Time course transcriptomics of IFNB1b drug therapy in multiple sclerosis

Crucial Roles of RSAD2/viperin in Immunomodulation, Mitochondrial Metabolism and Autoimmune Diseases

Autoimmune diseases are typically characterized by aberrant activation of immune system that leads to excessive inflammatory reactions and tissue damage. Nevertheless, precise targeted and efficient therapies are limited. Thus, studies into novel therapeutic targets for the management of autoimmune diseases are urgently needed. Radical S-adenosyl methionine domain-containing 2 (RSAD2) is an interferon-stimulated gene (ISG) renowned for the antiviral properties of the protein it encodes, named viperin. An increasing number of studies have underscored the new roles of RSAD2/viperin in immunomodulation and mitochondrial metabolism. Previous studies have shown that there is a complex interplay between RSAD2/vipeirn and mitochondria and that binding of the iron-sulfur (Fe-S) cluster is necessary for the involvement of viperin in mitochondrial metabolism. Viperin influences the proliferation and development of immune cells as well as inflammation via different signaling pathways. However, the function of RSAD2/viperin varies in different studies and a comprehensive overview of this emerging theme is lacking. This review will describe the characteristics of RSAD2/viperin, decipher its function in immunometabolic processes, and clarify the crosstalk between RSAD2/viperin and mitochondria. Furthermore, we emphasize the crucial roles of RSAD2 in autoimmune diseases and its potential application value.

Roles of interferon induced protein with tetratricopeptide repeats (IFIT) family in autoimmune disease

Interferon-induced tetrapeptide repeat (IFIT) family proteins are an important component of the antiviral immune response. There are four known members of the human IFIT family, namely IFIT1, IFIT2, IFIT3 and IFIT5. More and more evidence shows that IFIT family members are involved in a variety of pathophysiological processes in vivo, regulate the homeostasis and differentiation of a variety of cells including immune cells, and are closely related to a variety of autoimmune diseases, which is expected to become a new therapeutic target. This review reviews the biological roles of different IFIT proteins in various autoimmune diseases, and highlights the potential use of these molecules as biomarkers and prognostic factors in autoimmune diseases, with a view to providing ideas for exploring the diagnosis and treatment of autoimmune diseases.

Genome-Wide Expression Profile in People with Optic Neuritis Associated with Multiple Sclerosis

The aim of this study was to perform a genome-wide expression analysis of whole-blood samples from people with optic neuritis (ON) and to determine differentially expressed mRNAs compared to healthy control subjects. The study included eight people with acute ON and six healthy control subjects. Gene expression was analyzed using DNA microarrays for whole-human-genome analysis, which contain 54,675 25-base pairs. The additional biostatistical analysis included gene ontology analysis and gene set enrichment analysis (GSEA). Quantitative RT-PCR (qPCR) was used to confirm selected differentially expressed genes. In total, 722 differently expressed genes were identified, with 377 exhibiting increased, and 345 decreased, expression. Gene ontology analysis and GSEA revealed that protein phosphorylation and intracellular compartment, apoptosis inhibition, pathways involved in cell cycles, T and B cell functions, and anti-inflammatory central nervous system (CNS) pathways are implicated in ON pathology. qPCR confirmed the differential expression of eight selected genes, with SLPI, CR3, and ITGA4 exhibiting statistically significant results. In conclusion, whole-blood gene expression analysis showed significant differences in the expression profiles of people with ON compared to healthy control subjects. Additionally, pathways involved in T cell regulation and anti-inflammatory pathways within CNS were identified as important in the early phases of MS.

