A systems biology approach uncovers cell-specific gene regulatory effects of genetic associations in multiple sclerosis

Deciphering the tumor immune microenvironment from a multidimensional omics perspective: insight into next-generation CAR-T cell immunotherapy and beyond

Tumor immune microenvironment (TIME) consists of intra-tumor immunological components and plays a significant role in tumor initiation, progression, metastasis, and response to therapy. Chimeric antigen receptor (CAR)-T cell immunotherapy has revolutionized the cancer treatment paradigm. Although CAR-T cell immunotherapy has emerged as a successful treatment for hematologic malignancies, it remains a conundrum for solid tumors. The heterogeneity of TIME is responsible for poor outcomes in CAR-T cell immunotherapy against solid tumors. The advancement of highly sophisticated technology enhances our exploration in TIME from a multi-omics perspective. In the era of machine learning, multi-omics studies could reveal the characteristics of TIME and its immune resistance mechanism. Therefore, the clinical efficacy of CAR-T cell immunotherapy in solid tumors could be further improved with strategies that target unfavorable conditions in TIME. Herein, this review seeks to investigate the factors influencing TIME formation and propose strategies for improving the effectiveness of CAR-T cell immunotherapy through a multi-omics perspective, with the ultimate goal of developing personalized therapeutic approaches.

Potential biomarkers for multiple sclerosis stage from targeted proteomics and microRNA sequencing

Multiple sclerosis is a chronic demyelinating disease of the central nervous system. There is a need for new circulating biomarkers for multiple sclerosis, in particular, markers that differentiate multiple sclerosis subtypes (relapsing-remitting, secondary progressive and primary progressive multiple sclerosis), as this can help in making treatment decisions. In this study, we explore two classes of potential multiple sclerosis biomarkers-proteins and microRNAs-circulating in the cerebrospinal fluid and serum. Targeted medium-throughput proteomics (92 proteins) and microRNA sequencing were performed on serum samples collected in a cross-sectional case-control cohort (cohort I, controls n = 30, multiple sclerosis n = 75) and a prospective multiple sclerosis cohort (cohort II, n = 93). For cohort I, we also made these measurements in paired cerebrospinal fluid samples. In the cohort I cerebrospinal fluid, we observed differences between multiple sclerosis and controls for 13 proteins, including some previously described to be markers for multiple sclerosis [e.g. CD27, C-X-C motif chemokine 13 (CXCL13) and interleukin-7 (IL7)]. No microRNAs were significantly differentially expressed between multiple sclerosis and controls in the cerebrospinal fluid. In serum, 10 proteins, including angiopoietin-1 receptor (TIE2), and 16 microRNAs were significantly different between relapsing-remitting multiple sclerosis and secondary progressive multiple sclerosis after performing a meta-analysis combining both cohorts. In the prospective part of the study, participants with relapsing-remitting multiple sclerosis were followed for around 3 years, during which time 12 participants converted to secondary progressive multiple sclerosis. In these longitudinally collected serum samples, we observed a peak in granzyme B, A and H proteins around the time of conversion. Single-sample enrichment analysis of serum microRNA profiles revealed that the peak in granzyme B levels around conversion coincides with enrichment for microRNAs that are enriched in CD4+, CD8+ and natural killer cells (e.g. miRNA-150). We identified several proteins and microRNAs in serum that represent potential biomarkers for relapsing-remitting and secondary progressive multiple sclerosis. Conversion to secondary progressive disease is marked by a peak in granzyme B levels and enrichment for immune-related microRNAs. This indicates that specific immune cell-driven processes may contribute to the conversion of relapsing-remitting multiple sclerosis to secondary progressive multiple sclerosis.

Multiscale networks in multiple sclerosis

Complex diseases such as Multiple Sclerosis (MS) cover a wide range of biological scales, from genes and proteins to cells and tissues, up to the full organism. In fact, any phenotype for an organism is dictated by the interplay among these scales. We conducted a multilayer network analysis and deep phenotyping with multi-omics data (genomics, phosphoproteomics and cytomics), brain and retinal imaging, and clinical data, obtained from a multicenter prospective cohort of 328 patients and 90 healthy controls. Multilayer networks were constructed using mutual information for topological analysis, and Boolean simulations were constructed using Pearson correlation to identified paths within and among all layers. The path more commonly found from the Boolean simulations connects protein MK03, with total T cells, the thickness of the retinal nerve fiber layer (RNFL), and the walking speed. This path contains nodes involved in protein phosphorylation, glial cell differentiation, and regulation of stress-activated MAPK cascade, among others. Specific paths identified were subsequently analyzed by flow cytometry at the single-cell level. Combinations of several proteins (GSK3AB, HSBP1 or RS6) and immune cells (Th17, Th1 non-classic, CD8, CD8 Treg, CD56 neg, and B memory) were part of the paths explaining the clinical phenotype. The advantage of the path identified from the Boolean simulations is that it connects information about these known biological pathways with the layers at higher scales (retina damage and disability). Overall, the identified paths provide a means to connect the molecular aspects of MS with the overall phenotype.

Could NCOA5 a novel candidate gene for multiple sclerosis susceptibility?

BACKGROUND

Multiple sclerosis (MS) is an inflammatory immune-mediated demyelinating disease that causes a challenging and disabling condition. Environmental and genetic factors play a role in appearing the state of the disease. Recent studies have shown that nuclear cofactor genes may play a role in the pathogenesis of MS. NCOA5 is a nuclear receptor coactivator independent of AF2 that modulates ERa-mediated transcription. This gene is involved in the pathogenesis of diseases such as psoriasis, Behcet's disease, and cancer.

METHODS AND RESULTS

We investigated the relationship between the rs2903908 polymorphism of the NCOA5 gene and MS among 157 unrelated MS patients and 160 healthy controls by RT-PCR. The frequencies of the CC, CT, and TT genotypes were 19.87%, 37.82%, and 42.31%, respectively, for the MS group and 5.63%, 43.75%, and 50.62%, respectively, for the control group. The CC genotype and the C allele were found to be significantly higher in the patient group (the p values were 0.0002 and 0.003, respectively).

CONCLUSIONS

The fact that the CC genotype was found to be significantly higher in the patient group compared to the control group (p = 0.0002) and that it had a statistically significantly higher OR value (OR, 95% CI = 4.16, 1.91-9.05) suggests that the C allele may recessively predispose to MS for this polymorphism. These results suggest for the first time that the NCOA5 gene may have an effect on the occurrence of MS through different molecular pathways, which are discussed in the manuscript.

Decision trees to evaluate the risk of developing multiple sclerosis

Introduction

Multiple sclerosis (MS) is a persistent neurological condition impacting the central nervous system (CNS). The precise cause of multiple sclerosis is still uncertain; however, it is thought to arise from a blend of genetic and environmental factors. MS diagnosis includes assessing medical history, conducting neurological exams, performing magnetic resonance imaging (MRI) scans, and analyzing cerebrospinal fluid. While there is currently no cure for MS, numerous treatments exist to address symptoms, decelerate disease progression, and enhance the quality of life for individuals with MS.

