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Background:Pulmonary arterial hypertension with systemic sclerosis (SSc-PAH) is the main cause of death in patients with SSc. Early diagnosis and timely treatment are very important to reduce the mortality of patients with SSc-PAH1. At present, there are not many sensitive markers for the diagnosis of SSc-PAH. Therefore, it is necessary to mine more sensitive markers as more accurate and practical predictors, which is of great significance for the diagnosis and treatment of SSc-PAH.Objectives:To discover the differentially expressed genes (DEGs) and activated signaling pathways in SSc-PAH.Methods:Fifty-five samples (27 SSc-PAH v.s 28 normal controls) in GSE33463 chip data obtained from Gene Expression Omnibus (GEO) were included in this study. DEGs in SSc-PAH patients were screened by R, key pathways and hub genes were discoved by Metascape2, STRING3 and Cytoscape.Results:Total 431 genes with large differences were identified, including 238 up-regulated genes and 193 down-regulated genes, after standardizing the data (|logFC| > 1; P < 0.05). GO analysis showed that the upregulated genes were mainly involved in defense response to virus, hemoglobin complex, platelet alpha granule membrane and cytokine binding. The downregulated genes were mainly characterized by positive regulation of cell death, regulation of MAPK cascade, regulation of DNA-binding transcription factor activity and transcription factor AP-1 complex. Several significant enriched pathways obtained in the KEGG pathway analysis were Influenza A, Hepatitis C, IL-17 signaling pathway, MAPK signaling pathway, Toll-like receptor signaling pathway. Finally, after the selected differential genes were introduced into STRING online software, the data information of protein interaction network was derived, and 12 core genes in the network were identified, they were CXCL8, PPBP, LPAR1, FPR2, GNG11, CXCL10, LPAR5, JUN, C3AR1, CCR2, CCR3, IRF2.Conclusion:The genes and signal pathways related to SSc-PAH discovered by bioinformatics methods could not only provided new molecular markers for its diagnosis and treatment, but also provided new ideas for its related biological research.References:[1]Zheng JN, Li Y, Yan YM, et al. Identification and Validation of Key Genes Associated With Systemic Sclerosis-Related Pulmonary Hypertension. Front Genet 2020;11:816. doi: 10.3389/fgene.2020.00816 [published Online First: 2020/08/15].[2]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].[3]Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res 2019;47(D1):D607-D13. doi: 10.1093/nar/gky1131 [published Online First: 2018/11/27].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

Background:Dermatomyositis (DM) is a chronic systemic autoimmune disease characterized by inflammatory infiltrates in the skin and muscle1. The genes and pathways in the inflamed myopathies in patients with DM are poorly understood2.Objectives:To identify the key genes and pathways associated with DM and further discover its pathogenesis.Methods:Muscle tissue gene expression profile (GSE143323) were acquired from the GEO database, which included 39 DM samples and 20 normal samples. The differentially expressed genes (DEGs) in DM muscle tissue were screened by adopting the R software. Gene ontology (GO) and Kyoto Encyclopedia of Genome (KEGG) pathway enrichment analysis was performed by Metascape online analysis tool. A protein-protein interaction (PPI) network was then constructed by STRING software using the genes in significantly different pathways. Network of DEGs was analyzed by Cytoscape software. And degree of nodes was used to screen key genes.Results:Totally, 126 DEGs were obtained, which contained 122 up-regulated and 4 down-regulated. GO analysis revealed that most of the DEGs were significantly enriched in type I interferon signaling pathway, response to interferon-gamma, collagen-containing extracellular matrix, response to interferon-alpha and bacterium, positive regulation of cell death, leukocyte chemotaxis. KEGG pathway analysis showed that upregulated DEGs enhanced pathways associated with the hepatitis C, complement and coagulation cascades, p53 signaling pathway, RIG-I-like receptor signaling, Osteoclast differentiation, and AGE-RAGE signaling pathway. Ten hub genes were identified in DM, they were ISG15, IRF7, STAT1, MX1, OASL, OAS2, OAS1, OAS3, GBP1, and IRF9 according to the Cytoscape software and cytoHubba plugin.Conclusion:The findings from this bioinformatics network analysis study identified the key hub genes that might provide new molecular markers for its diagnosis and treatment.References:[1]Olazagasti JM, Niewold TB, Reed AM. Immunological biomarkers in dermatomyositis. Curr Rheumatol Rep 2015;17(11):68. doi: 10.1007/s11926-015-0543-y [published Online First: 2015/09/26].