scholarly journals Mechanism of Quercetin Therapeutic Targets for Alzheimer Disease and type 2 Diabetes Mellitus

2021 ◽  
Author(s):  
Guoxiu Zu ◽  
Keyun Sun ◽  
Ling Li ◽  
Xiuli Zu ◽  
Tao Han ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Pathway Enrichment

Abstract Quercetin has demonstrated antioxidant, anti-inflammatory, hypoglycemic, and hypolipidemic activities, suggesting therapeutic potential against type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD). In this study, potential molecular targets of quercetin were first identified using the Swiss Target Prediction platform and pathogenic targets of T2DM and AD were identified using Online Mendelian Inheritance in Man (OMIM), DisGeNET, TTD, DrugBank, and GeneCards databases. The 95 targets shared among quercetin, T2DM, and AD were used to establish a protein–protein interaction (PPI) network, top 25 core genes, and protein functional modules using MCODE. Metascape was then used for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. A protein functional module with best score was obtained from the PPI network using CytoHubba, and 6 high-probability quercetin targets (AKT1, JUN, MAPK, TNF, VEGFA, and EGFR) were confirmed by docking simulations. KEGG pathway enrichment analysis suggested that the major shared mechanisms for T2DM and AD include “AGE-RAGE signaling pathway in diabetic complications,” “pathways in cancer,” and “MAPK signaling pathway” (the key pathway). We speculate that quercetin may have therapeutic applications in T2DM and AD by targeting MAPK signaling, providing a theoretical foundation for future clinical research.

scholarly journals Mechanism of quercetin therapeutic targets for Alzheimer disease and type 2 diabetes mellitus

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Guoxiu Zu ◽  
Keyun Sun ◽  
Ling Li ◽  
Xiuli Zu ◽  
Tao Han ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Mapk Signaling ◽  
Pathway Enrichment Analysis ◽  
Ppi Network ◽  
Pathway Enrichment

AbstractQuercetin has demonstrated antioxidant, anti-inflammatory, hypoglycemic, and hypolipidemic activities, suggesting therapeutic potential against type 2 diabetes mellitus (T2DM) and Alzheimer’s disease (AD). In this study, potential molecular targets of quercetin were first identified using the Swiss Target Prediction platform and pathogenic targets of T2DM and AD were identified using online Mendelian inheritance in man (OMIM), DisGeNET, TTD, DrugBank, and GeneCards databases. The 95 targets shared among quercetin, T2DM, and AD were used to establish a protein–protein interaction (PPI) network, top 25 core genes, and protein functional modules using MCODE. Metascape was then used for gene ontology and kyoto encyclopedia of genes and genomes (KEGG) pathway enrichment analysis. A protein functional module with best score was obtained from the PPI network using CytoHubba, and 6 high-probability quercetin targets (AKT1, JUN, MAPK, TNF, VEGFA, and EGFR) were confirmed by docking simulations. Molecular dynamics simulation was carried out according to the molecular docking results. KEGG pathway enrichment analysis suggested that the major shared mechanisms for T2DM and AD include “AGE-RAGE signaling pathway in diabetic complications,” “pathways in cancer,” and “MAPK signaling pathway” (the key pathway). We speculate that quercetin may have therapeutic applications in T2DM and AD by targeting MAPK signaling, providing a theoretical foundation for future clinical research.

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 The Mechanism of Jinqi Jiangtang Tablet in Treatment of Type 2 Diabetes Mellitus Based on Network Pharmacology

2020 ◽  
Author(s):  
Mingjun Yang ◽  
Boni Song ◽  
Zhitong Bing ◽  
Juxiang Liu ◽  
Rui Li ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Drug Targets ◽  
Kegg Pathway ◽  
Enrichment Analysis ◽  
Network Pharmacology ◽  
Active Compounds ◽  
Online Tool

