scholarly journals Investigation of Candidate Genes and Mechanisms Underlying Obesity Associated Type 2 Diabetes Mellitus Using Bioinformatics Analysis and Screening of Small Drug Molecules 

2020 ◽  
Author(s):  
Prashanth G ◽  
Basavaraj Vastrad ◽  
Anandkumar Tengli ◽  
Chanabasayya Vastrad ◽  
Iranna Kotturshetti
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Plasma Membrane ◽  
Pathway Analysis ◽  
Regulatory Network ◽  
Target Genes ◽  
Hub Genes ◽  
Drug Molecules

Abstract BackgroundObesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the development mechanism of obesity associated type 2 diabetes mellitus. MethodsTo screen the differentially expressed genes (DEGs) that may play essential roles in obesity associated type 2 diabetes mellitus, the public expression profiling by high throughput sequencing data (GSE143319) were downloaded and screened for DEGs. Then, Gene Ontology (GO) function analysis and REACTOME pathway analysis were performed. To screen hub and target genes, the protein–protein interaction network, miRNA-target genes regulatory network and TF-target gene regulatory network were constructed. The Receiver operating characteristic (ROC) curve analysis and RT- PCR analysis of hub genes in obesity associated type 2 diabetes mellitus were also analyzed. Final molecular docking studies performed for screening small drug molecules. ResultsThere were 409 up regulated and 411 down regulated genes detected, and the biological processes of the GO analysis were enriched in regulation of ion transmembrane transport, intrinsic component of plasma membrane, transferase activity, transferring phosphorus-containing groups, cell adhesion, integral component of plasma membrane and signaling receptor binding, whereas, the REACTOME pathway analysis was enriched in integration of energy metabolism and extracellular matrix organization. The hub genes CEBPD, TP73, ESR2, TAB1, MAP3K5, FN1, UBD, RUNX1, PIK3R2 and TNF, which might play a essential role in obesity associated type 2 diabetes mellitus was further screened. ConclusionsThe present study could deepen the understanding of the molecular mechanism of obesity associated type 2 diabetes mellitus, which could be useful in developing clinical treatments of obesity associated type 2 diabetes mellitus.

scholarly journals Investigation of candidate genes and mechanisms underlying obesity associated type 2 diabetes mellitus using bioinformatics analysis and screening of small drug molecules

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
G. Prashanth ◽  
Basavaraj Vastrad ◽  
Anandkumar Tengli ◽  
Chanabasayya Vastrad ◽  
Iranna Kotturshetti
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Hub Genes ◽  
Pathway Enrichment ◽  
Drug Molecules

Abstract Background Obesity associated type 2 diabetes mellitus is a metabolic disorder ; however, the etiology of obesity associated type 2 diabetes mellitus remains largely unknown. There is an urgent need to further broaden the understanding of the molecular mechanism associated in obesity associated type 2 diabetes mellitus. Methods To screen the differentially expressed genes (DEGs) that might play essential roles in obesity associated type 2 diabetes mellitus, the publicly available expression profiling by high throughput sequencing data (GSE143319) was downloaded and screened for DEGs. Then, Gene Ontology (GO) and REACTOME pathway enrichment analysis were performed. The protein - protein interaction network, miRNA - target genes regulatory network and TF-target gene regulatory network were constructed and analyzed for identification of hub and target genes. The hub genes were validated by receiver operating characteristic (ROC) curve analysis and RT- PCR analysis. Finally, a molecular docking study was performed on over expressed proteins to predict the target small drug molecules. Results A total of 820 DEGs were identified between healthy obese and metabolically unhealthy obese, among 409 up regulated and 411 down regulated genes. The GO enrichment analysis results showed that these DEGs were significantly enriched in ion transmembrane transport, intrinsic component of plasma membrane, transferase activity, transferring phosphorus-containing groups, cell adhesion, integral component of plasma membrane and signaling receptor binding, whereas, the REACTOME pathway enrichment analysis results showed that these DEGs were significantly enriched in integration of energy metabolism and extracellular matrix organization. The hub genes CEBPD, TP73, ESR2, TAB1, MAP 3K5, FN1, UBD, RUNX1, PIK3R2 and TNF, which might play an essential role in obesity associated type 2 diabetes mellitus was further screened. Conclusions The present study could deepen the understanding of the molecular mechanism of obesity associated type 2 diabetes mellitus, which could be useful in developing therapeutic targets for obesity associated type 2 diabetes mellitus.

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.

Exploring Shared Pathogenesis of Alzheimer’s Disease and Type 2 Diabetes Mellitus via Co-expression Networks Analysis

2020 ◽  
Vol 17 (6) ◽  
pp. 566-575 ◽  
Author(s):  
Yukun Zhu ◽  
Xuelu Ding ◽  
Zhaoyuan She ◽  
Xue Bai ◽  
Ziyang Nie ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Protein Interaction Network ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network

