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Aim: To investigate the transcriptional changes induced by Fingolimod (FTY) in T cells of relapsing remitting multiple sclerosis patients. Patients & methods: Transcriptomic changes after 6 months of FTY therapy were evaluated on T cells from 24 relapsing remitting multiple sclerosis patients through RNA-sequencing, followed by technical validation and pathway analysis. Results: Among differentially expressed genes, CX3CR1 and CCR7 resulted strongly up- and downregulated, respectively. Two relevant genes were validated with quantitative PCR and we largely confirmed findings from two previous microarray-based studies with similar design. Pathway analysis pointed to an involvement of processes related to immune function and cell migration. Conclusion: Our data support the evidence that FTY induces major transcriptional changes in genes involved in immune response and cell trafficking in T lymphocytes.

A personalized approach is strongly advocated for treatment selection in Multiple Sclerosis patients due to the high number of available drugs. Machine learning methods proved to be valuable tools in the context of precision medicine. In the present work, we applied machine learning methods to identify a combined clinical and genetic signature of response to fingolimod that could support the prediction of drug response. Two cohorts of fingolimod-treated patients from Italy and France were enrolled and divided into training, validation, and test set. Random forest training and robust feature selection were performed in the first two sets respectively, and the independent test set was used to evaluate model performance. A genetic-only model and a combined clinical–genetic model were obtained. Overall, 381 patients were classified according to the NEDA-3 criterion at 2 years; we identified a genetic model, including 123 SNPs, that was able to predict fingolimod response with an AUROC= 0.65 in the independent test set. When combining clinical data, the model accuracy increased to an AUROC= 0.71. Integrating clinical and genetic data by means of machine learning methods can help in the prediction of response to fingolimod, even though further studies are required to definitely extend this approach to clinical applications

While the role of common genetic variants in multiple sclerosis (MS) has been elucidated in large genome-wide association studies, the contribution of rare variants to the disease remains unclear. Herein, a whole-genome sequencing study in four affected and four healthy relatives of a consanguineous Italian family identified a novel missense c.1801T > C (p.S601P) variant in the GRAMD1B gene that is shared within MS cases and resides under a linkage peak (LOD: 2.194). Sequencing GRAMD1B in 91 familial MS cases revealed two additional rare missense and two splice-site variants, two of which (rs755488531 and rs769527838) were not found in 1000 Italian healthy controls. Functional studies demonstrated that GRAMD1B, a gene with unknown function in the central nervous system (CNS), is expressed by several cell types, including astrocytes, microglia and neurons as well as by peripheral monocytes and macrophages. Notably, GRAMD1B was downregulated in vessel-associated astrocytes of active MS lesions in autopsied brains and by inflammatory stimuli in peripheral monocytes, suggesting a possible role in the modulation of inflammatory response and disease pathophysiology.

Multiple sclerosis (MS) is a complex disease of the central nervous system for which human leukocyte antigen (HLA) alleles are major contributors to susceptibility. Several investigations have focused on the relationship between HLA and clinical parameters, while few studies have evaluated its correlation with brain magnetic resonance imaging (MRI) measures. We investigated the association between the HLA genetic burden (HLAGB), originating from the most updated HLA alleles associated with MS, and neuroimaging endophenotypes, with a specific focus on brain atrophy metrics. A monocentric Italian cohort of 334 MS patients with imputed HLA alleles and cross-sectional volumetric measures of white matter (WM), gray matter (GM), hippocampus, thalamus and T2-hyperintense lesions was investigated. Linear regression models with covariate adjustment were fitted for each metric. We detected no effect of HLAGB on WM and GM volumes. Interestingly, we found a marginal correlation between higher HLAGB and lower hippocampal volume (β = −0.142, p = 0.063) and a nominal association between higher HLAGB and lower thalamic volume (β = −0.299, p = 0.047). No association was found with T2 lesion volumes. The putative impact of higher HLAGB on hippocampus and thalamus suggests, if replicated in independent cohorts, a possible cumulative contribution of HLA risk loci on brain volumetric traits linked to clinical deficits in MS.