Methods

This paper introduces a novel machine learning (ML) algorithm utilizing decision trees to address a key objective: creating a predictive tool for assessing the likelihood of MS development. It achieves this by combining prevalent demographic risk factors, specifically gender, with crucial immunogenetic risk markers, such as the alleles responsible for human leukocyte antigen (HLA) class I molecules and the killer immunoglobulin-like receptors (KIR) genes responsible for natural killer lymphocyte receptors.

Results

The study included 619 healthy controls and 299 patients affected by MS, all of whom originated from Sardinia. The gender feature has been disregarded due to its substantial bias in influencing the classification outcomes. By solely considering immunogenetic risk markers, the algorithm demonstrates an ability to accurately identify 73.24% of MS patients and 66.07% of individuals without the disease.

Discussion

Given its notable performance, this system has the potential to support clinicians in monitoring the relatives of MS patients and identifying individuals who are at an increased risk of developing the disease.

The interaction between Epstein-Barr virus and multiple sclerosis genetic risk loci: insights into disease pathogenesis and therapeutic opportunities

Multiple sclerosis (MS) is a chronic neurodegenerative autoimmune disease, characterised by the demyelination of neurons in the central nervous system. Whilst it is unclear what precisely leads to MS, it is believed that genetic predisposition combined with environmental factors plays a pivotal role. It is estimated that close to half the disease risk is determined by genetic factors. However, the risk of developing MS cannot be attributed to genetic factors alone, and environmental factors are likely to play a significant role by themselves or in concert with host genetics. Epstein-Barr virus (EBV) infection is the strongest known environmental risk factor for MS. There has been increasing evidence that leaves little doubt that EBV is necessary, but not sufficient, for developing MS. One plausible explanation is EBV may alter the host immune response in the presence of MS risk alleles and this contributes to the pathogenesis of MS. In this review, we discuss recent findings regarding how EBV infection may contribute to MS pathogenesis via interactions with genetic risk loci and discuss possible therapeutic interventions.

Integration of epigenetic and genetic profiles identifies multiple sclerosis disease-critical cell types and genes

Genome-wide association studies (GWAS) successfully identified multiple sclerosis (MS) susceptibility variants. Despite this notable progress, understanding the biological context of these associations remains challenging, due in part to the complexity of linking GWAS results to causative genes and cell types. Here, we aimed to address this gap by integrating GWAS data with single-cell and bulk chromatin accessibility data and histone modification profiles from immune and nervous systems. MS-GWAS associations are significantly enriched in regulatory regions of microglia and peripheral immune cell subtypes, especially B cells and monocytes. Cell-specific polygenic risk scores were developed to examine the cumulative impact of the susceptibility genes on MS risk and clinical phenotypes, showing significant associations with risk and brain white matter volume. The findings reveal enrichment of GWAS signals in B cell and monocyte/microglial cell-types, consistent with the known pathology and presumed targets of effective MS therapeutics.

Mendelian randomization and clinical trial evidence supports TYK2 inhibition as a therapeutic target for autoimmune diseases

BACKGROUND

To explore the associations of genetically proxied TYK2 inhibition with a wide range of disease outcomes and biomarkers to identify therapeutic repurposing opportunities, adverse effects, and biomarkers of efficacy.

METHODS

The loss-of-function missense variant rs34536443 in TYK2 gene was used as a genetic instrument to proxy the effect of TYK2 inhibition. A phenome-wide Mendelian randomization (MR) study was conducted to explore the associations of genetically-proxied TYK2 inhibition with 1473 disease outcomes in UK Biobank (N = 339,197). Identified associations were examined for replication in FinnGen (N = 260,405). We further performed tissue-specific gene expression MR, colocalization analyses, and MR with 247 blood biomarkers. A systematic review of randomized controlled trials (RCTs) on TYK2 inhibitor was performed to complement the genetic evidence.

FINDINGS

PheWAS-MR found that genetically-proxied TYK2 inhibition was associated with lower risk of a wide range of autoimmune diseases. The associations with hypothyroidism and psoriasis were confirmed in MR analysis of tissue-specific TYK2 gene expression and the associations with systemic lupus erythematosus, psoriasis, and rheumatoid arthritis were observed in colocalization analysis. There were nominal associations of genetically-proxied TYK2 inhibition with increased risk of prostate and breast cancer but not in tissue-specific expression MR or colocalization analyses. Thirty-seven blood biomarkers were associated with the TYK2 loss-of-function mutation. Evidence from RCTs confirmed the effectiveness of TYK2 inhibitors on plaque psoriasis and reported several adverse effects.

INTERPRETATION

This study supports TYK2 inhibitor as a potential treatment for psoriasis and several other autoimmune diseases. Increased pharmacovigilance is warranted in relation to the potential adverse effects.

FUNDING

None.

New Insights into Risk Genes and Their Candidates in Multiple Sclerosis

Oligodendrocytes are central nervous system glial cells that wrap neuronal axons with their differentiated myelin membranes as biological insulators. There has recently been an emerging concept that multiple sclerosis could be triggered and promoted by various risk genes that appear likely to contribute to the degeneration of oligodendrocytes. Despite the known involvement of vitamin D, immunity, and inflammatory cytokines in disease progression, the common causes and key genetic mechanisms remain unknown. Herein, we focus on recently identified risk factors and risk genes in the background of multiple sclerosis and discuss their relationships.

The immunology of multiple sclerosis

Our incomplete understanding of the causes and pathways involved in the onset and progression of multiple sclerosis (MS) limits our ability to effectively treat this complex neurological disease. Recent studies explore the role of immune cells at different stages of MS and how they interact with cells of the central nervous system (CNS). The findings presented here begin to question the exclusivity of an antigen-specific cause and highlight how seemingly distinct immune cell types can share common functions that drive disease. Innovative techniques further expose new disease-associated immune cell populations and reinforce how environmental context is critical to their phenotype and subsequent role in disease. Importantly, the differentiation of immune cells into a pathogenic state is potentially reversible through therapeutic manipulation. As such, understanding the mechanisms that provide plasticity to causal cell types is likely key to uncoupling these disease processes and may identify novel therapeutic targets that replace the need for cell ablation.

Impact of Multiple Sclerosis Risk Polymorphism rs7665090 on MANBA Activity, Lysosomal Endocytosis, and Lymphocyte Activation

Deficiencies in Mannosidase β (MANBA) are associated with neurological abnormalities and recurrent infections. The single nucleotide polymorphism located in the 3′UTR of MANBA, rs7665090, was found to be associated with multiple sclerosis (MS) susceptibility. We aimed to study the functional impact of this polymorphism in lymphocytes isolated from MS patients and healthy controls. A total of 152 MS patients and 112 controls were genotyped for rs7665090. MANBA mRNA expression was quantified through qPCR and MANBA enzymatic activity was analyzed. Upon phytohemagglutinin stimulation, immune activation was evaluated by flow cytometry detection of CD69, endocytic function, and metabolic rates with Seahorse XFp Analyzer, and results were stratified by variation in rs7665090. A significantly reduced gene expression (p < 0.0001) and enzymatic activity (p = 0.018) of MANBA were found in lymphocytes of MS patients compared to those of controls. The rs7665090*GG genotype led to a significant β-mannosidase enzymatic deficiency correlated with lysosomal dysfunction, as well as decreased metabolic activation in lymphocytes of MS patients compared to those of rs7665090*GG controls. In contrast, lymphocytes of MS patients and controls carrying the homozygous AA genotype behaved similarly. Our work provides new evidence highlighting the impact of the MS-risk variant, rs7665090, and the role of MANBA in the immunopathology of MS.