Exploring the Differences in Molecular Mechanisms and Key Biomarkers Between Membranous Nephropathy and Lupus Nephritis Using Integrated Bioinformatics Analysis

Background: Both membranous nephropathy (MN) and lupus nephritis (LN) are autoimmune kidney disease. In recent years, with the deepening of research, some similarities have been found in the pathogenesis of these two diseases. However, the mechanism of their interrelationship is not clear. The purpose of this study was to investigate the differences in molecular mechanisms and key biomarkers between MN and LN. Method: The expression profiles of GSE99325, GSE99339, GSE104948 and GSE104954 were downloaded from GEO database, and the differentially expressed genes (DEGs) of MN and LN samples were obtained. We used Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) for enrichment analysis of DEGs. A protein-protein interaction (PPI) network of DEGs was constructed using Metascape. We filtered DEGs with NetworkAnalyst. Finally, we used receiver operating characteristic (ROC) analysis to identify the most significant DEGs for MN and LN. Result: Compared with LN in the glomerulus, 14 DEGs were up-regulated and 77 DEGs were down-regulated in MN. Compared with LN in renal tubules, 21 DEGs were down-regulated, but no up-regulated genes were found in MN. According to the result of GO and KEGG enrichment, PPI network and Networkanalyst, we screened out six genes (IFI6, MX1, XAF1, HERC6, IFI44L, IFI44). Interestingly, among PLA2R, THSD7A and NELL1, which are the target antigens of podocyte in MN, the expression level of NELL1 in MN glomerulus is significantly higher than that of LN, while there is no significant difference in the expression level of PLA2R and THSD7A. Conclusion: Our study provides new insights into the pathogenesis of MN and LN by analyzing the differences in gene expression levels between MN and LN kidney samples, and is expected to be used to prepare an animal model of MN that is more similar to human.

Understanding Human Autoimmunity and Autoinflammation Through Transcriptomics

Transcriptomics, the high-throughput characterization of RNAs, has been instrumental in defining pathogenic signatures in human autoimmunity and autoinflammation. It enabled the identification of new therapeutic targets in IFN-, IL-1- and IL-17-mediated diseases. Applied to immunomonitoring, transcriptomics is starting to unravel diagnostic and prognostic signatures that stratify patients, track molecular changes associated with disease activity, define personalized treatment strategies, and generally inform clinical practice. Herein, we review the use of transcriptomics to define mechanistic, diagnostic, and predictive signatures in human autoimmunity and autoinflammation. We discuss some of the analytical approaches applied to extract biological knowledge from high-dimensional data sets. Finally, we touch upon emerging applications of transcriptomics to study eQTLs, B and T cell repertoire diversity, and isoform usage.

Phenibut (4-amino-3-phenyl-butyric acid): Availability, prevalence of use, desired effects and acute toxicity

INTRODUCTION AND AIMS

There has been a global increase in the availability and use of novel psychoactive substances (NPS) over the last decade. Phenibut (β-phenyl-γ-aminobutyric acid) is a GABAB agonist that is used as an NPS. Here, we bring together published scientific and grey information sources to further understand the prevalence of use, desired effects and acute toxicity of phenibut.

DESIGN AND METHODS

Using European Monitoring Centre for Drugs and Drug Addiction Internet snapshot methodology, we undertook an English language Internet snapshot survey in May 2015 to gather information on the availability and price of phenibut from Internet NPS retailers. To gather information on prevalence of use, desired effects and/or adverse effects, we searched grey literature (online drug discussion forums) and medical literature (PubMed and abstracts from selected International Toxicology conferences).

RESULTS

We found 48 unrelated Internet suppliers selling phenibut in amounts ranging from 5 g (US$1.60, £1.01/g) to 1000 kg (US$0.23, £0.14/g). Capsules containing 200-500 mg of phenibut were available in packs of between 6 (US$4.45, £2.80/g) and 360 (US$0.43, £0.27/g). According to the grey literature, phenibut is taken for its anxiolytic and euphoric properties, with tolerance and withdrawal syndromes commonly reported adverse effects. Phenibut is taken orally at an average dose of 2.4 g. Case reports in the medical literature feature users who present to emergency departments heavily sedated or experiencing withdrawal. There have been no reported deaths relating to phenibut use.

