scholarly journals Cancer Signaling Transcriptome Is Upregulated in Type 2 Diabetes Mellitus

2020 ◽  
Vol 10 (1) ◽  
pp. 85
Author(s):  
Enrique Almanza-Aguilera ◽  
Álvaro Hernáez ◽  
Dolores Corella ◽  
Albert Sanllorente ◽  
Emilio Ros ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Signaling Pathways ◽  
Differentially Expressed Genes ◽  
Differentially Expressed ◽  
Log P ◽  
P Value ◽  
Z Score ◽  
Elderly Individuals ◽  
Cancer Signaling

We aimed to explore the differences in the whole transcriptome of peripheral blood mononuclear cells between elderly individuals with and without type 2 diabetes (T2D). We conducted a microarray-based transcriptome analysis of 19 individuals with T2D and 15 without. Differentially expressed genes according to linear models were submitted to the Ingenuity Pathway Analysis system to conduct a functional enrichment analysis. We established that diseases, biological functions, and canonical signaling pathways were significantly associated with T2D patients when their logarithms of Benjamini–Hochberg-adjusted p-value were >1.30 and their absolute z-scores were >2.0 (≥2.0 meant “upregulation” and ≤ −2.0 “downregulation”). Cancer signaling pathways were the most upregulated ones in T2D (z-score = 2.63, −log(p-value) = 32.3; 88.5% (n = 906) of the total differentially expressed genes located in these pathways). In particular, integrin (z-score = 2.52, −log(p-value) = 2.03) and paxillin (z-score = 2.33, −log(p-value) = 1.46) signaling pathways were predicted to be upregulated, whereas the Rho guanosine diphosphate (Rho-GDP) dissociation inhibitor signaling pathway was predicted to be downregulated in T2D individuals (z-score = −2.14, −log(p-value) = 2.41). Our results suggest that, at transcriptional expression level, elderly individuals with T2D present an increased activation of signaling pathways related to neoplastic processes, T-cell activation and migration, and inflammation.

scholarly journals Identification of Potential Therapeutic Targets in the Liver of Pioglitazone-Treated Type 2 Diabetes Sprague-Dawley Rats via Expression Profile Chip and iTRAQ Assay

2018 ◽  
Vol 2018 ◽  
pp. 1-9
Author(s):  
Zhong-Xia Lu ◽  
Wen-Jun Xu ◽  
Yang-Sheng Wu ◽  
Chang-Yu Li ◽  
Yi-Tao Chen
Keyword(s):  
Type 2 Diabetes ◽  
Blood Glucose ◽  
Differentially Expressed Genes ◽  
Fasting Blood Glucose ◽  
Treated Group ◽  
Differentially Expressed ◽  
Model Group ◽  
Sprague Dawley ◽  
Sprague Dawley Rats

The aim of the present study was to identify key antidiabetic nodes in the livers of pioglitazone-treated type 2 diabetes mellitus Sprague-Dawley rats by transcriptomic and proteomic analysis. Rats were randomly divided into the control, the diabetes model, and the pioglitazone-treated groups. After treatment with pioglitazone for 11 weeks, the effects on fasting blood glucose, body weight, and blood biochemistry parameters were evaluated. Microarray and iTRAQ analysis were used to determine the differentially expressed genes/proteins in rat livers. 1.5-fold changes in gene expression and 1.2-fold changes in protein were set as the screening criteria. After treatment with pioglitazone for 11 weeks, fasting blood glucose in pioglitazone-treated rats was significantly lower than that in the model group. There was a tendency for pioglitazone to reduce TC, TG, TP, ALB, BUN, and HDL-c levels. Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) were applied to analyze differentially expressed genes/proteins. Furthermore, Western blotting and RT-qPCR were used to validate the results of microarray and iTRAQ. In conclusion, Cyp7a1, Cp, and RT1-EC2 are differentially expressed genes/proteins since they showed a similar trend in rats in the model group and the pioglitazone-treated group.

scholarly journals Research Status of Differentially Expressed Noncoding RNAs in Type 2 Diabetes Patients