Fingolimod (FTY), a second-line oral drug approved for relapsing remitting Multiple Sclerosis (RRMS) acts in preventing lymphocyte migration outside lymph nodes; moreover, several lines of evidence suggest that it also inhibits myeloid cell activation. In this study, we investigated the transcriptional changes induced by FTY in monocytes in order to better elucidate its mechanism of action. CD14+ monocytes were collected from 24 RRMS patients sampled at baseline and after 6 months of treatment and RNA profiles were obtained through next-generation sequencing. We conducted pathway and sub-paths analysis, followed by centrality analysis of cell-specific interactomes on differentially expressed genes (DEGs). We investigated also the predictive role of baseline monocyte transcription profile in influencing the response to FTY therapy. We observed a marked down-regulation effect (60 down-regulated vs. 0 up-regulated genes). Most of the down-regulated DEGs resulted related with monocyte activation and migration like IL7R, CCR7 and the Wnt signaling mediators LEF1 and TCF7. The involvement of Wnt signaling was also confirmed by subpaths analyses. Furthermore, pathway and network analyses showed an involvement of processes related to immune function and cell migration. Baseline transcriptional profile of the HLA class II gene HLA-DQA1 and HLA-DPA1 were associated with evidence of disease activity after 2 years of treatment. Our data support the evidence that FTY induces major transcriptional changes in monocytes, mainly regarding genes involved in cell trafficking and immune cell activation. The baseline transcriptional levels of genes associated with antigen presenting function were associated with disease activity after 2 years of FTY treatment.

BACKGROUND AND PURPOSE Multiple sclerosis (MS) susceptibility is influenced by genetics; however, little is known about genetic determinants of disease expression. We aimed at assessing genetic factors influencing quantitative neuroimaging measures in two cohorts of progressive MS (PMS) and relapsing-remitting MS (RRMS) patients. METHODS Ninety-nine PMS and 214 RRMS patients underwent a 3-T brain magnetic resonance imaging (MRI) scan, with the measurement of five MRI metrics including T2 lesion volumes and measures of white matter, grey matter, deep grey matter, and hippocampal volumes. A candidate pathway strategy was adopted; gene set analysis was carried out to estimate cumulative contribution of genes to MRI phenotypes, adjusting for relevant confounders, followed by single nucleotide polymorphism (SNP) regression analysis. RESULTS Seventeen Kyoto Encyclopedia of Genes and Genomes pathways and 42 Gene Ontology (GO) terms were tested. We additionally included in the analysis genes with enriched expression in brain cells. Gene set analysis revealed a differential pattern of association across the two cohorts, with processes related to sodium homeostasis being associated with grey matter volume in PMS (p = 0.002), whereas inflammatory-related GO terms such as adaptive immune response and regulation of inflammatory response appeared to be associated with T2 lesion volume in RRMS (p = 0.004 and p = 0.008, respectively). As for SNPs, the rs7104613T mapping to SPON1 gene was associated with reduced deep grey matter volume (β = -0.731, p = 3.2*10-7 ) in PMS, whereas we found evidence of association between white matter volume and rs740948A mapping to SEMA3A gene (β = 22.04, p = 5.5*10-6 ) in RRMS. CONCLUSIONS Our data suggest a different pattern of associations between MRI metrics and functional processes across MS disease courses, suggesting different phenomena implicated in MS.

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.

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

Multiple sclerosis (MS) is an inflammatory neurodegenerative disorder of the central nervous system (CNS). The migration of immune cells into the CNS is essential for its development, and plasma membrane molecules play an important role in triggering and maintaining the inflammation. We previously identified ninjurin2, a plasma membrane protein encoded by NINJ2 gene, as involved in the occurrence of relapse under Interferon-β treatment in MS patients. The aim of the present study was to investigate the involvement of NINJ2 in inflammatory conditions and in the migration of monocytes through the blood–brain barrier (BBB). We observed that NINJ2 is downregulated in monocytes and in THP-1 cells after stimulation with the pro-inflammatory cytokine LPS, while in hCMEC/D3 cells, which represent a surrogate of the BBB, LPS stimulation increases its expression. We set up a transmigration assay using an hCMEC/D3 transwell-based model, finding a higher transmigration rate of monocytes from MS subjects compared to healthy controls (HCs) in the case of an activated hCMEC/D3 monolayer. Moreover, a positive correlation between NINJ2 expression in monocytes and monocyte migration rate was observed. Overall, our results suggest that ninjurin2 could be involved in the transmigration of immune cells into the CNS in pro-inflammatory conditions. Further experiments are needed to elucidate the exact molecular mechanisms.