DISCUSSION AND CONCLUSIONS

Phenibut is readily available in the UK from Internet sites selling NPS. Its desired and adverse effects appear similar to other gamma-aminobutyric acid receptor agonists. [Owen DR, Wood DM, Archer JRH, Dargan PI. Phenibut (4-amino-3-phenyl-butyric acid): Availability, prevalence of use, desired effects and acute toxicity. Drug Alcohol Rev 2016;35:591-596].

Body fluid biomarkers in multiple sclerosis: how far we have come and how they could affect the clinic now and in the future

Multiple sclerosis (MS) is an autoimmune inflammatory disease of the central nervous system, which affects over 2.5 million people worldwide. Although MS has been extensively studied, many challenges still remain in regards to treatment, diagnosis and prognosis. Typically, prognosis and individual responses to treatment are evaluated by clinical tests such as the expanded disability status scale, MRI and presence of oligoclonal bands in the cerebrospinal fluid. However, none of these measures correlates strongly with treatment efficacy or disease progression across heterogeneous patient populations and subtypes of MS. Numerous studies over the past decades have attempted to identify sensitive and specific biomarkers for diagnosis, prognosis and treatment efficacy of MS. The objective of this article is to review and discuss the current literature on body fluid biomarkers in MS, including research on potential biomarker candidates in the areas of miRNA, mRNA, lipids and proteins.

The orally available, synthetic ether lipid edelfosine inhibits T cell proliferation and induces a type I interferon response

The drug edelfosine is a synthetic analog of 2-lysophosphatidylcholine. Edelfosine is incorporated by highly proliferating cells, e.g. activated immune cells. It acts on cellular membranes by selectively aggregating the cell death receptor Fas in membrane rafts and interference with phosphatidylcholine (PC) synthesis with subsequent induction of apoptosis. Edelfosine has been proposed for the treatment of autoimmune diseases like multiple sclerosis (MS). Earlier studies on the animal model of MS, experimental autoimmune encephalomyelitis (EAE), have generated first evidence for the efficacy of edelfosine treatment. However, it is unknown if the previously described mechanisms for edelfosine action, which are derived from in vitro studies, are solely responsible for the amelioration of EAE or if edelfosine may exert additional effects, which may be beneficial in the context of autoimmunity. Since it was the purpose of our studies to assess the potential usefulness of edelfosine for the treatment of MS, we examined its mechanism/s of action on immune functions in human T cells. Low doses of edelfosine led to a decrease in homeostatic proliferation, and further studies of the mechanism/s of action by genome-wide transcriptional profiling showed that edelfosine reduces the expression of MHC class II molecules, of molecules involved in MHC class II-associated processing and presentation, and finally upregulated a series of type I interferon-associated genes. The inhibition of homeostatic proliferation, as well as the effects on MHC class II expression and -presentation, and the induction of type I interferon-associated genes are novel and interesting in the context of developing edelfosine for clinical use in MS and possibly also other T cell-mediated autoimmune diseases.

Systems approaches to human autoimmune diseases

Systemic autoimmune diseases result from interactions between genes and environmental triggers that lead to dysregulation of both innate and adaptive immunity. Systems biology approaches enable the global characterization of complex systems at the DNA, RNA and protein levels. Recent technological breakthroughs such as deep sequencing or high-throughput proteomics are revealing novel inflammatory pathways involved in autoimmunity. Herein, we review recent developments, challenges and promising avenues in the use of systems approaches to understand human systemic autoimmune and autoinflammatory diseases.

