25 research outputs found

    Achieving sustained minimal disease activity with methotrexate in early interleukin 23-driven early psoriatic arthritis

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    OBJECTIVES: Methotrexate (MTX) is currently the recommended first-line therapy for treating psoriatic arthritis (PsA), despite lacking clear evidence. No estimates of efficacy of MTX in usual care and no clear MTX responsive clinical or laboratory variables are currently available. This study describes the response to MTX monotherapy in newly diagnosed patients with PsA in usual care. Second, we compared clinical variables and cytokine profiles in patients responding and not responding to MTX monotherapy. METHODS: We used data collected in the Dutch southwest Early Psoriatic Arthritis cohoRt study to select patients with PsA with oligoarthritis or polyarthritis, and at least 1 year follow-up. We analysed disease activity at 6 months of patients who started MTX monotherapy and still used MTX monotherapy 1 year after diagnosis. Cytokine profiles were determined at baseline and after 3 and 6 months with a bead-based multi-immunoassay. RESULTS: We identified 219 patients of which 183 (84%) patients started MTX monotherapy within 6 months after diagnosis. 90 patients used MTX monotherapy throughout the first year of which 44 patients (24%) reached minimal disease activity(MDA) at 6 months, decreasing to 33 patients (18%) after 1 year. Non-responders had significantly higher concentrations of interleukin (IL) 23 and IL-10 before and during MTX therapy. CONCLUSIONS: Our results showed that only 18% of patients with PsA are in sustained MDA after 1 year of MTX monotherapy and non-responders more often had IL-23-driven disease. Our results indicate the need for more treat-to-target and personalised therapy strategies in PsA

    How to Prepare Spectral Flow Cytometry Datasets for High Dimensional Data Analysis: A Practical Workflow

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    Spectral flow cytometry is an upcoming technique that allows for extensive multicolor panels, enabling simultaneous investigation of a large number of cellular parameters in a single experiment. To fully explore the resulting high-dimensional single cell datasets, high-dimensional analysis is needed, as opposed to the common practice of manual gating in conventional flow cytometry. However, preparing spectral flow cytometry data for high-dimensional analysis can be challenging, because of several technical aspects. In this article, we will give insight into the pitfalls of handling spectral flow cytometry datasets. Moreover, we will describe a workflow to properly prepare spectral flow cytometry data for high dimensional analysis and tools for integrating new data at later time points. Using healthy control data as example, we will go through the concepts of quality control, data cleaning, transformation, correcting for batch effects, subsampling, clustering and data integration. This methods article provides an R-based pipeline based on previously published packages, that are readily available to use. Application of our workflow will aid spectral flow cytometry users to obtain valid and reproducible results

    Characterization of Histone Modifications Associated with Inactive X-Chromosome in Trophoblast Stem Cells, eXtra-Embryonic Endoderm Cells and in In Vitro Derived Undifferentiated and Differentiated Epiblast Like Stem Cells.

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    In mouse, X-chromosome inactivation (XCI) can either be imprinted or random. Imprinted XCI (iXCI) is considered unstable and depending on continuous Xist expression, whereas random XCI (rXCI) is stably maintained even in the absence of Xist. Here we have systematically examined epigenetic modifications associated with the inactive X-chromosome (Xi) in Trophoblast Stem cells, eXtra-Embryonic Endoderm Cells, undifferentiated and differentiated Epiblast Like Stem Cells in order to understand intrinsic differences in epigenetic mechanisms involved in silencing of the inactive X-chromosome in lineages presenting iXCI and rXCI. Whereas euchromatic histone modifications are predominantly lost from the Xi territory in all cell types, the accumulation of heterochromatic modifications diverges in between the analysed cell lineages. Particularly, only the Xi of multipotent Trophoblast (iXCI) and Epiblast stem cells (rXCI) display a visible accumulation of Polycomb Repressive Complexes (PRCs), in contrast to the Xi in differentiated Epiblast Like Stem Cells and eXtra-embryonic Endoderm cells. Despite this, the histone modifications catalysed by PRCs, ubH2AK119 and H3K27me3, remain the best heterochromatic markers for the Xi in all assessed lineages. Heterochromatic chromatin modifications associated with the Xi are a reflection of the epigenetic landscape of the entire genome of the assessed cell regardless whether XCI is imprinted or random

    Single-cell rna sequencing reveals heterogeneity and functional diversity of lymphatic endothelial cells

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    Lymphatic endothelial cells (LECs) line the lymphatic vasculature and play a central role in the immune response. LECs have abilities to regulate immune transport, to promote immune cell survival, and to cross present antigens to dendritic cells. Single-cell RNA sequencing (scRNA) technology has accelerated new discoveries in the field of lymphatic vascular biology. This review will summarize these new findings in regard to embryonic development, LEC heterogeneity with associated functional diversity, and interactions with other cells. Depending on the organ, location in the lymphatic vascular tree, and micro-environmental conditions, LECs feature unique properties and tasks. Furthermore, adjacent stromal cells need the support of LECs for fulfilling their tasks in the immune response, such as immune cell transport and antigen presentation. Although aberrant lymphatic vasculature has been observed in a number of chronic inflammatory diseases, the knowledge on LEC heterogeneity and functional diversity in these diseases is limited. Combining scRNA sequencing data with imaging and more in-depth functional experiments will advance our knowledge of LECs in health and disease. Building the case, the LEC could be put forward as a new therapeutic target in chronic inflammatory diseases, counterweighting the current immune-cell focused therapies