Dissection of multiple sclerosis genetics identifies B and CD4+ T cells as driver cell subsets

Background

Multiple sclerosis (MS) is an autoimmune condition of the central nervous system with a well-characterized genetic background. Prior analyses of MS genetics have identified broad enrichments across peripheral immune cells, yet the driver immune subsets are unclear.

Results

We utilize chromatin accessibility data across hematopoietic cells to identify cell type-specific enrichments of MS genetic signals. We find that CD4 T and B cells are independently enriched for MS genetics and further refine the driver subsets to T_h17 and memory B cells, respectively. We replicate our findings in data from untreated and treated MS patients and find that immunomodulatory treatments suppress chromatin accessibility at driver cell types. Integration of statistical fine-mapping and chromatin interactions nominate numerous putative causal genes, illustrating complex interplay between shared and cell-specific genes.

Conclusions

Overall, our study finds that open chromatin regions in CD4 T cells and B cells independently drive MS genetic signals. Our study highlights how careful integration of genetics and epigenetics can provide fine-scale insights into causal cell types and nominate new genes and pathways for disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02694-y.

Coming of Age: Human Genomics and the Cancer-Immune Set Point

Cancer is largely a disease of the tumor cell genome. As a result, the majority of genetics research in oncology has concentrated on the role of tumor somatic mutations, as well as inherited risk variants, in disease susceptibility and response to targeted treatments. The advent and success of cancer immunotherapies, however, have opened new perspectives for the investigation of the role of inherited genetic variation in codetermining outcome and safety. It is increasingly likely that the entirety of germline genetic variation involved in regulating immune responses accounts for a significant fraction of the observed variability in responses to cancer immunotherapies. Although germline genetic data from patients treated with cancer immunotherapies are still scarce, this line of research benefits from a vast body of knowledge derived from studies into autoimmune and infectious disease phenotypes, thus not requiring a start from a blank slate. Here, we discuss how a thorough investigation of genomic variation relevant for individuals' variability in (auto)immune responses can contribute to the discovery of novel treatment approaches and drug targets, and yield predictive biomarkers to stratify cancer patient populations in precision and personalized medicine settings.

The Effect of Peripheral Immune Cell Counts on the Risk of Multiple Sclerosis: A Mendelian Randomization Study

Objectives

Multiple sclerosis (MS) is a complex central nervous system (CNS) demyelinating disease, the etiology of which involves the interplay between genetic and environmental factors. We aimed to determine whether genetically predicted peripheral immune cell counts may have a causal effect on MS.

Methods

We used genetic variants strongly associated with cell counts of circulating leukocyte, lymphocyte, monocyte, neutrophil, eosinophil, and basophil, in addition to some subpopulations of T and B lymphocyte, as instrumental variables (IVs) to perform Mendelian randomization (MR) analyses. The effect of immune cell counts on MS risk was measured using the summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) genome-wide association studies (GWAS).

Results

Our findings indicated that higher leucocyte count [odds ratio (OR), 1.24; 95% confidence interval (CI), 1.07 - 1.43; p = 0.0039] and lymphocyte count (OR, 1.17; 95% CI, 1.01 – 1.35; p = 0.0317) were causally associated with MS susceptibility. In addition, we also found that increase of genetically predicted natural killer T (NKT) cell count is also associated with an increase MS risk (OR, 1.24; 95% CI, 1.06 - 1.45; p = 0.0082).

Conclusions

These findings show that the genetic predisposition to higher peripheral immune cell counts can exert a causal effect on MS risk, which confirms the crucial role played by peripheral immunity in MS. Particularly, the causal association between NKT cell count and MS underscores the relevance of exploring the functional roles of NKT cells in disease pathogenesis in future.

A multi-step genomic approach prioritized TBKBP1 gene as relevant for multiple sclerosis susceptibility

Background

Over 200 genetic loci have been associated with multiple sclerosis (MS) explaining ~ 50% of its heritability, suggesting that additional mechanisms may account for the “missing heritability” phenomenon.

Objective

To analyze a large cohort of Italian individuals to identify markers associated with MS with potential functional impact in the disease.

Methods

We studied 2571 MS and 3234 healthy controls (HC) of continental Italian origin. Discovery phase included a genome wide association study (1727 MS, 2258 HC), with SNPs selected according to their association in the Italian cohort only or in a meta-analysis of signals with a cohort of European ancestry (4088 MS, 7144 HC). Top associated loci were then tested in two Italian cohorts through array-based genotyping (903 MS, 884 HC) and pool-based target sequencing (588 MS, 408 HC). Finally, functional prioritization through conditional eQTL and mQTL has been performed.

Results

Top associated signals overlap with already known MS loci on chromosomes 3 and 17. Three SNPs (rs4267364, rs8070463, rs67919208), all involved in the regulation of TBKBP1, were prioritized to be functionally relevant.

Conclusions

No evidence of novel signal of association with MS specific for the Italian continental population has been found; nevertheless, two MS loci seems to play a relevant role, raising the interest to further investigations for TBKBP1 gene.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00415-022-11109-8.

Pregnancy loss and risk of multiple sclerosis and autoimmune neurological disorder: A nationwide cohort study

Background

The loss of one or more pregnancies before viability (i.e. pregnancy loss or miscarriage), has been linked to an increased risk of diseases later in life such as myocardial infarction and stroke. Recurrent pregnancy loss (i.e. three consecutive pregnancy losses) and multiple sclerosis have both been linked to immunological traits, which could predispose to both occurrences. The objective of the current study was to investigate if pregnancy loss is associated with later autoimmune neurological disease.

Methods

This register-based cohort study, included the Danish female population age 12 or older between 1977–2017. Women were grouped hierarchically: 0, 1, 2, ≥3 pregnancy losses, primary recurrent pregnancy loss (i.e. not preceded by a delivery), and secondary recurrent pregnancy loss (i.e. preceded by a delivery). The main outcome was multiple sclerosis and additional outcomes were amyotrophic lateral sclerosis, Guillain-Barré syndrome, and myasthenia gravis. Bayesian Poisson regression estimated incidence rate ratios [IRR] and 95% credible intervals [CI] adjusted for year, age, live births, family history of an outcome, and education.