Combining genetic mapping with genome-wide expression in experimental autoimmune encephalomyelitis highlights a gene network enriched for T cell functions and candidate genes regulating autoimmunity

The experimental autoimmune encephalomyelitis (EAE) is an autoimmune disease of the central nervous system commonly used to study multiple sclerosis (MS). We combined clinical EAE phenotypes with genome-wide expression profiling in spleens from 150 backcross rats between susceptible DA and resistant PVG rat strains during the chronic EAE phase. This enabled correlation of transcripts with genotypes, other transcripts and clinical EAE phenotypes and implicated potential genetic causes and pathways in EAE. We detected 2285 expression quantitative trait loci (eQTLs). Sixty out of 599 cis-eQTLs overlapped well-known EAE QTLs and constitute positional candidate genes, including Ifit1 (Eae7), Atg7 (Eae20-22), Klrc3 (eEae22) and Mfsd4 (Eae17). A trans-eQTL that overlaps Eae23a regulated a large number of small RNAs and implicates a master regulator of transcription. We defined several disease-correlated networks enriched for pathways involved in cell-mediated immunity. They include C-type lectins, G protein coupled receptors, mitogen-activated protein kinases, transmembrane proteins, suppressors of transcription (Jundp2 and Nr1d1) and STAT transcription factors (Stat4) involved in interferon signaling. The most significant network was enriched for T cell functions, similar to genetic findings in MS, and revealed both established and novel gene interactions. Transcripts in the network have been associated with T cell proliferation and differentiation, the TCR signaling and regulation of regulatory T cells. A number of network genes and their family members have been associated with MS and/or other autoimmune diseases. Combining disease and genome-wide expression phenotypes provides a link between disease risk genes and distinct molecular pathways that are dysregulated during chronic autoimmune inflammation.

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.

Next-generation sequencing identifies microRNAs that associate with pathogenic autoimmune neuroinflammation in rats

MicroRNAs (miRNAs) are known to regulate most biological processes and have been found dysregulated in a variety of diseases, including multiple sclerosis (MS). In this study, we characterized miRNAs that associate with susceptibility to develop experimental autoimmune encephalomyelitis (EAE) in rats, a well-established animal model of MS. Using Illumina next-generation sequencing, we detected 544 miRNAs in the lymph nodes of EAE-susceptible Dark Agouti and EAE-resistant Piebald Virol Glaxo rats during immune activation. Forty-three miRNAs were found differentially expressed between the two strains, with 81% (35 out of 43) showing higher expression in the susceptible strain. Only 33% of tested miRNAs displayed differential expression in naive lymph nodes, suggesting that a majority of regulated miRNAs are EAE dependent. Further investigation of a selected six miRNAs indicates differences in cellular source and kinetics of expression. Several of the miRNAs, including miR-146a, miR-21, miR-181a, miR-223, and let-7, have previously been implicated in immune system regulation. Moreover, 77% (33 out of 43) of the miRNAs were associated with MS and other autoimmune diseases. Target genes likely regulated by the miRNAs were identified using computational predictions combined with whole-genome expression data. Differentially expressed miRNAs and their targets involve functions important for MS and EAE, such as immune cell migration through targeting genes like Cxcr3 and cellular maintenance and signaling by regulation of Prkcd and Stat1. In addition, we demonstrated that these three genes are direct targets of miR-181a. Our study highlights the impact of multiple miRNAs, displaying diverse kinetics and cellular sources, on development of pathogenic autoimmune inflammation.

Pharmacogenomic update on multiple sclerosis: a focus on actual and new therapeutic strategies

Multiple sclerosis (MS) is an inflammatory and demyelinating disease of central nervous system comprising several subtypes. Pharmacological treatment involves only few drugs. Among these, interferon beta (IFN-β) and glatiramer acetate were the most used. Although evidence supports the efficacy of these agents in treating MS symptoms, actual studies allowed to introduce new innovative drugs in clinical practice. Applying pharmacogenetic approach to MS, IFN-β and several other immune pathways were abundantly investigated. Numerous reports identified some promising therapy markers but only few markers have emerged as clinically useful. This may be partially due to differences in clinical and methodological criteria in the studies. Indeed, responder and non-responder definitions lack standardized clinical definition. The goal of this review is to treat advances in research on the pharmacogenetic markers of MS drugs and to highlight possible correlations between type of responses and genetic profile, with regard to clinical and methodological discrepancies in the studies.

