Blood RNA profiling in a large cohort of multiple sclerosis patients and healthy controls

Transcriptional network analysis of peripheral blood leukocyte subsets in multiple sclerosis identifies a pathogenic role for a cytotoxicity-associated gene network in myeloid cells

Multiple sclerosis (MS) is an autoimmune disease of the central nervous system affecting predominantly adults. It is a complex disease associated with both environmental and genetic risk factors. Although over 230 risk single-nucleotide polymorphisms have been associated with MS, all are common human variants. The mechanisms by which they increase the risk of MS, however, remain elusive. We hypothesized that a complex genetic phenotype such as MS could be driven by coordinated expression of genes controlled by transcriptional regulatory networks. We, therefore, constructed a gene coexpression network from microarray expression analyses of five purified peripheral blood leukocyte subsets of 76 patients with relapsing remitting MS and 104 healthy controls. These analyses identified a major network (or module) of expressed genes associated with MS that play key roles in cell-mediated cytotoxicity which was downregulated in monocytes of patients with MS. Manipulation of the module gene expression was achieved in vitro through small interfering RNA gene knockdown of identified drivers. In a mouse model, network gene knockdown modulated the autoimmune inflammatory MS model disease-experimental autoimmune encephalomyelitis. This research implicates a cytotoxicity-associated gene network in myeloid cells in the pathogenesis of MS.

Establishment of the Diagnostic Signature of Ferroptosis Genes in Multiple Sclerosis

Ferroptosis is a novel form of membrane-dependent cell death that differs from other cell death modalities such as necrosis, apoptosis, and autophagy. Multiple sclerosis (MS) is a chronic inflammatory disease of the central nervous system primarily affecting brain and spinal cord neurons. Although the pathogenesis of these two conditions may seem unrelated, recent studies have indicated a connection between ferroptosis and multiple sclerosis. In fact, ferroptosis plays a significant role in the development of MS, as evidenced by the presence of elevated iron levels and iron metabolism abnormalities in the brains, spinal cords, and other neurons of MS patients. These abnormalities disrupt iron homeostasis within cells, leading to the occurrence of ferroptosis. However, there is currently a lack of research on the diagnostic value of ferroptosis-related genes in multiple sclerosis. In this study, we employed bioinformatics methods to identify ferroptosis-related genes (ATM, GSK3B, HMGCR, KLF2, MAPK1, NFE2L1, NRAS, PCBP1, PIK3CA, RPL8, VDAC3) associated with the diagnosis of multiple sclerosis and constructed a diagnostic model. The results demonstrated that the diagnostic model accurately identified the patients' condition. Subsequently, subgroup analysis was performed based on the expression levels of ferroptosis-related genes, dividing patients into high and low expression groups. The results showed differences in immune function and immune cell infiltration between the two groups. Our study not only confirms the correlation between ferroptosis and multiple sclerosis but also demonstrates the diagnostic value of ferroptosis-related genes in the disease. This provides guidance for clinical practice and direction for further mechanistic research.

Role of ferroptosis in neuroimmunity and neurodegeneration in multiple sclerosis revealed by multi-omics data

Previous studies have found that ferroptosis plays an important role in a variety of neurological diseases. However, the precise role of ferroptosis in the multiple sclerosis patients remains uncertain. We defined and validated a computational metric of ferroptosis levels. The ferroptosis scores were computed using the AUCell method, which reflects the enrichment scores of ferroptosis-related genes through gene ranking. The reliability of the ferroptosis score was assessed using various methods, involving cells induced to undergo ferroptosis by six different ferroptosis inducers. Through a comprehensive approach integrating snRNA-seq, spatial transcriptomics, and spatial proteomics data, we explored the role of ferroptosis in multiple sclerosis. Our findings revealed that among seven sampling regions of different white matter lesions, the edges of active lesions exhibited the highest ferroptosis score, which was associated with activation of the phagocyte system. Remyelination lesions exhibit the lowest ferroptosis score. In the cortex, ferroptosis score were elevated in neurons, relevant to a variety of neurodegenerative disease-related pathways. Spatial transcriptomics demonstrated a significant co-localization among ferroptosis score, neurodegeneration and microglia, which was verified by spatial proteomics. Furthermore, we established a diagnostic model of multiple sclerosis based on 24 ferroptosis-related genes in the peripheral blood. Ferroptosis might exhibits a dual role in the context of multiple sclerosis, relevant to both neuroimmunity and neurodegeneration, thereby presenting a promising and novel therapeutic target. Ferroptosis-related genes in the blood that could potentially serve as diagnostic and prognostic markers for multiple sclerosis.

Novel biomarkers and interferon signature in secondary progressive multiple sclerosis

Multiple sclerosis (MS) exhibits poor immune regulation and subnormal interferon (IFN-β) signaling. Secondary Progressive MS displays waning exacerbations, relentless neurodegeneration, and diminished benefit of therapy. We find dysregulated serum protein balance (Th1/Th2) and excessive gene expression in Relapsing-Remitting MS vs. healthy controls (8700 differentially-expressed genes, DEG) and intermediate levels in SPMS (3900 DEG). Olfactory receptor genes (chemosensing), and WNT/ß-catenin (anti-inflammatory, repair) and metallothionein (anti-oxidant) gene pathways, have less expression in SPMS than RRMS. IFN-β treatment decreased pro-inflammatory and increased metallothionein gene expression in SPMS. These gene expression biomarkers suggest new targets for immune regulation and brain repair in this neurodegenerative disease.

SERTAD1 initiates NLRP3-mediated inflammasome activation through restricting NLRP3 polyubiquitination

We here demonstrate that SERTAD1 is an adaptor protein responsible for the regulation of lysine 63 (K63)-linked NLRP3 polyubiquitination by the Cullin1 E3 ubiquitin ligase upon inflammasome activation. SERTAD1 specifically binds to NLRP3 but not to other inflammasome sensors. This endogenous interaction increases after inflammasome activation, interfering with the interaction between NLRP3 and Cullin1. Interleukin (IL)-1β and IL-18 secretion, as well as the cleavage of gasdermin D, are decreased in SERTAD1 knockout bone-marrow-derived macrophages, together with reduced formation of the NLRP3 inflammasome complex. Additionally, SERTAD1-deficient mice show attenuated severity of monosodium-uric-acid-induced peritonitis and experimental autoimmune encephalomyelitis. Analysis of public datasets indicates that expression of SERTAD1 mRNA is significantly increased in the patients of autoimmune diseases. Thus, our findings uncover a function of SERTAD1 that specifically reduces Cullin1-mediated NLRP3 polyubiquitination via direct binding to NLRP3, eventually acting as a crucial factor to regulate the initiation of NLRP3-mediated inflammasome activation.

Exercise Reverses Immune-Related Genes in the Hippocampus of Multiple Sclerosis Patients

BACKGROUND

Multiple sclerosis (MS) is an autoimmune disease characterized by inflammatory demyelinating lesions in the white matter of the central nervous system. Studies have shown that exercise is beneficial for multiple sclerosis (MS). However, the molecular basis is largely unknown.