Results

After 40,380,194 years of follow-up, multiple sclerosis was diagnosed among 7,667 out of 1,513,544 included women (0.5%), median age at diagnosis 34.2 years (IQR 27.4–41.4 years), and median age at symptom onset 31.2 years (IQR 24.8–38.2). The adjusted IRR of multiple sclerosis after 1 pregnancy loss was: 1.03 (95% CI 0.95–1.11), 2 losses: 1.02 (95% CI 0.86–1.20), ≥3 non-consecutive losses: 0.81 (95% CI 0.51–1.24), primary recurrent pregnancy loss: 1.18 (95% CI 0.84–1.60), secondary recurrent pregnancy loss: 1.16 (95% CI 0.81–1.63), as compared to women with no pregnancy losses. Seven sensitivity analyses and analyses for additional outcomes did not show significantly elevated adjusted risk estimates.

Conclusions

In this nationwide study, pregnancy loss was not significantly associated with autoimmune neurological disorder.

Autophagy mediates ER stress and inflammation in Helicobacter pylori-related gastric cancer

Autophagy is a cellular degradation mechanism, which is triggered by the bacterium Helicobacter pylori. A single nucleotide polymorphism (SNP) in the autophagy gene ATG16L1 (rs2241880, G-allele) has been shown to dysregulate autophagy and increase intestinal endoplasmic reticulum (ER) stress. Here, we investigate the role of this SNP in H.pylori-mediated gastric carcinogenesis and its molecular pathways. ATG16L1 rs2241880 was genotyped in subjects from different ethnic cohorts (Dutch and Australian) presenting with gastric (pre)malignant lesions of various severity. Expression of GRP78 (a marker for ER stress) was assessed in gastric tissues. The effect of ATG16L1 rs2241880 on H.pylori-mediated ER stress and pro-inflammatory cytokine induction was investigated in organoids and CRISPR/Cas9 modified cell lines. Development of gastric cancer was associated with the ATG16L1 rs2241880 G-allele. Intestinal metaplastic cells in gastric tissue of patients showed increased levels of ER-stress. In vitro models showed that H.pylori increases autophagy while reducing ER stress, which appeared partly mediated by the ATG16L1 rs2241880 genotype. H.pylori-induced IL-8 production was increased while TNF-α production was decreased, in cells homozygous for the G-allele. The ATG16L1 rs2241880 G-allele is associated with progression of gastric premalignant lesions and cancer. Modulation of H.pylori-induced ER stress pathways and pro-inflammatory mediators by ATG16L1 rs2441880 may underlie this increased risk.

Genetics and functional genomics of multiple sclerosis

Multiple sclerosis (MS) is an inflammatory neurodegenerative disease with genetic predisposition. Over the last decade, genome-wide association studies with increasing sample size led to the discovery of robustly associated genetic variants at an exponential rate. More than 200 genetic loci have been associated with MS susceptibility and almost half of its heritability can be accounted for. However, many challenges and unknowns remain. Definitive studies of disease progression and endophenotypes are yet to be performed, whereas the majority of the identified MS variants are not yet functionally characterized. Despite these shortcomings, the unraveling of MS genetics has opened up a new chapter on our understanding MS causal mechanisms.

Expression and clinical significance of IL7R, NFATc2, and RNF213 in familial and sporadic multiple sclerosis

Multiple sclerosis (MS) is a chronic inflammatory and autoimmune disorder of the central nervous system characterized by myelin loss and axonal dysfunction. Increased production of inflammatory factors such as cytokines has been implicated in axon destruction. In the present study, we compared the expression level of IL7R, NFATc2, and RNF213 genes in the peripheral blood of 72 MS patients (37 familial MS, 35 sporadic MS) and 74 healthy controls (34 individuals with a family history of the disease, 40 healthy controls without a family history) via Real-time PCR. Our results showed that the expression level of IL7R was decreased in the sporadic patients in comparison with other groups. Additionally, there was an increased NFATc2 expression level in MS patients versus healthy controls. Increased expression of NFATc2 in sporadic and familial groups compared to the controls, and familial group versus FDR was also seen. Our results also represented an increased expression level of RNF213 in familial patients as compared to the control group. The similar RNF213 expression between sporadic and control group, as well as FDR and familial group was also seen. Diagnostic evaluation was performed by receiver operating characteristic (ROC) curve analysis and area under the curve (AUC) calculation. The correlation of clinical parameters including onset age and Expanded Disability Status Scale (EDSS) with our gene expression levels were also assessed. Overall, decreased expression level of IL7R in the sporadic cases and increased expression level of NFATc2 may be associated with the pathogenesis of MS disease. Confirmation of the effects of differential expression of RNF213 gene requires further studies in the wider statistical populations.

ZEB1 promotes pathogenic Th1 and Th17 cell differentiation in multiple sclerosis

Inappropriate CD4⁺ T helper (Th) differentiation can compromise host immunity or promote autoimmune disease. To identify disease-relevant regulators of T cell fate, we examined mutations that modify risk for multiple sclerosis (MS), a canonical organ-specific autoimmune disease. This analysis identified a role for Zinc finger E-box-binding homeobox (ZEB1). Deletion of ZEB1 protects against experimental autoimmune encephalitis (EAE), a mouse model of multiple sclerosis (MS). Mechanistically, ZEB1 in CD4⁺ T cells is required for pathogenic Th1 and Th17 differentiation. Genomic analyses of paired human and mouse expression data elucidated an unexpected role for ZEB1 in JAK-STAT signaling. ZEB1 inhibits miR-101-3p that represses JAK2 expression, STAT3/STAT4 phosphorylation, and subsequent expression of interleukin-17 (IL-17) and interferon gamma (IFN-γ). Underscoring its clinical relevance, ZEB1 and JAK2 downregulation decreases pathogenic cytokines expression in T cells from MS patients. Moreover, a Food and Drug Administration (FDA)-approved JAK2 inhibitor is effective in EAE. Collectively, these findings identify a conserved, potentially targetable mechanism regulating disease-relevant inflammation.

Qian et al. show that ZEB1 is required for the development of the autoimmune disease multiple sclerosis (MS). ZEB1, a transcription factor, promotes JAK-STAT signaling during Th1/Th17 differentiation by repressing expression of a JAK2-targeting miRNA. ZEB1 and JAK2 are potentially clinically relevant therapeutic targets for MS.

Proportions of circulating transitional B cells associate with MRI activity in interferon beta-treated multiple sclerosis patients

B-cells contribute to MS pathogenesis. The association of circulating B-cell phenotypes with combined unique active lesions (CUA) on MRI at 48 weeks follow-up was investigated in 50 interferon beta-treated MS patients. Transitional B-cell proportions were lower in participants with CUA at week 0 and 48 [p = 0.004, p = 0.002]. A decrease in circulating anti-EBNA-1 IgG levels between week 0 and 48 associated with absence of CUA [p = 0.047], but not with B-cell profiles. In a multi-factor model for CUA-risk, transitional B-cell proportions contributed independent from NK/T-cell ratio, change in anti-EBNA-1 IgG, and vitamin D supplementation. Transitional B-cells may predict treatment response in MS.

