Elevated type I interferon-like activity in a subset of multiple sclerosis patients: molecular basis and clinical relevance

Interferon beta-1a sc at 25 years: a mainstay in the treatment of multiple sclerosis over the period of one generation

INTRODUCTION

Interferon beta (IFN beta) preparations are an established group of drugs used for immunomodulation in patients with multiple sclerosis (MS). Subcutaneously (sc) applied interferon beta-1a (IFN beta-1a sc) has been in continuous clinical use for 25 years as a disease-modifying treatment.

AREAS COVERED

Based on data published since 2018, we discuss recent insights from analyses of the pivotal trial PRISMS and its long-term extension as well as from newer randomized studies with IFN beta-1a sc as the reference treatment, the use of IFN beta-1a sc across the patient life span and as a bridging therapy, recent data regarding the mechanisms of action, and potential benefits of IFN beta-1a sc regarding vaccine responses.

EXPERT OPINION

IFN beta-1a sc paved the way to effective immunomodulatory treatment of MS, enabled meaningful insights into the disease process, and remains a valid therapeutic option in selected vulnerable MS patient groups.

Defective Induction of IL-27-Mediated Immunoregulation by Myeloid DCs in Multiple Sclerosis

The purpose of this study was to examine whether myeloid dendritic cells (mDCs) from patients with multiple sclerosis (MS) and healthy controls (HCs) become similarly tolerogenic when exposed to IL-27 as this may represent a potential mechanism of autoimmune dysregulation. Our study focused on natural mDCs that were isolated from HCs and MS patient peripheral blood mononuclear cells (PBMCs). After a 24-h treatment with IL-27 ± lipopolysaccharide (LPS), the mDCs were either harvested to identify IL-27-regulated gene expression or co-cultured with naive T-cells to measure how the treated DC affected T-cell proliferation and cytokine secretion. mDCs isolated from HCs but not untreated MS patients became functionally tolerogenic after IL-27 treatment. Although IL-27 induced both HC and untreated MS mDCs to produce similar amounts of IL-10, the tolerogenic HC mDCs expressed PD-L2, IDO1, and SOCS1, while the non-tolerogenic untreated MS mDCs expressed IDO1 and IL-6R. Cytokine and RNA analyses identified two signature blocks: the first identified genes associated with mDC tolerizing responses to IL-27, while the second was associated with the presence of MS. In contrast to mDCs from untreated MS patients, mDCs from HCs and IFNb-treated MS patients became tolerogenic in response to IL-27. The genes differentially expressed in the different donor IL-27-treated mDCs may contain targets that regulate mDC tolerogenic responses.

Differential transcriptomic changes in the central nervous system and urinary bladders of mice infected with a coronavirus

Multiple sclerosis (MS) often leads to the development of neurogenic lower urinary tract symptoms (LUTS). We previously characterized neurogenic bladder dysfunction in a mouse model of MS induced by a coronavirus, mouse hepatitis virus (MHV). The aim of the study was to identify genes and pathways linking neuroinflammation in the central nervous system with urinary bladder (UB) dysfunction to enhance our understanding of the mechanisms underlying LUTS in demyelinating diseases. Adult C57BL/6 male mice (N = 12) received either an intracranial injection of MHV (coronavirus-induced encephalomyelitis, CIE group), or sterile saline (control group). Spinal cord (SC) and urinary bladders (UB) were collected from CIE mice at 1 wk and 4 wks, followed by RNA isolation and NanoString nCounter Neuroinflammation assay. Transcriptome analysis of SC identified a significantly changed expression of >150 genes in CIE mice known to regulate astrocyte, microglia and oligodendrocyte functions, neuroinflammation and immune responses. Two genes were significantly upregulated (Ttr and Ms4a4a), and two were downregulated (Asb2 and Myct1) only in the UB of CIE mice. Siglec1 and Zbp1 were the only genes significantly upregulated in both tissues, suggesting a common transcriptomic link between neuroinflammation in the CNS and neurogenic changes in the UB of CIE mice.

Immune cells transcriptome-based drug repositioning for multiple sclerosis

Objective

Finding target genes and target pathways of existing drugs for drug repositioning in multiple sclerosis (MS) based on transcriptomic changes in MS immune cells.

Materials and Methods

Based on transcriptome data from Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) in MS patients without treatment were identified by bioinformatics analysis according to the type of immune cells, as well as DEGs in MS patients before and after drug administration. Hub target genes of the drug for MS were analyzed by constructing the protein-protein interaction network, and candidate drugs targeting 2 or more hub target genes were obtained through the connectivity map (CMap) database and Drugbank database. Then, the enriched pathways of MS patients without treatment and the enriched pathways of MS patients before and after drug administration were intersected to obtain the target pathways of the drug for MS, and the candidate drugs targeting 2 or more target pathways were obtained through Kyoto Encyclopedia of Genes and Genomes (KEGG) database.

