclerosis (MS) is a disease attacking the central nervous system. According to MS Atlas's most recent statistics, there are more than 2.8 million people worldwide diagnosed with MS. Recently, studies started to explore machine learning techniques to predict MS using various data. The objective of this paper is to develop an ensemble approach for diagnosis of MS using gene expression profiles, while handling the class imbalance problem associated with the data. A hierarchical ensemble approach employing voting and boosting techniques is proposed. This approach adopts a heterogeneous voting approach using two base learners, random forest and support vector machine. Experiments show that our approach outperforms state-of-the-art methods, with the highest recorded accuracy being 92.81% and 93.5% with BoostFS and DEGs for feature selection, respectively. Conclusively, the proposed approach is able to efficiently diagnose MS using the gene expression profiles that are more relevant to the disease. The approach is not merely an ensemble classifier outperforming previous work; it also identifies differentially expressed genes between normal samples and patients with multiple sclerosis using a genome-wide expression microarray. The results obtained show that the proposed approach is an efficient diagnostic tool for MS.

Y chromosome is moving out of sex determination shadow

Although sex hormones play a key role in sex differences in susceptibility, severity, outcomes, and response to therapy of different diseases, sex chromosomes are also increasingly recognized as an important factor. Studies demonstrated that the Y chromosome is not a 'genetic wasteland' and can be a useful genetic marker for interpreting various male-specific physiological and pathophysiological characteristics. Y chromosome harbors male‑specific genes, which either solely or in cooperation with their X-counterpart, and independent or in conjunction with sex hormones have a considerable impact on basic physiology and disease mechanisms in most or all tissues development. Furthermore, loss of Y chromosome and/or aberrant expression of Y chromosome genes cause sex differences in disease mechanisms. With the launch of the human proteome project (HPP), the association of Y chromosome proteins with pathological conditions has been increasingly explored. In this review, the involvement of Y chromosome genes in male-specific diseases such as prostate cancer and the cases that are more prevalent in men, such as cardiovascular disease, neurological disease, and cancers, has been highlighted. Understanding the molecular mechanisms underlying Y chromosome-related diseases can have a significant impact on the prevention, diagnosis, and treatment of diseases.

T-cell surveillance of the human brain in health and multiple sclerosis

Circulating and tissue-resident T cells collaborate in the protection of tissues against harmful infections and malignant transformation but also can instigate autoimmune reactions. Similar roles for T cells in the brain have been less evident due to the compartmentized organization of the central nervous system (CNS). In recent years, beneficial as well as occasional, detrimental effects of T-cell-targeting drugs in people with early multiple sclerosis (MS) have increased interest in T cells patrolling the CNS. Next to studies focusing on T cells in the cerebrospinal fluid, phenotypic characteristics of T cells located in the perivascular space and the meninges as well as in the parenchyma in MS lesions have been reported. We here summarize the current knowledge about T cells infiltrating the healthy and MS brain and argue that understanding the dynamics of physiological CNS surveillance by T cells is likely to improve the understanding of pathological conditions, such as MS.

TOB1 Blocks Intestinal Mucosal Inflammation Through Inducing ID2-Mediated Suppression of Th1/Th17 Cell Immune Responses in IBD

BACKGROUND & AIMS

TOB1 is an anti-proliferative protein of Tob/BTG family and typically involved in the tumorigenesis and T cell activation. Although TOB1 is associated with T helper 17 cell-related autoimmunity, its role in modulating T cell-mediated immune responses in IBD remains poorly understood. Here, we explored its expression and the underlying mechanisms involved in the pathogenesis of inflammatory bowel disease (IBD).

METHODS

TOB1 and ID2 expression in IBD patients was examined by quantitative real time polymerase chain reaction and immunohistochemistry. IBD CD4⁺ T cells were transfected with lentivirus expressing TOB1, ID2, TOB1 short hairpin RNA and ID2 short hairpin RNA, respectively, and Tob1^-/-CD4⁺ T cells were transfected with lentivirus expressing Id2. Experimental colitis was established in Tob1^-/- mice by trinitrobenzene sulfonic acid enema and in Rag1^-/- mice reconstituted with Tob1^-/-CD45RB^highCD4⁺ T cells to further explore the role of Tob1 in intestinal mucosal inflammation. Splenic CD4⁺ T cells of Tob1^-/- mice were sorted to determine transcriptome differences by RNA sequencing.

RESULTS

TOB1 expression was decreased in inflamed mucosa and peripheral blood CD4⁺ T cells of IBD patients compared with healthy subjects. Overexpression of TOB1 downregulated IBD CD4⁺ T cells to differentiate into Th1/Th17 cells compared with control subjects. Severe colitis was observed in Tob1^-/- mice through trinitrobenzene sulfonic acid enema or in Rag1^-/- mice reconstituted with Tob1^-/-CD45RB^highCD4⁺ T cells, compared with control animals. RNA sequencing analysis revealed ID2 as functional target of TOB1 to inhibit IBD CD4⁺ T cell differentiation into Th1/Th17 cells. Mechanistically, TOB1 was associated with Smad4/5 to induce ID2 expression and restrain Th1/Th17 cell differentiation.

CONCLUSIONS

TOB1 restrains intestinal mucosal inflammation through suppressing Th1/Th17 cell-mediated immune responses via the Smad4/5-ID2 pathway. It may serve as a novel therapeutic target for treatment of human IBD.

Potential Biomarkers Associated with Multiple Sclerosis Pathology

Multiple sclerosis (MS) is a complex disease of the central nervous system (CNS) that involves an intricate and aberrant interaction of immune cells leading to inflammation, demyelination, and neurodegeneration. Due to the heterogeneity of clinical subtypes, their diagnosis becomes challenging and the best treatment cannot be easily provided to patients. Biomarkers have been used to simplify the diagnosis and prognosis of MS, as well as to evaluate the results of clinical treatments. In recent years, research on biomarkers has advanced rapidly due to their ability to be easily and promptly measured, their specificity, and their reproducibility. Biomarkers are classified into several categories depending on whether they address personal or predictive susceptibility, diagnosis, prognosis, disease activity, or response to treatment in different clinical courses of MS. The identified members indicate a variety of pathological processes of MS, such as neuroaxonal damage, gliosis, demyelination, progression of disability, and remyelination, among others. The present review analyzes biomarkers in cerebrospinal fluid (CSF) and blood serum, the most promising imaging biomarkers used in clinical practice. Furthermore, it aims to shed light on the criteria and challenges that a biomarker must face to be considered as a standard in daily clinical practice.