The CD8 T Cell-Epstein-Barr Virus-B Cell Trialogue: A Central Issue in Multiple Sclerosis Pathogenesis

The cause and the pathogenic mechanisms leading to multiple sclerosis (MS), a chronic inflammatory disease of the central nervous system (CNS), are still under scrutiny. During the last decade, awareness has increased that multiple genetic and environmental factors act in concert to modulate MS risk. Likewise, the landscape of cells of the adaptive immune system that are believed to play a role in MS immunopathogenesis has expanded by including not only CD4 T helper cells but also cytotoxic CD8 T cells and B cells. Once the key cellular players are identified, the main challenge is to define precisely how they act and interact to induce neuroinflammation and the neurodegenerative cascade in MS. CD8 T cells have been implicated in MS pathogenesis since the 80's when it was shown that CD8 T cells predominate in MS brain lesions. Interest in the role of CD8 T cells in MS was revived in 2000 and the years thereafter by studies showing that CNS-recruited CD8 T cells are clonally expanded and have a memory effector phenotype indicating in situ antigen-driven reactivation. The association of certain MHC class I alleles with MS genetic risk implicates CD8 T cells in disease pathogenesis. Moreover, experimental studies have highlighted the detrimental effects of CD8 T cell activation on neural cells. While the antigens responsible for T cell recruitment and activation in the CNS remain elusive, the high efficacy of B-cell depleting drugs in MS and a growing number of studies implicate B cells and Epstein-Barr virus (EBV), a B-lymphotropic herpesvirus that is strongly associated with MS, in the activation of pathogenic T cells. This article reviews the results of human studies that have contributed to elucidate the role of CD8 T cells in MS immunopathogenesis, and discusses them in light of current understanding of autoreactivity, B-cell and EBV involvement in MS, and mechanism of action of different MS treatments. Based on the available evidences, an immunopathological model of MS is proposed that entails a persistent EBV infection of CNS-infiltrating B cells as the target of a dysregulated cytotoxic CD8 T cell response causing CNS tissue damage.

Immunosenescence in multiple sclerosis: the identification of new therapeutic targets

The number of elderly multiple sclerosis (MS) patients is growing, mainly due to the increase in the life expectancy of the general population and the availability of effective disease-modifying treatments. However, current treatments reduce the frequency of relapses and slow the progression of the disease, but they cannot stop the disability accumulation associated with disease progression. One possible explanation is the impact of immunosenescence, which is associated with the accumulation of unusual immune cell subsets that are thought to have a role in the development of an early ageing process in autoimmunity. Here, we provide a recent overview of how senescence affects immune cell function and how it is involved in the pathogenesis of autoimmune diseases, particularly MS. Numerous studies have demonstrated age-related immune changes in experimental autoimmune encephalomyelitis models, and the premature onset of immunosenescence has been demonstrated in MS patients. Therefore, potential therapeutic strategies based on rejuvenating the immune system have been proposed. Senolytics and regenerative strategies using haematopoietic stem cells, therapies based on rejuvenating oligodendrocyte precursor cells, microglia and monocytes, thymus cells and senescent B and T cells are capable of reversing the process of immunosenescence and could have a beneficial impact on the progression of MS.

B Cells in Neuroinflammation: New Perspectives and Mechanistic Insights

In recent years, the role of B cells in neurological disorders has substantially expanded our perspectives on mechanisms of neuroinflammation. The success of B cell-depleting therapies in patients with CNS diseases such as neuromyelitis optica and multiple sclerosis has highlighted the importance of neuroimmune crosstalk in inflammatory processes. While B cells are essential for the adaptive immune system and antibody production, they are also major contributors of pro- and anti-inflammatory cytokine responses in a number of inflammatory diseases. B cells can contribute to neurological diseases through peripheral immune mechanisms, including production of cytokines and antibodies, or through CNS mechanisms following compartmentalization. Emerging evidence suggests that aberrant pro- or anti-inflammatory B cell populations contribute to neurological processes, including glial activation, which has been implicated in the pathogenesis of several neurodegenerative diseases. In this review, we summarize recent findings on B cell involvement in neuroinflammatory diseases and discuss evidence to support pathogenic immunomodulatory functions of B cells in neurological disorders, highlighting the importance of B cell-directed therapies.

Tyro3, Axl, Mertk receptor-mediated efferocytosis and immune regulation in the tumor environment

Three structurally related tyrosine receptor cell surface kinases, Tyro3, Axl, and Mertk (TAM) have been recognized to modulate immune function, tissue homeostasis, cardiovasculature, and cancer. The TAM receptor family appears to operate in adult mammals across multiple cell types, suggesting both widespread and specific regulation of cell functions and immune niches. TAM family members regulate tissue homeostasis by monitoring the presence of phosphatidylserine expressed on stressed or apoptotic cells. The detection of phosphatidylserine on apoptotic cells requires intermediary molecules that opsonize the dying cells and tether them to TAM receptors on phagocytes. This complex promotes the engulfment of apoptotic cells, also known as efferocytosis, that leads to the resolution of inflammation and tissue healing. The immune mechanisms dictating these processes appear to fall upon specific family members or may involve a complex of different receptors acting cooperatively to resolve and repair damaged tissues. Here, we focus on the role of TAM receptors in triggering efferocytosis and its consequences in the regulation of immune responses in the context of inflammation and cancer.

Corrected score methods for estimating Bayesian networks with error-prone nodes

Motivated by inferring cellular signaling networks using noisy flow cytometry data, we develop procedures to draw inference for Bayesian networks based on error-prone data. Two methods for inferring causal relationships between nodes in a network are proposed based on penalized estimation methods that account for measurement error and encourage sparsity. We discuss consistency of the proposed network estimators and develop an approach for selecting the tuning parameter in the penalized estimation methods. Empirical studies are carried out to compare the proposed methods with a naive method that ignores measurement error. Finally, we apply these methods to infer signaling networks using single cell flow cytometry data.

Mining Complex Genetic Patterns Conferring Multiple Sclerosis Risk

(1) Background: Complex genetic relationships, including gene-gene (G × G; epistasis), gene(n), and gene-environment (G × E) interactions, explain a substantial portion of the heritability in multiple sclerosis (MS). Machine learning and data mining methods are promising approaches for uncovering higher order genetic relationships, but their use in MS have been limited. (2) Methods: Association rule mining (ARM), a combinatorial rule-based machine learning algorithm, was applied to genetic data for non-Latinx MS cases (n = 207) and controls (n = 179). The objective was to identify patterns (rules) amongst the known MS risk variants, including HLA-DRB1*15:01 presence, HLA-A*02:01 absence, and 194 of the 200 common autosomal variants. Probabilistic measures (confidence and support) were used to mine rules. (3) Results: 114 rules met minimum requirements of 80% confidence and 5% support. The top ranking rule by confidence consisted of HLA-DRB1*15:01, SLC30A7-rs56678847 and AC093277.1-rs6880809; carriers of these variants had a significantly greater risk for MS (odds ratio = 20.2, 95% CI: 8.5, 37.5; p = 4 × 10⁻⁹). Several variants were shared across rules, the most common was INTS8-rs78727559, which was in 32.5% of rules. (4) Conclusions: In summary, we demonstrate evidence that specific combinations of MS risk variants disproportionately confer elevated risk by applying a robust analytical framework to a modestly sized study population.