2020 ◽  
Vol 2020 ◽  
pp. 1-18
Author(s):  
Rou Shi ◽  
Yingjian Chen ◽  
Yuanjun Liao ◽  
Rang Li ◽  
Chunwen Lin ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Signaling Pathways ◽  
Insulin Signaling ◽  
Target Genes ◽  
Mononuclear Cells ◽  
Noncoding Rnas ◽  
Vascular Complications ◽  
Differentially Expressed ◽  
Circular Rnas

Aims. Noncoding RNAs (ncRNAs) play an important role in the occurrence and development of type 2 diabetes mellitus (T2DM). This paper summarized the current evidences of the involvement microRNAs, long noncoding RNAs (lncRNAs), and circular RNAs (circRNAs) in the differential expressions and their interaction with each other in T2DM. Methods. The differentially expressed miRNAs, lncRNAs, and circRNAs in the blood circulation (plasma, serum, whole blood, and peripheral blood mononuclear cells) of patients with T2DM were found in PubMed, GCBI, and other databases. The interactions between ncRNAs were predicted based on the MiRWalk and the DIANA Tools databases. The indirect and direct target genes of lncRNAs and circRNAs were predicted based on the starBase V2.0, DIANA Tools, and LncRNA-Target databases. Then, GO and KEGG analysis on all miRNA, lncRNA, and circRNA target genes was performed using the mirPath and Cluster Profile software package in R language. The lncRNA–miRNA and circRNA–miRNA interaction diagram was constructed with Cytoscape. The aim of this investigation was to construct a mechanism diagram of lncRNA involved in the regulation of target genes on insulin signaling pathways and AGE–RAGE signaling pathways of diabetic complications. Results. A total of 317 RNAs, 283 miRNAs, and 20 lncRNAs and circRNAs were found in the circulation of T2DM. Dysregulated microRNAs and lncRNAs were found to be involved in signals related to metabolic disturbances, insulin signaling, and AGE–RAGE signaling in T2DM. In addition, lncRNAs participate in the regulation of key genes in the insulin signaling and AGE–RAGE signaling pathways through microRNAs, which leads to insulin resistance and diabetic vascular complications. Conclusion. Noncoding RNAs participate in the occurrence and development of type 2 diabetes and lead to its vascular complications by regulating different signaling pathways.

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 The Tri-ponderal Mass Index is associated with adiposity in adolescent type 2 diabetes mellitus: a cross-sectional analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Haifa Alfaraidi ◽  
Brandy Wicklow ◽  
Allison B. Dart ◽  
Elizabeth Sellers ◽  
Jonathan McGavock ◽  
...  
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Metabolic Syndrome ◽  
Type 2 Diabetes Mellitus ◽  
Secondary Data ◽  
P Value ◽  
Z Score ◽  
Cross Sectional ◽  
The Metabolic Syndrome

AbstractPediatric type 2 diabetes mellitus (T2DM) patients are often overweight or obese, yet there are no validated clinical measures of adiposity to stratify cardiometabolic risk in this population. The tri-ponderal mass index (TMI, kg/m3) has recently been reported as a measure of adiposity in children, but there has been no validation of the association of TMI with adiposity in pediatric T2DM. We hypothesized that in children with T2DM, the TMI can serve as a more accurate measure of adiposity when compared to BMI z-score, and that it is associated with components of the metabolic syndrome. This is a cross-sectional secondary data analysis from the Improving Renal Complications in Adolescents with Type 2 Diabetes Through REsearch (iCARE) study (n = 116, age 10.20–17.90 years). Spearman’s correlations and multivariable regression were used in the analyses. When compared to DXA, TMI demonstrated significant correlation with total adiposity versus BMI z-score (TMI r = 0.74, p-value < 0.0001; BMI z-score r = − 0.08, p-value 0.403). In regression analyses, TMI was associated with WHtR (B = 35.54, 95% CI 28.81, 42.27, p-value < 0.0001), MAP dipping (B = 1.73, 95% CI 0.12, 3.33, p-value = 0.035), and HDL (B = − 5.83, 95% CI − 10.13, − 1.54, p-value = 0.008). In conclusion, TMI is associated with adiposity and components of the metabolic syndrome in pediatric T2DM patients.