An Integrated Bioinformatics Analysis of the Potential Regulatory Effects of miR-21 on T-cell Related Target Genes in Multiple Sclerosis

Background:

Overexpression of miR-21 is a characteristic feature of patients with Multiple Sclerosis (MS) and is involved in gene regulation and the expression enhancement of pro-inflammatory factors including IFNγ and TNF-α following stimulation of T-cells via the T Cell Receptor (TCR). In this study, a novel integrated bioinformatics analysis was used to obtain a better understanding of the involvement of miR-21 in the development of MS, its protein biomarker signatures, RNA levels, and drug interactions through existing microarray and RNA-seq datasets of MS.

Methods:

In order to obtain data on the Differentially Expressed Genes (DEGs) in patients with MS and normal controls, the GEO2R web tool was used to analyze the Gene Expression Omnibus (GEO) datasets, and then Protein-Protein Interaction (PPI) networks of co-expressed DEGs were designed using STRING. A molecular network of miRNA-genes and drugs based on differentially expressed genes was created for T-cells of MS patients to identify the targets of miR-21, that may act as important regulators and potential biomarkers for early diagnosis, prognosis and, potential therapeutic targets for MS.

Results:

It found that seven genes (NRIP1, ARNT, KDM7A, S100A10, AK2, TGFβR2, and IL-6R) are regulated by drugs used in MS and miR-21. Finally, three overlapping genes (S100A10, NRIP1, KDM7A) were identified between miRNA-gene-drug network and nineteen genes as hub genes which can reflect the pathophysiology of MS.

Conclusion:

Our findings suggest that miR-21 and MS-related drugs can act synergistically to regulate several genes in the existing datasets, and miR-21 inhibitors have the potential to be used in MS treatment.

T cell composition and polygenic multiple sclerosis risk: A population-based study in children

Background and purpose

Patients with multiple sclerosis (MS) have altered T cell function and composition. Common genetic risk variants for MS affect proteins that function in the immune system. It is currently unclear to what extent T cell composition is affected by genetic risk factors for MS, and how this may precede a possible disease onset. Here, we aim to assess whether an MS polygenic risk score (PRS) is associated with an altered T cell composition in a large cohort of children from the general population.

Methods

We included genotyped participants from the population‐based Generation R study in whom immunophenotyping of blood T cells was performed at the age of 6 years. Analyses of variance were used to determine the impact of MS‐PRSs on total T cell numbers (n = 1261), CD4⁺ and CD8⁺ lineages, and subsets therein (n= 675). In addition, T‐cell‐specific PRSs were constructed based on functional pathway data.

Results

The MS‐PRS negatively correlated with CD8⁺ T cell frequencies (p = 2.92 × 10⁻³), which resulted in a positive association with CD4⁺/CD8⁺ T cell ratios (p = 8.27 × 10⁻⁹). These associations were mainly driven by two of 195 genome‐wide significant MS risk variants: the main genetic risk variant for MS, HLA‐DRB1*15:01 and an HLA‐B risk variant. We observed no significant associations for the T‐cell‐specific PRSs.

Conclusions

Our results suggest that MS‐associated genetic variants affect T cell composition during childhood in the general population.

Cell type-specific transcriptomics identifies neddylation as a novel therapeutic target in multiple sclerosis

Multiple sclerosis is an autoimmune disease of the CNS in which both genetic and environmental factors are involved. Genome-wide association studies revealed more than 200 risk loci, most of which harbour genes primarily expressed in immune cells. However, whether genetic differences are translated into cell-specific gene expression profiles and to what extent these are altered in patients with multiple sclerosis are still open questions in the field. To assess cell type-specific gene expression in a large cohort of patients with multiple sclerosis, we sequenced the whole transcriptome of fluorescence-activated cell sorted T cells (CD4+ and CD8+) and CD14+ monocytes from treatment-naive patients with multiple sclerosis (n = 106) and healthy subjects (n = 22). We identified 479 differentially expressed genes in CD4+ T cells, 435 in monocytes, and 54 in CD8+ T cells. Importantly, in CD4+ T cells, we discovered upregulated transcripts from the NAE1 gene, a critical subunit of the NEDD8 activating enzyme, which activates the neddylation pathway, a post-translational modification analogous to ubiquitination. Finally, we demonstrated that inhibition of NEDD8 activating enzyme using the specific inhibitor pevonedistat (MLN4924) significantly ameliorated disease severity in murine experimental autoimmune encephalomyelitis. Our findings provide novel insights into multiple sclerosis-associated gene regulation unravelling neddylation as a crucial pathway in multiple sclerosis pathogenesis with implications for the development of tailored disease-modifying agents.

A systematic review of the application of machine-learning algorithms in multiple sclerosis

INTRODUCTION

The applications of artificial intelligence, and in particular automatic learning or "machine learning" (ML), constitute both a challenge and a great opportunity in numerous scientific, technical, and clinical disciplines. Specific applications in the study of multiple sclerosis (MS) have been no exception, and constitute an area of increasing interest in recent years.

OBJECTIVE

We present a systematic review of the application of ML algorithms in MS.

MATERIALS AND METHODS

We used the PubMed search engine, which allows free access to the MEDLINE medical database, to identify studies including the keywords "machine learning" and "multiple sclerosis." We excluded review articles, studies written in languages other than English or Spanish, and studies that were mainly technical and did not specifically apply to MS. The final selection included 76 articles, and 38 were rejected.

CONCLUSIONS

After the review process, we established 4 main applications of ML in MS: 1) classifying MS subtypes; 2) distinguishing patients with MS from healthy controls and individuals with other diseases; 3) predicting progression and response to therapeutic interventions; and 4) other applications. Results found to date have shown that ML algorithms may offer great support for health professionals both in clinical settings and in research into MS.

