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      Autoimmunity in Down’s syndrome via cytokines, CD4 T cells and CD11c + B cells

      research-article
      1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 1 , 2 , 3 , 4 , 5 , 1 , 2 , 3 , 4 , 5 , 4 , 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 , 3 , 10 , 10 , 10 , 10 , 4 , 5 , 2 , 3 , 6 , 7 , 8 , 11 , 12 , 13 , 4 , 2 , 1 , 2 , 3 , 4 , 5 ,
      Nature
      Nature Publishing Group UK
      Autoimmunity, Chronic inflammation, Translational immunology, Immunogenetics, Immune tolerance

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          Abstract

          Down’s syndrome (DS) presents with a constellation of cardiac, neurocognitive and growth impairments. Individuals with DS are also prone to severe infections and autoimmunity including thyroiditis, type 1 diabetes, coeliac disease and alopecia areata 1, 2 . Here, to investigate the mechanisms underlying autoimmune susceptibility, we mapped the soluble and cellular immune landscape of individuals with DS. We found a persistent elevation of up to 22 cytokines at steady state (at levels often exceeding those in patients with acute infection) and detected basal cellular activation: chronic IL-6 signalling in CD4 T cells and a high proportion of plasmablasts and CD11c +Tbet highCD21 low B cells (Tbet is also known as TBX21). This subset is known to be autoimmune-prone and displayed even greater autoreactive features in DS including receptors with fewer non-reference nucleotides and higher IGHV4-34 utilization. In vitro, incubation of naive B cells in the plasma of individuals with DS or with IL-6-activated T cells resulted in increased plasmablast differentiation compared with control plasma or unstimulated T cells, respectively. Finally, we detected 365 auto-antibodies in the plasma of individuals with DS, which targeted the gastrointestinal tract, the pancreas, the thyroid, the central nervous system, and the immune system itself. Together, these data point to an autoimmunity-prone state in DS, in which a steady-state cytokinopathy, hyperactivated CD4 T cells and ongoing B cell activation all contribute to a breach in immune tolerance. Our findings also open therapeutic paths, as we demonstrate that T cell activation is resolved not only with broad immunosuppressants such as Jak inhibitors, but also with the more tailored approach of IL-6 inhibition.

          Abstract

          An autoimmune-prone state of steady-state cytokinopathy, hyperactivated CD4 T cells and ongoing B cell activation contributes to a breach in immune tolerance in individuals with Down’s syndrome.

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          Most cited references59

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          Is Open Access

          limma powers differential expression analyses for RNA-sequencing and microarray studies

          limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
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            Complex heatmaps reveal patterns and correlations in multidimensional genomic data.

            Parallel heatmaps with carefully designed annotation graphics are powerful for efficient visualization of patterns and relationships among high dimensional genomic data. Here we present the ComplexHeatmap package that provides rich functionalities for customizing heatmaps, arranging multiple parallel heatmaps and including user-defined annotation graphics. We demonstrate the power of ComplexHeatmap to easily reveal patterns and correlations among multiple sources of information with four real-world datasets.
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              FactoMineR: AnRPackage for Multivariate Analysis

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                Author and article information

                Contributors
                Dusan.Bogunovic@mssm.edu
                Journal
                Nature
                Nature
                Nature
                Nature Publishing Group UK (London )
                0028-0836
                1476-4687
                22 February 2023
                : 1-10
                Affiliations
                [1 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Center for Inborn Errors of Immunity, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                [2 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Department of Pediatrics, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                [3 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Mindich Child Health and Development Institute, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                [4 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Precision Immunology Institute, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                [5 ]GRID grid.59734.3c, ISNI 0000 0001 0670 2351, Department of Microbiology, , Icahn School of Medicine at Mount Sinai, ; New York, NY USA
                [6 ]GRID grid.412134.1, ISNI 0000 0004 0593 9113, Laboratory of Human Genetics of Infectious Diseases, , Necker Branch, INSERM U1163, Necker Hospital for Sick Children, ; Paris, France
                [7 ]GRID grid.10988.38, ISNI 0000 0001 2173 743X, University of Paris, Imagine Institute, ; Paris, France
                [8 ]GRID grid.134907.8, ISNI 0000 0001 2166 1519, St Giles Laboratory of Human Genetics of Infectious Diseases, Rockefeller Branch, , The Rockefeller University, ; New York, NY USA
                [9 ]GRID grid.50550.35, ISNI 0000 0001 2175 4109, Pediatric Hematology-Immunology and Rheumatology Unit, Necker Hospital for Sick Children, , Assistance Publique-Hôpitaux de Paris (AP-HP), ; Paris, France
                [10 ]GRID grid.453925.c, Institut Jérôme Lejeune, ; Paris, France
                [11 ]GRID grid.412134.1, ISNI 0000 0004 0593 9113, Department of Pediatrics, , Necker Hospital for Sick Children, ; Paris, France
                [12 ]GRID grid.413575.1, ISNI 0000 0001 2167 1581, Howard Hughes Medical Institute, ; New York, NY USA
                [13 ]GRID grid.94365.3d, ISNI 0000 0001 2297 5165, Laboratory of Clinical Immunology and Microbiology, National Institute of Allergy and Infectious Diseases, , National Institutes of Health, ; Bethesda, MD USA
                Author information
                http://orcid.org/0000-0003-4671-6349
                http://orcid.org/0000-0001-6071-760X
                http://orcid.org/0000-0002-1700-9162
                http://orcid.org/0000-0002-0256-2862
                http://orcid.org/0000-0001-5184-0390
                http://orcid.org/0000-0002-5899-7080
                http://orcid.org/0000-0002-5885-1276
                http://orcid.org/0000-0002-8335-0262
                http://orcid.org/0000-0001-5643-9520
                http://orcid.org/0000-0002-9277-3232
                Article
                5736
                10.1038/s41586-023-05736-y
                9945839
                36813963
                e0eb111d-67b4-4dac-b786-4ca50d21cd03
                © The Author(s), under exclusive licence to Springer Nature Limited 2023, Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

                This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.

                History
                : 16 December 2021
                : 17 January 2023
                Categories
                Article

                Uncategorized
                autoimmunity,chronic inflammation,translational immunology,immunogenetics,immune tolerance

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