Background: Alzheimer’s Disease (AD) and Type 2 Diabetes Mellitus (T2DM) have an increased incidence in modern society. Although increasing evidence has supported the close linkage between these two disorders, the inter-relational mechanisms remain to be fully elucidated. Objective: The primary purpose of this study is to explore the shared pathophysiological mechanisms of AD and T2DM. Methods: We downloaded the microarray data of AD and T2DM from the Gene Expression Omnibus (GEO) database and constructed co-expression networks by Weighted Gene Co-Expression Network Analysis (WGCNA) to identify gene network modules related to AD and T2DM. Then, Gene Ontology (GO) and pathway enrichment analysis were performed on the common genes existing in the AD and T2DM related modules by clusterProfiler and DOSE package. Finally, we utilized the STRING database to construct the protein-protein interaction network and found out the hub genes in the network. Results: Our findings indicated that seven and four modules were the most significant with AD and T2DM, respectively. Functional enrichment analysis showed that AD and T2DM common genes were mainly enriched in signaling pathways such as circadian entrainment, phagosome, glutathione metabolism and synaptic vesicle cycle. Protein-protein interaction network construction identified 10 hub genes (CALM1, LRRK2, RBX1, SLC6A1, TXN, SNRPF, GJA1, VWF, LPL, AGT) in AD and T2DM shared genes. Conclusions: Our work identified common pathogenesis of AD and T2DM. These shared pathways might provide a novel idea for further mechanistic studies and hub genes that may serve as novel therapeutic targets for diagnosis and treatment of AD and T2DM.

scholarly journals Identification of Hub Genes in Type 2 Diabetes Mellitus Using Bioinformatics Analysis

2020 ◽  
Vol Volume 13 ◽  
pp. 1793-1801
Author(s):  
YiXuan Lin ◽  
Jinju Li ◽  
Di Wu ◽  
FanJing Wang ◽  
ZhaoHui Fang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Bioinformatics Analysis ◽  
Hub Genes

scholarly journals High-Throughput Sequencing and Exploration of the lncRNA-circRNA-miRNA-mRNA Network in Type 2 Diabetes Mellitus

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Fang Yang ◽  
Yang Chen ◽  
Zhiqiang Xue ◽  
Yaogai Lv ◽  
Li Shen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Regulatory Network ◽  
Differential Expression Analysis ◽  
Differentially Expressed ◽  
Biological Functions ◽  
Ppi Network

Objective. Long noncoding RNA (lncRNA) and circular RNA (circRNA) are receiving increasing attention in diabetes research. However, there are still many unknown lncRNAs and circRNAs that need further study. The aim of this study is to identify new lncRNAs and circRNAs and their potential biological functions in type 2 diabetes mellitus (T2DM). Methods. RNA sequencing and differential expression analysis were used to identify the noncoding RNAs (ncRNAs) and mRNAs that were expressed abnormally between the T2DM and control groups. The competitive endogenous RNA (ceRNA) regulatory network revealed the mechanism of lncRNA and circRNA coregulating gene expression. The biological functions of lncRNA and circRNA were analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The candidate hub mRNAs were selected by the protein-protein interaction (PPI) network and validated by using the Gene Expression Omnibus (GEO) database. Results. Differential expression analysis results showed that 441 lncRNAs (366 upregulated and 75 downregulated), 683 circRNAs (354 upregulated and 329 downregulated), 93 miRNAs (63 upregulated and 30 downregulated), and 2923 mRNAs (1156 upregulated and 1779 downregulated) were identified as remarkably differentially expressed in the T2DM group. The ceRNA regulatory network showed that a single lncRNA and circRNA can be associated with multiple miRNAs, and then, they coregulate more mRNAs. Functional analysis showed that differentially expressed lncRNA (DElncRNA) and differentially expressed circRNA (DEcircRNA) may play important roles in the mTOR signaling pathway, lysosomal pathway, apoptosis pathway, and tuberculosis pathway. In addition, PIK3R5, AKT2, and CLTA were hub mRNAs screened out that were enriched in an important pathway by establishing the PPI network. Conclusions. This study is the first study to explore the molecular mechanisms of lncRNA and circRNA in T2DM through the ceRNA network cofounded by lncRNA and circRNA. Our study provides a novel insight into the T2DM from the ceRNA regulatory network.

scholarly journals HPLC-MS and Network Pharmacology Analysis to Reveal Quality Markers of Huo-Xue-Jiang-Tang Yin, a Chinese Herbal Medicine for Type 2 Diabetes Mellitus

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Qiugu Chen ◽  
Yuan Zhao ◽  
Maosheng Li ◽  
Ping Zheng ◽  
Shangbin Zhang ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Target Genes ◽  
Functional Enrichment ◽  
Network Pharmacology ◽  
Peptidase Activity ◽  
Active Components ◽  
Quality Markers

Huo-Xue-Jiang-Tang Yin (HXJTY) is a Chinese medicine formulation, which has been widely used for the treatment of various lipometabolism- and glycometabolism-related diseases in clinics. Currently, HXJTY is mainly prescribed to treat patients with type 2 diabetes mellitus (T2DM), yet its chemical and pharmacologic profiles remain to be elucidated. Here, the potential bioactive compound and action mechanism were investigated using chemical and network pharmacology analysis. A rapid HPLC-MS was employed to identify and quantify the component of HXJTY. On the basis of the identified chemical markers from HXJTY, a network pharmacology study, including target gene prediction and functional enrichment, was applied to screen out the main quality markers of HXJTY and explore its potential mechanism for the treatment of T2DM. The results showed that a total of 22 components were identified and quantified from HXJTY by HPLC-MS. Furthermore, 12 active components such as astragaloside IV, calycosin-7-O-β-D-glucoside, hydroxysafflor yellow A, and others were proposed as quality markers of HXJTY for treating T2DM based on network pharmacology analysis. In addition, 125 corresponding possible therapeutic target genes of T2DM were obtained. These target genes are mainly related to peptidase activity, hydrolase activity, phosphatase activity, and cofactor binding, suggesting the involvement of PI3K-Akt, MAPK, AGE-RAGE, and Rap1 signaling pathways in HXJTY-treated T2DM. Our results may provide a useful approach to identify potential quality markers and molecular mechanism of HXJTY for treating T2DM.

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