scholarly journals Altered gene expression and repressed markers of autophagy in skeletal muscle of insulin resistant patients with type 2 diabetes

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Andreas Buch Møller ◽  
Ulla Kampmann ◽  
Jakob Hedegaard ◽  
Kasper Thorsen ◽  
Iver Nordentoft ◽  
...  
Keyword(s):  
Gene Expression ◽  
Type 2 Diabetes ◽  
Skeletal Muscle ◽  
Insulin Resistant ◽  
Altered Gene Expression ◽  
Altered Gene

scholarly journals Loss of ARNT/HIF1β Mediates Altered Gene Expression and Pancreatic-Islet Dysfunction in Human Type 2 Diabetes

Cell ◽  
2005 ◽  
Vol 122 (3) ◽  
pp. 337-349 ◽  
Author(s):  
Jenny E. Gunton ◽  
Rohit N. Kulkarni ◽  
SunHee Yim ◽  
Terumasa Okada ◽  
Wayne J. Hawthorne ◽  
...  
Keyword(s):  
Gene Expression ◽  
Type 2 Diabetes ◽  
Pancreatic Islet ◽  
Altered Gene Expression ◽  
Human Type ◽  
Islet Dysfunction ◽  
Altered Gene

Role of potential COVID-19 immune system associated genes and the potential pathways linkage with type-2 diabetes

2021 ◽  
Vol 24 ◽  
Author(s):  
Nawal Helmi ◽  
Dalia Alammari ◽  
Mohammad Mobashir
Keyword(s):  
Gene Expression ◽  
Type 2 Diabetes ◽  
Immune System ◽  
Expression Patterns ◽  
Osteoclast Differentiation ◽  
Gene Expression Pattern ◽  
Common Source ◽  
Altered Gene Expression ◽  
Altered Gene

Background: Coronavirus is an enveloped positive-sense RNA virus and is characterized by club-like spikes projecting from its surface which is commonly associated with acute respiratory infections in humans but its ability to infect multiple host species and multiple diseases brings it to a complex pathogen group. The frequent interactions of wild animals with humans it is more prevalent a common source of such infections and SARS—CoV and MERS—CoV are the zoonotic pathogens among the leading cause of severe respiratory diseases in humans. Aim: The major purpose of this study was to study the gene expression profiling for those human samples which are infected with coronavirus or uninfected and compare the differential expression patterns and its functional impact. Methods: For this purpose, the previously studied samples have been collected from public database and the study had been performed and it includes gene expression analysis, pathway analysis, and the network-level understanding. The analysis presents the data for the differentially expressed genes, enriched pathways and the networks for the potential genes and gene sets. In terms of gene expression and the linkage of COVID-19 with type-2 diabetes. Results: We observe that there are a large number of genes which show altered gene expression pattern than the normal for coronavirus infection while in terms of pathways it appears that there are few sets of functions which are affected due to altered gene expression and they infer to infection, inflammation, and the immune system. Conclusions: Based on our study, we conclude that the potential genes which are affected due to infection are NFKBIA, MYC, FOXO3, BIRC3, ICAM1, IL8, CXCL1/2/5, GADD45A, RELB, SGK1, AREG, BBC3, DDIT3/4, EGR1, MTHFD2, and SESN2 and the functional changes are mainly associated with these pathways TNF, cytokine, NF—kB, TLR, TCR, BCR, Foxo, and TGF signaling pathways are among them and there are additional pathways such as hippo signaling, apoptosis, estrogen signaling, regulating pluropotency of stem cells, ErbB, Wnt, p53, cAMP, MAPK, PI3K—AKT, oxidative phosphorylation, protein processing in endoplasmic reticulum, prolactin signaling, adipocytokine, neurotrophine signaling, and longevity regulating pathways. SMARCD3, PARL, GLIPR1, STAT2, PMAIP1, GP1BA, and TOX genes and PI3K-Akt, focal adhesion, Foxo, phagosome, adrenergic, osteoclast differentiation, platelet activation, insulin, cytokine-cytokine interaction, apoptosis, ECM, JAK-STAT, and oxytocine signaling appear as the linkage between COVID-19 and Type-2 diabetes.