MATERIALS AND METHODS

We integrated multiple blood and hippocampus transcriptome data from subjects with physical activity or MS. Transcription change associations between physical activity and MS were analyzed with bioinformatic methods including GSEA (Gene Set Enrichment Analysis) and GO (Gene Ontology) analysis.

RESULTS

We find that exercise can specifically reverse immune-related genes in the hippocampus of MS patients, while this effect is not observable in blood. Moreover, many of these reversed genes encode immune-related receptors. Interestingly, higher levels of physical activity have more pronounced effects on the reversal of MS-related transcripts.

CONCLUSIONS

The immune-response related genes or pathways in the hippocampus may be the targets of exercise in alleviating MS conditions, which may offer new therapeutic clues for MS.

A deep transcriptome meta-analysis reveals sex differences in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS), a chronic auto-immune, inflammatory, and degenerative disease of the central nervous system, affects both males and females; however, females suffer from a higher risk of developing MS (2-3:1 ratio relative to males). The precise sex-based factors influencing risk of MS are currently unknown. Here, we explore the role of sex in MS to identify molecular mechanisms underlying observed MS sex differences that may guide novel therapeutic approaches tailored for males or females.

METHODS

We performed a rigorous and systematic review of genome-wide transcriptome studies of MS that included patient sex data in the Gene Expression Omnibus and ArrayExpress databases following PRISMA statement guidelines. For each selected study, we analyzed differential gene expression to explore the impact of the disease in females (IDF), in males (IDM) and our main goal: the sex differential impact of the disease (SDID). Then, for each scenario (IDF, IDM and SDID) we performed 2 meta-analyses in the main tissues involved in the disease (brain and blood). Finally, we performed a gene set analysis in brain tissue, in which a higher number of genes were dysregulated, to characterize sex differences in biological pathways.

RESULTS

After screening 122 publications, the systematic review provided a selection of 9 studies (5 in blood and 4 in brain tissue) with a total of 474 samples (189 females with MS and 109 control females; 82 males with MS and 94 control males). Blood and brain tissue meta-analyses identified, respectively, 1 (KIR2DL3) and 13 (ARL17B, CECR7, CEP78, IFFO2, LOC401127, NUDT18, RNF10, SLC17A5, STMP1, TRAF3IP2-AS1, UBXN2B, ZNF117, ZNF488) MS-associated genes that differed between males and females (SDID comparison). Functional analyses in the brain revealed different altered immune patterns in females and males (IDF and IDM comparisons). The pro-inflammatory environment and innate immune responses related to myeloid lineage appear to be more affected in females, while adaptive responses associated with the lymphocyte lineage in males. Additionally, females with MS displayed alterations in mitochondrial respiratory chain complexes, purine, and glutamate metabolism, while MS males displayed alterations in stress response to metal ion, amine, and amino acid transport.

CONCLUSION

We found transcriptomic and functional differences between MS males and MS females (especially in the immune system), which may support the development of new sex-based research of this disease. Our study highlights the importance of understanding the role of biological sex in MS to guide a more personalized medicine.

Identification of genetic variants that impact gene co-expression relationships using large-scale single-cell data

BACKGROUND

Expression quantitative trait loci (eQTL) studies show how genetic variants affect downstream gene expression. Single-cell data allows reconstruction of personalized co-expression networks and therefore the identification of SNPs altering co-expression patterns (co-expression QTLs, co-eQTLs) and the affected upstream regulatory processes using a limited number of individuals.

RESULTS

We conduct a co-eQTL meta-analysis across four scRNA-seq peripheral blood mononuclear cell datasets using a novel filtering strategy followed by a permutation-based multiple testing approach. Before the analysis, we evaluate the co-expression patterns required for co-eQTL identification using different external resources. We identify a robust set of cell-type-specific co-eQTLs for 72 independent SNPs affecting 946 gene pairs. These co-eQTLs are replicated in a large bulk cohort and provide novel insights into how disease-associated variants alter regulatory networks. One co-eQTL SNP, rs1131017, that is associated with several autoimmune diseases, affects the co-expression of RPS26 with other ribosomal genes. Interestingly, specifically in T cells, the SNP additionally affects co-expression of RPS26 and a group of genes associated with T cell activation and autoimmune disease. Among these genes, we identify enrichment for targets of five T-cell-activation-related transcription factors whose binding sites harbor rs1131017. This reveals a previously overlooked process and pinpoints potential regulators that could explain the association of rs1131017 with autoimmune diseases.

CONCLUSION

Our co-eQTL results highlight the importance of studying context-specific gene regulation to understand the biological implications of genetic variation. With the expected growth of sc-eQTL datasets, our strategy and technical guidelines will facilitate future co-eQTL identification, further elucidating unknown disease mechanisms.

The intracellular cation channel TMEM176B as a dual immunoregulator

Characterizing immune regulatory pathways is critical to understand physiological and pathophysiological processes as well as to identify novel immunotherapeutic targets. The cation channel TMEM176B has emerged in the last years as a potential new immunoregulatory player and pharmacological target. Here, we review how expression data, clinical associations of genetic variants and functional studies support a dual role for TMEM176B in regulating immune responses. Thus, TMEM176B can inhibit effector immune responses in some settings whereas it may also promote immunity by supporting antigen presentation in others. We also discuss a potential role for TMEM176B in regulating type 2 and 3 immunity and comment recent data on modulation of DC biology and inflammasome activation as well as CD8⁺ T cell responses. Understanding the role of TMEM176B in immunity is critical to propose rational pharmacological approaches targeting this channel.

The Ala134Thr variant in TMEM176B exerts a beneficial role in colorectal cancer prognosis by increasing NLRP3 inflammasome activation

PURPOSE

TMEM176B was recently described as a negative modulator of Nlrp3 inflammasome activation in mice. In the mouse model, the inhibition of TMEM176B leads to an increased anti-tumoral activity which is dependent on Nlrp3. Since we have recently shown that single nucleotide variants (SNPs) in inflammasome genes, including NLRP3, significantly affect colorectal cancer (CRC) prognosis, we proposed to investigate here the association between genetic variants in TMEM176B and CRC prognosis.

METHODS

Considering that, up to now, no genetic study analyzing this gene in humans exists, we selected possible functional SNPs and genotyped them in a cohort of CRC patients submitted to surgery and followed up for more than 10 years. Genotype-guided assays were realized to evaluate the effect of the variant on NLRP3 inflammasome activation. Gene expression from The Cancer Genome Atlas (TCGA) cohort was analyzed to valid possible prognostic and predictive features.

RESULTS

We identified the Ala134Thr variant (rs2072443) in TMEM176B as a protective factor for CRC prognosis. This SNP is associated with decreased gene expression and with an increased activation of NLRP3 inflammasome, at least in monocytes and dendritic cells. Furthermore, low TMEM176B expression is associated with higher overall survival.

CONCLUSION

Altogether, these findings supported the role of TMEM176B in NLRP3 inflammasome biology and for the first time demonstrated the genetic association between rs2072443 and CRC in humans.

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.

