Competing Endogenous RNA Network Analysis Explores the Key LncRNAs, MiRNAs, and MRNAs in Type 1 Diabetes

Overview

Journal BMC Med Genomics

Publisher Biomed Central

Specialty Genetics

Date 2021 Feb 2

PMID 33526014

Citations 4

Authors

Chang Li

Bo Wei

Jianyu Zhao

Affiliations

Soon will be listed here.

Abstract

Background: Type 1 diabetes (T1D, named insulin-dependent diabetes) has a relatively rapid onset and significantly decreases life expectancy. This study is conducted to reveal the long non-coding RNA (lncRNA)-microRNA (miRNA)-mRNA regulatory axises implicated in T1D.

Methods: The gene expression profile under GSE55100 (GPL570 and GPL8786 datasets; including 12 T1D samples and 10 normal samples for each dataset) was extracted from Gene Expression Omnibus database. Using limma package, the differentially expressed mRNAs (DE-mRNAs), miRNAs (DE-miRNAs), and lncRNAs (DE-lncRNAs) between T1D and normal samples were analyzed. For the DE-mRNAs, the functional terms were enriched by DAVID tool, and the significant pathways were enriched using gene set enrichment analysis. The interactions among DE-lncRNAs, DE-miRNAs and DE-mRNAs were predicted using mirwalk and starbase. The lncRNA-miRNA-mRNA interaction network analysis was visualized by Cytoscape. The key genes in the interaction network were verified by quantitatively real-time PCR.

Results: In comparison to normal samples, 236 DE-mRNAs, 184 DE-lncRNAs, and 45 DE-miRNAs in T1D samples were identified. For the 236 DE-mRNAs, 16 Gene Ontology (GO)_biological process (BP) terms, four GO_cellular component (CC) terms, and 57 significant pathways were enriched. A network involving 36 DE-mRNAs, 8 DE- lncRNAs, and 15 DE-miRNAs was built, such as TRG-AS1-miR-23b/miR-423-PPM1L and GAS5-miR-320a/miR-23b/miR-423-SERPINA1 regulatory axises. Quantitatively real-time PCR successfully validated the expression levels of TRG-AS1- miR-23b -PPM1L and GAS5-miR-320a- SERPINA1.

Conclusion: TRG-AS1-miR-23b-PPM1L and GAS5-miR-320a-SERPINA1 regulatory axises might impact the pathogenesis of T1D.

Citing Articles

Identification of key regulatory genes and their working mechanisms in type 1 diabetes.

Li H, Hu X, Li J, Jiang W, Wang L, Tan X BMC Med Genomics. 2023; 16(1):8.

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Comprehensive analysis of a TPX2-related TRHDE-AS1/PKIA ceRNA network involving prognostic signatures in Hepatitis B virus-infected hepatocellular carcinoma.

Li G, Wang Z, Chen D, Yin J, Mo Z, Sun B Front Cell Infect Microbiol. 2022; 12:1025900.

PMID: 36204642 PMC: 9530265. DOI: 10.3389/fcimb.2022.1025900.

Understanding Competitive Endogenous RNA Network Mechanism in Type 1 Diabetes Mellitus Using Computational and Bioinformatics Approaches.

Yi X, Cheng X Diabetes Metab Syndr Obes. 2021; 14:3865-3945.

PMID: 34526791 PMC: 8436179. DOI: 10.2147/DMSO.S315488.

Hub Genes Associated with the Diagnosis of Diabetic Retinopathy.

Tang Y, Tang Q, Wei H, Hu P, Zou D, Liang R Int J Gen Med. 2021; 14:1739-1750.

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