Janus-like effects of type I interferon in autoimmune diseases

In multiple sclerosis, type I interferon (IFN) is considered immune-modulatory, and recombinant forms of IFN-β are the most prescribed treatment for this disease. This is in contrast to most other autoimmune disorders, because type I IFN contributes to the pathologies. Even within the relapsing-remitting multiple sclerosis (RRMS) population, 30-50% of MS patients are non-responsive to this treatment, and it consistently worsens neuromyelitis optica, a disease similar to RRMS. In this article, we discuss the recent advances in the field of autoimmunity and introduce the theory explain how type I IFNs can be pro-inflammatory in disease that is predominantly driven by a Th17 response and are therapeutic when disease is predominantly Th1.

Transcriptomics: mRNA and alternative splicing

Transcriptomics has emerged as a powerful approach for biomarker discovery. In the present review, the two main types of high throughput transcriptomic technologies - microarrays and next generation sequencing - that can be used to identify candidate biomarkers are briefly described. Microarrays, the mainstream technology of the last decade, have provided hundreds of valuable datasets in a wide variety of diseases including multiple sclerosis (MS), in which this approach has been used to disentangle different aspects of its complex pathogenesis. RNA-seq, the current next generation sequencing approach, is expected to provide similar power as microarrays but extending their capabilities to aspects up to now more difficult to analyse such as alternative splicing and discovery of novel transcripts.

Data driven linear algebraic methods for analysis of molecular pathways: application to disease progression in shock/trauma

MOTIVATION

Although trauma is the leading cause of death for those below 45years of age, there is a dearth of information about the temporal behavior of the underlying biological mechanisms in those who survive the initial trauma only to later suffer from syndromes such as multiple organ failure. Levels of serum cytokines potentially affect the clinical outcomes of trauma; understanding how cytokine levels modulate intra-cellular signaling pathways can yield insights into molecular mechanisms of disease progression and help to identify targeted therapies. However, developing such analyses is challenging since it necessitates the integration and interpretation of large amounts of heterogeneous, quantitative and qualitative data. Here we present the Pathway Semantics Algorithm (PSA), an algebraic process of node and edge analyses of evoked biological pathways over time for in silico discovery of biomedical hypotheses, using data from a prospective controlled clinical study of the role of cytokines in multiple organ failure (MOF) at a major US trauma center. A matrix algebra approach was used in both the PSA node and PSA edge analyses with different matrix configurations and computations based on the biomedical questions to be examined. In the edge analysis, a percentage measure of crosstalk called XTALK was also developed to assess cross-pathway interference.

RESULTS

In the node/molecular analysis of the first 24h from trauma, PSA uncovered seven molecules evoked computationally that differentiated outcomes of MOF or non-MOF (NMOF), of which three molecules had not been previously associated with any shock/trauma syndrome. In the edge/molecular interaction analysis, PSA examined four categories of functional molecular interaction relationships--activation, expression, inhibition, and transcription--and found that the interaction patterns and crosstalk changed over time and outcome. The PSA edge analysis suggests that a diagnosis, prognosis or therapy based on molecular interaction mechanisms may be most effective within a certain time period and for a specific functional relationship.

Possibility of the use of public microarray database for identifying significant genes associated with oral squamous cell carcinoma

There are lots of studies attempting to identify the expression changes in oral squamous cell carcinoma. Most studies include insufficient samples to apply statistical methods for detecting significant gene sets. This study combined two small microarray datasets from a public database and identified significant genes associated with the progress of oral squamous cell carcinoma. There were different expression scales between the two datasets, even though these datasets were generated under the same platforms - Affymetrix U133A gene chips. We discretized gene expressions of the two datasets by adjusting the differences between the datasets for detecting the more reliable information. From the combination of the two datasets, we detected 51 significant genes that were upregulated in oral squamous cell carcinoma. Most of them were published in previous studies as cancer-related genes. From these selected genes, significant genetic pathways associated with expression changes were identified. By combining several datasets from the public database, sufficient samples can be obtained for detecting reliable information. Most of the selected genes were known as cancer-related genes, including oral squamous cell carcinoma. Several unknown genes can be biologically evaluated in further studies.