[2]Chen LY, Cui ZL, Hua FC, et al. Bioinformatics analysis of gene expression profiles of dermatomyositis. Mol Med Rep 2016;14(4):3785-90. doi: 10.3892/mmr.2016.5703 [published Online First: 2016/09/08].[3]Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 2019;10(1):1523. doi: 10.1038/s41467-019-09234-6 [published Online First: 2019/04/05].Acknowledgements:This project was supported by National Science Foundation of China (82001740), Open Fund from the Key Laboratory of Cellular Physiology (Shanxi Medical University) (KLCP2019) and Innovation Plan for Postgraduate Education in Shanxi Province (2020BY078).Disclosure of Interests:None declared

BackgroundAutoimmune diseases (AD) are a group of heterogeneous disorders caused by both genetic and environmental factors. Rheumatoid arthritis (RA) and Sjögrens syndrome (SS) are typical autoimmune diseases[1], Pulmonary fibrosis (PF) is the most common complication of AD. Despite the extensive study of the human gut microbiome in AD complicated with PF(AD-PF),the question of whether there are common microbial features characterizing AD-PF still remains[2].ObjectivesThis study focused on exploring differences between the microbiota diversity and peripheral lymphocyte subpopulations as well as cytokine in AD with PF is different from that of AD without PF.MethodsA total of 64 AD patients (44 AD without PF and 20 AD with PF) as well as 100 age- and sex- matched healthy controls (HCs) were enrolled in this study. The peripheral lymphocyte subsets were analyzed by flow cytometry and the gut microbiota were investigated via 16s rRNA sequencing. Alpha and Beta diversity (bray curtis distance-based) analysis was used to define the difference of gut microbiota profiles between patients and HCs. To explore the specific bacterial taxa associated with AD-PF, the STAMP software was used to compare the fecal microbiota composition. Spearman correlation analysis was used to determine the similarities in the microbiota community with clinical meatures among fecal samples.ResultsThere is a decrease that the richness and diversity index between HCs, AD and AD-PF patients. Principal co-ordinates analyses suggested that these three microbiota states explained a reasonable proportion of observed variance in gut microbiota composition (ANOSIM R2 = 0.113, p < 0.001; Figure 1b). Compared with HCs, there are obvious differences among 19 species of flora in AD without PF at the genus level, of which 2 species of flora (Lachnospira,Muribaculaceae) belong to AD-PF patients were showed much fewer. The relative abundance of Lachnospira was positive correlated with the absolute numbers of Th17, IL-6 and THF-α (P<0.05,Figure 1D-E)，which indicated Lachnospira may be the most critical among the AD-RF patients’ own species of flora. Therefore, the reduction of Lachnospira may influence the immune status of the intestinal tract of patients by producing less short-chain fatty acids.ConclusionOur results suggest that the decrease of Lachnospira may lead to the occurrence of AD with pulmonary interstitial fibrosis, which was closely correlated with lymphocyte subsets and Cytokines, maintaining the flora balance might be a potential therapeutic target for AD-PF.References[1]Ma Y, Shi N, Li M, Chen F, Niu H: Applications of Next-generation Sequencing in Systemic Autoimmune Diseases. Genomics Proteomics Bioinformatics 2015, 13(4):242-249.[2]Belkaid Y, Hand TW: Role of the microbiota in immunity and inflammation. Cell 2014, 157(1):121-141.AcknowledgementsThis work was supported by the National Natural Science Foundation of China (No. 82001740).Disclosure of InterestsNone declared