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      Type I interferon signature and cycling lymphocytes in macrophage activation syndrome

      research-article
      1 , 2 , 1 , 1 , 1 , 3 , 1 , 1 , 1 , 2 , 1 , 1 , 1 , 1 , 1 , 1 , 4 , 2 , 1 , 5 , 1 , 6 , 7 , 1 , 1 , 1 , 3 , 8 , 9 , 10 , 1 , 1 , 10 , 1 ,
      The Journal of Clinical Investigation
      American Society for Clinical Investigation
      Immunology, Inflammation, Cytokines

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          Abstract

          BACKGROUND

          Macrophage activation syndrome (MAS) is a life-threatening complication of Still’s disease (SD) characterized by overt immune cell activation and cytokine storm. We aimed to further understand the immunologic landscape of SD and MAS.

          METHOD

          We profiled PBMCs from people in a healthy control group and patients with SD with or without MAS using bulk RNA-Seq and single-cell RNA-Seq (scRNA-Seq). We validated and expanded the findings by mass cytometry, flow cytometry, and in vitro studies.

          RESULTS

          Bulk RNA-Seq of PBMCs from patients with SD-associated MAS revealed strong expression of genes associated with type I interferon (IFN-I) signaling and cell proliferation, in addition to the expected IFN-γ signal, compared with people in the healthy control group and patients with SD without MAS. scRNA-Seq analysis of more than 65,000 total PBMCs confirmed IFN-I and IFN-γ signatures and localized the cell proliferation signature to cycling CD38 +HLA-DR + cells within CD4 + T cell, CD8 + T cell, and NK cell populations. CD38 +HLA-DR + lymphocytes exhibited prominent IFN-γ production, glycolysis, and mTOR signaling. Cell-cell interaction modeling suggested a network linking CD38 +HLA-DR + lymphocytes with monocytes through IFN-γ signaling. Notably, the expansion of CD38 +HLA-DR + lymphocytes in MAS was greater than in other systemic inflammatory conditions in children. In vitro stimulation of PBMCs demonstrated that IFN-I and IL-15 — both elevated in MAS patients — synergistically augmented the generation of CD38 +HLA-DR + lymphocytes, while Janus kinase inhibition mitigated this response.

          CONCLUSION

          MAS associated with SD is characterized by overproduction of IFN-I, which may act in synergy with IL-15 to generate CD38 +HLA-DR + cycling lymphocytes that produce IFN-γ.

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          Most cited references66

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          Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

          Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.
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            The Molecular Signatures Database (MSigDB) hallmark gene set collection.

            The Molecular Signatures Database (MSigDB) is one of the most widely used and comprehensive databases of gene sets for performing gene set enrichment analysis. Since its creation, MSigDB has grown beyond its roots in metabolic disease and cancer to include >10,000 gene sets. These better represent a wider range of biological processes and diseases, but the utility of the database is reduced by increased redundancy across, and heterogeneity within, gene sets. To address this challenge, here we use a combination of automated approaches and expert curation to develop a collection of "hallmark" gene sets as part of MSigDB. Each hallmark in this collection consists of a "refined" gene set, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression. The hallmarks effectively summarize most of the relevant information of the original founder sets and, by reducing both variation and redundancy, provide more refined and concise inputs for gene set enrichment analysis.
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              Integrated analysis of multimodal single-cell data

              Summary The simultaneous measurement of multiple modalities represents an exciting frontier for single-cell genomics and necessitates computational methods that can define cellular states based on multimodal data. Here, we introduce “weighted-nearest neighbor” analysis, an unsupervised framework to learn the relative utility of each data type in each cell, enabling an integrative analysis of multiple modalities. We apply our procedure to a CITE-seq dataset of 211,000 human peripheral blood mononuclear cells (PBMCs) with panels extending to 228 antibodies to construct a multimodal reference atlas of the circulating immune system. Multimodal analysis substantially improves our ability to resolve cell states, allowing us to identify and validate previously unreported lymphoid subpopulations. Moreover, we demonstrate how to leverage this reference to rapidly map new datasets and to interpret immune responses to vaccination and coronavirus disease 2019 (COVID-19). Our approach represents a broadly applicable strategy to analyze single-cell multimodal datasets and to look beyond the transcriptome toward a unified and multimodal definition of cellular identity.
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                Author and article information