Contribution of Rare and Low-Frequency Variants to Multiple Sclerosis Susceptibility in the Italian Continental Population

Genome-wide association studies identified over 200 risk loci for multiple sclerosis (MS) focusing on common variants, which account for about 50% of disease heritability. The goal of this study was to investigate whether low-frequency and rare functional variants, located in MS-established associated loci, may contribute to disease risk in a relatively homogeneous population, testing their cumulative effect (burden) with gene-wise tests. We sequenced 98 genes in 588 Italian patients with MS and 408 matched healthy controls (HCs). Variants were selected using different filtering criteria based on allelic frequency and in silico functional impacts. Genes showing a significant burden (n = 17) were sequenced in an independent cohort of 504 MS and 504 HC. The highest signal in both cohorts was observed for the disruptive variants (stop-gain, stop-loss, or splicing variants) located in EFCAB13, a gene coding for a protein of an unknown function (p < 10^-4). Among these variants, the minor allele of a stop-gain variant showed a significantly higher frequency in MS versus HC in both sequenced cohorts (p = 0.0093 and p = 0.025), confirmed by a meta-analysis on a third independent cohort of 1298 MS and 1430 HC (p = 0.001) assayed with an SNP array. Real-time PCR on 14 heterozygous individuals for this variant did not evidence the presence of the stop-gain allele, suggesting a transcript degradation by non-sense mediated decay, supported by the evidence that the carriers of the stop-gain variant had a lower expression of this gene (p = 0.0184). In conclusion, we identified a novel low-frequency functional variant associated with MS susceptibility, suggesting the possible role of rare/low-frequency variants in MS as reported for other complex diseases.

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.

Dendritic Cells Require TMEM176A/B Ion Channels for Optimal MHC Class II Antigen Presentation to Naive CD4+ T Cells

Intracellular ion fluxes emerge as critical actors of immunoregulation but still remain poorly explored. In this study, we investigated the role of the redundant cation channels TMEM176A and TMEM176B (TMEM176A/B) in retinoic acid-related orphan receptor γt⁺ cells and conventional dendritic cells (DCs) using germline and conditional double knockout mice. Although Tmem176a/b appeared surprisingly dispensable for the protective function of Th17 and group 3 innate lymphoid cells in the intestinal mucosa, we found that they were required in conventional DCs for optimal Ag processing and presentation to CD4⁺ T cells. Using a real-time imaging method, we show that TMEM176A/B accumulate in dynamic post-Golgi vesicles preferentially linked to the late endolysosomal system and strongly colocalize with HLA-DM. Taken together, our results suggest that TMEM176A/B ion channels play a direct role in the MHC class II compartment of DCs for the fine regulation of Ag presentation and naive CD4⁺ T cell priming.

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.

Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis

Background

Multiple sclerosis (MS) is a central nervous system disease with a high disability rate. Modern molecular biology techniques have identified a number of key genes and diagnostic markers to MS, but the etiology and pathogenesis of MS remain unknown.

Results

In this study, the integration of three peripheral blood mononuclear cell (PBMC) microarray datasets and one peripheral blood T cells microarray dataset allowed comprehensive network and pathway analyses of the biological functions of MS-related genes. Differential expression analysis identified 78 significantly aberrantly expressed genes in MS, and further functional enrichment analysis showed that these genes were associated with innate immune response-activating signal transduction (p = 0.0017), neutrophil mediated immunity (p = 0.002), positive regulation of innate immune response (p = 0.004), IL-17 signaling pathway (p < 0.035) and other immune-related signaling pathways. In addition, a network of MS-specific protein–protein interactions (PPI) was constructed based on differential genes. Subsequent analysis of network topology properties identified the up-regulated CXCR4, ITGAM, ACTB, RHOA, RPS27A, UBA52, and RPL8 genes as the hub genes of the network, and they were also potential biomarkers of MS through Rap1 signaling pathway or leukocyte transendothelial migration. RT-qPCR results demonstrated that CXCR4 was obviously up-regulated, while ACTB, RHOA, and ITGAM were down-regulated in MS patient PBMC in comparison with normal samples. Finally, support vector machine was employed to establish a diagnostic model of MS with a high prediction performance in internal and external datasets (mean AUC = 0.97) and in different chip platform datasets (AUC = (0.93).

Conclusion

This study provides new understanding for the etiology/pathogenesis of MS, facilitating an early identification and prediction of MS.

Genetic Variation in WNT9B Increases Relapse Hazard in Multiple Sclerosis

OBJECTIVE

Many multiple sclerosis (MS) genetic susceptibility variants have been identified, but understanding disease heterogeneity remains a key challenge. Relapses are a core feature of MS and a common primary outcome of clinical trials, with prevention of relapses benefiting patients immediately and potentially limiting long-term disability accrual. We aim to identify genetic variation associated with relapse hazard in MS by analyzing the largest study population to date.

METHODS

We performed a genomewide association study (GWAS) in a discovery cohort and investigated the genomewide significant variants in a replication cohort. Combining both cohorts, we captured a total of 2,231 relapses occurring before the start of any immunomodulatory treatment in 991 patients. For assessing time to relapse, we applied a survival analysis utilizing Cox proportional hazards models. We also investigated the association between MS genetic risk scores and relapse hazard and performed a gene ontology pathway analysis.

RESULTS

The low-frequency genetic variant rs11871306 within WNT9B reached genomewide significance in predicting relapse hazard and replicated (meta-analysis hazard ratio (HR) = 2.15, 95% confidence interval (CI) = 1.70-2.78, p = 2.07 × 10^-10 ). A pathway analysis identified an association of the pathway "response to vitamin D" with relapse hazard (p = 4.33 × 10^-6 ). The MS genetic risk scores, however, were not associated with relapse hazard.

INTERPRETATION

Genetic factors underlying disease heterogeneity differ from variants associated with MS susceptibility. Our findings imply that genetic variation within the Wnt signaling and vitamin D pathways contributes to differences in relapse occurrence. The present study highlights these cross-talking pathways as potential modulators of MS disease activity. ANN NEUROL 2021;89:884-894.

Constructing and validating a diagnostic nomogram for multiple sclerosis via bioinformatic analysis

The purpose of this study was to identify biomarkers and construct a diagnostic prediction model for multiple sclerosis (MS). Microarray datasets in the Gene Expression Omnibus (GEO) were downloaded. Weighted gene coexpression analysis (WGCNA) was used to search for hub modules and biomarkers related to MS. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were used to roughly define their biological functions and pathways. Least absolute shrinkage and selection operator (LASSO) regression and multivariate logistic regression analysis were used to identify the diagnostic biomarkers and construct a nomogram. The calibration curve and receiver operating characteristic (ROC) curve were used to judge the diagnostic predictive ability. In addition, cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm was used to calculate the proportion of 22 kinds of immune cells. GSE41850 was used as the training set, and GSE17048 was used as the test set. WGCNA revealed one hub module containing 165 hub genes. Most of their biological functions and pathways are related to cell metabolism and immune cell activation. The diagnostic nomogram contained ARPC5, ROD1, UBQLN2, ZNF281, ABCA1 and FAS. The ROC curve and the calibration curve of the training set and test set confirmed that the nomogram had great prediction ability. In addition, monocytes and M0 macrophages were significantly different between MS patients and healthy people. The expression of ARPC5, ZNF281 and ABCA1 is correlated with M0 macrophages. The nomogram provides new insights and contributes to the accurate diagnosis of MS.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02675-1.

