• Shuting Yang, Chuqing Cao, Zhiguo Xie, and Zhiguang Zhou.
• Department of Metabolism & Endocrinology, The Second Xiangya Hospital, Central South University, Changsha 410008, China.
• Ann Transl Med. 2020 Mar 1; 8 (6): 295.

BackgroundType 1 diabetes is an autoimmune disease strongly related to genetic factors. Although studies on T1D susceptibility genes have achieved great progress, the molecular mechanism of T1D remains to be explained.MethodsTo explore the underlying mechanisms of T1D, bioinformatic analysis based on a microarray database was used to determine the key biomarkers of T1D as well as their biofunctions and interactions. The microarray database GSE55100 was downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were processed by packages in R Software. The database for Annotation, Visualization, and Integrated Discovery (DAVID, version 6.8) was used to conduct gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. The protein-protein interaction network was analyzed with the Search Tool for the Retrieval of Interacting Genes (STRING), and the module analysis was performed using Cytoscape.ResultsSeventy-eight DEGs and 13 hub genes were identified. The biofunctions and pathways of these DEGs were enriched in immune response, extracellular exosome, cytokine activity and antigen processing and presentation. Thirteen DEGs with MCODE score ≥2 were selected as hub genes including MMP9, ARG1, CAMP, CHI3L1, CRISP3, SLPI, LCN2, PGLYRP1, LTF, RETN, CEACAM1, CEACAM8 and MS4A3.ConclusionsThe identification and analyses of the DEGs and hub genes from database GSE55100 provide novel prospectives of the pathogenesis of T1D.2020 Annals of Translational Medicine. All rights reserved.

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