A pathogenic and clonally expanded B cell transcriptome in active multiple sclerosis

B cells serve as a key weapon against infectious diseases. They also contribute to multiple autoimmune diseases, including multiple sclerosis (MS) where depletion of B cells is a highly effective therapy. We describe a comprehensive profile of central nervous system (CNS)-specific transcriptional B cell phenotypes in MS at single-cell resolution with paired immune repertoires. We reveal a polyclonal immunoglobulin M (IgM) and IgG1 cerebrospinal fluid B cell expansion polarized toward an inflammatory, memory and plasmablast/plasma cell phenotype, with differential up-regulation of specific proinflammatory pathways. We did not find evidence that CNS B cells harbor a neurotropic virus. These data support the targeting of activated resident B cells in the CNS as a potentially effective strategy for control of treatment-resistant chronic disease.

Central nervous system B cells have several potential roles in multiple sclerosis (MS): secretors of proinflammatory cytokines and chemokines, presenters of autoantigens to T cells, producers of pathogenic antibodies, and reservoirs for viruses that trigger demyelination. To interrogate these roles, single-cell RNA sequencing (scRNA-Seq) was performed on paired cerebrospinal fluid (CSF) and blood from subjects with relapsing-remitting MS (RRMS; n = 12), other neurologic diseases (ONDs; n = 1), and healthy controls (HCs; n = 3). Single-cell immunoglobulin sequencing (scIg-Seq) was performed on a subset of these subjects and additional RRMS (n = 4), clinically isolated syndrome (n = 2), and OND (n = 2) subjects. Further, paired CSF and blood B cell subsets (RRMS; n = 7) were isolated using fluorescence activated cell sorting for bulk RNA sequencing (RNA-Seq). Independent analyses across technologies demonstrated that nuclear factor kappa B (NF-κB) and cholesterol biosynthesis pathways were activated, and specific cytokine and chemokine receptors were up-regulated in CSF memory B cells. Further, SMAD/TGF-β1 signaling was down-regulated in CSF plasmablasts/plasma cells. Clonally expanded, somatically hypermutated IgM+ and IgG1+ CSF B cells were associated with inflammation, blood–brain barrier breakdown, and intrathecal Ig synthesis. While we identified memory B cells and plasmablast/plasma cells with highly similar Ig heavy-chain sequences across MS subjects, similarities were also identified with ONDs and HCs. No viral transcripts, including from Epstein–Barr virus, were detected. Our findings support the hypothesis that in MS, CSF B cells are driven to an inflammatory and clonally expanded memory and plasmablast/plasma cell phenotype.

A systematic review of the applications of artificial intelligence and machine learning in autoimmune diseases

Autoimmune diseases are chronic, multifactorial conditions. Through machine learning (ML), a branch of the wider field of artificial intelligence, it is possible to extract patterns within patient data, and exploit these patterns to predict patient outcomes for improved clinical management. Here, we surveyed the use of ML methods to address clinical problems in autoimmune disease. A systematic review was conducted using MEDLINE, embase and computers and applied sciences complete databases. Relevant papers included "machine learning" or "artificial intelligence" and the autoimmune diseases search term(s) in their title, abstract or key words. Exclusion criteria: studies not written in English, no real human patient data included, publication prior to 2001, studies that were not peer reviewed, non-autoimmune disease comorbidity research and review papers. 169 (of 702) studies met the criteria for inclusion. Support vector machines and random forests were the most popular ML methods used. ML models using data on multiple sclerosis, rheumatoid arthritis and inflammatory bowel disease were most common. A small proportion of studies (7.7% or 13/169) combined different data types in the modelling process. Cross-validation, combined with a separate testing set for more robust model evaluation occurred in 8.3% of papers (14/169). The field may benefit from adopting a best practice of validation, cross-validation and independent testing of ML models. Many models achieved good predictive results in simple scenarios (e.g. classification of cases and controls). Progression to more complex predictive models may be achievable in future through integration of multiple data types.

Biomarkers of Multiple Sclerosis

The search for an ideal multiple sclerosis biomarker with good diagnostic value, prognostic reference and an impact on clinical outcome has yet to be realized and is still ongoing. The aim of this review is to establish an overview of the frequent biomarkers for multiple sclerosis that exist to date. The review summarizes the results obtained from electronic databases, as well as thorough manual searches. In this review the sources and methods of biomarkers extraction are described; in addition to the description of each biomarker, determination of the prognostic, diagnostic, disease monitoring and treatment response values besides clinical impact they might possess. We divided the biomarkers into three categories according to the achievement method: laboratory markers, genetic-immunogenetic markers and imaging markers. We have found two biomarkers at the time being considered the gold standard for MS diagnostics. Unfortunately, there does not exist a single solitary marker being able to present reliable diagnostic value, prognostic value, high sensitivity and specificity as well as clinical impact. We need more studies to find the best biomarker for MS.

Analysis of defective pathways and drug repositioning in Multiple Sclerosis via machine learning approaches

BACKGROUND

Although some studies show that there could be a genetic predisposition to develop Multiple Sclerosis (MS), attempts to find genetic signatures related to MS diagnosis and development are extremely rare.

METHOD

We carried out a retrospective analysis of two different microarray datasets, using machine learning techniques to understand the defective pathways involved in this disease. We have modeled two data sets that are publicly accessible. The first was used to establish the list of most discriminatory genes; whereas, the second one was utilized for validation purposes.

RESULTS

The analysis provided a list of high discriminatory genes with predictive cross-validation accuracy higher than 95%, both in learning and in blind validation. The results were confirmed via the holdout sampler. The most discriminatory genes were related to the production of Hemoglobin. The biological processes involved were related to T-cell Receptor Signaling and co-stimulation, Interferon-Gamma Signaling and Antigen Processing and Presentation. Drug repositioning via CMAP methodologies highlighted the importance of Trichostatin A and other HDAC inhibitors.

CONCLUSIONS

The defective pathways suggest viral or bacterial infections as plausible mechanisms involved in MS development. The pathway analysis also confirmed coincidences with Epstein-Barr virus, Influenza A, Toxoplasmosis, Tuberculosis and Staphylococcus Aureus infections. Th17 Cell differentiation, and CD28 co-stimulation seemed to be crucial in the development of this disease. Furthermore, the additional knowledge provided by this analysis helps to identify new therapeutic targets.

