Diabetes Metab J.  2022 May;46(3):451-463. 10.4093/dmj.2021.0018.

Identification of Key Genes and Pathways in Peripheral Blood Mononuclear Cells of Type 1 Diabetes Mellitus by Integrated Bioinformatics Analysis

• Li X
• Liao M
• Guan J
• Zhou L
• Shen R
• Long M
• Shao J

• KMID: 2530184
• DOI: http://doi.org/10.4093/dmj.2021.0018

Abstract

Background
The onset and progression of type 1 diabetes mellitus (T1DM) is closely related to autoimmunity. Effective monitoring of the immune system and developing targeted therapies are frontier fields in T1DM treatment. Currently, the most available tissue that reflects the immune system is peripheral blood mononuclear cells (PBMCs). Thus, the aim of this study was to identify key PBMC biomarkers of T1DM.
Methods
Common differentially expressed genes (DEGs) were screened from the Gene Expression Omnibus (GEO) datasets GSE9006, GSE72377, and GSE55098, and PBMC mRNA expression in T1DM patients was compared with that in healthy participants by GEO2R. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and protein-protein interaction (PPI) network analyses of DEGs were performed using the Cytoscape, DAVID, and STRING databases. The vital hub genes were validated by reverse transcription-polymerase chain reaction using clinical samples. The disease-gene-drug interaction network was built using the Comparative Toxicogenomics Database (CTD) and Drug Gene Interaction Database (DGIdb).
Results
We found that various biological functions or pathways related to the immune system and glucose metabolism changed in PBMCs from T1DM patients. In the PPI network, the DEGs of module 1 were significantly enriched in processes including inflammatory and immune responses and in pathways of proteoglycans in cancer. Moreover, we focused on four vital hub genes, namely, chitinase-3-like protein 1 (CHI3L1), C-X-C motif chemokine ligand 1 (CXCL1), matrix metallopeptidase 9 (MMP9), and granzyme B (GZMB), and confirmed them in clinical PBMC samples. Furthermore, the disease-gene-drug interaction network revealed the potential of key genes as reference markers in T1DM.
Conclusion
These results provide new insight into T1DM pathogenesis and novel biomarkers that could be widely representative reference indicators or potential therapeutic targets for clinical applications.

Keyword

Computational biology; Diabetes mellitus, type 1; Immune system; Leukocytes, mononuclear; Protein interaction maps

Figure

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  Fig. 1. Flow chart of bioinformatics and validation. GEO, Gene Expression Omnibus; T1DM, type 1 diabetes mellitus; KEGG, Kyoto Encyclopedia of Genes and Genomes; DEG, differentially expressed genes; PPI, protein-protein interaction.

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  Fig. 2. Volcanos plot of three datasets. (A) Volcano plots of the distribution of differentially expressed genes (DEGs) in each dataset, fold change >1.2, P<0.05. (B) Venn plot of upregulated and downregulated DEGs in these datasets. (C) The expression heatmap of the top 10 upregulated and downregulated DEGs.

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  Fig. 3. Functional and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis of common differentially expressed genes (DEGs). Biological functional enrichment of upregulated (A) and downregulated (B) DEGs via Cytoscape Gluego. Bubble plot of upregulated (C) and downregulated (D) DEG-enriched KEGG pathways via Database for Annotation, Visualization and Integrated Discovery (DAVID). FFAR2, free fatty acid receptor 2; CHI3L1, chitinase-3-like protein 1; EGR1, early growth response 1; ABCA1, ATP binding cassette subfamily A member 1; SASH1, SAM and SH3 domain containing 1; PTK2B, protein tyrosine kinase 2 beta; TLR, toll like receptor; MMP9, matrix metalloproteinase-9; IL17RC, interleukin 17 receptor C; PSEN1, presenilin 1; EPOR, erythropoietin receptor; LTP, lipid-transfer protein; NAMPT, nicotinamide phosphoribosyl transferase; IFNGR2, interferon gamma receptor 2; CSF3R, colony stimulating factor 3 receptor; FLOT1, flotillin 1; SEC14L1, SEC14 like lipid binding 1; ATM, ATM serine/threonine kinase; WNK1, WNK lysine deficient protein kinase 1; PIK3R1, phosphoinositide3-kinase regulatory subunit 1; OSBPL8, oxysterol binding protein like 8; SYNE2, spectrin repeat containing nuclear envelope protein 2; ADGRG1, adhesion G protein-coupled receptor G1; HTLV-1, human T-lymphotropic virus type 1.

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  Fig. 4. Determination of vital hub genes and related biological processes. (A) Top 10 ranked hub gene networks generated by Cytohubba. (B) The expression heatmap of the top 10 ranked hub genes. (C) The network of hub genes and related biological processes constructed by ClueGO. (D) Venn plot of common genes between the top 10 regulated differentially expressed genes (DEGs) and hub genes: chitinase-3-like protein 1 (CHI3L1), chemokine C-X-C motif ligand 1 (CXCL1), matrix metalloproteinase-9 (MMP9), and granzyme B (GZMB). (E) Reverse transcription-polymerase chain reaction (RT-PCR) detection of CHI3L1, CXCL1, MMP9, and GZMB mRNA expression in peripheral blood mononuclear cell of healthy participants and type 1 diabetes mellitus (T1DM) patients (n=10). SPTAN1, spectrin alpha non-erythrocytic 1; LTF, lactotransferrin; IL1RN, interleukin 1 receptor antagonist; TLR, toll like receptor; LAMP1, lysosomal associated membrane protein 1. aP<0.05, b P<0.01, unpaired t-test.

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  Fig. 5. Disease-gene-drug network analysis centered on four vital hub genes. CXCL1, chemokine (C-X-C motif) ligand 1; MMP9, matrix metalloproteinase-9; CHI3L1, chitinase-3-like protein 1; GZMB, granzyme B.

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