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Project description:Sleeve gastrectomy (SG) can improve diabetes mellitus dramatically. However, the mechanisms remain largely undetermined. With the advancement of in-depth bioinformatic analysis, non-coding RNAs especially circular RNAs(circRNAs), have been implicated in many biological processes. To explore whether circRNAs mediate the amelioration of diabetes mellitus after SG, we subjected liver samples of diabetic rats after SG and shame operations for RNA sequencing. Through RNA sequencing, we identified a dramatically differentially expressed profile of 107 circRNAs. Some of these specific circRNAs were only expressed in diabetic rats after SG, which may be promising biological markers of SG prognosis.
2023-11-23 | GSE162013 | GEO
Project description:Sleeve gastrectomy (SG) could improve diabetes mellitus dramatically. However, the mechanisms remain largely undetermined. With the advancement of in-depth bioinformatic analysis, non-coding RNAs especially long non-coding RNAs(lncRNAs), have been implicated in many biological processes. To explore whether lncRNAs mediate the amelioration of diabetes mellitus condition after SG, we subjected liver samples of diabetic rats after SG and shame operations for RNA sequencing. Further, interaction network between lncRNAs and mRNAs/microRNAs(miRNAs) were constructed to infer the function of lncRNAs in diabetic remission, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Through RNA sequencing, we identified more than 9000 lncRNAs with a dramatically differentially expressed profile of 147 lncRNAs. Some of these specific lncRNAs were only expressed in diabetic rats after SG, which may be promising biological markers of diabetic remission and SG prognosis. Through co-analysis between lncRNAs and mRNAs, 20 potential target genes of lncRNAs were screened out. Further bioinformatic analysis indicated the differentially expressed lncRNAs harbored various miRNAs binding sites and three representative lncRNA-miRNA networks of lnc50 and lnc136 were constructed. The KEGG analysis revealed that differential expressed lncRNAs were mainly related to mitogen-activated protein kinase (MAPK) pathway. These results demonstrated that SG dramatically altered expression profile of lncRNAs on diabetes mellitus, and altered lncRNAs expression may contribute to the improvement on diabetic remission through MAPK pathway by interaction with mRNA/miRNA. Our findings provide valuable resources for molecular mechanism of diabetic remission after SG and is benefit for development of lncRNAs-based diagnostic and therapeutic interventions of diabetes mellitus.
2023-11-23 | GSE162018 | GEO
Project description:Next generation sequencing of circular and lnc RNAs in diabetes mellitus rats after sleeve gastrectomy
| PRJNA680313 | ENA
Project description:Next generation sequencing of circular RNAs in diabetes mellitus rats after sleeve gastrectomy
| PRJNA680322 | ENA
Project description:Next generation sequencing of long non-coding RNAs in diabetes mellitus rats after sleeve gastrectomy
| PRJNA680323 | ENA
Project description:Background Single-anastomosis duodenal-ileal bypass with sleeve gastrectomy (SADI-S) is one of the most effective bariatric procedures in the treatment of type 2 diabetes mellitus (T2DM). However, the mechanisms by which SADI-S improves T2DM are not well-known. Objective To explore the effects of SADI-S on metabolites in the stool of rats with T2DM. Methods Twenty rats were fed on high-fat diet and administered with a low-dose (30mg/kg) of streptozotocin to establish T2DM models. The rats were then randomly assigned to the SADI-S group (n=10) and sham operation group (n=9). Stool samples were collected from all rats at 8 weeks after surgery and stored at -80 °C. Metabolomics analysis was performed to identify differential metabolites through ultra- performance liquid chromatography-mass spectrometry. Results At 8-week after surgery, rats of the SADI-S group showed significantly decreased fasting blood glucose, glucose tolerance test 2-hour, glycated haemoglobin, and body weight compared with those of the sham group. A total of 245 differential metabolites were identified between the two groups. Among them, 16 metabolites such as branched-chain amino acids (valine), aromatic amino acid (phenylalanine), bile acid (cholic acid, lithocholic acid, and β-muricholic acid), short-chain fatty acid (isobutyric acid), and phospholipid [lysoPE(17:0), lysoPE(20:3) and lysoPS(16:0)] were associated to the T2DM remission after SADI-S. Conclusion SADI-S improves T2DM in rats by regulating phenylalanine biosynthesis, valine, phenylalanine, alanine, glutamate, proline, bile acid, and phospholipid metabolism pathways.