Results

We obtained 50 hub target genes for CD4⁺ T cells in Fingolimod for MS, 15 hub target genes for Plasmacytoid dendritic cells (pDCs) and 7 hub target genes for Peripheral blood mononuclear cells (PBMC) in interferon-β (IFN-β) for MS. 6 candidate drugs targeting two or more hub targets (Fostamatinib, Copper, Artenimol, Phenethyl isothiocyanate, Aspirin and Zinc) were obtained. In addition, we obtained 4 target pathways for CD19⁺ B cells and 15 target pathways for CD4⁺ T cells in Fingolimod for MS, 7 target pathways for pDCs and 6 target pathways for PBMC in IFN-β for MS, most of which belong to the immune system and viral infectious disease pathways. We obtained 69 candidate drugs targeting two target pathways.

Conclusion

We found that applying candidate drugs that target both the “PI3K-Akt signaling pathway” and “Chemokine signaling pathway” (e.g., Nemiralisib and Umbralisib) or applying tyrosine kinase inhibitors (e.g., Fostamatinib) may be potential therapies for the treatment of MS.

Identification and Clinical Validation of Key Extracellular Proteins as the Potential Biomarkers in Relapsing-Remitting Multiple Sclerosis

Background

Multiple sclerosis (MS) is a demyelinating disease of the central nervous system (CNS) mediated by autoimmunity. No objective clinical indicators are available for the diagnosis and prognosis of MS. Extracellular proteins are most glycosylated and likely to enter into the body fluid to serve as potential biomarkers. Our work will contribute to the in-depth study of the functions of extracellular proteins and the discovery of disease biomarkers.

Methods

MS expression profiling data of the human brain was downloaded from the Gene Expression Omnibus (GEO). Extracellular protein-differentially expressed genes (EP-DEGs) were screened by protein annotation databases. GO and KEGG were used to analyze the function and pathway of EP-DEGs. STRING, Cytoscape, MCODE and Cytohubba were used to construct a protein-protein interaction (PPI) network and screen key EP-DEGs. Key EP-DEGs levels were detected in the CSF of MS patients. ROC curve and survival analysis were used to evaluate the diagnostic and prognostic ability of key EP-DEGs.

Results

We screened 133 EP-DEGs from DEGs. EP-DEGs were enriched in the collagen-containing extracellular matrix, signaling receptor activator activity, immune-related pathways, and PI3K-Akt signaling pathway. The PPI network of EP-DEGs had 85 nodes and 185 edges. We identified 4 key extracellular proteins IL17A, IL2, CD44, IGF1, and 16 extracellular proteins that interacted with IL17A. We clinically verified that IL17A levels decreased, but Del-1 and resolvinD1 levels increased. The diagnostic accuracy of Del-1 (AUC: 0.947) was superior to that of IgG (AUC: 0.740) with a sensitivity of 82.4% and a specificity of 100%. High Del-1 levels were significantly associated with better relapse-free and progression-free survival.

Conclusion

IL17A, IL2, CD44, and IGF1 may be key extracellular proteins in the pathogenesis of MS. IL17A, Del-1, and resolvinD1 may co-regulate the development of MS and Del-1 is a potential biomarker of MS. We used bioinformatics methods to explore the biomarkers of MS and validated the results in clinical samples. The study provides a theoretical and experimental basis for revealing the pathogenesis of MS and improving the diagnosis and prognosis of MS.

ETV7 limits antiviral gene expression and control of influenza viruses

The type I interferon (IFN) response is an important component of the innate immune response to viral infection. Precise control of IFN responses is critical because insufficient expression of IFN-stimulated genes (ISGs) can lead to a failure to restrict viral spread, whereas excessive ISG activation can result in IFN-related pathologies. Although both positive and negative regulatory factors control the magnitude and duration of IFN signaling, it is also appreciated that several ISGs regulate aspects of the IFN response themselves. In this study, we performed a CRISPR activation screen to identify previously unknown regulators of the type I IFN response. We identified the strongly induced ISG encoding ETS variant transcription factor 7 (ETV7) as a negative regulator of the type I IFN response. However, ETV7 did not uniformly suppress ISG transcription. Instead, ETV7 preferentially targeted a subset of antiviral ISGs that were particularly important for IFN-mediated control of influenza viruses. Together, our data assign a function for ETV7 as an IFN response regulator and also identify ETV7 as a potential therapeutic target to increase innate antiviral responses and enhance IFN-based antiviral therapies.

Chronic Neurological Disorders: Genetic and Epigenetic Markers for Monitoring of Pharmacotherapy

Introduction

Chronic neurological diseases are a major cause of mortality and morbidity in the world. With increasing life expectancy in the developing world, the incidence and prevalence of these diseases are predicted to rise even further. This has also contributed to an increase in disability-adjusted life years (DALYs) for noncommunicable diseases. Treatment for such diseases also poses a challenge with multiple genetic and epigenetic factors leading to a varied outcome. Personalization of treatment is one way that treatment outcome/prognosis of disease can be improved, and pharmacogenomics plays a significant role in this context.

