Duodenal-Jejunal Exclusion Surgery Improves Type 2 Diabetes in a Rat Model Through Regulation of Early Glucose Metabolism

Transcriptome Changes and Metabolic Outcomes After Bariatric Surgery in Adults With Obesity and Type 2 Diabetes

Context

Bariatric surgery has been shown to be effective in inducing complete remission of type 2 diabetes in adults with obesity. However, its efficacy in achieving complete diabetes remission remains variable and difficult to predict before surgery.

Objective

We aimed to characterize bariatric surgery-induced transcriptome changes associated with diabetes remission and the predictive role of the baseline transcriptome.

Methods

We performed a whole-genome microarray in peripheral mononuclear cells at baseline (before surgery) and 2 and 12 months after bariatric surgery in a prospective cohort of 26 adults with obesity and type 2 diabetes. We applied machine learning to the baseline transcriptome to identify genes that predict metabolic outcomes. We validated the microarray expression profile using a real-time polymerase chain reaction.

Results

Sixteen patients entered diabetes remission at 12 months and 10 did not. The gene-expression analysis showed similarities and differences between responders and nonresponders. The difference included the expression of critical genes (SKT4, SIRT1, and TNF superfamily), metabolic and signaling pathways (Hippo, Sirtuin, ARE-mediated messenger RNA degradation, MSP-RON, and Huntington), and predicted biological functions (β-cell growth and proliferation, insulin and glucose metabolism, energy balance, inflammation, and neurodegeneration). Modeling the baseline transcriptome identified 10 genes that could hypothetically predict the metabolic outcome before bariatric surgery.

Conclusion

The changes in the transcriptome after bariatric surgery distinguish patients in whom diabetes enters complete remission from those who do not. The baseline transcriptome can contribute to the prediction of bariatric surgery-induced diabetes remission preoperatively.

Effect of duodenal-jejunal bypass on diabetes in the early postoperative period

Metabolic surgery is an effective treatment for patients with type 2 diabetes mellitus (T2DM). The aim of this study was to investigate the effect of duodenal-jejunal bypass (DJB) in a rat model of T2DM during the early postoperative period. A rat model of non-obese T2DM was allocated to two groups: a sham group and a DJB group. On postoperative day 1 (1POD), oral glucose tolerance testing (OGTT) was performed and the changes of glucose transporter expressions in the small intestine was evaluated. [18F]-fluorodeoxyglucose ([18]-FDG) uptake was measured in sham- and DJB-operated rats using positron emission tomography-computed tomography (PET-CT). DJB improved the glucose tolerance of the rats on 1POD. The expression of sodium-glucose cotransporter 1 (SGLT1) and glucose transporter 1 (GLUT1) was high, and that of GLUT2 was low in the alimentary limb (AL) of rats in the DJB group. PET-CT showed that [18F]-FDG uptake was high in the proximal jejunum of DJB-operated rats. These results may show that DJB improve glucose tolerance in very early postoperative period as the result of glucose accumulation in the AL because of changes in glucose transporter expression.

Investigating the change in gene expression profile of blood mononuclear cells post-laparoscopic sleeve gastrectomy in Chinese obese patients

BACKGROUND

Laparoscopic sleeve gastrectomy (LSG) is a sustainable technique that effectively treats morbid obesity. However, the molecular mechanisms underlying the improvement of metabolic health following this process warrants more investigation. This study investigates LSG-related molecules and uses bulk RNA-sequencing high-throughput analysis to unravel their regulatory mechanisms.

METHODS

Peripheral blood mononuclear cells (PBMC) were collected from ten obese patients with BMI ≥ 32.5 kg/m² in the Department of General Surgery of Kunming First People's Hospital. After LSG, patients were followed up for one month, and blood samples were retaken. Blood samples from ten patients before and after LSG and bulk RNA-Seq data were analyzed in this study. LSG-associated gene expression was detected by weighted gene coexpression network analysis (WGCNA) and differential analysis. Subsequently, essential signature genes were identified using logistic least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) algorithms. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and single-sample gene set enrichment analysis (ssGSEA) were utilized to reveal the potential functions of the target genes. Furthermore, the Pearson correlation of signature genes with leptin and lipocalin was also explored. Finally, we constructed a robust endogenous RNA (ceRNA) network based on miRWalk and starBase databases.

RESULTS

We identified 18 overlapping genes from 91 hub genes, and 165 differentially expressed mRNAs (DE-mRNA), which were revealed to be significantly associated with immune cells, immune response, inflammatory response, lipid storage, and localization upon functional enrichment analysis. Three signature genes, IRF1, NFKBIA, and YRDC, were identified from the 18 overlapping genes by LASSO and SVM-REF algorithms. The logistic regression model based on the three signature genes highlighted how robustly they discriminated between samples. ssGSEA indicated these genes to be involved in lipid metabolism and degradation pathways. Moreover, leptin levels were significantly reduced in patients undergoing LSG, and NFKBIA significantly negatively correlated with leptin. Finally, we identified how the long non-coding RNA (lncRNA) ATP2B1-AS1 regulated the expression of the signature genes by competitively binding to six microRNAs (miRNAs), which were hsa-miR-6509-5p, hsa-miR-330-5P, hsa-miR-154-5P, hsa-miR-145-5P, hsa-miR4726-5P and hsa-miR-134-5P.

CONCLUSION

This study identified three critical regulatory genes significantly differentiated between patients before and after LSG treatment and highlighted their potentially crucial role after bariatric surgery. This provides novel insights to increase our understanding of the underlying mechanisms of weight loss and associated metabolic improvement after bariatric surgery.

A short review on the features of the non-obese diabetic Goto-Kakizaki rat intestine

The Goto-Kakizaki (GK) rat is a non-obese experimental model of type 2 diabetes mellitus (T2DM) that allows researchers to monitor diabetes-induced changes without jeopardizing the effects of obesity. This rat strain exhibits notable gastrointestinal features associated with T2DM, such as marked alterations in intestinal morphology, reduced intestinal motility, slow transit, and modified microbiota compared to Wistar rats. The primary treatments for diabetic patients include administration of hypoglycemic agents and insulin, and lifestyle changes. Emerging procedures, including alternative therapies, metabolic surgeries, and modulation of the intestinal microbiota composition, have been shown to improve the diabetic state of GK rats. This review describes the morpho-physiological diabetic-associated features of the gastrointestinal tract (GIT) of GK rats. We also describe promising strategies, e.g., metabolic surgery and modulation of gut microbiota composition, used to target the GIT of this animal model to improve the diabetic state.