Cytokine and Gene Expression Profiling in Patients with HFE-Associated Hereditary Hemochromatosis according to Genetic Profile

BACKGROUND

Hemochromatosis gene (HFE)-associated hereditary hemochromatosis (HH) is characterized by downregulation of hepcidin synthesis, leading to increased intestinal iron absorption.

OBJECTIVES

The objectives were to characterize and elucidate a possible association between gene expression profile, hepcidin levels, disease severity, and markers of inflammation in HFE-associated HH patients.

METHODS

Thirty-nine HFE-associated HH patients were recruited and assigned to 2 groups according to genetic profile: C282Y homozygotes in 1 group and patients with H63D, as homozygote or in combination with C282Y, in the other group. Eleven healthy first-time blood donors were recruited as controls. Gene expression was characterized from peripheral blood cells, and inflammatory cytokines and hepcidin-25 isoform were quantified in serum. Biochemical disease characteristics were recorded.

RESULTS

Elevated levels of interleukin 8 were observed in a significant higher proportion of patients than controls. In addition, compared to controls, gene expression of ζ-globin was significantly increased among C282Y homozygote patients, while gene expression of matrix metalloproteinase 8, and other neutrophil-secreted proteins, was significantly upregulated in patients with H63D.

CONCLUSION

Different disease signatures may characterize HH patients according to their HFE genetic profile. Studies on larger populations, including analyses at protein level, are necessary to confirm these findings.

Genomic, proteomic, and systems biology approaches in biomarker discovery for multiple sclerosis

Multiple sclerosis (MS) is a neuroinflammatory disorder characterized by autoimmune-mediated inflammatory lesions in CNS leading to myelin damage and axonal loss. MS is a heterogenous disease with variable and unpredictable disease course. Due to its complex nature, MS is difficult to diagnose and responses to specific treatments may vary between individuals. Therefore, there is an indisputable need for biomarkers for early diagnosis, prediction of disease exacerbations, monitoring the progression of disease, and for measuring responses to therapy. Genomic and proteomic studies have sought to understand the molecular basis of MS and find biomarker candidates. Advances in next-generation sequencing and mass-spectrometry techniques have yielded an unprecedented amount of genomic and proteomic data; yet, translation of the results into the clinic has been underwhelming. This has prompted the development of novel data science techniques for exploring these large datasets to identify biologically relevant relationships and ultimately point towards useful biomarkers. Herein we discuss optimization of omics study designs, advances in the generation of omics data, and systems biology approaches aimed at improving biomarker discovery and translation to the clinic for MS.

Whole-Transcriptome Analysis in Peripheral Blood Mononuclear Cells from Patients with Lipid-Specific Oligoclonal IgM Band Characterization Reveals Two Circular RNAs and Two Linear RNAs as Biomarkers of Highly Active Disease

The presence of anti-myelin lipid-specific oligoclonal IgM bands (LS-OCMBs) has been defined as an accurate predictor of an aggressive evolution of multiple sclerosis. However, the detection of this biomarker is performed in cerebrospinal fluid, a quite invasive liquid biopsy. In the present study we aimed at studying the expression profile of miRNA, snoRNA, circRNA and linearRNA in peripheral blood mononuclear cells (PBMCs) from patients with lipid-specific oligoclonal IgM band characterization. We included a total of 89 MS patients, 47 with negative LS-OCMB status and 42 with positive status. Microarray (miRNA and snoRNA) and RNA-seq (circular and linear RNAs) were used to perform the profiling study in the discovery cohort and candidates were validated by RT-qPCR in the whole cohort. The biomarker potential of the candidates was evaluated by ROC curve analysis. RNA-seq and RT-qPCR validation revealed that two circular (hsa_circ_0000478 and hsa_circ_0116639) and two linear RNAs (IRF5 and MTRNR2L8) are downregulated in PBMCs from patients with positive LS-OCMBs. Finally, those RNAs show a performance of a 70% accuracy in some of the combinations. The expression of hsa_circ_0000478, hsa_circ_0116639, IRF5 and MTRNR2L8 might serve as minimally invasive biomarkers of highly active disease.

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.

Engineered immunological niches to monitor disease activity and treatment efficacy in relapsing multiple sclerosis

Relapses in multiple sclerosis can result in irreversible nervous system tissue injury. If these events could be detected early, targeted immunotherapy could potentially slow disease progression. We describe the use of engineered biomaterial-based immunological niches amenable to biopsy to provide insights into the phenotype of innate immune cells that control disease activity in a mouse model of multiple sclerosis. Differential gene expression in cells from these niches allow monitoring of disease dynamics and gauging the effectiveness of treatment. A proactive treatment regimen, given in response to signal within the niche but before symptoms appeared, substantially reduced disease. This technology offers a new approach to monitor organ-specific autoimmunity, and represents a platform to analyze immune dysfunction within otherwise inaccessible target tissues.

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.

Next-Generation Neuroimmunology: New Technologies to Understand Central Nervous System Autoimmunity

Understanding neuroimmunological disorders is essential for developing new diagnostic and therapeutic strategies. Rodent models have provided valuable insights, but are sometimes equated with their human counterparts. Here, we summarize how novel technologies may enable an improved human-focused view of immune mechanisms. Recent studies have applied these new technologies to the brain parenchyma, its surrounding cerebrospinal fluid, and peripheral immune compartments. Therapeutic interventions have also facilitated translational understanding in a reverse way. However, with improved technology, access to patient samples remains a rate-limiting step in translational research. We anticipate that next-generation neuroimmunology is likely to integrate, in the immediate future, diverse technical tools for optimal diagnosis, prognosis, and treatment of neuroimmunological disorders.

Genetic and gene expression signatures in multiple sclerosis

Multiple sclerosis (MS) exhibits a well-documented increased incidence in individuals with respective family history, that is, is a heritable disease. In the last decade, genome-wide association studies have enabled the agnostic interrogation of the whole genome at a large scale. To date, over 200 genetic associations have been described at the strict level of genome-wide significance. Our current understanding of MS genetics can explain up to half of the disease's heritability, raising the important question of whether this is enough information to leverage toward improving diagnosis in MS. Parallel advancements in technologies that allow the characterization of the full transcriptome down to the single-cell level have enabled the generation of an unprecedented wealth of information. Transcriptional changes of putative causal cells could be utilized to identify early signs of disease onset. These recent findings in genetics and genomics, coupled with new technologies and deeply phenotyped cohorts, have the potential to improve the diagnosis of MS.