The Putative Association of TOB1-AS1 Long Non-coding RNA with Immune Tolerance: A Study on Multiple Sclerosis Patients

The hallmark of multiple sclerosis (MS) pathogenesis is the breakdown of peripheral tolerance in the immune system. However, its molecular mechanism is not completely understood. Since long non-coding RNAs (lncRNAs) has played important roles in regulation of immunological pathways, here, we evaluated the expression of a novel lncRNA, TOB1-AS1, and its putative associated coding genes in the mechanism of maintaining immune tolerance in peripheral blood of MS patients to assess their possible roles in MS pathogenesis. In this study, 39 MS patients and 32 healthy matched controls were recruited. Real-time PCR standard curve method was used to quantify transcript levels of TOB1-AS1, TOB1, SKP2, and TSG. In addition, the potential sex hormone receptor binding sites on target genes promoter were analyzed using JASPR software. This work demonstrates a negative correlation between TOB1-AS1 expression and EDSS of patients. Also, a robust dysregulation of co-expression of TOB1-AS1 lncRNA and the coding genes in MS patients compared to controls was observed. Such dysregulation in this pathway may be related to MS pathogenesis and response to interferon treatment.

Biomarkers in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic neurodegenerative autoimmune disease with a complex clinical course characterized by inflammation, demyelination, and axonal degeneration. Diagnosis of MS most commonly includes finding lesions in at least two separate areas of the central nervous system (CNS), including the brain, spinal cord, and optic nerves. In recent years, there has been a remarkable increase in the number of available treatments for MS. An optimal treatment is usually based on a personalized approach determined by an individual patient's prognosis and treatment risks. Biomarkers that can predict disability progression, monitor ongoing disease activity, and assess treatment response are integral in making important decisions regarding MS treatment. This review describes MS biomarkers that are currently being used in clinical practice; it also reviews and consolidates published findings from clinically relevant potential MS biomarkers in recent years. The work also discusses the challenges of validating and application of biomarkers in MS clinical practice.

SUMMIT (Serially Unified Multicenter Multiple Sclerosis Investigation): creating a repository of deeply phenotyped contemporary multiple sclerosis cohorts

BACKGROUND

There is a pressing need for robust longitudinal cohort studies in the modern treatment era of multiple sclerosis.

OBJECTIVE

Build a multiple sclerosis (MS) cohort repository to capture the variability of disability accumulation, as well as provide the depth of characterization (clinical, radiologic, genetic, biospecimens) required to adequately model and ultimately predict a patient's course.

METHODS

Serially Unified Multicenter Multiple Sclerosis Investigation (SUMMIT) is an international multi-center, prospectively enrolled cohort with over a decade of comprehensive follow-up on more than 1000 patients from two large North American academic MS Centers (Brigham and Women's Hospital (Comprehensive Longitudinal Investigation of Multiple Sclerosis at the Brigham and Women's Hospital (CLIMB; BWH)) and University of California, San Francisco (Expression/genomics, Proteomics, Imaging, and Clinical (EPIC))). It is bringing online more than 2500 patients from additional international MS Centers (Basel (Universitätsspital Basel (UHB)), VU University Medical Center MS Center Amsterdam (MSCA), Multiple Sclerosis Center of Catalonia-Vall d'Hebron Hospital (Barcelona clinically isolated syndrome (CIS) cohort), and American University of Beirut Medical Center (AUBMC-Multiple Sclerosis Interdisciplinary Research (AMIR)).

RESULTS AND CONCLUSION

We provide evidence for harmonization of two of the initial cohorts in terms of the characterization of demographics, disease, and treatment-related variables; demonstrate several proof-of-principle analyses examining genetic and radiologic predictors of disease progression; and discuss the steps involved in expanding SUMMIT into a repository accessible to the broader scientific community.

Increased expression of microRNAs, miR-20a and miR-326 in PBMCs of patients with type 1 diabetes

Type 1 diabetes (T1D) is an autoimmune disorder which is characterized by autoimmune attack on β cells of pancreas and lack of insulin. The involvement of microRNAs (miRNAs) in the development of immune system and their differential expression in various autoimmune diseases including T1D have been well established. In this study, the association between expression levels of miR-20a, miR-326 and T1D were evaluated. The expression levels of miR-20a and miR-326 were measured in the PBMCs of 21 T1D patients and 16 healthy controls using qPCR method. In silico analysis was also performed on targetome of miR-20a and miR-326. Both miR-20a (p value: 0.015) and miR-326 (p value: 0.005) were upregulated in the PBMCs of T1D patients compared to healthy controls. Furthermore, different dysregulated miR326-mRNA and miR20a-mRNA interactions were also suggested using integrative computational analysis. The expression level of miR-20a and miR-326 indicates significant association with T1D which suggests the possible regulatory effects of these non-coding RNAs in T1D.

Sex-Specific Gene-by-Vitamin D Interactions Regulate Susceptibility to Central Nervous System Autoimmunity

Vitamin D3 (VitD) insufficiency is postulated to represent a major modifiable risk factor for multiple sclerosis (MS). While low VitD levels strongly correlate with higher MS risk in white populations, this is not the case for other ethnic groups, suggesting the existence of a genetic component. Moreover, VitD supplementation studies in MS so far have not shown a consistent benefit. We sought to determine whether direct manipulation of VitD levels modulates central nervous system autoimmune disease in a sex-by-genotype-dependent manner. To this end, we used a dietary model of VitD modulation, together with the autoimmune animal model of MS, experimental autoimmune encephalomyelitis (EAE). To assess the impact of genotype-by-VitD interactions on EAE susceptibility, we utilized a chromosome substitution (consomic) mouse model that incorporates the genetic diversity of wild-derived PWD/PhJ mice. High VitD was protective in EAE in female, but not male C57BL/6J (B6) mice, and had no effect in EAE-resistant PWD/PhJ (PWD) mice. EAE protection was accompanied by sex- and genotype-specific suppression of proinflammatory transcriptional programs in CD4 T effector cells, but not CD4 regulatory T cells. Decreased expression of proinflammatory genes was observed with high VitD in female CD4 T effector cells, specifically implicating a key role of MHC class II genes, interferon gamma, and Th1 cell-mediated neuroinflammation. In consomic strains, effects of VitD on EAE were also sex- and genotype dependent, whereby high VitD: (1) was protective, (2) had no effect, and (3) unexpectedly had disease-exacerbating effects. Systemic levels of 25(OH)D differed across consomic strains, with higher levels associated with EAE protection only in females. Analysis of expression of key known VitD metabolism genes between B6 and PWD mice revealed that their expression is genetically determined and sex specific and implicated Cyp27b1 and Vdr as candidate genes responsible for differential EAE responses to VitD modulation. Taken together, our results support the observation that the association between VitD status and MS susceptibility is genotype dependent and suggest that the outcome of VitD status in MS is determined by gene-by-sex interactions.