Abstract Background: Type 2 Diabetes Mellitus(T2DM) is an endocrine disease that caused mainly by insulin resistance (IR) and β cell dysfunction. The incidence of T2DM is quite high in the worldwide. To explore the molecular mechanism of Jinqi Jiangtang Tablet(JJT) in treating of T2DM based on Network Pharmacology. Methods: The active compounds, targets of three Traditional Chinese medicines in JJT were obtained by the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform（TCMSP） database and Uniprot database; The targets of T2DM were screened through the Drugbank database; The compound-target network was constructed via the Cytoscape 3.7.2 software and used the built-in Network analyzer to analyze and select the key active compounds; The overlapping targets of drug and disease targets were gained by the VENNY online tool and the targets were built by STRING website to select the key genes; Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway were performed on the potential targets using DAVID6.8 online tool to study the mechanism of overlapping targets. Via Systems Dock platform to validate the interaction between compound and targets Results: Twenty-five active compounds of JJT were screened, 101 drug targets, 142 disease targets and twenty-one overlapping targets. GO enrichment analysis showed that the biological processes (BP)mainly included the blood circulation ,etc. Cell composition(CC) mainly affected the integral component of plasma membrane, etc. Molecular functions(MF) mainly involved alpha-adrenergic receptor activity, etc. KEGG pathway analysis showed that there were twelve pathways related to T2DM, among which PPAR signaling pathway was related to T2DM mostly. RXRA is one of key targets of JJT and berberine performed well. Conclusions: This study revealed the mechanism of JJT in treatment of T2DM preliminarily and supplied a further foundation for studying its mechanism.

scholarly journals The Identification of Hub Genes and Pathways in type 2 Diabetes Mellitus by Bioinformatics Analysis

2020 ◽  
Author(s):  
Jing Li ◽  
Xinkui Jiang ◽  
Libo Chen ◽  
Hong Chen
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Bioinformatics Analysis ◽  
Enrichment Analysis ◽  
Ppi Network ◽  
Hub Genes ◽  
Metabolism Pathway ◽  
Core Genes

Abstract Background This study aimed to identify potential core genes and pathways involved in type 2 diabetes mellitus (T2DM) through exhaustive bioinformatics analysis. This study elucidated parts of the pathogenesis of T2DM and screened therapeutic targets of the treatment. Method: The original microarray data GSE25724 was downloaded from the Gene Expression Omnibus database. Data were processed by the limma package in R software and the differentially expressed genes(DEGs) were identified. Gene Ontology(GO) functional analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG) pathway analysis were carried out to identify potential biological functions and pathways of the DEGs. The STRING(Search Tool for the Retrieval of Interacting Genes ) and Cytoscape software were used to establish a protein-protein interaction(PPI) network for the DEGs.Hub genes were identified using the PPI network.Results In total, 75 DEGs were involved in T2DM, with 1 up-regulated gene, and 74 down-regulated genes. GO enrichment analysis showed that DEGs mainly enriched in the regulation of hormone levels, unfolded protein binding.KEGG pathway enrichment analysis showed that DEGs were significantly enriched in the fatty acid metabolism pathway, propionate metabolism pathway, and degradation pathway of valine, leucine, and isoleucine. Furthermore,Neuroendocrine protein 7B2(SCG5),Synaptosomal-associated protein 25 (SNAP25), Sterol Carrier Protein 2 (SCP2), Carboxypeptidase E (CPE),and Protein Convertase Subtilisin/Kexin Type 1 (PCSK1) were the core genes in the PPI network.Conclusion This study identified 5 hub genes as potential biomarkers of type 2 diabetes through bioinformatics analysis, which might increase our understanding of the potential molecular mechanisms of T2DM and provided targets for further research.

scholarly journals Exploring the Regulatory Mechanism of Modified Huanglian Maidong Decoction on Type 2 Diabetes Mellitus Biological Network Based on Systematic Pharmacology

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Qi He ◽  
Tianqing Zhang ◽  
Bing Jin ◽  
Yonghe Wu ◽  
Jiamin Wu ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Pathway Enrichment Analysis ◽  
Therapeutic Effects ◽  
Inflammatory Factor ◽  
Biological Processes ◽  
Ppi Network ◽  
Model Group