KIF5A and the contribution of susceptibility genotypes as a predictive biomarker for multiple sclerosis

There is increasing interest in the development of multiple sclerosis (MS) biomarkers that reflect central nervous system tissue injury to determine prognosis. We aimed to assess the prognostic value of kinesin superfamily motor protein KIF5A in MS by measuring levels of KIF5A in cerebrospinal fluid (CSF) combined with analysis of single nucleotide polymorphisms (SNPs; rs12368653 and rs703842) located within a MS susceptibility gene locus at chromosome 12q13-14 region. Enzyme-linked immunosorbent assay was used to measure KIF5A in CSF obtained from two independent biobanks comprising non-inflammatory neurological disease controls (NINDC), clinically isolated syndrome (CIS) and MS cases. CSF KIF5A expression was significantly elevated in progressive MS cases compared with NINDCs, CIS and relapsing-remitting MS (RRMS). In addition, levels of KIF5A positively correlated with change in MS disease severity scores (EDSS, MSSS and ARMSSS), in RRMS patients who had documented disease progression at 2-year clinical follow-up. Copies of adenine risk alleles (AG/AA; rs12368653 and rs703842) corresponded with a higher proportion of individuals in relapse at the time of lumbar puncture (LP), higher use of disease-modifying therapies post LP and shorter MS duration. Our study suggests that CSF KIF5A has potential as a predictive biomarker in MS and further studies into the potential prognostic value of analysing MS susceptibility SNPs should be considered.

The role of Epstein-Barr virus in the etiology of multiple sclerosis: a current review

Introduction: Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of the central nervous system. While its exact etiology is unknown, it is generally believed that MS is caused by environmental triggers in genetically predisposed individuals. Strong and consistent evidence suggests a key role of Epstein-Barr virus (EBV), a B lymphotropic human gammaherpesvirus, in the etiology of MS. Areas covered: This review summarizes recent developments in the field of EBV and MS with a focus on potential mechanisms underlying the role of EBV in MS. PubMed was searched for the terms 'Epstein-Barr virus' and 'multiple sclerosis'. Expert opinion: The current evidence is compatible with the working hypothesis that MS is a rare complication of EBV infection. Under the premise of a causative role of EBV in MS, it needs to be postulated that EBV causes a specific, and likely persistent, change(s) that is necessarily required for the development of MS. However, although progress has been made, the nature of that change and thus the precise mechanism explaining the role of EBV in MS remain elusive. The mechanism of EBV in MS therefore is a pressing question, whose clarification may substantially advance the pathophysiological understanding, rational therapies, and prevention of MS.

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.

The association of genetic variants IL2RA rs2104286, IFI30 rs11554159 and IKZF3 rs12946510 with multiple sclerosis onset and severity in patients from Serbia

An algorithm Probabilistic Identification of Causal SNPs, identified 434 causal variants for multiple sclerosis (MS) including IL2RA rs2104286, IFI30 rs11554159 and IKZF3 rs12946510. Analysis of individual and combined effects of these variants in the Serbian population identified that Il2RA rs2104286 G allele carriers had a lower risk for developing MS (gender adjusted OR = 0.63, p = .003). With regard to the IFI30 rs11554159 recessive genetic model, among HLA-DRB1*15:01 positive patients, the AA homozygote had a significantly higher MSSS compared to the G allele carriers (p = .003). This study confirms role of IL2RA rs2104286 in MS and suggest the role of IFI30 rs11554159 in disease severity, which needs validation.

Summary-data-based Mendelian randomization prioritizes potential druggable targets for multiple sclerosis

Multiple sclerosis is a complex autoimmune disease caused by a combination of genetic and environmental factors. Translation of Genome-Wide Association Study findings into therapeutics and effective preventive strategies has been limited to date. We used summary-data-based Mendelian randomization to synthesize findings from public expression quantitative trait locus, methylation quantitative trait locus and Multiple Sclerosis Genome-Wide Association Study datasets. By correlating the effects of methylation on multiple sclerosis, methylation on expression and expression on multiple sclerosis susceptibility, we prioritize genetic loci with evidence of influencing multiple sclerosis susceptibility. We overlay these findings onto a list of 'druggable' genes, i.e. genes which are currently, or could theoretically, be targeted by therapeutic compounds. We use GeNets and search tool for the retrieval of interacting genes/proteins to identify protein-protein interactions and druggable pathways enriched in our results. We extend these findings to a model of Epstein-Barr virus-infected B cells, lymphoblastoid cell lines. We conducted a systematic review of prioritized genes using the Open Targets platform to identify completed and planned trials targeting prioritized genes in multiple sclerosis and related disease areas. Expression of 45 genes in peripheral blood was strongly associated with multiple sclerosis susceptibility (False discovery rate 0.05). Of these 45 genes, 20 encode a protein which is currently targeted by an existing therapeutic compound. These genes were enriched for Gene Ontology terms pertaining to immune system function and leucocyte signalling. We refined this prioritized gene list by restricting to loci where CpG site methylation was associated with multiple sclerosis susceptibility, with gene expression and where expression was associated with multiple sclerosis susceptibility. This approach yielded a list of 15 prioritized druggable target genes for which there was evidence of a pathway linking methylation, expression and multiple sclerosis. Five of these 15 genes are targeted by existing drugs and three were replicated in a smaller expression Quantitative Trait Loci dataset (CD40, MERTK and PARP1). In lymphoblastoid cell lines, this approach prioritized 7 druggable gene targets, of which only one was prioritized by the multi-omic approach in peripheral blood (FCRL3). Systematic review of Open Targets revealed multiple early-phase trials targeting 13/20 prioritized genes in disorders related to multiple sclerosis. We use public datasets and summary-data-based Mendelian randomization to identify a list of prioritized druggable genetic targets in multiple sclerosis. We hope our findings could be translated into a platform for developing targeted preventive therapies.

CD8+ T cell gene expression analysis identifies differentially expressed genes between multiple sclerosis patients and healthy controls

BACKGROUND

Genetic and clinical observations have indicated T cells are involved in MS pathology. There is little insight in how T cells are involved and whether or not these can be used as markers for MS.

OBJECTIVES

Analysis of the gene expression profiles of circulating CD8+ T cells of MS patients compared to healthy controls.

METHODS

RNA from purified CD8+ T cells was sequenced and analyzed for differential gene expression. Pathway analyses of genes at several p-value cutoffs were performed to identify putative pathways involved.

RESULTS

We identified 36 genes with significant differential gene expression in MS patients. Four genes reached at least 2-fold differences in expression. The majority of differentially expressed genes was higher expressed in MS patients. Genes associated to MS in GWAS showed enrichment amongst the differentially expressed genes. We did not identify enrichment of specific pathways amongst the differentially expressed genes in MS patients.

CONCLUSIONS

CD8+ T cells of MS patients show differential gene expression, with predominantly higher activity of genes in MS patients. We do not identify specific biological pathways in our study. More detailed analysis of CD8+ T cells and subtypes of these may increase understanding of how T cells are involved in MS.