Why monkeys do not get multiple sclerosis (spontaneously): An evolutionary approach

The goal of this review is to apply an evolutionary lens to understanding the origins of multiple sclerosis (MS), integrating three broad observations. First, only humans are known to develop MS spontaneously. Second, humans have evolved large brains, with characteristically large amounts of metabolically costly myelin. This myelin is generated over long periods of neurologic development—and peak MS onset coincides with the end of myelination. Third, over the past century there has been a disproportionate increase in the rate of MS in young women of childbearing age, paralleling increasing westernization and urbanization, indicating sexually specific susceptibility in response to changing exposures. From these three observations about MS, a life history approach leads us to hypothesize that MS arises in humans from disruption of the normal homeostatic mechanisms of myelin production and maintenance, during our uniquely long myelination period. This review will highlight under-explored areas of homeostasis in brain development, that are likely to shed new light on the origins of MS and to raise further questions about the interactions between our ancestral genes and modern environments.

Dynamic Response Genes in CD4+ T Cells Reveal a Network of Interactive Proteins that Classifies Disease Activity in Multiple Sclerosis

Multiple sclerosis (MS) is a chronic inflammatory disease of the CNS and has a varying disease course as well as variable response to treatment. Biomarkers may therefore aid personalized treatment. We tested whether in vitro activation of MS patient-derived CD4+ T cells could reveal potential biomarkers. The dynamic gene expression response to activation was dysregulated in patient-derived CD4+ T cells. By integrating our findings with genome-wide association studies, we constructed a highly connected MS gene module, disclosing cell activation and chemotaxis as central components. Changes in several module genes were associated with differences in protein levels, which were measurable in cerebrospinal fluid and were used to classify patients from control individuals. In addition, these measurements could predict disease activity after 2 years and distinguish low and high responders to treatment in two additional, independent cohorts. While further validation is needed in larger cohorts prior to clinical implementation, we have uncovered a set of potentially promising biomarkers.

Fluid biomarker and electrophysiological outcome measures for progressive MS trials

Progressive multiple sclerosis (MS) is characterized by insidious clinical worsening that is difficult to accurately quantify and predict. Biofluid markers and electrophysiological measures are potential candidate outcome measures in clinical trials, allowing the quantification of nervous damage occurring in the disease. Neurofilaments are highly specific neuronal proteins. They may have come closest to such applications by their higher concentrations repeatedly demonstrated in cerebrospinal fluid (CSF) in all stages of MS, during relapses, their responsiveness to disease-modifying treatments in relapsing and progressive MS and their associations with measures of inflammatory and degenerative magnetic resonance imaging (MRI) outcomes. Digital single-molecule array (Simoa) technology improves accuracy of bioassays in the quantification of neurofilament light chain (NfL) in serum and plasma. NfL seems to mark a common final path of neuroaxonal injury independent of specific causal pathways. CSF and blood levels of NfL are highly correlated across various diseases including MS, suggesting that blood measurements may be useful in assessing response to treatment and predicting future disease activity. Other biomarkers like matrix metalloproteinases, chemokines, or neurotrophic factors have not been studied to a similar extent. Such measures, especially in blood, need further validation to enter the trial arena or clinical practice. The broadening armamentarium of highly sensitive assay technologies in the future may shed even more light on patient heterogeneity and mechanisms leading to disability in MS. Evoked potentials (EPs) are used in clinical practice to measure central conduction of central sensorimotor pathways. They correlate with and predict the severity of clinical involvement of their corresponding function. Their validation for use in multicenter studies is still lacking, with the exception of visual EPs. If further validated, EPs and fluid biomarkers would represent useful outcome measures for clinical trials, being related to specific mechanisms of the ongoing pathologic changes.

Clinically Isolated Syndrome According to McDonald 2010: Intrathecal IgG Synthesis Still Predictive for Conversion to Multiple Sclerosis

While the revised McDonald criteria of 2010 allow for the diagnosis of multiple sclerosis (MS) in an earlier stage, there is still a need to identify the risk factors for conversion to MS in patients with clinically isolated syndrome (CIS). Since the latest McDonald criteria were established, the prognostic role of cerebrospinal fluid (CSF) and visual evoked potentials (VEP) in CIS patients is still poorly defined. We conducted a monocentric investigation including patients with CIS in the time from 2010 to 2015. Follow-ups of 120 patients revealed that 42% converted to MS. CIS patients with positive oligoclonal bands (OCB) were more than twice as likely to convert to MS as OCB negative patients (hazard ratio = 2.6). The probability to develop MS was even higher when a quantitative intrathecal IgG synthesis was detected (hazard ratio = 3.8). In patients with OCB, VEP did not add further information concerning the conversion rate to MS. In patients with optic neuritis and negative OCB, a significantly higher rate converted to MS when VEP were delayed. In conclusion, the detection of an intrathecal IgG synthesis increases the conversion probability to MS. Pathological VEP can help to predict the conversion rate to MS in patients with optic neuritis without an intrathecal IgG synthesis.

Natural genetic variation profoundly regulates gene expression in immune cells and dictates susceptibility to CNS autoimmunity

Regulation of gene expression in immune cells is known to be under genetic control, and likely contributes to susceptibility to autoimmune diseases such as multiple sclerosis (MS). How this occurs in concert across multiple immune cell types is poorly understood. Using a mouse model that harnesses the genetic diversity of wild-derived mice, more accurately reflecting genetically diverse human populations, we provide an extensive characterization of the genetic regulation of gene expression in five different naive immune cell types relevant to MS. The immune cell transcriptome is shown to be under profound genetic control, exhibiting diverse patterns: global, cell-specific and sex-specific. Bioinformatic analysis of the genetically controlled transcript networks reveals reduced cell type specificity and inflammatory activity in wild-derived PWD/PhJ mice, compared with the conventional laboratory strain C57BL/6J. Additionally, candidate MS-GWAS (genome-wide association study candidate genes for MS susceptibility) genes were significantly enriched among transcripts overrepresented in C57BL/6J cells compared with PWD. These expression level differences correlate with robust differences in susceptibility to experimental autoimmune encephalomyelitis, the principal model of MS, and skewing of the encephalitogenic T-cell responses. Taken together, our results provide functional insights into the genetic regulation of the immune transcriptome, and shed light on how this in turn contributes to susceptibility to autoimmune disease.