scholarly journals A Transcriptional Sequencing Analysis of Islet Stellate Cell and Pancreatic Stellate Cell

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaohang Wang ◽  
Wei Li ◽  
Juan Chen ◽  
Sheng Zhao ◽  
Shanhu Qiu ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Differentially Expressed Genes ◽  
Stellate Cell ◽  
Differentially Expressed ◽  
Transcriptional Analysis ◽  
Sequencing Analysis ◽  
Pancreatic Stellate Cell ◽  
Genome Wide ◽  
Differential Expressed Genes

Background. Our previous studies have shown that islet stellate cell (ISC), similar to pancreatic stellate cell (PSC) in phenotype and biological characters, may be responsible for the islet fibrosis in type 2 diabetes. To further identify the differences between PSC and ISC and for better understanding of the physiological function of ISC, we employed genome-wide transcriptional analysis on the PSCs and ISCs of Wistar rats. Method. PSCs and ISCs from each rat were primarily cultured at the same condition. Genome-wide transcriptional sequence of stellate cells was generated. The identified differentially expressed genes were validated using RT-PCR. Results. 32 significant differentially expressed genes between PSCs and ISCs were identified. Moreover, collagen type 11a1 (COL11A1), was found to be expressed 2.91-fold higher in ISCs compared with PSCs, indicating that COL11A1 might be a potential key gene modulating the differences between PSC and ISC. Conclusions. Our study identified and validated the differences between PSC and ISC in genome-wide transcriptional scale, confirming the assumption that ISC and PSC are similar other than identical. Moreover, our data might be instrumental for further investigation of ISC and islet fibrosis, and some differential expressed genes may provide an insight into new therapeutic targets for type 2 diabetes.

563-P: Differentially Expressed Plasma miRNAs Are Closely Associated with the Presence of Microvascular Complications in Type 2 Diabetes: The 1000 Qatar-Omics Study Cohort

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 563-P
Author(s):  
AMMIRA S. AKIL ◽  
SUJITHA SUBASH PADMAJEYA ◽  
LAILA A. JERMAN ◽  
ALYA AL-KURBI ◽  
AMAL M. HUSSEIN ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Microvascular Complications ◽  
Differentially Expressed ◽  
Study Cohort ◽  
Plasma Mirnas

scholarly journals MicroRNAs and Oxidative Stress: An Intriguing Crosstalk to Be Exploited in the Management of Type 2 Diabetes

Antioxidants ◽  
2021 ◽  
Vol 10 (5) ◽  
pp. 802
Author(s):  
Teresa Vezza ◽  
Aranzazu M. de Marañón ◽  
Francisco Canet ◽  
Pedro Díaz-Pozo ◽  
Miguel Marti ◽  
...  
Keyword(s):  
Oxidative Stress ◽  
Type 2 Diabetes ◽  
Signaling Pathways ◽  
Current Knowledge ◽  
Critical Role ◽  
Cell Dysfunction ◽  
Non Coding Rnas ◽  
And Oxidative Stress ◽  
Molecular Crosstalk

Type 2 diabetes is a chronic disease widespread throughout the world, with significant human, social, and economic costs. Its multifactorial etiology leads to persistent hyperglycemia, impaired carbohydrate and fat metabolism, chronic inflammation, and defects in insulin secretion or insulin action, or both. Emerging evidence reveals that oxidative stress has a critical role in the development of type 2 diabetes. Overproduction of reactive oxygen species can promote an imbalance between the production and neutralization of antioxidant defence systems, thus favoring lipid accumulation, cellular stress, and the activation of cytosolic signaling pathways, and inducing β-cell dysfunction, insulin resistance, and tissue inflammation. Over the last few years, microRNAs (miRNAs) have attracted growing attention as important mediators of diverse aspects of oxidative stress. These small endogenous non-coding RNAs of 19–24 nucleotides act as negative regulators of gene expression, including the modulation of redox signaling pathways. The present review aims to provide an overview of the current knowledge concerning the molecular crosstalk that takes place between oxidative stress and microRNAs in the physiopathology of type 2 diabetes, with a special emphasis on its potential as a therapeutic target.

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