Methodology

This article reviewed the evidence pertaining to the association of genetic and epigenetic markers with major neurological disorders like multiple sclerosis (MS), Alzheimer's disease (AD), and Parkinson's disease (PD), which are a major source of burden among neurological disorders. Types of studies included are peer-reviewed original research articles from the PubMed database (1999-2018).

Results

This study compiled data regarding specific genetic and epigenetic markers with a significant correlation between the clinical diagnosis of the disease and prognosis of therapy from 65 studies. In a single platform, this review highlights the clues to some vital questions, such as why interferon beta (IFN-β) therapy fails to improve symptoms in all MS patients? why cholinesterase inhibitors fail to improve cognitive impairment in a subset of people suffering from AD? or why some individuals on levodopa (L-DOPA) for PD suffer from side-effects ranging from dyskinesia to hallucination while others do not?

Conclusion

This article summarizes the genetic and epigenetic factors that may either require monitoring or help in deciding future pharmacotherapy in a patient suffering from MS, AD, and PD. As the health care system develops and reaches newer heights, we expect more and more of these biomarkers to be used as pharmacotherapeutic outcome indicators.

The effect of IFN-β 1a on expression of MDA5 and RIG-1 in multiple sclerosis patients

The aims of this study were to compare mRNA levels of melanoma differentiation-associated protein 5 (MDA5) and retinoic acid-inducible gene 1 (RIG-1) in multiple sclerosis (MS) patients in comparison to the healthy controls as well as investigating the effects of IFN-β 1a on the expression of these molecules. In this study, mRNA levels of MDA5 and RIG-1 in peripheral leukocytes of 30 new cases of MS patients and 35 healthy controls were evaluated using the real-time-PCR method. mRNA levels of MDA5 and RIG-1 were determined in the MS patients 6 months after treatment with standard doses of IFN-β 1a. mRNA levels of MDA5 and RIG-1 were significantly decreased in the MS patients in comparison to the healthy controls. The analysis also revealed that IFN-β 1a therapy leads to the upregulation of RIG-1, but not MDA5, in the total MS patients and the female group. MS patients suffer from insufficient expression of MDA5 and RIG-1, and IFN-β 1a therapy results in the upregulation of RIG-1 in the patients, especially in the female patients. Thus, it seems that IFN-β 1a not only decreased pathogenic inflammatory responses but also modulated the expression of RIG-1 to protect the patients from infectious diseases and upregulation of IFN-I in a positive feedback.

Bayesian approach for predicting responses to therapy from high-dimensional time-course gene expression profiles

Background

Historical and updated information provided by time-course data collected during an entire treatment period proves to be more useful than information provided by single-point data. Accurate predictions made using time-course data on multiple biomarkers that indicate a patient’s response to therapy contribute positively to the decision-making process associated with designing effective treatment programs for various diseases. Therefore, the development of prediction methods incorporating time-course data on multiple markers is necessary.

Results

We proposed new methods that may be used for prediction and gene selection via time-course gene expression profiles. Our prediction method consolidated multiple probabilities calculated using gene expression profiles collected over a series of time points to predict therapy response. Using two data sets collected from patients with hepatitis C virus (HCV) infection and multiple sclerosis (MS), we performed numerical experiments that predicted response to therapy and evaluated their accuracies. Our methods were more accurate than conventional methods and successfully selected genes, the functions of which were associated with the pathology of HCV infection and MS.

Conclusions

The proposed method accurately predicted response to therapy using data at multiple time points. It showed higher accuracies at early time points compared to those of conventional methods. Furthermore, this method successfully selected genes that were directly associated with diseases.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-021-04052-4.

Feature selection based on differentially correlated gene pairs reveals the mechanism of IFN-β therapy for multiple sclerosis

Multiple sclerosis (MS) is one of the most common neurological disabilities of the central nervous system. Immune-modulatory therapy with Interferon-β (IFN-β) is a commonly used first-line treatment to prevent MS patients from relapses. Nevertheless, a large proportion of MS patients on IFN-β therapy experience their first relapse within 2 years of treatment initiation. Feature selection, a machine learning strategy, is routinely used in the fields of bioinformatics and computational biology to determine which subset of genes is most relevant to an outcome of interest. The majority of feature selection methods focus on alterations in gene expression levels. In this study, we sought to determine which genes are most relevant to relapse of MS patients on IFN-β therapy. Rather than the usual focus on alterations in gene expression levels, we devised a feature selection method based on alterations in gene-to-gene interactions. In this study, we applied the proposed method to a longitudinal microarray dataset and evaluated the IFN-β effect on MS patients to identify gene pairs with differentially correlated edges that are consistent over time in the responder group compared to the non-responder group. The resulting gene list had a good predictive ability on an independent validation set and explicit biological implications related to MS. To conclude, it is anticipated that the proposed method will gain widespread interest and application in personalized treatment research to facilitate prediction of which patients may respond to a specific regimen.