IL4I1 augments CNS remyelination and axonal protection by modulating T cell driven inflammation

SEE PLUCHINO AND PERUZZOTTI-JAMETTI DOI101093/AWW266 FOR A SCIENTIFIC COMMENTARY ON THIS ARTICLE: Myelin regeneration (remyelination) is a spontaneous process that occurs following central nervous system demyelination. However, for reasons that remain poorly understood, remyelination fails in the progressive phase of multiple sclerosis. Emerging evidence indicates that alternatively activated macrophages in central nervous system lesions are required for oligodendrocyte progenitor differentiation into remyelinating oligodendrocytes. Here, we show that an alternatively activated macrophage secreted enzyme, interleukin-four induced one (IL4I1), is upregulated at the onset of inflammation resolution and remyelination in mouse central nervous system lesions after lysolecithin-induced focal demyelination. Focal demyelination in mice lacking IL4I1 or interleukin 4 receptor alpha (IL4Rα) results in increased proinflammatory macrophage density, remyelination impairment, and axonal injury in central nervous system lesions. Conversely, recombinant IL4I1 administration into central nervous system lesions reduces proinflammatory macrophage density, enhances remyelination, and rescues remyelination impairment in IL4Rα deficient mice. We find that IL4I1 does not directly affect oligodendrocyte differentiation, but modulates inflammation by reducing interferon gamma and IL17 expression in lesioned central nervous system tissues, and in activated T cells from splenocyte cultures. Remarkably, intravenous injection of IL4I1 into mice with experimental autoimmune encephalomyelitis at disease onset significantly reversed disease severity, resulting in recovery from hindlimb paralysis. Analysis of post-mortem tissues reveals reduced axonal dystrophy in spinal cord, and decreased CD4⁺ T cell populations in spinal cord and spleen tissues. These results indicate that IL4I1 modulates inflammation by regulating T cell expansion, thereby permitting the formation of a favourable environment in the central nervous system tissue for remyelination. Therefore, IL4I1 is a potentially novel therapeutic for promoting central nervous system repair in multiple sclerosis.

A validated gene regulatory network and GWAS identifies early regulators of T cell-associated diseases

Early regulators of disease may increase understanding of disease mechanisms and serve as markers for presymptomatic diagnosis and treatment. However, early regulators are difficult to identify because patients generally present after they are symptomatic. We hypothesized that early regulators of T cell-associated diseases could be found by identifying upstream transcription factors (TFs) in T cell differentiation and by prioritizing hub TFs that were enriched for disease-associated polymorphisms. A gene regulatory network (GRN) was constructed by time series profiling of the transcriptomes and methylomes of human CD4(+) T cells during in vitro differentiation into four helper T cell lineages, in combination with sequence-based TF binding predictions. The TFs GATA3, MAF, and MYB were identified as early regulators and validated by ChIP-seq (chromatin immunoprecipitation sequencing) and small interfering RNA knockdowns. Differential mRNA expression of the TFs and their targets in T cell-associated diseases supports their clinical relevance. To directly test if the TFs were altered early in disease, T cells from patients with two T cell-mediated diseases, multiple sclerosis and seasonal allergic rhinitis, were analyzed. Strikingly, the TFs were differentially expressed during asymptomatic stages of both diseases, whereas their targets showed altered expression during symptomatic stages. This analytical strategy to identify early regulators of disease by combining GRNs with genome-wide association studies may be generally applicable for functional and clinical studies of early disease development.

Immune cell-specific transcriptional profiling highlights distinct molecular pathways controlled by Tob1 upon experimental autoimmune encephalomyelitis

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system characterized by focal lymphocytic infiltration, demyelination and neurodegeneration. Despite the recent advances in understanding MS molecular basis, no reliable biomarkers have been identified yet to monitor disease progression. Our group has previously reported that low levels of TOB1 in CD4(+) T cells are strongly associated with a higher risk of MS conversion in individuals experiencing an initial demyelinating event. Consistently, Tob1 ablation in mice exacerbates the clinical phenotype of the MS model experimental autoimmune encephalomyelitis (EAE). To shed light on Tob1 molecular functions in the immune system, we have conducted the first cell-based transcriptomic analysis in Tob1(-/-) and wildtype mice upon EAE. Next-generation sequencing was employed to characterize the changes in gene expression in T and B cells at pre- and post-symptomatic EAE stages. Remarkably, we found only modest overlap among the different genetic signatures, suggesting that Tob1 may control distinct genetic programs in the different cytotypes. This hypothesis was corroborated by gene ontology and global interactome analyses, which highlighted specific cellular pathways in each cellular subset before and after EAE induction. In summary, our work pinpoints a multifaceted activity of Tob1 in both homeostasis and disease progression.

Increased expression of Tbet in CD4(+) T cells from clinically isolated syndrome patients at high risk of conversion to clinically definite MS

Background

The ability to identify clinically isolated syndrome (CIS) patients at high risk of progression to clinically definite multiple sclerosis (CDMS) would be clinically beneficial. The initiation of T cell mediated autoimmune diseases such as multiple sclerosis (MS) requires the initial inappropriate activation and differentiation of auto-reactive CD4⁺ T cells. The quiescence of naive T cells is actively maintained by molecules such as TOB1, which control the threshold of activation. Upon activation, CD4⁺ T cells can differentiate into various subsets depending on the milieu present. Th1 and Th17 cells are strongly implicated in MS, while regulatory T (Treg) cells constrain autoimmune inflammation and prevent autoimmunity.