Differential Expression of SMAD Genes and S1PR1 on Circulating CD4+ T Cells in Multiple Sclerosis and Crohn's Disease

The Th17 immune response plays a key role in autoimmune diseases such as multiple sclerosis (MS) and inflammatory bowel disease (IBD). Expression of Th17-related genes in inflamed tissues has been reported in autoimmune diseases. However, values are frequently obtained using invasive methods. We aimed to identify biomarkers of MS in an accessible sample, such as blood, by quantifying the relative expression of 91 Th17-related genes in CD4+ T lymphocytes from patients with MS during a relapse or during a remitting phase. We also compared our findings with those of healthy controls. After confirmation in a validation cohort, expression of SMAD7 and S1PR1 mRNAs was decreased in remitting disease (-2.3-fold and -1.3-fold, respectively) and relapsing disease (-2.2-fold and -1.3-fold, respectively). No differential expression was observed for other SMAD7-related genes, namely, SMAD2, SMAD3, and SMAD4. Under-regulation of SMAD7 and S1PR1 was also observed in another autoimmune disease, Crohn's disease (CD) (-4.6-fold, -1.6-fold, respectively), suggesting the presence of common markers for autoimmune diseases. In addition, expression of TNF, SMAD2, SMAD3, and SMAD4 were also decreased in CD (-2.2-fold, -1.4-fold, -1.6-fold, and -1.6-fold, respectively). Our study suggests that expression of SMAD7 and S1PR1 mRNA in blood samples are markers for MS and CD, and TNF, SMAD2, SMAD3, and SMAD4 for CD. These genes could prove useful as markers of autoimmune diseases, thus obviating the need for invasive methods.

Increased level of NEAT1 long non-coding RNA is detectable in peripheral blood cells of patients with Parkinson's disease

Parkinson's disease (PD) is the second most prevalent neurodegenerative disorder that poses serious burden to individuals and society as well. Although a number of PD associated genetic factors have been identified, the molecular mechanism of the disease so far has not been completely elucidated. Involvement of long non-coding RNAs (lncRNAs) in the pathology of neurodegenerative disorders is attracting increased interest because of the diverse mechanisms lncRNAs affect gene expression and cellular homeostasis at different levels. We aimed to test the feasibility of detecting alterations in lncRNA levels in easily accessible samples of PD patients by routine laboratory technique. By narrowing the number of selected lncRNAs implicated in neurodegeneration and increasing the number of PD samples included, we found one out of 41 lncRNAs readily detectable in increased level in peripheral blood of PD patients. We detected NEAT1 to be significantly up-regulated in PD patients in multiple comparisons. NEAT1 is the core element of nuclear paraspeckles and it plays role in regulation of transcription, mRNA and miRNA levels, mitochondrial and cellular homeostasis. Our finding is in accord with recent data demonstrating changes in the level of NEAT1 in neurons of PD patients and in several models of the disease. However, to our knowledge this is the first study to report NEAT1 up-regulation in blood of PD patients. Identification of altered expression of this lncRNA in the periphery might help to a better understanding of the mechanisms underlying PD, and can contribute to the identification of new therapeutic targets and disease markers.

Single-Cell Sequencing Reveals the Relationship between Phenotypes and Genotypes of Klinefelter Syndrome

Klinefelter syndrome (KS) is one of the most common congenital disorders of male infertility. Given its high heterogeneity in clinical and genetic presentation, the relationship between transcriptome, clinical phenotype, and associated co-morbidities seen in KS has not been fully clarified. Here, we report a 47,XXY Chinese male with infertility and analyzed the differences in gene expression patterns of peripheral blood mononuclear cells (PBMCs) with regard to a Chinese male and a female control with normal karyotype by single-cell sequencing. A total of 24,439 cells were analyzed and divided into 5 immune cell types (including B cells, T cells, macrophage cells, dendritic cells, and natural killer cells) according to marker genes. Using unsupervised dimensionality reduction and clustering algorithms, we identified molecularly distinct subpopulations of cells between the KS patient and both controls. Gene ontology enrichment analyses yielded terms associated with well-known comorbidities seen in KS as well as an affected immune system and type I diabetes mellitus. Based on our data, we identified several candidate genes which may be implicated in regulating the phenotype of KS. Overall, this analysis provides a comprehensive map of the cell types of PBMCs in a KS patient at the single-cell level, which will contribute to the prevention of comorbidity and improvement of the life quality of KS patients.

A pharmacogenetic study implicates NINJ2 in the response to Interferon-β in multiple sclerosis

BACKGROUND

Multiple sclerosis (MS) is a disease in which biomarker identification is fundamental to predict response to treatments and to deliver the optimal drug to patients. We previously found an association between rs7298096, a polymorphism upstream to the NINJ2 gene, and the 4-year response to interferon-β (IFNβ) treatment in MS patients.

OBJECTIVES

To analyse the association between rs7298096 and time to first relapse (TTFR) during IFNβ therapy in MS patients and to better investigate its functional role.

METHODS

Survival analysis was applied in three MS cohorts from different countries (n = 1004). We also studied the role of the polymorphism on gene expression using GTEx portal and a luciferase assay. We interrogated GEO datasets to explore the relationship between NINJ2 expression, IFNβ and TTFR.

RESULTS

Rs7298096_AA patients show a shorter TTFR than rs7298096_G-carriers (P_{meta-analysis} = 3 × 10^-4, hazard ratio = 1.41). Moreover, rs7298096_AA is associated with a higher NINJ2 expression in blood (p = 7.0 × 10^-6), which was confirmed in vitro (p = 0.009). Finally, NINJ2 expression is downregulated by IFNβ treatment and related to TTFR.

CONCLUSIONS

Rs7298096 could influence MS disease activity during IFNβ treatment by modulating NINJ2 expression in blood. The gene encodes for an adhesion molecule involved in inflammation and endothelial cells activation, supporting its role in MS.

Lipid-related genetic polymorphisms significantly modulate the association between lipids and disability progression in multiple sclerosis

OBJECTIVE

To investigate whether lipid-related or body mass index (BMI)-related common genetic polymorphisms modulate the associations between serum lipid levels, BMI and disability progression in multiple sclerosis (MS).

METHODS

The association between disability progression (annualised Expanded Disability Status Scale (EDSS) change over 5 years, ΔEDSS) and lipid-related or BMI-related genetic polymorphisms was evaluated in a longitudinal cohort (n=184), diagnosed with MS. We constructed a cumulative genetic risk score (CGRS) of associated polymorphisms (p<0.05) and examined the interactions between the CGRS and lipid levels (measured at baseline) in predicting ΔEDSS. All analyses were conducted using linear regression.

RESULTS

Five lipid polymorphisms (rs2013208, rs9488822, rs17173637, rs10401969 and rs2277862) and one BMI polymorphism (rs2033529) were nominally associated with ΔEDSS. The constructed lipid CGRS showed a significant, dose-dependent association with ΔEDSS (p_trend=1.4×10^-6), such that participants having ≥6 risk alleles progressed 0.38 EDSS points per year faster compared with those having ≤3. This CGRS model explained 16% of the variance in ΔEDSS. We also found significant interactions between the CGRS and lipid levels in modulating ΔEDSS, including high-density lipoprotein (HDL; p_interaction=0.005) and total cholesterol:high-density lipoprotein ratio (TC:HDL; p_interaction=0.030). The combined model (combination of CGRS and the lipid parameter) explained 26% of the disability variance for HDL and 27% for TC:HDL.