Pattern Recognition Receptors in Multiple Sclerosis and Its Animal Models

Pattern recognition receptors (PRRs) coordinate the innate immune response and have a significant role in the development of multiple sclerosis (MS). Accumulating evidence has identified both pathogenic and protective functions of PRR signaling in MS and its animal model, experimental autoimmune encephalomyelitis (EAE). Additionally, evidence for PRR signaling in non-immune cells and PRR responses to host-derived endogenous ligands has also revealed new pathways controlling the development of CNS autoimmunity. Many PRRs remain uncharacterized in MS and EAE, and understanding the distinct triggers and functions of PRR signaling in CNS autoimmunity requires further investigation. In this brief review, we discuss the diverse pathogenic and protective functions of PRRs in MS and EAE, and highlight major avenues for future research.

Toll-like receptors in the pathogenesis of neuroinflammation

Toll-like receptors (TLRs) are discovered as crucial pattern recognition receptors (PRRs) involved in the recognition of pathogen-associated molecular patterns (PAMPs). Later studies showed their involvement in the recognition of various damage/danger-associated molecular patterns (DAMPs) generated by host itself. Thus, TLRs are capable of recognizing wide-array of patterns/molecules derived from pathogens and host as well and initiating a proinflammatory immune response through the activation of NF-κB and other transcription factors causing synthesis of proinflammatory molecules. The process of neuroinflammation is seen under both sterile and infectious inflammatory diseases of the central nervous system (CNS) and may lead to the development of neurodegeneration. The present article is designed to highlight the importance of TLRs in the pathogenesis of neuroinflammation under diverse conditions. TLRs are expressed by various immune cells present in CNS along with neurons. However out of thirteen TLRs described in mammals, some are present and active in these cells, while some are absent and are described in detail in main text. The role of various immune cells present in the brain and their role in the pathogenesis of neuroinflammation depending on the type of TLR expressed is described. Thereafter the role of TLRs in bacterial meningitis, viral encephalitis, stroke, Alzheimer's disease (AD), Parkinson's disease (PD), and autoimmune disease including multiple sclerosis (MS) is described. The article is designed for both neuroscientists needing information regarding TLRs in neuroinflammation and TLR biologists or immunologists interested in neuroinflammation.

Elastic net-based prediction of IFN-β treatment response of patients with multiple sclerosis using time series microarray gene expression profiles

INF-β has been widely used to treat patients with multiple sclerosis (MS) in relapse. Accurate prediction of treatment response is important for effective personalization of treatment. Microarray data have been frequently used to discover new genes and to predict treatment responses. However, conventional analytical methods suffer from three difficulties: high-dimensionality of datasets; high degree of multi-collinearity; and achieving gene identification in time-course data. The use of Elastic net, a sparse modelling method, would decrease the first two issues; however, Elastic net is currently unable to solve these three issues simultaneously. Here, we improved Elastic net to accommodate time-course data analyses. Numerical experiments were conducted using two time-course microarray datasets derived from peripheral blood mononuclear cells collected from patients with MS. The proposed methods successfully identified genes showing a high predictive ability for INF-β treatment response. Bootstrap sampling resulted in an 81% and 78% accuracy for each dataset, which was significantly higher than the 71% and 73% accuracy obtained using conventional methods. Our methods selected genes showing consistent differentiation throughout all time-courses. These genes are expected to provide new predictive biomarkers that can influence INF-β treatment for MS patients.

Decreased interferon-β induced STAT-4 activation in immune cells and clinical outcome in multiple sclerosis

OBJECTIVES

Interferon-β (IFN-β) is used in the treatment of multiple sclerosis (MS). IFN-β activation of signal transduction and activation of transcription (STAT)-4 is linked to its immunomodulatory effects. Previous studies suggest a type I IFN deficit in immune cells of patients MS, but data on interferon-α/β receptor (IFNAR) expression and the relationship with treatment response are conflicting. Here, we compare IFN-β-mediated STAT4 activation in immune cells of untreated patients with MS and controls.

MATERIALS AND METHODS

Peripheral blood mononuclear cells from 27 untreated patients with relapsing MS, obtained before the initiation of IFN-β treatment, and 12 matched controls were treated in vitro with IFN-β. Total and phosphorylated STAT4 (pSTAT4) and IFNAR were measured by flow cytometry and quantitative PCR. The patients were followed up for 5 years.

RESULTS

pSTAT4 induction by IFN-β was lower in patients with MS than in controls, as was expression of IFNAR. pSTAT4 expression did not correlate with the clinical outcome at 5 years, measured by EDSS change. There was a negative correlation between the baseline IFNAR1 mRNA levels and relapse rate.

CONCLUSIONS

The results suggest decreased IFN-β responsiveness in patients with MS, associated with reduced STAT4 activation and reduced IFNAR expression. This reduced responsiveness does not appear to affect the long-term clinical outcome of IFN-β treatment.