Findings

We therefore investigated the expression of TOB1, CD44 and Treg, Th1 and Th17 transcription factors in relation to CIS progression. The expression of TOB1, CD44, FOXP3, TBX21 and RORC genes were measured in CD4⁺ T cells from 10 healthy controls, 20 CIS patients within 3 months of initial clinical presentation and 10 relapsing remitting MS patients sampled within 2 months of relapse. CIS patients were subsequently grouped into those who converted to CDMS within 1 year and those who remained CIS. No differences in the expression of TOB1, CD44, FOXP3 and RORC were observed. There was a significant increase in the expression of the Th1 transcription factor Tbet, encoded by TBX21, in CIS patients that converted within 1 year compared with those who did not.

Conclusion

This pilot data suggests a role for Th1 cells in CIS progression and warrants further evaluation in a larger cohort.

Neuroimmunotherapies Targeting T Cells: From Pathophysiology to Therapeutic Applications

Therapeutic options for multiple sclerosis (MS) have significantly increased over the last few years. T lymphocytes are considered to play a central role in initiating and perpetuating the pathological immune response. Currently approved therapies for MS target T lymphocytes, either in an unspecific manner or directly by interference with specific T-cell pathways. While the concept of "T-cell-specific therapy" implies specificity and selectivity, currently approved approaches come from a general shaping of the immune system towards anti-inflammatory immune responses by non-T-cell-selective immune suppression or immune modulation (e.g., interferons-immune modulation approach) to a depletion of immune cell populations involving T cells (e.g., anti-CD52, alemtuzumab-immune selective depletion approach), or a selective inhibition of distinct molecular pathways in order to sequester leucocytes (e.g., natalizumab-leukocyte sequestration approach). This review will highlight the rationale and results of different T-cell-directed therapeutic approaches coming from basic animal experiments to clinical trials. We will first discuss the pathophysiological rationale for targeting T lymphocytes in MS leading to currently approved treatments acting on T lymphocytes. Furthermore, we will disuss previous promising concepts that have failed to show efficacy in clinical trials or were halted as a result of unexpected adverse events. Learning from the discrepancies between expectations and failures in practical outcomes helps to optimize future research approaches and clinical study designs. As our current view of MS pathogenesis and patient needs is rapidly evolving, novel therapeutic approaches targeting T lymphocytes will also be discussed, including specific molecular interventions such as cytokine-directed treatments or strategies enhancing immunoregulatory mechanisms. Based on clinical experience and novel pathophysiological approaches, T-cell-based strategies will remain a pillarstone of MS therapy.

Meta-Analysis of Multiple Sclerosis Microarray Data Reveals Dysregulation in RNA Splicing Regulatory Genes

Abnormalities in RNA metabolism and alternative splicing (AS) are emerging as important players in complex disease phenotypes. In particular, accumulating evidence suggests the existence of pathogenic links between multiple sclerosis (MS) and altered AS, including functional studies showing that an imbalance in alternatively-spliced isoforms may contribute to disease etiology. Here, we tested whether the altered expression of AS-related genes represents a MS-specific signature. A comprehensive comparative analysis of gene expression profiles of publicly-available microarray datasets (190 MS cases, 182 controls), followed by gene-ontology enrichment analysis, highlighted a significant enrichment for differentially-expressed genes involved in RNA metabolism/AS. In detail, a total of 17 genes were found to be differentially expressed in MS in multiple datasets, with CELF1 being dysregulated in five out of seven studies. We confirmed CELF1 downregulation in MS (p = 0.0015) by real-time RT-PCRs on RNA extracted from blood cells of 30 cases and 30 controls. As a proof of concept, we experimentally verified the unbalance in alternatively-spliced isoforms in MS of the NFAT5 gene, a putative CELF1 target. In conclusion, for the first time we provide evidence of a consistent dysregulation of splicing-related genes in MS and we discuss its possible implications in modulating specific AS events in MS susceptibility genes.

Peripheral blood biomarkers in multiple sclerosis

Multiple sclerosis is the most common autoimmune disorder affecting the central nervous system. The heterogeneity of pathophysiological processes in MS contributes to the highly variable course of the disease and unpredictable response to therapies. The major focus of the research on MS is the identification of biomarkers in biological fluids, such as cerebrospinal fluid or blood, to guide patient management reliably. Because of the difficulties in obtaining spinal fluid samples and the necessity for lumbar puncture to make a diagnosis has reduced, the research of blood-based biomarkers may provide increasingly important tools for clinical practice. However, currently there are no clearly established MS blood-based biomarkers. The availability of reliable biomarkers could radically alter the management of MS at critical phases of the disease spectrum, allowing for intervention strategies that may prevent evolution to long-term neurological disability. This article provides an overview of this research field and focuses on recent advances in blood-based biomarker research.

Multiple sclerosis-associated CLEC16A controls HLA class II expression via late endosome biogenesis

C-type lectins are key players in immune regulation by driving distinct functions of antigen-presenting cells. The C-type lectin CLEC16A gene is located at 16p13, a susceptibility locus for several autoimmune diseases, including multiple sclerosis. However, the function of this gene and its potential contribution to these diseases in humans are poorly understood. In this study, we found a strong upregulation of CLEC16A expression in the white matter of multiple sclerosis patients (n = 14) compared to non-demented controls (n = 11), mainly in perivascular leukocyte infiltrates. Moreover, CLEC16A levels were significantly enhanced in peripheral blood mononuclear cells of multiple sclerosis patients (n = 69) versus healthy controls (n = 46). In peripheral blood mononuclear cells, CLEC16A was most abundant in monocyte-derived dendritic cells, in which it strongly co-localized with human leukocyte antigen class II. Treatment of these professional antigen-presenting cells with vitamin D, a key protective environmental factor in multiple sclerosis, downmodulated CLEC16A in parallel with human leukocyte antigen class II. Knockdown of CLEC16A in distinct types of model and primary antigen-presenting cells resulted in severely impaired cytoplasmic distribution and formation of human leucocyte antigen class II-positive late endosomes, as determined by immunofluorescence and electron microscopy. Mechanistically, CLEC16A participated in the molecular machinery of human leukocyte antigen class II-positive late endosome formation and trafficking to perinuclear regions, involving the dynein motor complex. By performing co-immunoprecipitations, we found that CLEC16A directly binds to two critical members of this complex, RILP and the HOPS complex. CLEC16A silencing in antigen-presenting cells disturbed RILP-mediated recruitment of human leukocyte antigen class II-positive late endosomes to perinuclear regions. Together, we identify CLEC16A as a pivotal gene in multiple sclerosis that serves as a direct regulator of the human leukocyte antigen class II pathway in antigen-presenting cells. These findings are a first step in coupling multiple sclerosis-associated genes to the regulation of the strongest genetic factor in multiple sclerosis, human leukocyte antigen class II.

