scholarly journals Identification of differentially expressed genes in the endothelial precursor cells of patients with type 2 diabetes mellitus by bioinformatics analysis

2019 ◽  
Author(s):  
Zhida Shen ◽  
Qi Chen ◽  
Hangying Ying ◽  
Zetao Ma ◽  
Xukun Bi ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Differentially Expressed Genes ◽  
Bioinformatics Analysis ◽  
Precursor Cells ◽  
Differentially Expressed

scholarly journals Bioinformatics Analysis of Key Genes and Pathways for Obesity Associated Type 2 Diabetes Mellitus as a Therapeutic Target

2020 ◽  
Author(s):  
Basavaraj Vastrad ◽  
Anandkumar Tengli ◽  
Chanabasayya Vastrad ◽  
Iranna Kotturshetti
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Differentially Expressed Genes ◽  
Regulatory Network ◽  
Metabolic Disorder ◽  
Target Gene ◽  
Bioinformatics Analysis ◽  
Hub Genes

AbstractObesity associated type 2 diabetes mellitus is one of the most common metabolic disorder worldwide. The prognosis of obesity associated type 2 diabetes mellitus patients has remained poor, though considerable efforts have been made to improve the treatment of this metabolic disorder. Therefore, identifying significant differentially expressed genes (DEGs) associated in metabolic disorder advancement and exploiting them as new biomarkers or potential therapeutic targets for metabolic disorder is highly valuable. Differentially expressed genes (DEGs) were screened out from gene expression omnibus (GEO) dataset (GSE132831) and subjected to GO and REACTOME pathway enrichment analyses. The protein - protein interactions network, module analysis, target gene - miRNA regulatory network and target gene - TF regulatory network were constructed, and the top ten hub genes were selected. The relative expression of hub genes was detected in RT-PCR. Furthermore, diagnostic value of hub genes in obesity associated type 2 diabetes mellitus patients was investigated using the receiver operating characteristic (ROC) analysis. Small molecules were predicted for obesity associated type 2 diabetes mellitus by using molecular docking studies. A total of 872 DEGs, including 439 up regulated genes and 432 down regulated genes were observed. Second, functional enrichment analysis showed that these DEGs are mainly involved in the axon guidance, neutrophil degranulation, plasma membrane bounded cell projection organization and cell activation. The top ten hub genes (MYH9, FLNA, DCTN1, CLTC, ERBB2, TCF4, VIM, LRRK2, IFI16 and CAV1) could be utilized as potential diagnostic indicators for obesity associated type 2 diabetes mellitus. The hub genes were validated in obesity associated type 2 diabetes mellitus. This investigation found effective and reliable molecular biomarkers for diagnosis and prognosis by integrated bioinformatics analysis, suggesting new and key therapeutic targets for obesity associated type 2 diabetes mellitus.

scholarly journals Serum microRNA profiling and bioinformatics analysis of patients with type 2 diabetes mellitus in a Chinese population

2017 ◽  
Vol 15 (4) ◽  
pp. 2143-2153 ◽  
Author(s):  
Ze-Min Yang ◽  
Long-Hui Chen ◽  
Min Hong ◽  
Ying-Yu Chen ◽  
Xiao-Rong Yang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Chinese Population ◽  
Bioinformatics Analysis ◽  
Serum Microrna ◽  
Microrna Profiling

scholarly journals Identification of Perturbed Pathways Rendering Susceptibility to Tuberculosis in Type 2 Diabetes Mellitus Patients Using BioNSi Simulation of Integrated Network of Implicated Human Genes

2021 ◽  
Author(s):  
Jyoti Rani ◽  
Anasuya Bhargav ◽  
Malabika Datta ◽  
Urmi Bajpai ◽  
Srinivasan Ramachandran
Keyword(s):  
Gene Expression ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Mapk Signaling ◽  
Differentially Expressed ◽  
P Value ◽  
Receptor Signaling ◽  
Chronic Hyperglycemia

Abstract Adaptive immune response of the Th1 arm is the main defense against tuberculosis (TB). However, in Type 2 Diabetes Mellitus (T2DM) patients, chronic hyperglycemia and inflammation underlie susceptibility to TB and results in poor TB control. The molecular pathways causing susceptibility of diabetics to tuberculosis is not fully understood. Here, an integrative pathway-based approach is used to investigate the perturbed pathways in T2DM patients rendering susceptibility to TB. We obtained 36 genes implicated in the Type 2 diabetes associated tuberculosis (T2DMTB) from literature. Gene expression analysis on T2DM patients’ data (GSE28168) showed that DEFA1 is differentially expressed at Padj < 0.05. The genes CAMP, CD14, CORO1A, LAMP1, TLR4, IL17F and SOCS3 were differentially expressed in T2DM patients at P value < 0.05. 7 microRNAs associated with these T2DMTB genes were obtained from NetworkAnalyst and verified for their literature evidences. The hsa-miR-146a microRNA was differentially expressed at Padj < 0.05. The human host TB susceptibility genes TNFRSF10A, MSRA, GPR148, SLC37A3, PXK, PROK2, REV3L, PGM1, HIST3H2A, PLAC4, LETM2, EMP2 and were also differentially expressed at Padj < 0.05. We included all these genes and added the remaining 28 genes from the T2DMTB set and the rest of differentially expressed genes at Padj < 0.05 in STRING and obtained a well-connected network with high confidence score greater than 0.7. From this network we extracted the KEGG pathways at FDR < 0.05 and retained only Diabetes and TB pathways among the disease pathways. The network was simulated with BioNSi using gene expression data from GSE26168. The Necroptosis pathway showed the maximum perturbations in T2DM patients, followed by NOD-like receptor signaling, Toll-like receptor signaling, NF-kappa-B signaling and MAPK signaling. These pathways likely underlie susceptibility to TB in T2DM patients.

scholarly journals Identification of Circular RNAs Regulating Islet β-Cell Autophagy in Type 2 Diabetes Mellitus

2019 ◽  
Vol 2019 ◽  
pp. 1-10 ◽  
Author(s):  
Chao Bai ◽  
Wenwen Yang ◽  
Yao Lu ◽  
Wei Wei ◽  
Zongbao Li ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Signaling Pathway ◽  
Expression Profile ◽  
Mapk Signaling ◽  
Mapk Signaling Pathway ◽  
Differentially Expressed ◽  
Qrt Pcr

This study is to identify the circular RNA (circRNA) expression profile that is functionally related to pancreatic islet β-cell autophagy and their potential regulation mechanisms in type 2 diabetes mellitus (T2DM). T2DM rat model was constructed by administration of high-fat and high-sugar diet. β-cells were isolated from islets by flow cytometry. CircRNA expression profile in β-cells was detected by circRNA microarrays, and the differentially expressed circRNAs were identified and validated by qRT-PCR. MicroRNA (miRNA) target prediction software and multiple bioinformatic approaches were used to construct a map of circRNA-miRNA interactions for the differentially expressed circRNAs. A total of 825 differentially expressed circular transcripts were identified in T2DM rats compared with control rats, among which 388 were upregulated and 437 were downregulated. Ten circRNAs were identified to have significant differences by qRT-PCR. GO analysis enriched terms such as organelle membrane and protein binding and the top enriched pathways for the circRNAs included MAPK signaling pathway. The differentially expressed circRNAs might involve in MAPK signaling pathway, apoptosis, and Ras signaling pathway. We speculate that these circRNAs, especially rno_circRNA_008565, can regulate the autophagy of islet β-cells via interactions with miRNA. Dysregulation of several circRNAs may play a role in T2DM development, and rno_circRNA_008565 may be a potential regulator of β-cell autophagy.

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