| S-EPMC9530139 | biostudies-literature
Project description:Diabetes mellitus (DM) is an endocrine disorder characterized by a relative or absolute lack of insulin due to the dysfunction or destruction of β-cells. DM is one of the fastest growing challenges to global health in the 21st century and places a tremendous burden on affected individuals and their families and countries. Although insulin and antidiabetic drugs have been used to treat DM, a radical cure for the disease is unavailable. The pathogenesis of DM remains unclear. Emerging roles of circular RNAs (circRNAs) in DM have become a subject of global research. CircRNAs have been verified to participate in the onset and progression of DM, implying their potential roles as novel biomarkers and treatment tools. In the present review, we briefly introduce the characteristics of circRNAs. Next, we focus on specific roles of circRNAs in type 1 diabetes mellitus, type 2 diabetes mellitus, gestational diabetes mellitus and diabetes-associated complications.
| S-EPMC9376240 | biostudies-literature
Project description:BackgroundNo currently available biomarkers or treatment regimens fully meet therapeutic needs of type 1 diabetes mellitus (T1DM). Circular RNA (circRNA) is a recently identified class of stable noncoding RNA that have been documented as potential biomarkers for various diseases. Our objective was to identify and analyze plasma circRNAs altered in T1DM.MethodsWe used microarray to screen differentially expressed plasma circRNAs in patients with new onset T1DM (n=3) and age-/gender-matched healthy controls (n=3). Then, we selected six candidates with highest fold-change and validated them by quantitative real-time polymerase chain reaction in independent human cohort samples (n=12). Bioinformatic tools were adopted to predict putative microRNAs (miRNAs) sponged by these validated circRNAs and their downstream messenger RNAs (mRNAs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to gain further insights into T1DM pathogenesis.ResultsWe identified 68 differentially expressed circRNAs, with 61 and seven being up- and downregulated respectively. Four of the six selected candidates were successfully validated. Curations of their predicted interacting miRNAs revealed critical roles in inflammation and pathogenesis of autoimmune disorders. Functional relations were visualized by a circRNA-miRNA-mRNA network. GO and KEGG analyses identified multiple inflammation-related processes that could be potentially associated with T1DM pathogenesis, including cytokine-cytokine receptor interaction, inflammatory mediator regulation of transient receptor potential channels and leukocyte activation involved in immune response.ConclusionOur study report, for the first time, a profile of differentially expressed plasma circRNAs in new onset T1DM. Further in silico annotations and bioinformatics analyses supported future application of circRNAs as novel biomarkers of T1DM.
| S-EPMC7801755 | biostudies-literature
Project description:ObjectiveThis study aimed to evaluate microRNAs (miRNAs) as predictive biomarkers for type 2 diabetes (T2D) remission 12 months after sleeve gastrectomy (SG).MethodsA total of 179 serum miRNAs were profiled, and 26 clinical variables were collected from 46 patients. Two patients were later excluded because of hemolysis, and six patients with unclear remission status were set aside to evaluate the prediction models. The remaining 38 patients were included for model building. Variable selection was done using different approaches, including Least Absolute Shrinkage and Selection Operator (LASSO). Prediction models were then developed using LASSO and assessed in the validation set.ResultsA total of 26 out of 38 patients achieved T2D remission 12 months after SG. The prediction model with only clinical variables misclassified two patients, which were correctly classified using miRNAs. Two miRNA-only models achieved an accuracy of one but performed poorly for the validation set. The best miRNA model was a mixed model (accuracy: 0.974) containing four miRNAs (hsa-miR-32-5p, hsa-miR-382-5p, hsa-miR-1-3p, and hsa-miR-21-5p) and four clinical variables (T2D medication, sex, age, and fasting blood glucose). These miRNAs are involved in pathways related to obesity and insulin resistance.ConclusionsThis study suggests that four serum miRNAs might be predictive biomarkers for T2D remission 12 months after SG, but further validation studies are needed.
| S-EPMC9306824 | biostudies-literature
Project description:This dataset consists of single-cell RNA-seq (10X) data of pancreatic islets isolated from healthy and diabetic db/db mice that underwent VSG surgery, Sham surgery (Control) and Sham surgery + pair-feeding (Calorie-restriction control).
2021-09-01 | GSE174194 | GEO