Identification of a gene expression signature in peripheral blood of multiple sclerosis patients treated with disease-modifying therapies

Multiple Sclerosis (MS) is an inflammatory disease with neurodegenerative alterations, ultimately progressing to neurological handicap. Therapies are effective in counteracting inflammation but not neurodegeneration. Biomarkers predicting disease course or treatment response are lacking. We investigated whether altered gene and protein expression profiles were detectable in the peripheral blood of 78 relapsing remitting MS (RR-MS) patients treated by disease-modifying therapies. A discovery/validation study on RR-MS responsive to glatiramer acetate identified 8 differentially expressed genes: ITGA2B, ITGB3, CD177, IGJ, IL5RA, MMP8, P2RY12, and S100β. A longitudinal study on glatiramer acetate, Interferon-β, or Fingolimod treated RR-MS patients confirmed that 7 out of 8 genes were downregulated with reference to the different therapies, whereas S100β was always upregulated. Thus, we identified a peripheral gene signature associated with positive response in RR-MS which may also explain drug immunomodulatory effects. The usefulness of this signature as a biomarker needs confirmation on larger series of patients.

Identifying Multi-Dimensional Co-Clusters in Tensors Based on Hyperplane Detection in Singular Vector Spaces

Co-clustering, often called biclustering for two-dimensional data, has found many applications, such as gene expression data analysis and text mining. Nowadays, a variety of multi-dimensional arrays (tensors) frequently occur in data analysis tasks, and co-clustering techniques play a key role in dealing with such datasets. Co-clusters represent coherent patterns and exhibit important properties along all the modes. Development of robust co-clustering techniques is important for the detection and analysis of these patterns. In this paper, a co-clustering method based on hyperplane detection in singular vector spaces (HDSVS) is proposed. Specifically in this method, higher-order singular value decomposition (HOSVD) transforms a tensor into a core part and a singular vector matrix along each mode, whose row vectors can be clustered by a linear grouping algorithm (LGA). Meanwhile, hyperplanar patterns are extracted and successfully supported the identification of multi-dimensional co-clusters. To validate HDSVS, a number of synthetic and biological tensors were adopted. The synthetic tensors attested a favorable performance of this algorithm on noisy or overlapped data. Experiments with gene expression data and lineage data of embryonic cells further verified the reliability of HDSVS to practical problems. Moreover, the detected co-clusters are well consistent with important genetic pathways and gene ontology annotations. Finally, a series of comparisons between HDSVS and state-of-the-art methods on synthetic tensors and a yeast gene expression tensor were implemented, verifying the robust and stable performance of our method.

Disease-modifying therapies and infectious risks in multiple sclerosis

Immunomodulatory and immunosuppressive treatments for multiple sclerosis (MS) are associated with an increased risk of infection, which makes treatment of this condition challenging in daily clinical practice. Use of the expanding range of available drugs to treat MS requires extensive knowledge of treatment-associated infections, risk-minimizing strategies and approaches to monitoring and treatment of such adverse events. An interdisciplinary approach to evaluate the infectious events associated with available MS treatments has become increasingly relevant. In addition, individual stratification of treatment-related infectious risks is necessary when choosing therapies for patients with MS, as well as during and after therapy. Determination of the individual risk of infection following serial administration of different immunotherapies is also crucial. Here, we review the modes of action of the available MS drugs, and relate this information to the current knowledge of drug-specific infectious risks and risk-minimizing strategies.

A gene expression study denies the ability of 25 candidate biomarkers to predict the interferon-beta treatment response in multiple sclerosis patients

We studied the baseline expression level of 25 interferon-regulated genes (MxA, GPR3, IL17RC, ISG15, TRAIL, OASL, IFIT1, IFIT2, RSAD2, OAS3, IFI44L, TRIM22, IL10, CXCL10, STAT1, OAS1, OAS2, IFNAR1, IFNAR2, IFNβ, ISG20, IFI6, PKR, IRF7, USP18), recurrently proposed in the literature as predictive biomarkers of interferon-beta treatment response, in whole blood of 10 "responders" and 10 "non-responders" multiple sclerosis relapsing-remitting patients, retrospectively selected on the basis of stringent clinical criteria after a five years follow-up. However, we cannot confirm the predictive value of these candidate biomarkers.

Close Encounters of the First Kind: Innate Sensors and Multiple Sclerosis

Although autoimmune diseases by definition imply adaptive immune system pathologies, growing evidence points to the relevance of innate receptors in modulating the initiation and progression of the autoreactive response. Multiple sclerosis (MS) is a chronic autoimmune disease characterised by central nervous system (CNS) demyelination, inflammation and axonal damage, in which the role of several pathogens such as herpes viruses have long been described as potential triggers. Encounters of these pathogens with altered innate receptors in susceptible individuals might drive pathological autoreactivity and inflammation, overcoming tolerance and causing subsequent CNS damage. In particular, functional and genetic studies reveal that Toll-like receptor (TLR) 2 and the Nod-like receptor (NLR) P3 could be involved in MS pathogenesis, whereas TLR3, the triggering receptor expressed on myeloid cells (TREM)-2 and the C-type lectin receptors (CLRs) MBL and MASP-3 would have a putative protective role. A better understanding of these interactions will provide important insights into the aetiopathogenesis of MS and could help design potential targets for novel therapies.