                Contributors
                Journal
                J Clin Invest
                J Clin Invest
                J Clin Invest
                The Journal of Clinical Investigation
                American Society for Clinical Investigation
                0021-9738
                1558-8238
                15 November 2023
                15 November 2023
                15 November 2023
                : 133
                : 22
                : e165616
                Affiliations
                [1 ]Division of Immunology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, USA.
                [2 ]Department of Rheumatology and Immunology, Guangdong Second Provincial General Hospital, Southern Medical University, Guangzhou, China.
                [3 ]Department of Rheumatology, The Second Affiliated Hospital of Zhejiang University School of Medicine, Hangzhou, China.
                [4 ]Center for Data Sciences, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts, USA.
                [5 ]Department of Rheumatology, Immunology and Allergy, Zhejiang University School of Medicine, Hangzhou, China.
                [6 ]Department of Cardiology, Department of Pediatrics, and
                [7 ]Department of Anesthesiology, Critical Care, and Pain Medicine, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts, USA.
                [8 ]The MOE Key Laboratory of Biosystems Homeostasis and Protection, Life Sciences Institute, Zhejiang University, Hangzhou, China.
                [9 ]Division of Rheumatology, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USA.
                [10 ] Division of Rheumatology, Inflammation, and Immunity, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA.
                Author notes
                Address correspondence to: Pui Y. Lee, Boston Children’s Hospital, 1 Blackfan Circle, Karp RB10th floor, Boston, Massachusetts 02115, USA. Phone: 1.617.355.6117; Email: pui.lee@ 123456childrens.harvard.edu .

                Authorship note: ZH, KEB, LC, and YD contributed equally to this work.

                Author information
                http://orcid.org/0000-0002-2955-7385
                http://orcid.org/0000-0001-9931-4197
                http://orcid.org/0000-0001-8978-3184
                http://orcid.org/0009-0009-8750-1679
                http://orcid.org/0000-0002-1691-4814
                http://orcid.org/0000-0002-3545-8957
                http://orcid.org/0000-0002-4610-2657
                http://orcid.org/0000-0002-7516-0848
                http://orcid.org/0000-0002-3117-173X
                http://orcid.org/0000-0002-6445-252X
                http://orcid.org/0000-0003-2328-3536
                http://orcid.org/0000-0002-7794-9017
                http://orcid.org/0000-0002-3084-3071
                http://orcid.org/0000-0002-0083-5695
                http://orcid.org/0000-0002-5761-7365
                http://orcid.org/0000-0003-3837-5337
                http://orcid.org/0000-0002-1821-167X
                http://orcid.org/0000-0003-0242-4029
                http://orcid.org/0000-0002-2126-3702
                http://orcid.org/0000-0002-5779-4193
                Article
                165616
                10.1172/JCI165616
                10645381
                37751296
                a086df12-b504-47af-8e76-8955f4f279bf
                © 2023 Huang et al.

                This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 22 September 2022
                : 19 September 2023
                Funding
                Funded by: National Institute of Arthritis and Musculoskeletal and Skin Diseases, https://doi.org/10.13039/100000069;
                Award ID: P30-AR070253
                Funded by: Charles H. Hood Foundation, https://doi.org/10.13039/100001680;
                Award ID: Child Health Research Award
                Funded by: Arthritis National Research Foundation, https://doi.org/10.13039/100000964;
                Award ID: All Arthritis Grant
                Funded by: Rheumatology Research Foundation, https://doi.org/10.13039/100006260;
                Award ID: K Supplement Award
                Categories
                Clinical Medicine

                immunology,inflammation,cytokines
                immunology, inflammation, cytokines

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