    Characterizing memory T helper cells in patients with psoriasis, subclinical, or early psoriatic arthritis using a machine learning algorithm

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    Background: Psoriasis patients developing psoriatic arthritis (PsA) are thought to go through different phases. Understanding the underlying events in these phases is crucial to diagnose PsA early. Here, we have characterized the circulating memory T helper (Th) cells in psoriasis patients with or without arthralgia, psoriasis patients who developed PsA during follow-up (subclinical PsA), early PsA patients and healthy controls to elucidate their role in PsA development. Methods: We used peripheral blood mononuclear cells of sex and age-matched psoriasis patients included in Rotterdam Joint Skin study (n=22), early PsA patients included in Dutch South West Early Psoriatic Arthritis Cohort (DEPAR) (n=23) and healthy controls (HC; n=17). We profiled memory Th cell subsets with flow cytometry and used the machine learning algorithm FlowSOM to interpret the data. Results: Three of the 22 psoriasis patients developed PsA during 2-year follow-up. FlowSOM identified 12 clusters of memory Th cells, including Th1, Th2, Th17/22, and Th17.1 cells. All psoriasis and PsA patients had higher numbers of Th17/22 than healthy controls. Psoriasis patients without arthralgia had lower numbers of CCR6-CCR4+CXCR3+ memory Th cells and higher numbers of CCR6+CCR4-CXCR3-memory Th cells compared to HC. PsA patients had higher numbers of Th2 cells and CCR6+CCR4+CXCR3- cells, but lower numbers of CCR6+CCR4+CXCR3+ memory Th cells compared to HC. The number of CCR6+ Th17.1 cells negatively correlated with tender joint counts and the number of CCR6+ Th17 cells positively correlated with skin disease severity. Conclusions: Unsupervised clustering analysis revealed differences in circulating memory Th cells between psoriasis and PsA patients compared to HC; however, no specific subset was identified characterizing subclinical PsA patients

    The heterogeneous human memory CCR6+ T helper-17 populations differ in T-bet and cytokine expression but all activate synovial fibroblasts in an IFNγ-independent manner

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    Background: Chronic synovial inflammation is an important hallmark of inflammatory arthritis, but the cells and mechanisms involved are incompletely understood. Previously, we have shown that CCR6+ memory T-helper (memTh) cells and synovial fibroblasts (SF) activate each other in a pro-inflammatory feedforward loop, which potentially drives persistent synovial inflammation in inflammatory arthritis. However, the CCR6+ memTh cells are a heterogeneous population, containing Th17/Th22 and Th17.1 cells. Currently, it is unclear which of these subpopulations drive SF activation and how they should be targeted. In this study, we examined the individual contribution of these CCR6+ memTh subpopulations to SF activation and examined ways to regulate their function. Methods: Th17/Th22 (CXCR3−CCR4+), Th17.1 (CXCR3+CCR4−), DP (CXCR3+CCR4+), and DN (CXCR3−CCR4−) CCR6+ memTh, cells sorted from PBMC of healthy donors or treatment-naïve early rheumatoid arthritis (RA) patients, were cocultured with SF from RA patients with or without anti-IL17A, anti-IFNγ, or 1,25(OH)2D3. Cultures were analyzed by RT-PCR, ELISA, or flow cytometry. Results: Th17/Th22, Th17.1, DP, and DN cells equally express RORC but differ in production of TBX21 and cytokines like IL-17A and IFNγ. Despite these differences, all the individual CCR6+ memTh subpopulations, both from healthy individuals and RA patients, were more potent in activating SF than the classical Th1 cells. SF activation was partially inhibited by blocking IL-17A, but not by inhibiting IFNγ or TBX21. However, active vitamin D inhibited the pathogenicity of all subpopulations leading to suppression of SF activation. Conclusions: Human CCR6+ memTh cells contain several subpopulations that equally express RORC but differ in TBX21, IFNγ, and IL-17A expression. All individual Th17 subpopulations are more potent in activating SF than classical Th1 cells in an IFNγ-independent manner. Furthermore, our data suggest that IL-17A is not dominant in this T cell-SF activation loop but that a multiple T cell cytokine inhibitor, such as 1,25(OH)2D3, is able to suppress CCR6+ memTh subpopulation-driven SF activation

    Immuno-RNA FISH for EZH2 or H3K27me3 and <i>Xist</i> in TS cells and XEN cells.

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    <p>Immuno-RNA FISH detecting EZH2 or H3K27me3 (Rhodamine red) together with <i>Xist</i> (FITC) on TS cells and XEN cells.</p

    Immuno-RNA FISH for H4K20me1 and <i>Xist</i> in XEN cells, TS cells, EpiLCs and differentiating EpiLCs.

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    <p>Immuno-RNA FISH detecting H4K20me1 (Rhodamine red) together with <i>Xist</i> (FITC) on TS cells, XEN cells, EpiLCs and differentiated EpiLCs.</p

    Overview of Xi associated heterochromatic marks in TS cells, XEN cells, EpiLCs and differentiated EpiLCs.

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    <p>Comprehensive overview of accumulation of RING1B, EZH2, SUZI12, JARID2, H4K20me1, H3K9me2, H3K27me3 and ubH2AK119 (categorized present if found in more than 10% of the cells).</p
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