Bioinformatics analysis of hepatic gene expression profiles in type 2 diabetes mellitus

The epidemic of type 2 diabetes mellitus (T2DM) is an important global health concern. Our earlier epidemiological investigation in Pakistan prompted us to conduct a molecular investigation to decipher the differential genetic pathways of this health condition in relation to non-diabetic controls. Our microarray studies of global gene expression were conducted on the Affymetrix platform using Human Genome U133 Plus 2.0 Array along with Ingenuity Pathway Analysis (IPA) to associate the affected genes with their canonical pathways. High-throughput qRT-PCR TaqMan Low Density Array (TLDA) was performed to validate the selected differentially expressed genes of our interest, viz., ARNT, LEPR, MYC, RRAD, CYP2D6, TP53, APOC1, APOC2, CYP1B1, SLC2A13, and SLC33A1 using a small population validation sample (n = 15 cases and their corresponding matched controls). Overall, our small pilot study revealed a discrete gene expression profile in cases compared to controls. The disease pathways included: Insulin Receptor Signaling, Type II Diabetes Mellitus Signaling, Apoptosis Signaling, Aryl Hydrocarbon Receptor Signaling, p53 Signaling, Mitochondrial Dysfunction, Chronic Myeloid Leukemia Signaling, Parkinson’s Signaling, Molecular Mechanism of Cancer, and Cell Cycle G1/S Checkpoint Regulation, GABA Receptor Signaling, Neuroinflammation Signaling Pathway, Dopamine Receptor Signaling, Sirtuin Signaling Pathway, Oxidative Phosphorylation, LXR/RXR Activation, and Mitochondrial Dysfunction, strongly consistent with the evidence from epidemiological studies. These gene fingerprints could lead to the development of biomarkers for the identification of subgroups at high risk for future disease well ahead of time, before the actual disease becomes visible.

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Analysis of gene expression profiles in insulin-sensitive tissues from pre-diabetic and diabetic Zucker diabetic fatty rats

Journal of Molecular Endocrinology ◽

10.1677/jme.1.01679 ◽

2005 ◽

Vol 34 (2) ◽

pp. 299-315 ◽

Cited By ~ 42

Author(s):

Young Ho Suh ◽

Younyoung Kim ◽

Jeong Hyun Bang ◽

Kyoung Suk Choi ◽

June Woo Lee ◽

...

Keyword(s):

Gene Expression ◽

Insulin Resistance ◽

Type 2 Diabetes ◽

Skeletal Muscle ◽

Adipose Tissue ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Zucker Diabetic Fatty Rats ◽

Zdf Rats

Insulin resistance occurs early in the disease process, preceding the development of type 2 diabetes. Therefore, the identification of molecules that contribute to insulin resistance and leading up to type 2 diabetes is important to elucidate the molecular pathogenesis of the disease. To this end, we characterized gene expression profiles from insulin-sensitive tissues, including adipose tissue, skeletal muscle, and liver tissue of Zucker diabetic fatty (ZDF) rats, a well characterized type 2 diabetes animal model. Gene expression profiles from ZDF rats at 6 weeks (pre-diabetes), 12 weeks (diabetes), and 20 weeks (late-stage diabetes) were compared with age- and sex-matched Zucker lean control (ZLC) rats using 5000 cDNA chips. Differentially regulated genes demonstrating > 1.3-fold change at age were identified and categorized through hierarchical clustering analysis. Our results showed that while expression of lipolytic genes was elevated in adipose tissue of diabetic ZDF rats at 12 weeks of age, expression of lipogenic genes was decreased in liver but increased in skeletal muscle of 12 week old diabetic ZDF rats. These results suggest that impairment of hepatic lipogenesis accompanied with the reduced lipogenesis of adipose tissue may contribute to development of diabetes in ZDF rats by increasing lipogenesis in skeletal muscle. Moreover, expression of antioxidant defense genes was decreased in the liver of 12-week old diabetic ZDF rats as well as in the adipose tissue of ZDF rats both at 6 and 12 weeks of age. Cytochrome P450 (CYP) genes were also significantly reduced in 12 week old diabetic liver of ZDF rats. Genes involved in glucose utilization were downregulated in skeletal muscle of diabetic ZDF rats, and the hepatic gluconeogenic gene was upregulated in diabetic ZDF rats. Genes commonly expressed in all three tissue types were also observed. These profilings might provide better fundamental understanding of insulin resistance and development of type 2 diabetes.