Objective. To explore the mechanism of modified Huanglian Maidong decoction (Maidong-Sanqi-Huanglian Compounds, MSHCs) intervention in type 2 diabetes mellitus (T2DM). Method. This study used PubChem and SciFinder to collect the molecular structure of MSHCs, used PharmMapper to predict the potential targets of MSHC, and combined them with the T2DM gene to construct MSHC-T2DM protein-protein interaction (PPI) network. The plugin MCODE in Cytoscape 3.7.1 was then used to perform cluster analysis on the MSHC-T2DM PPI network. The genes and targets were input into DAVID for Gene Ontology (GO) and pathway enrichment analysis. Finally, animal experiments were performed to verify the therapeutic effect of MSHC on T2DM. Results. Several T2DM-related targets, clusters, signaling pathways, and biological processes are found. The experimental results showed that compared with the blank group, the content of fasting blood glucose (FBG) in the model group was higher ( P < 0.01 ). Compared with the model group, the content of FBG decreased and the insulin level increased in the MSHC medium-dose (0.15 g/kg) and high-dose (0.45 g/kg) groups and metformin group after 4 weeks of drug administration ( P < 0.05 ). MSHC can also improve blood liquid levels and inflammatory factor levels ( P < 0.05 ). Conclusion. MSHC may achieve therapeutic effects through regulating the T2DM-related targets, biological processes, and pathways, such as insulin resistance, energy metabolism, oxidative stress, and inflammation, found in this research.

System Pharmacological Mechanism and Compatibility Laws of Jianghuang from Traditional Chinese Medicine In Blood-Regulating Formulae

2020 ◽  
Author(s):  
Zhiqiang Liu ◽  
Bolong Wang
Keyword(s):  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Kegg Pathway ◽  
Inflammatory Diseases ◽  
Enrichment Analysis ◽  
Pathway Enrichment Analysis ◽  
Pharmacological Effects ◽  
Ppi Network ◽  
Pathway Enrichment ◽  
Pharmacological Mechanism

Abstract Background: Jianghuang (JH) is a popular ingredient in blood-regulating traditional Chinese Medicine (TCM) that could be effective for the treatment of various diseases. We demonstrate the compatibility laws and system pharmacological mechanisms of the key formula containing JH by leveraging data mining of bioinformatics databases.Material/Methods: The compatibility laws of blood-regulating formulae containing JH from the Chinese Traditional Medicine Formula Dictionary were analyzed using a generalized rule induction (GRI) algorithm implemented. The putative target gene and miRNA were retrieved via a combination of the Arrowsmith knowledge discovery tool and FunRich 3.1.3. System pharmacological mechanisms are traced by their protein-protein interaction (PPI) network, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was conducted using Uniprot, the Human Protein Atlas (HPA), STRING 11.0, and KOBAS 3.0.Results: We found that the JH-CX-DG formula (Ligusticum chuanxiong-Angelica sinensis) could represent a key formula containing JH in blood-regulating TCM formulae. The JH-CX-DG formula was observed to directly target AKT, TLR4, caspase-3, PI3K, mTOR, p38 MAPK, VEGF, iNOS, Nrf2, BDNF, NF-κB, Bcl-2, and Bax 13 targets and regulate targets through 13 miRNA. The PPI network and KEGG pathway enrichment analysis showed that the JH-CX-DG formula possess potential pharmacological effects including anti-inflammatory, improving microcirculation, and anti-tumor through the regulation of multiple pathways including PI3K/Akt, MAPK, Toll-like receptor, T cell receptor, EGFR, VEGFR, Apoptosis, HIF-1 (p < 0.05).Conclusion: The JH-CX-DG formula can exert beneficial pharmacological effects through multi-target and multi-pathway interactions. It can be effectively administered for the treatment of inflammatory diseases, microcirculation disorders, cardiovascular disease, and cancer. We found a new effective drug formula through analyzing the compatibility law and systemic pharmacological mechanism of JH. Our study provides a theoretical basis and directions for subsequent research on the JH-CX-DG formula.

scholarly journals Gene Expression Profiling of Type 2 Diabetes Mellitus by Bioinformatics Analysis

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.

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.

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.

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