INTERPRETATION

In this prospective cohort study, both lipid levels and lipid-related polymorphisms individually and jointly were associated with significantly increased disability progression in MS. These results indicate that these polymorphisms and tagged genes might be potential points of intervention to moderate disability progression.

DNA methylation signatures of monozygotic twins clinically discordant for multiple sclerosis

Multiple sclerosis (MS) is an inflammatory, demyelinating disease of the central nervous system with a modest concordance rate in monozygotic twins, which strongly argues for involvement of epigenetic factors. We observe highly similar peripheral blood mononuclear cell-based methylomes in 45 MS-discordant monozygotic twins. Nevertheless, we identify seven MS-associated differentially methylated positions (DMPs) of which we validate two, including a region in the TMEM232 promoter and ZBTB16 enhancer. In CD4 + T cells we find an MS-associated differentially methylated region in FIRRE. Additionally, 45 regions show large methylation differences in individual pairs, but they do not clearly associate with MS. Furthermore, we present epigenetic biomarkers for current interferon-beta treatment, and extensive validation shows that the ZBTB16 DMP is a signature for prior glucocorticoid treatment. Taken together, this study represents an important reference for epigenomic MS studies, identifies new candidate epigenetic markers, and highlights treatment effects and genetic background as major confounders.

Monozygotic (MZ) twins are ideal to study the influence of non-genetic factors on complex phenotypes. Here, Souren et al. perform an EWAS in peripheral blood mononuclear cells from 45 MZ twins discordant for multiple sclerosis and identify disease and treatment-associated epigenetic markers.

Gene expression analysis delineates the potential roles of multiple interferons in systemic lupus erythematosus

A role for interferon (IFN) in systemic lupus erythematosus (SLE) pathogenesis is inferred from the prominent IFN gene signature (IGS), but the major IFN species and its relationship to disease activity are unknown. A bioinformatic approach employing individual IFN species gene signatures to interrogate SLE microarray datasets demonstrates a putative role for numerous IFN species, with prominent expression of IFNB1 and IFNW signatures. In contrast with other SLE-affected organs, the IGS is less prominent in lupus nephritis. SLE patients with active and inactive disease have readily detectable IGS and the IGS changes synchronously with a monocyte signature but not disease activity, and is significantly related to monocyte transcripts. Monocyte over-expression of three times as many IGS transcripts as T and B cells and IGS retention in monocytes, but not T and B cells from inactive SLE patients contribute to the lack of correlation between the IGS and SLE disease activity.

Illuminating an Invisible Epidemic: A Systemic Review of the Clinical and Economic Benefits of Early Diagnosis and Treatment in Inflammatory Disease and Related Syndromes

Healthcare expenditures in the United States are growing at an alarming level with the Centers for Medicare and Medicaid Services (CMS) projecting that they will reach $5.7 trillion per year by 2026. Inflammatory diseases and related syndromes are growing in prevalence among Western societies. This growing population that affects close to 60 million people in the U.S. places a significant burden on the healthcare system. Characterized by relatively slow development, these diseases and syndromes prove challenging to diagnose, leading to delayed treatment against the backdrop of inevitable disability progression. Patients require healthcare attention but are initially hidden from clinician's view by the seemingly generalized, non-specific symptoms. It is imperative to identify and manage these underlying conditions to slow disease progression and reduce the likelihood that costly comorbidities will develop. Enhanced diagnostic criteria coupled with additional technological innovation to identify inflammatory conditions earlier is necessary and in the best interest of all healthcare stakeholders. The current total cost to the U.S. healthcare system is at least $90B dollars annually. Through unique analysis of financial cost drivers, this review identifies opportunities to improve clinical outcomes and help control these disease-related costs by 20% or more.

The Association Between Vitamin D and Multiple Sclerosis Risk: 1,25(OH)2D3 Induces Super-Enhancers Bound by VDR

A super-enhancer (SE) is a cluster of enhancers with a relatively high density of particular chromatin features. SEs typically regulate key genes that can determine cell identity and differentiation. Identifying SEs and their effects may be critical in predicting key regulatory genes, such as master transcription factor genes or oncogenes. Signal inducible SEs are dense stretches of signal terminal transcription factor (TF) binding regions, and may modulate the interaction between environmental factors (e.g., Vitamin D) and genetic factors (i.e., risk variants) in complex diseases such as multiple sclerosis (MS). As a complex autoimmune disease, the etiology and progression of MS, including the interaction between Vitamin D and MS risk variants, is still unclear and can be explored from the aspect of signal SEs. Vitamin D [with its active form: 1,25(OH)₂D₃], is an environmental risk factor for MS. It binds the Vitamin D receptor (VDR) and regulates gene expression. This study explores the association between VDR super-enhancers (VSEs) and MS risk variants. Firstly, we reanalyse public ChIP-seq and RNA-seq data to classify VSEs into three categories according to their combinations of persistent and secondary VDR binding. Secondly, we indicate the genes with VSE regions that are near MS risk variants. Furthermore, we find that MS risk variants are enriched in VSE regions, and we indicate some genes with a VSE overlapping MS risk variant for further exploration. We also find two clusters of genes from the set of genes showing correlation of expression patterns with the MS risk gene ZMIZ1 that appear to be regulated by VSEs in THP-1 cells. It is the first time that VSEs have been analyzed, and we directly connect the genetic risk factors for MS risk with Vitamin D based on VSEs.

Changes in expression profiles of internal jugular vein wall and plasma protein levels in multiple sclerosis

Background

Multiple sclerosis (MS) is an inflammatory, demyelinating and degenerative disorder of the central nervous system (CNS). Several observations support interactions between vascular and neurodegenerative mechanisms in multiple sclerosis (MS). To investigate the contribution of the extracranial venous compartment, we analysed expression profiles of internal jugular vein (IJV), which drains blood from CNS, and related plasma protein levels.

Methods

We studied a group of MS patients (n = 19), screened by echo-color Doppler and magnetic resonance venography, who underwent surgical reconstruction of IJV for chronic cerebrospinal venous insufficiency (CCSVI). Microarray-based transcriptome analysis was conducted on specimens of IJV wall from MS patients and from subjects undergoing carotid endarterectomy, as controls. Protein levels were determined by multiplex assay in: i) jugular and peripheral plasma from 17 MS/CCSVI patients; ii) peripheral plasma from 60 progressive MS patients, after repeated sampling and iii) healthy individuals.

Results

Of the differentially expressed genes (≥ 2 fold-change, multiple testing correction, P < 0.05), the immune-related CD86 (8.5 fold-change, P = 0.002) emerged among the up regulated genes (N = 409). Several genes encoding HOX transcription factors and histones potentially regulated by blood flow, were overexpressed. Smooth muscle contraction and cell adhesion processes emerged among down regulated genes (N = 515), including the neuronal cell adhesion L1CAM as top scorer (5 fold-change, P = 5 × 10^− 4).

Repeated measurements in jugular/peripheral plasma and overtime in peripheral plasma showed conserved individual plasma patterns for immune-inflammatory (CCL13, CCL18) and adhesion (NCAM1, VAP1, SELL) proteins, despite significant variations overtime (SELL P < 0.0001). Both age and MS disease phenotypes were determinants of VAP1 plasma levels.

