scholarly journals Molecular mechanisms linking peri-implantitis and type 2 diabetes mellitus revealed by transcriptomic analysis

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7124 ◽  
Author(s):  
Tianliang Yu ◽  
Aneesha Acharya ◽  
Nikos Mattheos ◽  
Simin Li ◽  
Dirk Ziebolz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Signaling Pathway ◽  
Cross Talk ◽  
Molecular Mechanisms ◽  
Hub Genes ◽  
Ppi Networks

Aims To explore molecular mechanisms that link peri-implantitis and type 2 diabetes mellitus (T2DM) by bioinformatic analysis of publicly available experimental transcriptomic data. Materials and methods Gene expression data from peri-implantitis were downloaded from the Gene Expression Omnibus database, integrated and differentially expressed genes (DEGs) in peri-implantitis were identified. Next, experimentally validated and computationally predicted genes related to T2DM were downloaded from the DisGeNET database. Protein–protein interaction network (PPI) pairs of DEGs related to peri-implantitis and T2DM related genes were constructed, “hub” genes and overlapping DEG were determined. Functional enrichment analysis was used to identify significant shared biological processes and signaling pathways. The PPI networks were subjected to cluster and specific class analysis for identifying “leader” genes. Module network analysis of the merged PPI network identified common or cross-talk genes connecting the two networks. Results A total of 92 DEGs overlapped between peri-implantitis and T2DM datasets. Three hub genes (IL-6, NFKB1, and PIK3CG) had the highest degree in PPI networks of both peri-implantitis and T2DM. Three leader genes (PSMD10, SOS1, WASF3), eight cross-talk genes (PSMD10, PSMD6, EIF2S1, GSTP1, DNAJC3, SEC61A1, MAPT, and NME1), and one signaling pathway (IL-17 signaling) emerged as peri-implantitis and T2DM linkage mechanisms. Conclusions Exploration of available transcriptomic datasets revealed IL-6, NFKB1, and PIK3CG expression along with the IL-17 signaling pathway as top candidate molecular linkage mechanisms between peri-implantitis and T2DM.

scholarly journals Transcriptional Profiling and Biological Pathway(s) Analysis of Type 2 Diabetes Mellitus in a Pakistani Population

2020 ◽  
Vol 17 (16) ◽  
pp. 5866
Author(s):  
Zarish Noreen ◽  
Christopher A. Loffredo ◽  
Attya Bhatti ◽  
Jyothirmai J. Simhadri ◽  
Gail Nunlee-Bland ◽  
...  
Keyword(s):  
Gene Expression ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Mitochondrial Dysfunction ◽  
Signaling Pathway ◽  
Health Concern ◽  
Receptor Signaling ◽  
Small Pilot Study

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.

scholarly journals Constitution of a comprehensive phytochemical profile and network pharmacology based investigation to decipher molecular mechanisms of Teucrium polium L. in the treatment of type 2 diabetes mellitus

PeerJ ◽  
2020 ◽  
Vol 8 ◽  
pp. e10111
Author(s):  
Vahap Murat Kutluay ◽  
Neziha Yagmur Diker
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Signaling Pathway ◽  
Insulin Signaling ◽  
Molecular Mechanisms ◽  
Network Pharmacology ◽  
Teucrium Polium ◽  
Phytochemical Profile