Biomarkers of therapeutic response in multiple sclerosis: current status

Multiple sclerosis (MS) is an autoimmune disease of unknown cause, in which chronic inflammation drives multifocal demyelination of axons in both white and gray matter in the CNS. The pathological course of the disease is heterogeneous and involves an early, predominantly inflammatory demyelinating disease phase of relapsing-remitting MS (RRMS), which, over a variable period of time, evolves into a progressively degenerative stage associated with axonal loss and scar formation, causing physical and cognitive disability. For patients with RRMS, there is a growing arsenal of disease-modifying agents (DMAs), with varying degrees of efficacy, as defined by reduced relapse rates, improved magnetic resonance imaging outcomes, and preservation of neurological function. Establishment of personalized treatment plans remains one of the biggest challenges in therapeutic decision-making in MS because the disease prognosis and individual therapeutic outcomes are extremely difficult to predict. Current research is aimed at discovery and validation of biomarkers that reliably measure disease progression and effective therapeutic intervention. Individual biomarker candidates with evident clinical utility are highlighted in this review and include neutralizing autoantibodies against DMAs, fetuin-A, osteopontin, isoprostanes, chemokine (C-X-C motif) ligand 13 (CXCL13), neurofilament light and heavy, and chitinase 3-like protein. In addition, application of more advanced screening technologies has opened up new categories of biomarkers that move beyond detection of individual soluble proteins, including gene expression and autoantibody arrays, microRNAs, and circulating microvesicles/exosomes. Development of clinically useful biomarkers in MS will not only shape the practice of personalized medicine but will also serve as surrogate markers to enable investigation of innovative treatments within clinical trials that are less costly, are of shorter duration, and have more certainty of outcomes.

The role of antiproliferative gene Tob1 in the immune system

Tob1 (transducer of ERBB2-1, TOB1 is humans) is a member of the antiproliferative (APRO) family of proteins that controls cell cycle progression in several cell types. In addition, Tob1 has been implicated in diverse cellular mechanisms such as embryonic dorsal development, and T helper 17 (Th17) cell function. More recently, evidence linking Tob1 function to experimental and human immune related disorders has mounted, thus underscoring the potential of this molecule as a biomarker and as a therapeutic target. This article reviews these functions with an emphasis on their implications for human autoimmune diseases such as multiple sclerosis.

Better safe than sorry: TOB1 employs multiple parallel regulatory pathways to keep Th17 cells quiet

Th17 cells are key players in antibacterial and antifungal immunity, but have also been implicated in autoimmunity. Interestingly, Th17 cells poorly proliferate upon stimulation, a phenotype that was attributed to a decreased sensitivity to T-cell receptor (TCR) stimulation, and to low IL-2 production by Th17 cells. In this issue of the European Journal of Immunology, Santarlasci et al. [Eur. J. Immunol. 2014. 44: 654-661] shed further light on the molecular mechanism that keeps Th17 cells at bay. They identify the transcriptional regulator TOB1, which not only impairs IL-2 production in Th17 cells, but also blocks the expression of cell cycle genes. Strikingly, TOB1 suppresses Th17-cell proliferation through several pathways, including impaired signal transduction, transcription, and possibly also post-transcriptional regulation.

Naive CD4 T-cell activation identifies MS patients having rapid transition to progressive MS

Objective:

Our objective was to determine whether altered naive CD4 T-cell biology contributes to development of disease progression in secondary progressive multiple sclerosis (SPMS).

Methods:

We compared the naive CD4 T-cell gene expression profiles of 19 patients with SPMS and 14 healthy controls (HCs) using a whole-genome microarray approach. We analyzed surface protein expression of critical genes by flow cytometry after T-cell receptor (TCR) stimulation of naive CD4 T cells isolated from HCs and patients with SPMS.

Results:

Hierarchical clustering segregated patients with SPMS into 2 subgroups: SP-1, which had a short duration of relapsing-remitting multiple sclerosis (MS), and SP-2, which had a long duration of relapsing-remitting MS. SP-1 patients upregulated numerous immune genes, including genes within TCR and toll-like receptor (TLR) signaling pathways. SP-2 patients showed immune gene downregulation in comparison with HCs. We identified an SP-1–specific transcriptional signature of 3 genes (TLR4, TLR2, and chemokine receptor 1), and these genes had higher surface protein expression in SP-1 than in SP-2. After TCR stimulation for 48 hours, only SP-1 showed a progressive linear increase in TLR2 and TLR4 protein expression.

Conclusions:

Differences in naive CD4 T-cell biology, notably of TCR and TLR signaling pathways, identified patients with MS with more rapid conversion to secondary progression, a critical determinant of long-term disability in MS.

Stemness of T cells and the hematopoietic stem cells: fate, memory, niche, cytokines

Stem cells are able to generate both cells that differentiate and cells that remain undifferentiated but potentially have the same developmental program. The prolonged duration of the protective immune memory for infectious diseases such as polio, small pox, and measles, suggested that memory T cells may have stem cell properties. Understanding the molecular basis for the life-long persistence of memory T cells may be useful to project targeted therapies for immune deficiencies and infectious diseases and to formulate vaccines. In the last decade evidence from different laboratories shows that memory T cells may share self-renewal pathways with bone marrow hematopoietic stem cells. In stem cells the intrinsic self-renewal activity, which depends on gene expression, is known to be modulated by extrinsic signals from the environment that may be tissue specific. These extrinsic signals for stemness of memory T cells include cytokines such as IL-7 and IL-15 and there are other cytokine signals for maintaining the cytokine signature (TH1, TH2, etc.) of memory T cells. Intrinsic and extrinsic pathways that might be common to bone marrow hematopoietic stem cells and memory T lymphocytes are discussed and related to self-renewal functions.