Data supported cerebral related-mechanisms regulating ANGPT1 levels, which were remarkably lower in jugular plasma and correlated in repeated assays but not between jugular/peripheral compartments.

Conclusions

This study provides for the first time expression patterns of the IJV wall, suggesting signatures of altered vascular mRNA profiles in MS disease also independently from CCSVI. The combined transcriptome-protein analysis provides intriguing links between IJV wall transcript alteration and plasma protein expression, thus highlighting proteins of interest for MS pathophysiology.

Electronic supplementary material

The online version of this article (10.1186/s10020-018-0043-4) contains supplementary material, which is available to authorized users.

Identification of key target genes and biological pathways in multiple sclerosis brains using microarray data obtained from the Gene Expression Omnibus database

OBJECTIVE

The purpose of this study was to investigate critical genes in multiple sclerosis (MS) using microarray data from brain tissue in MS.

MATERIALS

The expression profile data set of MS (GSE38010) downloaded from the Gene Expression Omnibus database contained gene information from five plaque tissues from MS brains and two white matter tissues from healthy controls. An R package was applied to process these raw chip data. Gene Ontology (GO) functional analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis and protein-protein interaction (PPI) network analysis were performed to investigate interactions between differentially expressed genes (DEGs) in MS brain tissues.

RESULTS

This study identified a total of 1065 DEGs, including 530 up-regulated genes and 535 down-regulated genes, in MS brain tissue samples compared to those in normal white matter tissue samples. GO and KEGG pathway enrichment analyses showed that the up-regulated DEGs were mainly related to neuron development, neuron projection morphogenesis and neuron differentiation. Furthermore, the down-regulated DEGs were largely related to axon ensheathment, ensheathment of neurons and nervous system development. Seven key genes were found as hub genes in the maintenance of the PPI network.

CONCLUSION

Several key target genes and their GO and KEGG pathway enrichment identified in the present study may serve as feasible targets for MS therapies.

Integrative analysis of Multiple Sclerosis using a systems biology approach

Multiple sclerosis (MS) is a chronic autoimmune disorder characterized by inflammatory-demyelinating events in the central nervous system. Despite more than 40 years of MS research its aetiology remains unknown. This study aims to identify the most frequently reported and consistently regulated molecules in MS in order to generate molecular interaction networks and thereby leading to the identification of deregulated processes and pathways which could give an insight of the underlying molecular mechanisms of MS. Driven by an integrative systems biology approach, gene-expression profiling datasets were combined and stratified into "Non-treated" and "Treated" groups and additionally compared to other disease patterns. Molecular identifiers from dataset comparisons were matched to our Multiple Sclerosis database (MuScle; www.padb.org/muscle ). From 5079 statistically significant molecules, correlation analysis within groups identified a panel of 16 high-confidence genes unique to the naïve MS phenotype, whereas the "Treated" group reflected a common pattern associated with autoimmune disease. Pathway and gene-ontology clustering identified the Interferon gamma signalling pathway as the most relevant amongst all significant molecules, and viral infections as the most likely cause of all down-stream events observed. This hypothesis-free approach revealed the most significant molecular events amongst different MS phenotypes which can be used for further detailed studies.

Identification of Shared Molecular Signatures Indicate the Susceptibility of Endometriosis to Multiple Sclerosis

Women with endometriosis (EMS) appear to be at a higher risk of developing other autoimmune diseases predominantly multiple sclerosis (MS). Though EMS and MS are evidently diverse in their phenotype, they are linked by a common autoimmune condition or immunodeficiency which could play a role in the expansion of endometriosis and possibly increase the risk of developing MS in women with EMS. However, the common molecular links connecting EMS with MS are still unclear. We conducted a meta-analysis of microarray experiments focused on EMS and MS with their respective controls. The GEO2R web application discovered a total of 711 and 1516 genes that are differentially expressed across the experimental conditions in EMS and MS, respectively with 129 shared DEGs between them. The functional enrichment analysis of DEGs predicts the shared gene expression signatures as well as the overlapping biological processes likely to infer the co-occurrence of EMS with MS. Network based meta-analysis unveiled six interaction networks/crosstalks through overlapping edges between commonly dysregulated pathways of EMS and MS. The PTPN1, ERBB3, and CDH1 were observed to be the highly ranked hub genes connected with disease-related genes of both EMS and MS. Androgen receptor (AR) and nuclear factor-kB p65 (RelA) were observed to be the most enriched transcription factor in the upstream of shared down-regulated and up-regulated genes, respectively. The two disease sample sets compared through crosstalk interactions between shared pathways revealed commonly up- and down-regulated expressions of 10 immunomodulatory proteins as probable linkers between EMS and MS. This study pinpoints the number of shared genes, pathways, protein kinases, and upstream regulators that may help in the development of biomarkers for diagnosis of MS and endometriosis at the same time through improved understanding of shared molecular signatures and crosstalk.

Cross-platform comparison of independent datasets identifies an immune signature associated with improved survival in metastatic melanoma

Platform and study differences in prognostic signatures from metastatic melanoma (MM) gene expression reports often hinder consensus arrival. We performed survival/outcome-based pairwise comparisons of three independent MM gene expression profiles using the threshold-free algorithm rank-rank hypergeometric overlap analysis (RRHO). We found statistically significant overlap for genes overexpressed in favorable outcome (FO) groups, but no overlap for poor outcome (PO) groups. This “favorable outcome signature” (FOS) of 228 genes coinciding on all three overlapping gene lists showed immune function predominated in FO MM. Surprisingly, specific cell signature-enrichment analysis showed B cell-associated genes enriched in FO MM, along with T cell-associated genes. Higher levels of B and T cells (p<0.05) and their relative proximity (p<0.05) were detected in FO-to-PO tumor comparisons from an independent MM patients cohort. Finally, expression of FOS in two independent Stage III MM tumor datasets correctly predicted clinical outcome in 12/14 and 44/70 patients using a weighted gene voting classifier (area under the curve values 0.96 and 0.75, respectively). This RRHO-based, cross-study analysis emphasizes the RRHO approach power, confirms T cells relevance for prolonged MM survival, supports a favorable role for B cells in anti-melanoma immunity, and suggests B cells potential as means of intervention in melanoma treatment.

Attempts to Overcome Remyelination Failure: Toward Opening New Therapeutic Avenues for Multiple Sclerosis

Multiple sclerosis (MS) is a chronic immune-mediated disorder of the central nervous system that results in destruction of the myelin sheath wrapped around the axons and eventual axon degeneration. The disease is pathologically heterogeneous; however, perhaps its most frustrating aspect is the lack of efficient regenerative response for remyelination. Current treatment strategies are based on anti-inflammatory or immunomodulatory medications that have the potential to reduce the numbers of newly evolving lesions. However, therapies are still required that can repair already damaged myelin for which current treatments are not effective. A prerequisite for the development of such new treatments is understanding the reasons for insufficient endogenous repair. This review briefly summarizes the currently suggested causes of remyelination failure in MS and possible solutions.