The type I interferons: Basic concepts and clinical relevance in immune-mediated inflammatory diseases

There is increasing scientific and clinical interest in elucidating the biology of type I Interferons, which began approximately 60 years ago with the concept of "viral interference", a property that reduces the ability of a virus to infect cells. Although our understanding of the multiple cellular and molecular functions of interferons has advanced significantly, much remains to be learned and type I Interferons remain an active and fascinating area of inquiry. In this review, we cover some general aspects of type I interferon genes, with emphasis on interferon-alpha, and various aspects of molecular mechanisms triggered by type I interferons and toll-like receptor signaling by the Janus activated kinase/signal transducer activation of transcription (JAK-STAT) pathway and interferon regulatory factor pathway. We will also describe the role of type I interferons in autoimmune and inflammatory diseases, and its potential use as therapeutic agent.

[Immunotherapy and infectious issues in multiple sclerosis. Self-injectable and oral drugs for immunotherapy]

Immunotherapy is generally associated with an increased risk for the development of infections. Due to the continuously expanding spectrum of new and potent immunotherapy treatment options for multiple sclerosis (MS), this article describes the currently known risks for treatment-related infections and the current recommendations for prevention of corresponding problems with drugs used in treatment strategies for MS and their mechanisms of action. The new treatment options in particular are linked to specific and severe infections; therefore, intensive and long-lasting monitoring is required before, during and after treatment and multidisciplinary surveillance of patients is needed. This article gives a detailed review of drug-specific red flags and current recommendations for the prophylaxis of infections associated with treatment of relapsing-remitting MS and when using self-injectable and oral disease-modifying immunotherapeutic drugs.

Clair EW. Solving the puzzle of autoimmunity: critical questions

Despite recent advances in delineating the pathogenic mechanisms of autoimmune disease, the puzzle that reveals the true picture of these diverse immunological disorders is yet to be solved. We know that the human leukocyte antigen (HLA) loci as well as many different genetic susceptibility loci with relatively small effect sizes predispose to various autoimmune diseases and that environmental factors are involved in triggering disease. Models for mechanisms of disease become increasingly complex as relationships between components of both the adaptive and innate immune systems are untangled at the molecular level. In this article, we pose some of the important questions about autoimmunity where the answers will advance our understanding of disease pathogenesis and improve the rational design of novel therapies. How is autoimmunity triggered, and what components of the immune response drive the clinical manifestations of disease? What determines whether a genetically predisposed individual will develop an autoimmune disease? Is restoring immune tolerance the secret to finding cures for autoimmune disease? Current research efforts seek answers to these big questions.

Analysis of polymorphisms in RIG-I-like receptor genes in German multiple sclerosis patients

Variation in genes encoding retinoid acid-inducible gene I (RIG-I)-like receptors (RLRs) has been implicated in the pathogenesis of autoimmune disorders. We investigated if polymorphisms in the IFIH1, RIG-I, LGP2 and VISA genes influence the risk for multiple sclerosis (MS) in a German case-control cohort comprising 716 patients and 706 controls. Evaluation of 18 single nucleotide polymorphisms (SNPs) in the four genes did not reveal significant single-SNP associations with MS risk, but two VISA polymorphisms were modestly associated with age of onset. Further, we provide initial evidence for combinatorial effects of polymorphic variants in the RIG-I, LGP2 and IFIH1 genes on MS risk.

Baseline MxA mRNA expression predicts interferon beta response in multiple sclerosis patients

BACKGROUND

Myxovirus resistance protein A (MxA) is a molecule induced after interferon-beta injection, mostly used to evaluate its bioactivity. There is little available data on clinical utility of baseline MxA mRNA status. The objective of the study is to investigate whether baseline MxA mRNA expression can predict relapse and disease progression in multiple sclerosis patients treated with interferon-beta.

METHODS

Baseline blood samples were obtained before the first interferon-beta dose was administered to evaluate MxA mRNA expression using real-time polymerase chain reaction (PCR). Demographic and clinical variables were prospectively recorded to define treatment responder and non responder groups.

RESULTS

104 patients were included in the study. Baseline MxA mRNA expression was significantly lower in the group of patients who met the definition of responders (1.07 vs 1.95, Student t test, p<0.0001). A threshold of 1.096 was established using Receiver Operating Characteristic analysis to differentiate between responders and non-responders (sensitivity 73.9%, specificity 69.0%). Survival analysis using this threshold showed that time to next relapse (p<0.0001) and to EDSS progression (p = 0.01) were significantly higher in patients with lower MxA titers.

CONCLUSION

The results suggest that baseline MxA mRNA levels may be useful for predicting whether multiple sclerosis patients will respond or not to interferon-beta treatment.

