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Integrated analysis of transcriptome profiling of lncRNAs and mRNAs in livers of type 2 diabetes mellitus

  • Xi Lan
  • , Jing Han
  • , Binxian Wang
  • , Mingzhu Sun
  • Beijing Jiaotong University
  • The First Affiliated Hospital of Xi’an Jiaotong University
  • Xi'an Jiaotong University
  • The Second Affiliated Hospital of Xi'an Jiaotong University

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

Long noncoding RNAs (lncRNAs) influence the progression of almost all human diseases, but the participation of lncRNAs in type 2 diabetes mellitus (T2DM) has not been fully elucidated. This study aimed to systematically compare the tran-scriptome profiling of lncRNAs and mRNAs in livers between patients with T2DM and controls, to identify key genes associated with T2DM pathogenesis, and to predict the underlying molecular mechanisms. As a result, a total of 1,512 differentially expressed (DE) lncRNAs and 1,923 DE mRNAs were identified through microarray analysis. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis indicated that multiple metabolic processes were dys-regulated such as small molecule, organic acid, lipid, and branched chain amino acid metabolism. Protein-protein interaction network was constructed, and 10 hub mRNAs were identified, including EHHADH, ATM, ACOX1, PIK3R1, EGFR, UQCRFS1, HMGCL, UQCRC2, NDUFS3, and F2. RT-qPCR was conducted to verify the validity of microarray results. Then, coding-noncoding co-expression network and competing endogenous RNA (ceRNA) network were analyzed to predict the lncRNA-mRNA and lncRNA-miRNA-mRNA regulatory patterns. Subsequently, 10 key intermediating miRNAs in ceRNA networks with a node degree >80 were identified, including hsa-miR-5692a, hsa-miR-12136, hsa-miR-5680, hsa-miR-1305, hsa-miR-6833-5p, hsa-miR-7159-5p, hsa-miR-548as-3p, hsa-miR-6873-3p, hsa-miR-1290, and hsa-miR-4768-5p. In conclu-sion, this study evaluated the transcriptome profiling of lncRNAs and mRNAs in livers from patients with T2DM, with a value for understanding the molecular mechanism of disease pathogenesis and identifying effective biomarkers in clinical diagnosis.

Original languageEnglish
Pages (from-to)86-97
Number of pages12
JournalPhysiological Genomics
Volume54
Issue number2
DOIs
StatePublished - Feb 2022

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • liver
  • lncRNA
  • microarray
  • transcriptome
  • type 2 diabetes mellitus

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