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Differently Expressed Genes (DEGs) Relevant to Type 2 Diabetes Mellitus Identification and Pathway Analysis via Integrated Bioinformatics Analysis

Medical Science Monitor ◽

10.12659/msm.918407 ◽

2019 ◽

Vol 25 ◽

pp. 9237-9244

Author(s):

Xuanqiang Che ◽

Ran Zhao ◽

Hua Xu ◽

Xue Liu ◽

Shumiao Zhao ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Pathway Analysis ◽

Bioinformatics Analysis ◽

Differently Expressed Genes

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Expression profiles of long noncoding RNAs in type 2 diabetes mellitus rat associated with the progression of ischemia-reperfursion injury

10.21203/rs.3.rs-20462/v1 ◽

2020 ◽

Author(s):

Wenhao Song ◽

Yao Gong ◽

Pei Tu ◽

Lin Zhang ◽

Zhili Jin ◽

...

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Reperfusion Injury ◽

Ischemia Reperfusion Injury ◽

Expression Profiles ◽

Ischemia Reperfusion ◽

Diabetic Rats ◽

Myocardial Ischemia Reperfusion

Abstract Background The aim of this study was to analyze the expressions of long noncoding RNA(lncRNA) in rat with type 2 diabetes mellitus(T2DM) complicated with acute myocardial ischemia reperfusion injury(IRI). Methods Type 2 diabetic rats were induced by high calorie diet combined with streptozotocin. IRI rats models were established by the ligation and release of left anterior descending coronary artery(LAD). The expression levels of lncRNA and mRNA in myocardial tissues of rats were detected via high-throughput sequencing technology, and Gene Ontology analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis were performed. Result Transcriptome analyses were performed to show expression profiles of mRNAs and lncRNAs in myocardial tissues of diabetic rats with IRI. A total of 2,476 lncRNAs and 710 mRNAs were differentially expressed between operation group and sham operation group. Then, an mRNA-lncRNA coexpression network was constructed. Finally, the present study verified that TCONS_00036439、TCONS_00151548、TCONS_00153276、TCONS_00344188、TCONS_00277692、TCONS_00236469、TCONS_00236468、TCONS_00153290、TCONS_00360941、TCONS_00142622 were associated with the initiation and development of ischemia reperfusion injury. Then, an lncRNA-mRNA coexpression network was constructed. Conclusion There is differential expression of lncRNAs in myocardial IRI tissues of diabetic rats. Building gene regulation networks to find the nodal gene and lncRNA is useful for understanding the pathogenesis of type 2 diabetes mellitus complicated with acute myocardial ischemia reperfusion injury and providing new therapy target.

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Gene Expression Profiling of Type 2 Diabetes Mellitus by Bioinformatics Analysis

Computational and Mathematical Methods in Medicine ◽

10.1155/2020/9602016 ◽

2020 ◽

Vol 2020 ◽

pp. 1-10

Author(s):

Huijing Zhu ◽

Xin Zhu ◽

Yuhong Liu ◽

Fusong Jiang ◽

Miao Chen ◽

...

Keyword(s):

Gene Expression ◽

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Candidate Genes ◽

Signaling Pathway ◽

Bioinformatics Analysis ◽

Kegg Pathway ◽

Ppi Network ◽

Kegg Pathway Analysis

Objective. The aim of this study was to identify the candidate genes in type 2 diabetes mellitus (T2DM) and explore their potential mechanisms. Methods. The gene expression profile GSE26168 was downloaded from the Gene Expression Omnibus (GEO) database. The online tool GEO2R was used to obtain differentially expressed genes (DEGs). Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Metascape for annotation, visualization, and comprehensive discovery. The protein-protein interaction (PPI) network of DEGs was constructed by using Cytoscape software to find the candidate genes and key pathways. Results. A total of 981 DEGs were found in T2DM, including 301 upregulated genes and 680 downregulated genes. GO analyses from Metascape revealed that DEGs were significantly enriched in cell differentiation, cell adhesion, intracellular signal transduction, and regulation of protein kinase activity. KEGG pathway analysis revealed that DEGs were mainly enriched in the cAMP signaling pathway, Rap1 signaling pathway, regulation of lipolysis in adipocytes, PI3K-Akt signaling pathway, MAPK signaling pathway, and so on. On the basis of the PPI network of the DEGs, the following 6 candidate genes were identified: PIK3R1, RAC1, GNG3, GNAI1, CDC42, and ITGB1. Conclusion. Our data provide a comprehensive bioinformatics analysis of genes, functions, and pathways, which may be related to the pathogenesis of T2DM.

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