Multiple Sclerosis (MS) is caused by a still unknown interplay between genetic and environmental factors. Epigenetics, including DNA methylation, represents a model for environmental factors to influence MS risk. Twenty-six affected and 26 unaffected relatives from 8 MS multiplex families were analysed in a multicentric Italian study using MeDIP-Seq, followed by technical validation and biological replication in two additional families of differentially methylated regions (DMRs) using SeqCap Epi Choice Enrichment kit (Roche®). Associations from MeDIP-Seq across families were combined with aggregation statistics, yielding 162 DMRs at FDR ≤ 0.1. Technical validation and biological replication led to 2 hypo-methylated regions, which point to NTM and BAI3 genes, and to 2 hyper-methylated regions in PIK3R1 and CAPN13. These 4 novel regions contain genes of potential interest that need to be tested in larger cohorts of patients.

We assembled and analyzed genetic data of 47,351 multiple sclerosis (MS) subjects and 68,284 control subjects and establish a reference map of the genetic architecture of MS that includes 200 autosomal susceptibility variants outside the major histocompatibility complex (MHC), one chromosome X variant, and 32 independent associations within the extended MHC. We used an ensemble of methods to prioritize up to 551 potentially associated MS susceptibility genes, that implicate multiple innate and adaptive pathways distributed across the cellular components of the immune system. Using expression profiles from purified human microglia, we do find enrichment for MS genes in these brain - resident immune cells. Thus, while MS is most likely initially triggered by perturbation of peripheral immune responses the functional responses of microglia and other brain cells are also altered and may have a role in targeting an autoimmune process to the central nervous system.One Sentence Summary:We report a detailed genetic and genomic map of multiple sclerosis, and describe the role of putatively affected genes in the peripheral immune system and brain resident microglia.

The aim of the study is the identification of genetic factors that influence the long-term response to interferon-β (IFNβ) (4-year follow-up). We performed a genome-wide association study in 337 IFNβ-treated Italian multiple sclerosis patients at the extreme of treatment response, and we meta-analyzed association effects, integrating results with pathway analysis, gene-expression profiling of IFNβ-stimulated peripheral blood mononuclear cells from 20 healthy controls (HC) and expression quantitative locus (eQTL) analyses. From meta-analysis, 43 markers were associated at P

Background: The genetic component of multiple sclerosis (MS) is now set to 200 autosomal common variants. However, it is unclear how genetic knowledge be clinically used in the differential diagnosis between MS and other inflammatory conditions like adult-onset postinfectious neurological syndromes (PINS). The aim of this study was to investigate whether PINS and MS have a shared genetic background using an updated polygenic risk scores. Methods: Eighty-eight PINS patients have been consecutively recruited between 1996 and 2016 at Mondino Foundation of Pavia, diagnosed according to clinical, MRI and CSF findings and followed-up for several years. Patients were typed using Illumina array, and genotypes imputed using the 1000 Genomes Project reference panel. A weighted genetic risk score (wGRS) has been calculated based on autosomal MS risk loci derived from large-scale studies, and an HLA genetic burden (HLAGB) was also calculated on loci associated to MS. Results: PINS occurred as an episode of myelitis in 44% of patients, encephalomyelitis in 44%, and encephalitis in remaining cases, with an involvement of peripheral nervous system in 41% of patients. Mean age of onset was 50.1 years, and female:male ratio was 1.4. Patients were followed-up for a mean of 7.2 years, and at last visit 55% had a low disability grade (mRS 0–1). Disease was monophasic in 67% of patients, relapsing in 18% and chronic-progressive in 15%. The wGRS of PINS cases was comparable to 370 healthy controls, while significantly lower compared to 907 bout-onset MS (BOMS) cases (wGRS= 20.9 vs 21.2; p