scholarly journals Analysis of gene expression profiles in insulin-sensitive tissues from pre-diabetic and diabetic Zucker diabetic fatty rats

2005 ◽  
Vol 34 (2) ◽  
pp. 299-315 ◽  
Author(s):  
Young Ho Suh ◽  
Younyoung Kim ◽  
Jeong Hyun Bang ◽  
Kyoung Suk Choi ◽  
June Woo Lee ◽  
...  
Keyword(s):  
Gene Expression ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Skeletal Muscle ◽  
Adipose Tissue ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Zucker Diabetic Fatty Rats ◽  
Zdf Rats

Insulin resistance occurs early in the disease process, preceding the development of type 2 diabetes. Therefore, the identification of molecules that contribute to insulin resistance and leading up to type 2 diabetes is important to elucidate the molecular pathogenesis of the disease. To this end, we characterized gene expression profiles from insulin-sensitive tissues, including adipose tissue, skeletal muscle, and liver tissue of Zucker diabetic fatty (ZDF) rats, a well characterized type 2 diabetes animal model. Gene expression profiles from ZDF rats at 6 weeks (pre-diabetes), 12 weeks (diabetes), and 20 weeks (late-stage diabetes) were compared with age- and sex-matched Zucker lean control (ZLC) rats using 5000 cDNA chips. Differentially regulated genes demonstrating > 1.3-fold change at age were identified and categorized through hierarchical clustering analysis. Our results showed that while expression of lipolytic genes was elevated in adipose tissue of diabetic ZDF rats at 12 weeks of age, expression of lipogenic genes was decreased in liver but increased in skeletal muscle of 12 week old diabetic ZDF rats. These results suggest that impairment of hepatic lipogenesis accompanied with the reduced lipogenesis of adipose tissue may contribute to development of diabetes in ZDF rats by increasing lipogenesis in skeletal muscle. Moreover, expression of antioxidant defense genes was decreased in the liver of 12-week old diabetic ZDF rats as well as in the adipose tissue of ZDF rats both at 6 and 12 weeks of age. Cytochrome P450 (CYP) genes were also significantly reduced in 12 week old diabetic liver of ZDF rats. Genes involved in glucose utilization were downregulated in skeletal muscle of diabetic ZDF rats, and the hepatic gluconeogenic gene was upregulated in diabetic ZDF rats. Genes commonly expressed in all three tissue types were also observed. These profilings might provide better fundamental understanding of insulin resistance and development of type 2 diabetes.

Abstract TMP32: Transcriptome Changes of Brain Myeloid Cells After Ischemic Stroke in Type 2 Diabetic Mice

Stroke ◽  
2020 ◽  
Vol 51 (Suppl_1) ◽  
Author(s):  
Shunsuke Omodaka ◽  
Atsushi Kanoke ◽  
Suwei Wong ◽  
Dvir Aran ◽  
Jialing Liu
Keyword(s):  
Gene Expression ◽  
Antigen Processing ◽  
Mononuclear Cells ◽  
Myeloid Cells ◽  
Enrichment Analysis ◽  
Marker Genes ◽  
Sham Operation ◽  
Altered Gene Expression ◽  
Altered Gene

