Literature DB >> 35976509

Transcriptome analysis of peripheral blood mononuclear cells in patients with type 1 diabetes mellitus.

Zhaoxiang Wang1, Li Zhang2, Fengyan Tang2, Zhongming Yang1, Mengzhu Wang1, Jue Jia1, Dong Wang1, Ling Yang1, Shao Zhong3, Guoyue Yuan4.   

Abstract

PURPOSE: Type 1 diabetes mellitus (T1DM) is a chronic autoimmune disease characterized by the destruction of pancreatic β cells. The goal of this study was to explore potential biological biomarkers for T1DM.
METHODS: Two microarray datasets (GSE55098 and GSE156035) about human peripheral blood mononuclear cells (PBMCs) were systematically extracted from the Gene Expression Omnibus (GEO) database. Common genes were identified from the perspective of differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) respectively, and hub genes were identified by least absolute shrinkage and selection operator (LASSO) analysis. We also observed the expression of these hub genes in some common autoimmune diseases and predicted transcription factors (TFs) that might be associated with these genes.
RESULTS: Seven hub genes (DDIT4, ESCO2, SH3BP4, PRICKLE1, EPM2AIP1, KCNJ15 and GRM8) were finally identified. Receiver operating characteristic (ROC) analysis showed that the high expression of these genes could well predict the occurrence of T1DM. Gene set enrichment analysis (GSEA) suggested that most of these hub genes may be mainly involved in the changes of biological functions such as inflammation, infection, immunity, cancer, and apoptosis. Further, compared with the control group, the expression levels of these hub genes also changed in some other autoimmune diseases, such as rheumatoid arthritis (RA), systemic lupus erythematosus (SLE), primary biliary cholangitis (PBC), etc., indicating that they might be the common targets of these autoimmune diseases.
CONCLUSIONS: The present study identified novel genes associated with T1DM from the PBMCs perspective that might provide new ideas for the early diagnosis, monitoring, evaluation, and prediction of T1DM.
© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  Differentially expressed genes; PBMCs; Type 1 diabetes mellitus; WGCNA

Mesh:

Substances:

Year:  2022        PMID: 35976509     DOI: 10.1007/s12020-022-03163-z

Source DB:  PubMed          Journal:  Endocrine        ISSN: 1355-008X            Impact factor:   3.925


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