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      Dysregulated long non-coding RNA in Sjögren’s disease impacts both interferon and adaptive immune responses

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          Abstract

          Objective

          Sjögren’s disease (SjD) is an autoimmune disease characterised by inflammatory destruction of exocrine glands. Patients with autoantibodies to Ro/SSA (SjD Ro+) exhibit more severe disease. Long non-coding RNAs (lncRNAs) are a functionally diverse class of non-protein-coding RNAs whose role in autoimmune disease pathology has not been well characterised.

          Methods

          Whole blood RNA-sequencing (RNA-seq) was performed on SjD cases (n=23 Ro/SSA negative (SjD Ro−); n=27 Ro/SSA positive (SjD Ro+) and healthy controls (HCs; n=27). Bioinformatics and pathway analyses of differentially expressed (DE) transcripts (log 2 fold change ≥2 or ≤0.5; p adj<0.05) were used to predict lncRNA function. LINC01871 was characterised by RNA-seq analyses of HSB-2 cells with CRISPR-targeted LINC01871 deletion ( LINC01871 −/ ) and in vitro stimulation assays.

          Results

          Whole blood RNA-seq revealed autoantibody-specific transcription profiles and disproportionate downregulation of DE transcripts in SjD cases relative to HCs. Sixteen DE lncRNAs exhibited correlated expression with the interferon (IFN)-regulated gene, RSAD2, in SjD Ro+ (r≥0.65 or ≤−0.6); four antisense lncRNAs exhibited IFN-regulated expression in immune cell lines. LINC01871 was upregulated in all SjD cases. RNA-seq and pathway analyses of LINC01871 −/ cells implicated roles in cytotoxic function, differentiation and IFNγ induction. LINC01871 was induced by IFNγ in a myeloid cell line and regulated by calcineurin/NFAT pathway and T cell receptor (TCR) signalling in primary human T cells.

          Conclusion

          LINC01871 influences expression of many immune cell genes and growth factors, is IFNγ inducible, and regulated by calcineurin signalling and TCR ligand engagement. Altered LINC01871 expression may influence the dysregulated T cell inflammatory pathways implicated in SjD.

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          Most cited references77

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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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            Is Open Access

            The Gene Ontology Resource: 20 years and still GOing strong

            Abstract The Gene Ontology resource (GO; http://geneontology.org) provides structured, computable knowledge regarding the functions of genes and gene products. Founded in 1998, GO has become widely adopted in the life sciences, and its contents are under continual improvement, both in quantity and in quality. Here, we report the major developments of the GO resource during the past two years. Each monthly release of the GO resource is now packaged and given a unique identifier (DOI), enabling GO-based analyses on a specific release to be reproduced in the future. The molecular function ontology has been refactored to better represent the overall activities of gene products, with a focus on transcription regulator activities. Quality assurance efforts have been ramped up to address potentially out-of-date or inaccurate annotations. New evidence codes for high-throughput experiments now enable users to filter out annotations obtained from these sources. GO-CAM, a new framework for representing gene function that is more expressive than standard GO annotations, has been released, and users can now explore the growing repository of these models. We also provide the ‘GO ribbon’ widget for visualizing GO annotations to a gene; the widget can be easily embedded in any web page.
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              Classification criteria for Sjögren's syndrome: a revised version of the European criteria proposed by the American-European Consensus Group.

              C Vitali (2002)
              Classification criteria for Sjögren's syndrome (SS) were developed and validated between 1989 and 1996 by the European Study Group on Classification Criteria for SS, and broadly accepted. These have been re-examined by consensus group members, who have introduced some modifications, more clearly defined the rules for classifying patients with primary or secondary SS, and provided more precise exclusion criteria.
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                Author and article information

                Journal
                RMD Open
                RMD Open
                rmdopen
                rmdopen
                RMD Open
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                2056-5933
                2022
                30 November 2022
                : 8
                : 2
                : e002672
                Affiliations
                [1 ]departmentGenes and Human Disease Research Program , Oklahoma Medical Research Foundation , Oklahoma City, Oklahoma, USA
                [2 ]departmentArthritis and Clinical Immunology Research Program , Oklahoma Medical Research Foundation , Oklahoma City, Oklahoma, USA
                [3 ]departmentDepartment of Pathology , The University of Oklahoma Health Sciences Center , Oklahoma City, Oklahoma, USA
                [4 ]departmentDepartment of Oral and Maxillofacial Pathology , The University of Oklahoma College of Dentistry , Oklahoma City, Oklahoma, USA
                [5 ]departmentOral Diagnosis and Radiology Department , The University of Oklahoma College of Dentistry , Oklahoma City, Oklahoma, USA
                [6 ]departmentDepartment of Ophthalmology, Dean McGee Eye Institute , The University of Oklahoma Health Sciences Center , Oklahoma City, Oklahoma, USA
                [7 ]departmentDepartment of Medicine , University of Oklahoma Health Sciences Center , Oklahoma City, OK, USA
                [8 ]US Department of Veteran Affairs Medical Center , Oklahoma City, Oklahoma, USA
                [9 ]departmentCenter for Bioinformatics, Department of Public Health Sciences , Henry Ford Health System , Detroit, Michigan, USA
                Author notes
                [Correspondence to ] Dr Christopher J Lessard; chris-lessard@ 123456omrf.org
                Author information
                http://orcid.org/0000-0002-9574-7355
                http://orcid.org/0000-0002-1580-869X
                http://orcid.org/0000-0001-7744-2948
                http://orcid.org/0000-0003-2440-3843
                Article
                rmdopen-2022-002672
                10.1136/rmdopen-2022-002672
                9717416
                36456101
                4fb08a21-8ffd-468b-9b71-7f47d6b007fa
                © Author(s) (or their employer(s)) 2022. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.

                This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See:  http://creativecommons.org/licenses/by-nc/4.0/.

                History
                : 16 August 2022
                : 09 September 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100001298, Presbyterian Health Foundation;
                Funded by: FundRef http://dx.doi.org/10.13039/100003392, Sjögren’s Syndrome Foundation;
                Funded by: National Institutes of Health (NIH);
                Award ID: P20GM103456
                Award ID: P30AR073750
                Award ID: P50AR060804
                Award ID: R01AR065953
                Award ID: R01AR074310
                Award ID: R01HL113326
                Award ID: R21AR079089
                Award ID: R33AR076803
                Award ID: U54GM104938
                Award ID: UM1AI144292
                Categories
                Sjögren Syndrome
                1506
                Original research
                Custom metadata
                unlocked

                sjogren's syndrome,polymorphism, genetic,autoimmune diseases,autoimmunity,autoantibodies

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