Development of resistance to biologic therapies with reference to IFN-β

All biotherapeutics have the potential to generate anti-drug antibodies (ADAs) in patients. The main factors leading to an immune response are thought to be product, treatment and patient related. In this review, reasons for the formation of ADAs, and particularly neutralizing antibodies (NAbs), are considered, with a focus on IFN-β as a well-studied example. The time course for the production of NAbs, the measurement of NAbs, the defining of IFN-β responders and non-responders, the implications for disease progression in patients, and future methods for avoiding the production of ADAs and of tolerizing patients are considered.

Pharmacogenomics and multiple sclerosis: moving toward individualized medicine

Notwithstanding the availability of disease-modifying treatments including interferon-β, glatiramer acetate, and natalizumab, a considerable proportion of multiple sclerosis (MS) patients experience continued progression of disease, clinical relapses, disease activity on MRI, and adverse effects. Application of gene expression, proteomic or genomic approaches is universally accepted as a suitable strategy toward the identification of biomarkers with predictive value for beneficial/poor clinical response to therapy and treatment risks. This review focuses on recent progress in research on the pharmacogenomics of disease-modifying therapies for MS. Although MS drug response biomarkers are not yet routinely implemented in the clinic, the diversity of reported, promising molecular markers is rapidly increasing. Even though most of these markers await further validation, given time, this research is likely to empower neurologists with an enhanced armamentarium to facilitate rational decisions on therapy and patient management.

Reassessment of blood gene expression markers for the prognosis of relapsing-remitting multiple sclerosis

Despite considerable advances in the treatment of multiple sclerosis, current drugs are only partially effective. Most patients show reduced disease activity with therapy, but still experience relapses, increasing disability, and new brain lesions. Since there are no reliable clinical or biological markers of disease progression, long-term prognosis is difficult to predict for individual patients. We identified 18 studies that suggested genes expressed in blood as predictive biomarkers. We validated the prognostic value of those genes with three different microarray data sets comprising 148 patients in total. Using these data, we tested whether the genes were significantly differentially expressed between patients with good and poor courses of the disease. Poor progression was defined by relapses and/or increase of disability during a two-year follow-up, independent of the administered therapy. Of 110 genes that have been proposed as predictive biomarkers, most could not be confirmed in our analysis. However, the G protein-coupled membrane receptor GPR3 was expressed at significantly lower levels in patients with poor disease progression in all data sets. GPR3 has therefore a high potential to be a biomarker for predicting future disease activity. In addition, we examined the IL17 cytokines and receptors in more detail and propose IL17RC as a new, promising, transcript-based biomarker candidate. Further studies are needed to better understand the roles of these receptors in multiple sclerosis and its treatment and to clarify the utility of GPR3 and IL17RC expression levels in the blood as markers of long-term prognosis.

Search for specific biomarkers of IFNβ bioactivity in patients with multiple sclerosis