Multiple sclerosis treatment effects on plasma cytokine receptor levels

Genetic variants within some cytokine receptor genes have been associated with MS susceptibility, including IL7RA and IL2RA. As these genes are expressed by cells targeted by immune-modulatory drugs, we explored the potential role of their gene products as biomarkers in monitoring MS treatment. We assessed the impact of natalizumab followed by fingolimod on the intra-individual changes of plasma protein levels of sIL-7Rα, sIL-2Rα and also sIL-6R and sgp130 in MS patients. During natalizumab treatment we observed a decline in sgp130 and sIL-7Rα levels, while subsequent fingolimod treatment lead to increased sgp130 and sIL-7Rα and decreased sIL-2Rα levels. In addition, during fingolimod treatment sIL-7Rα levels were increasing significantly more in patients homozygous for the MS risk genotype of rs6897932. We also observed an effect of the MS associated rs71624119 on sgp130 levels. These results may elucidate the pharmacodynamics of treatments and help identify biomarkers for MS outcomes.

Transcriptional dysregulation of Interferome in experimental and human Multiple Sclerosis

Recent evidence indicates that single multiple sclerosis (MS) susceptibility genes involved in interferon (IFN) signaling display altered transcript levels in peripheral blood of untreated MS subjects, suggesting that responsiveness to endogenous IFN is dysregulated during neuroinflammation. To prove this hypothesis we exploited the systematic collection of IFN regulated genes (IRG) provided by the Interferome database and mapped Interferome changes in experimental and human MS. Indeed, central nervous system tissue and encephalitogenic CD4 T cells during experimental autoimmune encephalomyelitis were characterized by massive changes in Interferome transcription. Further, the analysis of almost 500 human blood transcriptomes showed that (i) several IRG changed expression at distinct MS stages with a core of 21 transcripts concordantly dysregulated in all MS forms compared with healthy subjects; (ii) 100 differentially expressed IRG were validated in independent case-control cohorts; and (iii) 53 out of 100 dysregulated IRG were targeted by IFN-beta treatment in vivo. Finally, ex vivo and in vitro experiments established that IFN-beta administration modulated expression of two IRG, ARRB1 and CHP1, in immune cells. Our study confirms the impairment of Interferome in experimental and human MS, and describes IRG signatures at distinct disease stages which can represent novel therapeutic targets in MS.

Methylation of TMEM176A is an independent prognostic marker and is involved in human colorectal cancer development

Colorectal cancer (CRC) is the third most common malignancy and the fourth most common cause of cancer related death worldwide. This study was designed to find tumor suppressors involved in CRC development by performing RNA-seq. Eight CRC cell lines and 130 cases of primary CRC samples were used. RNA-seq, methylation-specific PCR (MSP), flow cytometry, transwell assays, and a xenograft mouse model were used. Reduction of TMEM176A expression was confirmed in human CRC cells by RNA-seq. TMEM176A was expressed in LS180 and SW620 cells, loss of TMEM176A expression was observed in LOVO, HCT116, RKO, and DLD1 cells, and reduced TMEM176A expression was found in HT29 and SW480 cells. Unmethylation of the TMEM176A promoter was found in LS180 and SW620 cells, whereas complete methylation was found in LOVO, HCT116, RKO, and DLD1 cells, and partial methylation was found in HT29 and SW480 cells. Promoter region methylation correlated with loss of/reduced expression of TMEM176A. Re-expression of TMEM176A was induced by 5-aza-2'-deoxycytidine. TMEM176A was methylated in 50.77% of primary colorectal cancers. Methylation of TMEM176A was associated with tumor metastasis (P<0.05) and was an independent prognostic factor for 5-year overall survival (OS) according to Cox proportional hazards model analysis (P<0.05). TMEM176A induced apoptosis and inhibited cell migration and invasion in CRC cells. TMEM176A suppressed CRC cell growth both in vitro and in vivo. Our results suggest that expression of TMEM176A is regulated by promoter region methylation. TMEM176A methylation is an independent prognostic marker for 5-year OS in CRC, and may act as a tumor suppressor in CRC.

Data characterizing the ZMIZ1 molecular phenotype of multiple sclerosis

The data presented in this article are related to the research article entitled "The autoimmune risk gene ZMIZ1 is a vitamin D responsived marker of a molecular phenotype of multiple sclerosis" Fewings et al. (2017) [1]. Here we identify the set of genes correlated with ZMIZ1 in multiple cohorts, provide phenotypic details on those cohorts, and identify the genes negatively correlated with ZMIZ1 and the cells predominantly expressing those genes. We identify the metabolic pathways in which the molecular phenotype genes are over-represented. Finally, we present the flow cytometry gating strategy we have used to identify the immune cells from blood which are producing ZMIZ1 and RPS6.

The autoimmune risk gene ZMIZ1 is a vitamin D responsive marker of a molecular phenotype of multiple sclerosis

Multiple Sclerosis (MS) is a neurological condition driven in part by immune cells from the peripheral circulation, the targets for current successful therapies. The autoimmune and MS risk gene ZMIZ1 is underexpressed in blood in people with MS. We show that, from three independent sets of transcriptomic data, expression of ZMIZ1 is tightly correlated with that of hundreds of other genes. Further we show expression is partially heritable (heritability 0.26), relatively stable over time, predominantly in plasmacytoid dendritic cells and non-classical monocytes, and that levels of ZMIZ1 protein expression are reduced in MS. ZMIZ1 gene expression is increased in response to calcipotriol (1,25 Vitamin D3) (p < 0.0003) and associated with Epstein Barr Virus (EBV) EBNA-1 antibody titre (p < 0.004). MS therapies fingolimod and dimethyl fumarate altered blood ZMIZ1 gene expression compared to untreated MS. The phenotype indicates susceptibility to MS, and may correspond with clinical response and represent a novel clinical target.

Genetic overlap between multiple sclerosis and several cardiovascular disease risk factors

BACKGROUND

Epidemiological findings suggest a relationship between multiple sclerosis (MS) and cardiovascular disease (CVD) risk factors, although the nature of this relationship is not well understood.

OBJECTIVE

We used genome-wide association study (GWAS) data to identify shared genetic factors (pleiotropy) between MS and CVD risk factors.

METHODS

Using summary statistics from a large, recent GWAS (total n > 250,000 individuals), we investigated overlap in single nucleotide polymorphisms (SNPs) associated with MS and a number of CVD risk factors including triglycerides (TG), low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, body mass index, waist-to-hip ratio, type 2 diabetes, systolic blood pressure, and C-reactive protein level.

RESULTS AND CONCLUSION

Using conditional enrichment plots, we found 30-fold enrichment of MS SNPs for different levels of association with LDL and TG SNPs, with a corresponding reduction in conditional false discovery rate (FDR). We identified 133 pleiotropic loci outside the extended major histocompatibility complex with conditional FDR < 0.01, of which 65 are novel. These pleiotropic loci were located on 21 different chromosomes. Our findings point to overlapping pathobiology between clinically diagnosed MS and cardiovascular risk factors and identify novel common variants associated with increased MS risk.