Background Type 2 diabetes mellitus (T2DM) is a metabolic disease affecting a huge population worldwide. Teucrium polium L. has been used as a folk medicine for the treatment of T2DM in Anatolia, Turkey. The antihyperglycemic effect of the plant was reported previously. However, there was no detailed study on the underlying molecular mechanisms. In this study, we generated a research plan to clarify the active constituents of the extract and uncover the molecular mechanisms using network pharmacology analysis. Methods For this purpose, we composed a dataset of 126 compounds for the phytochemical profile of the aerial parts of T. polium. Drug-likeness of the compounds was evaluated, and 52 compounds were selected for further investigation. A total of 252 T2DM related targets hit by selected compounds were subjected to DAVID database. Results The KEGG pathway analysis showed enrichment for the TNF signaling pathway, insulin resistance, the HIF-1 signaling pathway, apoptosis, the PI3K-AKT signaling pathway, the FOXO signaling pathway, the insulin signaling pathway, and type 2 diabetes mellitus which are related to T2DM . AKT1, IL6, STAT3, TP53, INS, and VEGFA were found to be key targets in protein-protein interaction. Besides these key targets, with this study the role of GSK3β, GLUT4, and PDX1 were also discussed through literature and considered as important targets in the antidiabetic effect of T. polium. Various compounds of T. polium were shown to interact with the key targets activating PI3K-AKT and insulin signaling pathways. Conclusions According to these findings, mainly phenolic compounds were identified as the active components and IRS1/PI3K/AKT signaling and insulin resistance were identified as the main pathways regulated by T. polium. This study reveals the relationship of the compounds in T. polium with the targets of T2DM in human. Our findings suggested the use of T. polium as an effective herbal drug in the treatment of T2DM and provides new insights for further research on the antidiabetic effect of T. polium.

scholarly journals Role of TLR4/MyD88/NF-κB signaling in heart and liver-related complications in a rat model of type 2 diabetes mellitus

2021 ◽  
Vol 49 (3) ◽  
pp. 030006052199759
Author(s):  
Jiajia Tian ◽  
Yanyan Zhao ◽  
Lingling Wang ◽  
Lin Li
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Signaling Pathway ◽  
Rat Model ◽  
Fasting Blood Glucose ◽  
Diabetic Rats ◽  
Primary Response ◽  
Monocyte Chemoattractant Protein 1

Aims To analyze expression of members of the Toll-like receptor (TLR)4/myeloid differentiation primary response 88 (MyD88)/nuclear factor (NF)-κB signaling pathway in the heart and liver in a rat model of type 2 diabetes mellitus (T2DM). Our overall goal was to understand the underlying pathophysiological mechanisms. Methods We measured fasting blood glucose (FBG) and insulin (FINS) in a rat model of T2DM. Expression of members of the TLR4/MyD88/NF-κB signaling pathway as well as downstream cytokines was investigated. Levels of mRNA and protein were assessed using quantitative real-time polymerase chain reaction and western blotting, respectively. Protein content of tissue homogenates was assessed using enzyme-linked immunosorbent assays. Results Diabetic rats had lower body weights, higher FBG, higher FINS, and higher intraperitoneal glucose tolerance than normal rats. In addition, biochemical indicators related to heart and liver function were elevated in diabetic rats compared with normal rats. TLR4 and MyD88 were involved in the occurrence of T2DM as well as T2DM-related heart and liver complications. TLR4 caused T2DM-related heart and liver complications through activation of NF-κB. Conclusions TLR4/MyD88/NF-κB signaling induces production of tumor necrosis factor-α, interleukin-6, and monocyte chemoattractant protein-1, leading to the heart- and liver-related complications of T2DM.

scholarly journals Insulin Resistance and Diabetes Mellitus in Alzheimer’s Disease

Cells ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 1236
Author(s):  
Jesús Burillo ◽  
Patricia Marqués ◽  
Beatriz Jiménez ◽  
Carlos González-Blanco ◽  
Manuel Benito ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Alzheimer’S Disease ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Alzheimer's Disease ◽  
Type 2 Diabetes Mellitus ◽  
Insulin Signaling ◽  
Molecular Mechanisms ◽  
Progressive Disease

Type 2 diabetes mellitus is a progressive disease that is characterized by the appearance of insulin resistance. The term insulin resistance is very wide and could affect different proteins involved in insulin signaling, as well as other mechanisms. In this review, we have analyzed the main molecular mechanisms that could be involved in the connection between type 2 diabetes and neurodegeneration, in general, and more specifically with the appearance of Alzheimer’s disease. We have studied, in more detail, the different processes involved, such as inflammation, endoplasmic reticulum stress, autophagy, and mitochondrial dysfunction.