Ataxin-1 regulates B cell function and the severity of autoimmune experimental encephalomyelitis

Ataxin-1 (ATXN1) is a ubiquitous polyglutamine protein expressed primarily in the nucleus where it binds chromatin and functions as a transcriptional repressor. Mutant forms of ataxin-1 containing expanded glutamine stretches cause the movement disorder spinocerebellar ataxia type 1 (SCA1) through a toxic gain-of-function mechanism in the cerebellum. Conversely, ATXN1 loss-of-function is implicated in cancer development and Alzheimer's disease (AD) pathogenesis. ATXN1 was recently nominated as a susceptibility locus for multiple sclerosis (MS). Here, we show that Atxn1-null mice develop a more severe experimental autoimmune encephalomyelitis (EAE) course compared to wildtype mice. The aggravated phenotype is mediated by increased T helper type 1 (Th1) cell polarization, which in turn results from the dysregulation of B cell activity. Ataxin-1 ablation in B cells leads to aberrant expression of key costimulatory molecules involved in proinflammatory T cell differentiation, including cluster of differentiation (CD)44 and CD80. In addition, comprehensive phosphoflow cytometry and transcriptional profiling link the exaggerated proliferation of ataxin-1 deficient B cells to the activation of extracellular signal-regulated kinase (ERK) and signal transducer and activator of transcription (STAT) pathways. Lastly, selective deletion of the physiological binding partner capicua (CIC) demonstrates the importance of ATXN1 native interactions for correct B cell functioning. Altogether, we report a immunomodulatory role for ataxin-1 and provide a functional description of the ATXN1 locus genetic association with MS risk.

The Microbiome as a Therapeutic Target for Multiple Sclerosis: Can Genetically Engineered Probiotics Treat the Disease?

There is an increasing interest in the intestinal microbiota as a critical regulator of the development and function of the immune, nervous, and endocrine systems. Experimental work in animal models has provided the foundation for clinical studies to investigate associations between microbiota composition and function and human disease, including multiple sclerosis (MS). Initial work done using an animal model of brain inflammation, experimental autoimmune encephalomyelitis (EAE), suggests the existence of a microbiota-gut-brain axis connection in the context of MS, and microbiome sequence analyses reveal increases and decreases of microbial taxa in MS intestines. In this review, we discuss the impact of the intestinal microbiota on the immune system and the role of the microbiome-gut-brain axis in the neuroinflammatory disease MS. We also discuss experimental evidence supporting the hypothesis that modulating the intestinal microbiota through genetically modified probiotics may provide immunomodulatory and protective effects as a novel therapeutic approach to treat this devastating disease.

Epigenetic insights into multiple sclerosis disease progression

Multiple sclerosis (MS), a chronic inflammatory demyelinating and neurodegenerative disease of the central nervous system, is today a leading cause of unpredictable lifelong disability in young adults. The treatment of patients in progressive stages remains highly challenging, alluding to our limited understanding of the underlying pathological processes. In this review, we provide insights into the mechanisms underpinning MS progression from a perspective of epigenetics, that refers to stable and mitotically heritable, yet reversible, changes in the genome activity and gene expression. We first recapitulate findings from epigenetic studies examining the brain tissue of progressive MS patients, which support a contribution of DNA and histone modifications in impaired oligodendrocyte differentiation, defective myelination/remyelination and sustained neuro-axonal vulnerability. We next explore possibilities for identifying factors affecting progression using easily accessible tissues such as blood by comparing epigenetic signatures in peripheral immune cells and brain tissue. Despite minor overlap at individual methylation sites, nearly 30% of altered genes reported in peripheral immune cells of progressive MS patients were found in brain tissue, jointly converging on alterations of neuronal functions. We further speculate about the mechanisms underlying shared epigenetic patterns between blood and brain, which likely imply the influence of internal (genetic control) and/or external (e.g. smoking and ageing) factors imprinting a common signature in both compartments. Overall, we propose that epigenetics might shed light on clinically relevant mechanisms involved in disease progression and open new avenues for the treatment of progressive MS patients in the future.

Bacterial Peptidoglycan as a Driver of Chronic Brain Inflammation

Peptidoglycan (PGN) is a cell wall component of both Gram-positive and Gram-negative bacteria. Signature fragments of PGN are proinflammatory through engagement of pattern recognition receptors (PRR) on resident tissue cells and circulating leukocytes. Despite its abundance in the gut microbiota, there is limited recognition that PGN could contribute to chronic neuroinflammation. This review highlights current insights into the roles of PGN as a determinant of brain inflammation, notably in multiple sclerosis (MS) and its experimental autoimmune encephalomyelitis (EAE) models. Recent studies demonstrate PGN in blood of healthy adult humans. PGN amplifies autoimmune pathology via activation of innate immune cells. Novel uptake routes through (altered) gut mucosa by myeloid leukocyte subsets promote PGN transport to the brain.

Recent advances in network medicine: From disease mechanisms to new treatment strategies

Conventional reductionist approaches have guided most of our understanding in disease diagnostic and treatment. However, most diseases are not consequence of perturbations in a single protein or metabolite, but rather of the effect that these perturbations have in their cellular context. The emerging field of network medicine offers a set of tools to explore molecular networks and to retrieve insights about mechanisms of different diseases. The study of the protein interactome, the map of physical interactions among human proteins, revealed that disease proteins tend to interact with each other, linking diseases to well-defined interactome neighborhoods. These disease-associated neighborhoods have been defined as disease modules, and they can uncover the biological significance of genes identified by genetic studies, reveal molecular mechanisms that connect different phenotypes, and help identify new pharmacological strategies for disease treatment. Therefore, network medicine offers a framework in which the complexity of different aspects of multiple sclerosis can be explored in an integrative fashion, which can ultimately provide insights about disease mechanisms and treatment.

Reworking GWAS Data to Understand the Role of Nongenetic Factors in MS Etiopathogenesis

Genome-wide association studies have identified more than 200 multiple sclerosis (MS)-associated loci across the human genome over the last decade, suggesting complexity in the disease etiology. This complexity poses at least two challenges: the definition of an etiological model including the impact of nongenetic factors, and the clinical translation of genomic data that may be drivers for new druggable targets. We reviewed studies dealing with single genes of interest, to understand how MS-associated single nucleotide polymorphism (SNP) variants affect the expression and the function of those genes. We then surveyed studies on the bioinformatic reworking of genome-wide association studies (GWAS) data, with aggregate analyses of many GWAS loci, each contributing with a small effect to the overall disease predisposition. These investigations uncovered new information, especially when combined with nongenetic factors having possible roles in the disease etiology. In this context, the interactome approach, defined as “modules of genes whose products are known to physically interact with environmental or human factors with plausible relevance for MS pathogenesis”, will be reported in detail. For a future perspective, a polygenic risk score, defined as a cumulative risk derived from aggregating the contributions of many DNA variants associated with a complex trait, may be integrated with data on environmental factors affecting the disease risk or protection.