Introduction: Type 2 diabetes mellitus (T2DM) is associated with poor outcome after stroke. Brain myeloid cells are considered to play a pivotal role in modulating brain damage and recovery after stroke, but how myeloid response to stroke under diabetic condition is largely unclear. We used single-cell RNA sequencing (scRNA seq) to determine the transcriptome profiles of brain myeloid cells under diabetic and ischemic conditions using T2DM mouse model. Hypothesis: The altered gene expression in the brain myeloid cells under diabetic condition leads to the aggravation of ischemic brain injury. Methods: We performed scRNA seq in Percoll gradient-isolated brain mononuclear cells from middle-aged db/db and db/+ mice three days after direct middle cerebral artery occlusion (MCAO) or sham-operation. Clusters of brain myeloid cells were predominantly annotated as macrophages (mp) or microglia (mg) according to the expression of marker genes in each cell type. We identified DM-unique differentially expressed genes (DEGs) and stroke-unique DEGs, and assessed the biological role of these DEGs by enrichment analysis. Results: Myeloid cell population was increased in DM ( db/db without MCAO; mp 37.3% mg 10.6%) and stroke ( db/+ with MCAO; mp 26.2% mg 33.2%) group compared to control ( db/+ without MCAO; mp 3.4% mg 0.8%) group. In macrophages, 91 DM-unique (64 up- and 27 down-regulated) and 464 stroke-unique (458 up- and 6 down-regulated) DEGs were identified, whereas 258 stroke-unique (254 up- and 4 down-regulated) DEGs were identified in microglia. Enrichment analysis revealed that DM-unique down-regulated DEGs in macrophages were related to MHC class II antigen processing involved in Staphylococcus aureus infection pathway, indicating a possible relationship between immunosuppression and stroke aggravation in diabetes. DM-unique and stroke-unique up-regulated DEGs were related to oxidative phosphorylation, phagocytosis, and protein metabolism. Conclusions: The present study demonstrated altered gene expression profile and molecular network of brain myeloid cells in response to diabetic and ischemic conditions by scRNA seq, providing a clue to the underlying mechanism of the adverse effect of T2DM on stroke.

A gene expression signature for insulin resistance

2011 ◽  
Vol 43 (3) ◽  
pp. 110-120 ◽  
Author(s):  
Nicky Konstantopoulos ◽  
Victoria C. Foletta ◽  
David H. Segal ◽  
Katherine A. Shields ◽  
Andrew Sanigorski ◽  
...  
Keyword(s):  
Gene Expression ◽  
Insulin Resistance ◽  
Type 2 Diabetes ◽  
Large Scale ◽  
Gene Expression Signature ◽  
Channel Blockers ◽  
Expression Signature ◽  
Insulin Resistant ◽  
Novel Strategy

Insulin resistance is a heterogeneous disorder caused by a range of genetic and environmental factors, and we hypothesize that its etiology varies considerably between individuals. This heterogeneity provides significant challenges to the development of effective therapeutic regimes for long-term management of type 2 diabetes. We describe a novel strategy, using large-scale gene expression profiling, to develop a gene expression signature (GES) that reflects the overall state of insulin resistance in cells and patients. The GES was developed from 3T3-L1 adipocytes that were made “insulin resistant” by treatment with tumor necrosis factor-α (TNF-α) and then reversed with aspirin and troglitazone (“resensitized”). The GES consisted of five genes whose expression levels best discriminated between the insulin-resistant and insulin-resensitized states. We then used this GES to screen a compound library for agents that affected the GES genes in 3T3-L1 adipocytes in a way that most closely resembled the changes seen when insulin resistance was successfully reversed with aspirin and troglitazone. This screen identified both known and new insulin-sensitizing compounds including nonsteroidal anti-inflammatory agents, β-adrenergic antagonists, β-lactams, and sodium channel blockers. We tested the biological relevance of this GES in participants in the San Antonio Family Heart Study ( n = 1,240) and showed that patients with the lowest GES scores were more insulin resistant (according to HOMA_IR and fasting plasma insulin levels; P < 0.001). These findings show that GES technology can be used for both the discovery of insulin-sensitizing compounds and the characterization of patients into subtypes of insulin resistance according to GES scores, opening the possibility of developing a personalized medicine approach to type 2 diabetes.

Identification of Altered Gene Expression in Skeletal Muscle during Sepsis Using Differential Display

1996 ◽  
Vol 64 (1) ◽  
pp. 63-67 ◽  
Author(s):  
Gregory M. Tiao ◽  
Karen Hudson ◽  
Michael A. Lieberman ◽  
Josef E. Fischer ◽  
Per-Olof Hasselgren
Keyword(s):  
Gene Expression ◽  
Skeletal Muscle ◽  
Differential Display ◽  
Altered Gene Expression ◽  
Altered Gene
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