508 research outputs found

    The molecular signature of therapeutic mesenchymal stem cells exposes the architecture of the hematopoietic stem cell niche synapse

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    BACKGROUND: The hematopoietic stem cells (HSCs) niche of the bone marrow is comprised of HSCs, osteoblasts, endothelial cells and a stromal component of non-hematopoietic multipotent cells of mesenchymal origin named "mesenchymal stem cells" (MSCs). RESULTS: Here we studied the global transcriptional profile of murine MSCs with immuno-therapeutic potential and compared it with that of 486 publicly available microarray datasets from 12 other mouse tissues or cell types. Principal component analysis and hierarchical clustering identified a unique pattern of gene expression capable of distinctively classifying MSCs from other tissues and cells. We then performed an analysis aimed to identify absolute and relative abundance of transcripts in all cell types. We found that the set of transcripts uniquely expressed by MSCs is enriched in transcription factors and components of the Wnt signaling pathway. The analysis of differentially expressed genes also identified a set of genes specifically involved in the HSC niche and is complemented by functional studies that confirm the findings. Interestingly, some of these genes play a role in the maintenance of HSCs in a quiescent state supporting their survival and preventing them from proliferating and differentiating. We also show that MSCs modulate T cell functions in vitro and, upon in vivo administration, ameliorate experimental autoimmune encephalomyelitis (EAE). CONCLUSION: Altogether, these findings provide novel and important insights on the mechanisms of T cell function regulation by MSCs and help to cement the rationale for their application in the treatment of autoimmune diseases

    Silent progression in disease activity-free relapsing multiple sclerosis.

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    ObjectiveRates of worsening and evolution to secondary progressive multiple sclerosis (MS) may be substantially lower in actively treated patients compared to natural history studies from the pretreatment era. Nonetheless, in our recently reported prospective cohort, more than half of patients with relapsing MS accumulated significant new disability by the 10th year of follow-up. Notably, "no evidence of disease activity" at 2 years did not predict long-term stability. Here, we determined to what extent clinical relapses and radiographic evidence of disease activity contribute to long-term disability accumulation.MethodsDisability progression was defined as an increase in Expanded Disability Status Scale (EDSS) of 1.5, 1.0, or 0.5 (or greater) from baseline EDSS = 0, 1.0-5.0, and 5.5 or higher, respectively, assessed from baseline to year 5 (±1 year) and sustained to year 10 (±1 year). Longitudinal analysis of relative brain volume loss used a linear mixed model with sex, age, disease duration, and HLA-DRB1*15:01 as covariates.ResultsRelapses were associated with a transient increase in disability over 1-year intervals (p = 0.012) but not with confirmed disability progression (p = 0.551). Relative brain volume declined at a greater rate among individuals with disability progression compared to those who remained stable (p < 0.05).InterpretationLong-term worsening is common in relapsing MS patients, is largely independent of relapse activity, and is associated with accelerated brain atrophy. We propose the term silent progression to describe the insidious disability that accrues in many patients who satisfy traditional criteria for relapsing-remitting MS. Ann Neurol 2019;85:653-666

    Genotype-Phenotype correlations in multiple sclerosis: HLA genes influence disease severity inferred by 1HMR spectroscopy and MRI measures

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    Genetic susceptibility to multiple sclerosis (MS) is associated with the human leukocyte antigen (HLA) DRB1*1501 allele. Here we show a clear association between DRB1*1501 carrier status and four domains of disease severity in an investigation of genotype-phenotype associations in 505 robust, clinically well characterized MS patients evaluated cross-sectionally: (i) a reduction in the N-acetyl-aspartate (NAA) concentration within normal appearing white matter (NAWM) via 1HMR spectroscopy (P = 0.025), (ii) an increase in the volume of white matter (WM) lesions utilizing conventional anatomical MRI techniques (1,127 mm3; P = 0.031), (iii) a reduction in normalized brain parenchymal volume (nBPV) (P = 0.023), and (iv) impairments in cognitive function as measured by the Paced Auditory Serial Addition Test (PASAT-3) performance (Mean Z Score: DRB1*1501+: 0.110 versus DRB1*1501-: 0.048; P = 0.004). In addition, DRB1*1501+ patients had significantly more women (74% versus 63%; P = 0.009) and a younger mean age at disease onset (32.4 years versus 34.3 years; P = 0.025). Our findings suggest that DRB1*1501 increases disease severity in MS by facilitating the development of more T2-foci, thereby increasing the potential for irreversible axonal compromise and subsequent neuronal degeneration, as suggested by the reduction of NAA concentrations in NAWM, ultimately leading to a decline in brain volume. These structural aberrations may explain the significant differences in cognitive performance observed between DRB1*1501 groups. The overall goal of a deep phenotypic approach to MS is to develop an array of meaningful biomarkers to monitor the course of the disease, predict future disease behaviour, determine when treatment is necessary, and perhaps to more effectively recommend an available therapeutic interventio

    Pathway and network-based analysis of genome-wide association studies in multiple sclerosis

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    Genome-wide association studies (GWAS) testing several hundred thousand SNPs have been performed in multiple sclerosis (MS) and other complex diseases. Typically, the number of markers in which the evidence for association exceeds the genome-wide significance threshold is very small, and markers that do not exceed this threshold are generally neglected. Classical statistical analysis of these datasets in MS revealed genes with known immunological functions. However, many of the markers showing modest association may represent false negatives. We hypothesize that certain combinations of genes flagged by these markers can be identified if they belong to a common biological pathway. Here we conduct a pathway-oriented analysis of two GWAS in MS that takes into account all SNPs with nominal evidence of association (P < 0.05). Gene-wise P-values were superimposed on a human protein interaction network and searches were conducted to identify sub-networks containing a higher proportion of genes associated with MS than expected by chance. These sub-networks, and others generated at random as a control, were categorized for membership of biological pathways. GWAS from eight other diseases were analyzed to assess the specificity of the pathways identified. In the MS datasets, we identified sub-networks of genes from several immunological pathways including cell adhesion, communication and signaling. Remarkably, neural pathways, namely axon-guidance and synaptic potentiation, were also over-represented in MS. In addition to the immunological pathways previously identified, we report here for the first time the potential involvement of neural pathways in MS susceptibilit

    Pathway and network-based analysis of genome-wide association studies in multiple sclerosis

    Get PDF
    Genome-wide association studies (GWAS) testing several hundred thousand SNPs have been performed in multiple sclerosis (MS) and other complex diseases. Typically, the number of markers in which the evidence for association exceeds the genome-wide significance threshold is very small, and markers that do not exceed this threshold are generally neglected. Classical statistical analysis of these datasets in MS revealed genes with known immunological functions. However, many of the markers showing modest association may represent false negatives. We hypothesize that certain combinations of genes flagged by these markers can be identified if they belong to a common biological pathway. Here we conduct a pathway-oriented analysis of two GWAS in MS that takes into account all SNPs with nominal evidence of association (P < 0.05). Gene-wise P-values were superimposed on a human protein interaction network and searches were conducted to identify sub-networks containing a higher proportion of genes associated with MS than expected by chance. These sub-networks, and others generated at random as a control, were categorized for membership of biological pathways. GWAS from eight other diseases were analyzed to assess the specificity of the pathways identified. In the MS datasets, we identified sub-networks of genes from several immunological pathways including cell adhesion, communication and signaling. Remarkably, neural pathways, namely axon-guidance and synaptic potentiation, were also over-represented in MS. In addition to the immunological pathways previously identified, we report here for the first time the potential involvement of neural pathways in MS susceptibility
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