scholarly journals Use of Network Pharmacology to Explore the Mechanism of Gegen (Puerariae lobatae Radix) in the Treatment of Type 2 Diabetes Mellitus Associated with Hyperlipidemia

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Guozhen Yuan ◽  
Shuai Shi ◽  
Qiulei Jia ◽  
Jingjing Shi ◽  
Shuqing Shi ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Signaling Pathway ◽  
Fluid Shear Stress ◽  
Chinese Herbs ◽  
Network Pharmacology ◽  
Biological Processes ◽  
Active Ingredients

Rapid increases in metabolic disorders, such as type 2 diabetes mellitus (T2DM) and hyperlipidemia, are becoming a substantial challenge to worldwide public health. Traditional Chinese medicine has a long history and abundant experience in the treatment of diabetes and hyperlipidemia, and Puerariae lobatae Radix (known as Gegen in Chinese) is one of the most prevalent Chinese herbs applied to treat these diseases. The underlying mechanism by which Gegen simultaneously treats diabetes and hyperlipidemia, however, has not been clearly elucidated to date. Therefore, we systematically explored the potential mechanism of Gegen in the treatment of T2DM complicated with hyperlipidemia based on network pharmacology. We screened the potential targets of Gegen, T2DM, and hyperlipidemia in several online databases. Then, the hub targets were analyzed by performing protein-protein interaction, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment assays, and finally, the complicated connections among compounds, targets, and pathways were visualized in Cytoscape. We found that isoflavones, including daidzein, genistein, and puerarin, as well as β-sitosterol, are the key active ingredients of Gegen responsible for its antidiabetic and antihyperlipidemia effects, which mainly target AKR1B1, EGFR, ESR, TNF, NOS3, MAPK3, PPAR, CYP19A1, INS, IL6, and SORD and multiple pathways, such as the PI3K-Akt signaling pathway; the AGE-RAGE signaling pathway in diabetic complications, fluid shear stress, and atherosclerosis; the PPAR signaling pathway; insulin resistance; the HIF-1 signaling pathway; the TNF signaling pathway; and others. These active ingredients also target multiple biological processes, including the regulation of glucose and lipid metabolism, the maintenance of metabolic homeostasis, and anti-inflammatory and antioxidant pathways. In conclusion, Gegen is a promising therapeutic phytomedicine for T2DM with hyperlipidemia that targets multiple proteins, biological processes, and pathways.

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 Pathophysiology of Type 2 Diabetes Mellitus

2020 ◽  
Vol 21 (17) ◽  
pp. 6275 ◽  
Author(s):  
Unai Galicia-Garcia ◽  
Asier Benito-Vicente ◽  
Shifa Jebari ◽  
Asier Larrea-Sebal ◽  
Haziq Siddiqi ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Insulin Release ◽  
Molecular Mechanisms ◽  
Metabolic Memory ◽  
Insulin Metabolism ◽  
Insulin Synthesis

Type 2 Diabetes Mellitus (T2DM), one of the most common metabolic disorders, is caused by a combination of two primary factors: defective insulin secretion by pancreatic β-cells and the inability of insulin-sensitive tissues to respond appropriately to insulin. Because insulin release and activity are essential processes for glucose homeostasis, the molecular mechanisms involved in the synthesis and release of insulin, as well as in its detection are tightly regulated. Defects in any of the mechanisms involved in these processes can lead to a metabolic imbalance responsible for the development of the disease. This review analyzes the key aspects of T2DM, as well as the molecular mechanisms and pathways implicated in insulin metabolism leading to T2DM and insulin resistance. For that purpose, we summarize the data gathered up until now, focusing especially on insulin synthesis, insulin release, insulin sensing and on the downstream effects on individual insulin-sensitive organs. The review also covers the pathological conditions perpetuating T2DM such as nutritional factors, physical activity, gut dysbiosis and metabolic memory. Additionally, because T2DM is associated with accelerated atherosclerosis development, we review here some of the molecular mechanisms that link T2DM and insulin resistance (IR) as well as cardiovascular risk as one of the most important complications in T2DM.

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