Enhanced in vivo efficacy of a type I interferon superagonist with extended plasma half-life in a mouse model of multiple sclerosis

IFNβ is a common therapeutic option to treat multiple sclerosis. It is unique among the family of type I IFNs in that it binds to the interferon receptors with high affinity, conferring exceptional biological properties. We have previously reported the generation of an interferon superagonist (dubbed YNSα8) that is built on the backbone of a low affinity IFNα but modified to exhibit higher receptor affinity than even for IFNβ. Here, YNSα8 was fused with a 600-residue hydrophilic, unstructured N-terminal polypeptide chain comprising proline, alanine, and serine (PAS) to prolong its plasma half-life via "PASylation." PAS-YNSα8 exhibited a 10-fold increased half-life in both pharmacodynamic and pharmacokinetic assays in a transgenic mouse model harboring the human receptors, notably without any detectable loss in biological potency or bioavailability. This long-lived superagonist conferred significantly improved protection from MOG35-55-induced experimental autoimmune encephalomyelitis compared with IFNβ, despite being injected with a 4-fold less frequency and at an overall 16-fold lower dosage. These data were corroborated by FACS measurements showing a decrease of CD11b(+)/CD45(hi) myeloid lineage cells detectable in the CNS, as well as a decrease in IBA(+) cells in spinal cord sections determined by immunohistochemistry for PAS-YNSα8-treated animals. Importantly, PAS-YNSα8 did not induce antibodies upon repeated administration, and its biological efficacy remained unchanged after 21 days of treatment. A striking correlation between increased levels of CD274 (PD-L1) transcripts from spleen-derived CD4(+) cells and improved clinical response to autoimmune encephalomyelitis was observed, indicating that, at least in this mouse model of multiple sclerosis, CD274 may serve as a biomarker to predict the effectiveness of IFN therapy to treat this complex disease.

Multiple sclerosis treatment and infectious issues: update 2013

Immunomodulation and immunosuppression are generally linked to an increased risk of infection. In the growing field of new and potent drugs for multiple sclerosis (MS), we review the current data concerning infections and prevention of infectious diseases. This is of importance for recently licensed and future MS treatment options, but also for long-term established therapies for MS. Some of the disease-modifying therapies (DMT) go along with threats of specific severe infections or complications, which require a more intensive long-term monitoring and multi-disciplinary surveillance. We update the existing warning notices and infectious issues which have to be considered using drugs for multiple sclerosis.

Feasibility of the use of combinatorial chemokine arrays to study blood and CSF in multiple sclerosis

Meningeal inflammation, including the presence of semi-organized tertiary lymphoid tissue, has been associated with cortical pathology at autopsy in secondary progressive multiple sclerosis (SPMS). Accessible and robust biochemical markers of cortical inflammation for use in SPMS clinical trials are needed. Increased levels of chemokines in the cerebrospinal fluid (CSF) can report on inflammatory processes occurring in the cerebral cortex of MS patients. A multiplexed chemokine array that included BAFF, a high sensitivity CXCL13 assay and composite chemokine scores were developed to explore differences in lymphoid (CXCL12, CXCL13, CCL19 and CCL21) and inflammatory (CCL2, CXCL9, CXCL10 and CXCL11) chemokines in a small pilot study. Paired CSF and serum samples were obtained from healthy controls (n=12), relapsing-remitting MS (RRMS) (n=21) and SPMS (N=12). A subset of the RRMS patients (n = 9) was assessed upon disease exacerbation and 1 month later following iv methylprednisone. SPMS patients were sampled twice to ascertain stability. Both lymphoid and inflammatory chemokines were elevated in RRMS and SPMS with the highest levels found in the active RRMS group. Inflammatory and lymphoid chemokine signatures were defined and generally correlated with each other. This small exploratory clinical study shows the feasibility of measuring complex and potentially more robust chemokine signatures in the CSF of MS patients during clinical trials. No differences were found between stable RRMS and SPMS. Future trials with larger patient cohorts with this chemokine array are needed to further characterize the differences, or the lack thereof, between stable RRMS and SPMS.

Multiple sclerosis: modulation of toll-like receptor (TLR) expression by interferon-β includes upregulation of TLR7 in plasmacytoid dendritic cells