Myxovirus A (MxA), a protein encoded by the MX1 gene with antiviral activity, has proven to be a sensitive measure of IFNβ bioactivity in multiple sclerosis (MS). However, the use of MxA as a biomarker of IFNβ bioactivity has been criticized for the lack of evidence of its role on disease pathogenesis and the clinical response to IFNβ. Here, we aimed to identify specific biomarkers of IFNβ bioactivity in order to compare their gene expression induction by type I IFNs with the MxA, and to investigate their potential role in MS pathogenesis. Gene expression microarrays were performed in PBMC from MS patients who developed neutralizing antibodies (NAB) to IFNβ at 12 and/or 24 months of treatment and patients who remained NAB negative. Nine genes followed patterns in gene expression over time similar to the MX1, which was considered the gold standard gene, and were selected for further experiments: IFI6, IFI27, IFI44L, IFIT1, HERC5, LY6E, RSAD2, SIGLEC1, and USP18. In vitro experiments in PBMC from healthy controls revealed specific induction of selected biomarkers by IFNβ but not IFNγ, and several markers, in particular USP18 and HERC5, were shown to be significantly induced at lower IFNβ concentrations and more selective than the MX1 as biomarkers of IFNβ bioactivity. In addition, USP18 expression was deficient in MS patients compared with healthy controls (p = 0.0004). We propose specific biomarkers that may be considered in addition to the MxA to evaluate IFNβ bioactivity, and to further explore their implication in MS pathogenesis.

Interferon-β exacerbates Th17-mediated inflammatory disease

Interferon (IFN)-β is the treatment most often prescribed for relapsing-remitting multiple sclerosis (RRMS). 30-50% of MS patients, however, do not respond to IFN-β. In some cases, IFN-β exacerbates MS, and it consistently worsens neuromyelitis optica (NMO). To eliminate unnecessary treatment for patients who are non-responsive to IFN-β, and to avoid possible harm, researchers are identifying biomarkers that predict treatment outcome before treatment is initiated. These biomarkers reveal insights into the mechanisms of disease. Recent discoveries on human samples from patients with RRMS, NMO, psoriasis, rheumatoid arthritis, systemic lupus erythematosus and ulcerative colitis, indicate that IFN-β is ineffective and might worsen clinical status in diverse diseases when a Th17 immune response is prominent.

Differential gene expression and translational approaches to identify biomarkers of interferon beta activity in multiple sclerosis

More than 16 years ago human interferon-β-1b (IFN-β-1β) was shown to be effective in the treatment of the relapsing-remitting form of multiple sclerosis (MS). Over time, IFN-β has been demonstrated to be both a safe and effective treatment. However, the mechanism of action of IFN-β in MS remains unknown. To better understand the mechanism of action of IFN-β, considerable effort has been made in transcriptional profiling of peripheral blood mononuclear cells collected from MS patients. IFN-β is known to induce a large number of genes that play an important role in regulating responses to viral infection, immune modulation, and cell proliferation. Identifying differentially induced genes that are linked to the beneficial effects observed during treatment is under active investigation. IFN biomarkers in MS patients have been proposed but have not been clearly confirmed in independent studies or consistently correlated with clinical measures of disease progression. Organizing single genes or gene signatures grouped according to molecular mechanisms meaningful in MS may help to link IFN activity measurements to clinical outcomes. In this review, IFN activity measurements will be discussed with a specific emphasis on what is known about differential gene expression and treatment effects in MS.

Co-regulatory expression quantitative trait loci mapping: method and application to endometrial cancer

Background

Expression quantitative trait loci (eQTL) studies have helped identify the genetic determinants of gene expression. Understanding the potential interacting mechanisms underlying such findings, however, is challenging.

Methods

We describe a method to identify the trans-acting drivers of multiple gene co-expression, which reflects the action of regulatory molecules. This method-termed co-regulatory expression quantitative trait locus (creQTL) mapping-allows for evaluation of a more focused set of phenotypes within a clear biological context than conventional eQTL mapping.

Results

Applying this method to a study of endometrial cancer revealed regulatory mechanisms supported by the literature: a creQTL between a locus upstream of STARD13/DLC2 and a group of seven IFNβ-induced genes. This suggests that the Rho-GTPase encoded by STARD13 regulates IFNβ-induced genes and the DNA damage response.

Conclusions

Because of the importance of IFNβ in cancer, our results suggest that creQTL may provide a finer picture of gene regulation and may reveal additional molecular targets for intervention. An open source R implementation of the method is available at http://sites.google.com/site/kenkompass/.