The Rare IL22RA2 Signal Peptide Coding Variant rs28385692 Decreases Secretion of IL-22BP Isoform-1, -2 and -3 and Is Associated with Risk for Multiple Sclerosis

The IL22RA2 locus is associated with risk for multiple sclerosis (MS) but causative variants are yet to be determined. In a single nucleotide polymorphism (SNP) screen of this locus in a Basque population, rs28385692, a rare coding variant substituting Leu for Pro at position 16 emerged significantly (p = 0.02). This variant is located in the signal peptide (SP) shared by the three secreted protein isoforms produced by IL22RA2 (IL-22 binding protein-1(IL-22BPi1), IL-22BPi2 and IL-22BPi3). Genotyping was extended to a Europe-wide case-control dataset and yielded high significance in the full dataset (p = 3.17 × 10^-4). Importantly, logistic regression analyses conditioning on the main known MS-associated SNP at this locus, rs17066096, revealed that this association was independent from the primary association signal in the full case-control dataset. In silico analysis predicted both disruption of the alpha helix of the H-region of the SP and decreased hydrophobicity of this region, ultimately affecting the SP cleavage site. We tested the effect of the p.Leu16Pro variant on the secretion of IL-22BPi1, IL-22BPi2 and IL-22BPi3 and observed that the Pro16 risk allele significantly lowers secretion levels of each of the isoforms to around 50%-60% in comparison to the Leu16 reference allele. Thus, our study suggests that genetically coded decreased levels of IL-22BP isoforms are associated with augmented risk for MS.

Integrative Analyses of Genes Associated With Osteoporosis in CD16+ Monocyte

BACKGROUND

Osteoporosis is a metabolic bone disease characterized by decreased bone mineral density and abnormal bone quality. Monocytes can secret cytokines for bone resorption, resulting in bone mass loss. However, the mechanism by which monocytes subpopulations lead to osteoporosis remains unclear. The aim of this study was to identify genes associated with osteoporosis in monocytes subsets.

METHODS

Three microarray datasets including GSE7158 (transcription of low/high-peak bone mass), GSE101489 (transcription of CD16+/CD16- monocyte) and GSE93883 (miRNA expression profile of primary osteoporosis) were derived from the Gene Expression Omnibus (GEO) database and analyzed with GEO2R tool to identify differentially expressed genes (DEGs). Functional enrichment was analyzed using Metascape database and GSEA software. STRING was utilized for the Protein-Protein Interaction Network construct. The hub genes were screened out using the Cytoscape software. Related miRNAs were predicted in miRWalk, miRDB, and TargetScan databases.

RESULTS

Total 368 DEGs from GSE7158 were screened out, which were mostly enriched in signaling, positive regulation of biological process and immune system process. The hub genes were clustered into two modules by PPI network analysis. We identified 15 overlapping DGEs between GSE101489 and GSE7158 microarray datasets. Moreover, all of them were up-regulated genes in both datasets. Then, nine key genes were screened out from above 15 overlapping DEGs using Cytoscape software. It is a remarkable fact that the nine genes were all in one hub gene module of GSE7158. Additionally, 183 target miRNAs were predicted according to the above nine DEGs. After cross-verification with miRNA express profile dataset for osteoporosis (GSE93883), 12 DEmiRNAs were selected. Finally, a miRNA-mRNA network was constructed with the nine key genes and 12 miRNAs, which were involved in osteoporosis.

CONCLUSION

Our analysis results constructed a gene expression framework in monocyte subsets for osteoporosis. This approach could provide a novel insight into osteoporosis.

Gene Therapy Approaches in an Autoimmune Demyelinating Disease: Multiple Sclerosis

Multiple Sclerosis (MS) is the most common autoimmune demyelinating disease of the Central Nervous System (CNS). It is a multifactorial disease which develops in an immune-mediated way under the influences of both genetic and environmental factors. Demyelination is observed in the brain and spinal cord leading to neuro-axonal damage in patients with MS. Due to the infiltration of different immune cells such as T-cells, B-cells, monocytes and macrophages, focal lesions are observed in MS. Currently available medications treating MS are mainly based on two strategies; i) to ease specific symptoms or ii) to reduce disease progression. However, these medications tend to induce different adverse effects with limited therapeutic efficacy due to the protective function of the blood-brain barrier. Therefore, researchers have been working for the last four decades to discover better solutions by introducing gene therapy approaches in treating MS generally by following three strategies, i) prevention of specific symptoms, ii) halt or reverse disease progression and iii) heal CNS damage by promoting remyelination and axonal repair. In last two decades, there have been some remarkable successes of gene therapy approaches on the experimental mice model of MS - experimental autoimmune encephalomyelitis (EAE) which suggests that it is not far that the gene therapy approaches would start in human subjects ensuring the highest levels of safety and efficacy. In this review, we summarised the gene therapy approaches attempted in different animal models towards treating MS.

Intrathecal, Not Systemic Inflammation Is Correlated With Multiple Sclerosis Severity, Especially in Progressive Multiple Sclerosis

Objective: To test the hypothesis that Multiple Sclerosis (MS) patients have increased peripheral inflammation compared to healthy donors and that this systemic activation of the immune system, reflected by acute phase reactants (APRs) measured in the blood, contributes to intrathecal inflammation, which in turn contributes to the development of disability in MS. Methods: Eight serum APRs measured in a prospectively-collected cross-sectional cohort with a total of 51 healthy donors and 291 untreated MS patients were standardized and assembled into related biomarker clusters to derive global measures of systemic inflammation. The resulting APR clusters were compared between diagnostic categories and correlated to equivalently-derived cerebrospinal fluid (CSF) biomarkers of innate and adaptive immunity. Finally, correlations were calculated between biomarkers of systemic and intrathecal inflammation and MS severity measures, which predict future rates of disability progression. Results: While two blood APR clusters were elevated in MS patients, only one exhibited a weak correlation with MS severity. All CSF inflammation clusters, except CSF albumin, correlated with at least one measure of MS severity, with biomarkers of humoral adaptive immunity exhibiting the strongest correlations, especially in Progressive MS. Conclusion: Systemic inflammation does not appear to be strongly associated with intrathecal inflammation in MS. Positive correlations between markers of intrathecal inflammation, especially of humoral immunity, with MS severity measures support a pathogenic role of intrathecal (compartmentalized) inflammation in central nervous system tissue destruction, including in Progressive MS.

Large-Scale "OMICS" Studies to Explore the Physiopatholgy of HIV-1 Infection

In this review, we present the main large-scale experimental studies that have been performed in the HIV/AIDS field. These “omics” studies are based on several technologies including genotyping, RNA interference, and transcriptome or epigenome analysis. Due to the direct connection with disease evolution, there has been a large focus on genotyping cohorts of well-characterized patients through genome-wide association studies (GWASs), but there have also been several invitro studies such as small interfering RNA (siRNA) interference or transcriptome analyses of HIV-1–infected cells. After describing the major results obtained with these omics technologies—including some with a high relevance for HIV-1 treatment—we discuss the next steps that the community needs to embrace in order to derive new actionable therapeutic or diagnostic targets. Only integrative approaches that combine all big data results and consider their complex interactions will allow us to capture the global picture of HIV molecular pathogenesis. This novel challenge will require large collaborative efforts and represents a huge open field for innovative bioinformatics approaches.