Interferon-β is an established treatment for patients with multiple sclerosis (MS) but its mechanisms of action are not well understood. Viral infections are a known trigger of MS relapses. Toll-like receptors (TLRs) are key components of the innate immune system, which sense conserved structures of viruses and other pathogens. Effects of interferon-β on mRNA levels of all known human TLRs (TLR1-10) and the TLR adaptor molecule MyD88 were analyzed in peripheral blood mononuclear cells (PBMCs) of healthy donors by quantitative real-time PCR and by transcriptome analysis in PBMCs of 25 interferon-β-treated patients with relapsing-remitting MS. Regulation of TLR protein expression by interferon-β was investigated by flow cytometry of leukocyte subsets of healthy subjects and of untreated, interferon-β-, or glatiramer acetate-treated patients with MS. Interferon-β specifically upregulated mRNA expression of TLR3, TLR7, and MyD88 and downregulated TLR9 mRNA in PBMCs of healthy donors as well as in PBMCs of patients with MS. Plasmacytoid dendritic cells (pDCs) were identified as the major cell type responding to interferon-β with increased expression of TLR7 and MyD88 protein. In line with this, expression of TLR7 protein was increased in pDCs of interferon-β-treated, but not untreated or glatiramer acetate-treated patients with MS. Interferon-β-induced upregulation of TLR7 in pDCs is of functional relevance since pre-treatment of PBMCs with interferon-β resulted in a strongly increased production of interferon-α upon stimulation with the TLR7 agonist loxoribine. Flow cytometry confirmed pDCs as the cellular source of interferon-α production induced by activation of TLR7. Thus, upregulation of TLR7 in pDCs and a consequently increased activation of pDCs by TLR7 ligands represents a novel immunoregulatory mechanism of interferon-β. We hypothesize that this mechanism could contribute to a reduction of virus-triggered relapses in patients with MS.

MicroRNA expression changes during interferon-beta treatment in the peripheral blood of multiple sclerosis patients

MicroRNAs (miRNAs) are small non-coding RNA molecules acting as post-transcriptional regulators of gene expression. They are involved in many biological processes, and their dysregulation is implicated in various diseases, including multiple sclerosis (MS). Interferon-beta (IFN-beta) is widely used as a first-line immunomodulatory treatment of MS patients. Here, we present the first longitudinal study on the miRNA expression changes in response to IFN-beta therapy. Peripheral blood mononuclear cells (PBMC) were obtained before treatment initiation as well as after two days, four days, and one month, from patients with clinically isolated syndrome (CIS) and patients with relapsing-remitting MS (RRMS). We measured the expression of 651 mature miRNAs and about 19,000 mRNAs in parallel using real-time PCR arrays and Affymetrix microarrays. We observed that the up-regulation of IFN-beta-responsive genes is accompanied by a down-regulation of several miRNAs, including members of the mir-29 family. These differentially expressed miRNAs were found to be associated with apoptotic processes and IFN feedback loops. A network of miRNA-mRNA target interactions was constructed by integrating the information from different databases. Our results suggest that miRNA-mediated regulation plays an important role in the mechanisms of action of IFN-beta, not only in the treatment of MS but also in normal immune responses. miRNA expression levels in the blood may serve as a biomarker of the biological effects of IFN-beta therapy that may predict individual disease activity and progression.

Interferon-beta therapy in multiple sclerosis: the short-term and long-term effects on the patients' individual gene expression in peripheral blood

Therapy with interferon-beta (IFN-beta) is a mainstay in the management of relapsing-remitting multiple sclerosis (MS), with proven long-term effectiveness and safety. Much has been learned about the molecular mechanisms of action of IFN-beta in the past years. Previous studies described more than a hundred genes to be modulated in expression in blood cells in response to the therapy. However, for many of these genes, the precise temporal expression pattern and the therapeutic relevance are unclear. We used Affymetrix microarrays to investigate in more detail the gene expression changes in peripheral blood mononuclear cells from MS patients receiving subcutaneous IFN-beta-1a. The blood samples were obtained longitudinally at five different time points up to 2 years after the start of therapy, and the patients were clinically followed up for 5 years. We examined the functions of the genes that were upregulated or downregulated at the transcript level after short-term or long-term treatment. Moreover, we analyzed their mutual interactions and their regulation by transcription factors. Compared to pretreatment levels, 96 genes were identified as highly differentially expressed, many of them already after the first IFN-beta injection. The interactions between these genes form a large network with multiple feedback loops, indicating the complex crosstalk between innate and adaptive immune responses during therapy. We discuss the genes and biological processes that might be important to reduce disease activity by attenuating the proliferation of autoreactive immune cells and their migration into the central nervous system. In summary, we present novel insights that extend the current knowledge on the early and late pharmacodynamic effects of IFN-beta therapy and describe gene expression differences between the individual patients that reflect clinical heterogeneity.

Role of toll-like receptors in multiple sclerosis

Multiple Sclerosis (MS) is an autoimmune disease in which Central Nervous System (CNS) lesions result from perivascular immune cell infiltration associated with damage to myelin, oligodendrocytes and neurons. CNS autoimmunity and its regulation are dominated by the inflammatory cytokines IL17 and IFNγ, and the opposing regulatory cytokines IL10 and the type I IFNs. Toll-like receptors (TLR) play a critical role in modulating cytokine and chemokine secretion in response to exogenous Pathogen Associated to Molecular Patterns and endogenous Danger-Associated to Molecular Patterns. Here, we systematically examine the evidence that TLR play a major role in the initiation disease, the triggering of relapses, and regulation of CNS damage. Data from human studies are supported analyses of a variety of animal models, including Experimental Autoimmune Encephalomyelitis in TLR-deficient mice.