Integrative analyses of biomarkers and pathways for adipose tissue after bariatric surgery

Identification of differential immune cells and related diagnostic genes in patients with diabetic retinopathy

BACKGROUND

Diabetic retinopathy (DR) is a frequent microvascular abnormality associated with diabetes mellitus. The loss of retinal immunity is an important underlying mechanism of the DR pathogenesis, including the change in retinal immunosuppressive characteristics and the blood-retinal barrier disturbances. Therefore, this investigation screens immune-associated biomarkers in the retina of DR patients.

METHODS

In this investigation, the differential expression genes (DEGs) were acquired from Gene Expression Omnibus data GSE102485. The relative expression of 22 immune cell types in each sample was calculated by CIBERSORT analysis based on gene expression profile. The core module closely associated with immune infiltration was also screened by weighted gene co-expression network analysis (WGCNA). The overlapping DEGs and module genes were the differentially expressed immune-related genes (DEIRGs). With the help of the genes/proteins (STRING) database and MCODE plug-in, the protein-protein interaction (PPI) network hub genes were screened. Furthermore, the miRNA-hub genes and transcription factor (TF)-hub gene regulatory network were used to explain the possible signal pathways in DR. The hub genes verification was carried out by Polymerase Chain Reaction. Lastly, select CSF1R and its related pathway factor p-ERK1/2 to verify their expression in RF/6A under normal and high glucose environments.

RESULTS

A total of 3583 principle DEGs, that enriched immune-related GO terms and infection-related pathways were identified. CIBERSORT analysis showed that naive B cells, M2 macrophages, eosinophils, and neutrophil infiltration were significantly different. After intersecting 3583 DEGs, 168 DEIRGs and 181 module genes were identified. Furthermore, 15 hub genes, TYROBP, FCGR3A, CD163, FCGR2A, PTPRC, TLR2, CD14, VSIG4, HCK, CSF1R, LILRB2, ITGAM, CTSS, CD86, and LY86, were identified via PPI network. The identified hub genes were up-regulated in DR and showed a high DR diagnostic value. Regulatory networks of the miRNA- and TF-hub genes can help understand the etiology of disease at the genetic level and optimize treatment strategy. CD14, VSIG4, HCK, and CSF1R were verified to be highly expressed in the vitreous of patients with DR. n RF/6A, CSF1R, and p-ERK1/2 were significantly overexpressed under high glucose conditions, with a statistically significant difference.

CONCLUSION

This investigation identified 15 genes (TYROBP, FCGR3A, CD163, FCGR2A, PTPRC, TLR2, CD14, VSIG4, HCK, CSF1R, LILRB2, ITGAM, CTSS, CD86, and LY86) as hub DR genes, which may serve as a new potential point for the diagnosis and treatment of DR. CSF1R/p-ERK1/2 signaling may promotes the development of retinal neovascularization.

Prevalence of mental disorders in patients with pathological obesity selected for bariatric surgery in the KOS-BAR nationwide multi-centre pilot programme - a preliminary report

Obesity affects over 600,000 people in Poland, and bariatric surgery is a vital part of the multidisciplinary approach to treatment. To improve outcomes, Poland's public health institutions implemented the KOS-BAR programme, a multicentre nationwide pilot initiative that includes psychiatric evaluations of patients. The aim of this study was to assess the prevalence of mental disorders, verify diagnoses, and evaluate pharmacotherapy efficacy for patients under psychiatric treatment and selected for bariatric surgery. Of the 180 patients evaluated, 40% had a history of mental disorders, with depressive and eating disorders being the most common diagnoses. Patients selected for revision surgery had a higher incidence of depressive and compulsive eating disorders. Psychiatric support can improve patient cooperation and optimize long-term outcomes after bariatric surgery. A more complete evaluation of the psychological profile and depressive disorder's impact on bariatric treatment outcomes will be the next step for this group of patients.

Identification of immune infiltration-related biomarkers in carotid atherosclerotic plaques

Atherosclerosis is a chronic lipid-driven inflammatory response of the innate and adaptive immune systems, and it is responsible for several cardiovascular ischemic events. The present study aimed to determine immune infiltration-related biomarkers in carotid atherosclerotic plaques (CAPs). Gene expression profiles of CAPs were extracted from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) between the CAPs and control groups were screened by the "limma" package in R software. Immune cell infiltration between the CAPs and control groups was evaluated by the single sample gene set enrichment analysis. Key infiltrating immune cells in the CAPs group were screened by the Wilcoxon test and least absolute shrinkage and selection operator regression. The weighted gene co-expression network analysis was used to identify immune cell-related genes. Hub genes were identified by the protein-protein interaction (PPI) network. Receiver operating characteristic curve analysis was performed to assess the gene's ability to differentiate between the CAPs and control groups. Finally, we constructed a miRNA-gene-transcription factor network of hub genes by using the ENCODE database. Eleven different types of immune infiltration-related cells were identified between the CAPs and control groups. A total of 1,586 differentially expressed immunity-related genes were obtained through intersection between DEGs and immune-related genes. Twenty hub genes were screened through the PPI network. Eventually, 7 genes (BTK, LYN, PTPN11, CD163, CD4, ITGAL, and ITGB7) were identified as the hub genes of CAPs, and these genes may serve as the estimable drug targets for patients with CAPs.

LncRNA NEAT1: A novel regulator associated with the inflammatory response in acute respiratory distress syndrome

BACKGROUND

Acute respiratory distress syndrome (ARDS) is a life-threatening condition with an unfavorable prognosis. As the pathogenesis of ARDS remains unclear, we aimed to identify the core genes associated with ARDS and the mechanisms by which competing endogenous RNAs (ceRNAs) regulate the disease's progression.

METHODS

Three mRNA microarray datasets (GSE17355, GSE48787, and GSE130936), derived from the Gene Expression Omnibus (GEO) database, were selected. Common differentially expressed genes (DEGs) related to acute lung injury (ALI) were identified and subjected to enrichment analysis. Then, hub genes were figured out through the protein-protein interaction (PPI) network and functional analysis, and targeted miRNAs and lncRNAs were predicted. Finally, the ceRNA networks associated with ALI were constructed and validated experimentally.

RESULTS

A total of 155 upregulated and 93 downregulated DEGs were identified in the three datasets. The TNF signaling pathway and IL-17 signaling pathway were the most enriched pathways. Then, eleven DEGs enriched in the IL-17 signaling pathway were selected as the hub genes. Three miRNAs (mmu-mir-155-5p, mmu-mir-21a-5p, and mmu-mir-122-5p), which were located in the lung tissue and predicted to bind the hub genes at the same time, and two lncRNAs (Neat1 and Tug1), which have binding sites for the aforementioned miRNAs, were filtered. With qPCR verification, we identified a ceRNA network composed of NEAT1, miR-21-5p, MMP9, and CXCL5. NEAT1 knockdown promoted the migration and reduced the expression of pro-inflammatory factor and reactive oxygen species (ROS) in lung epithelial cells. We eventually confirmed that NEAT1/miR-21-5p/CXCL5/MMP9 played a pivotal role in regulating the inflammatory response in ALI.

CONCLUSION

The IL-17 signaling pathway is of great importance in the pathogenesis of ARDS. NEAT1/miR-21-5p is involved in the inflammation of ALI by regulating CXCL5 and MMP9.

Integrated bioinformatics approach reveals methylation-regulated differentially expressed genes in obesity

Objective

To identify DNA methylation and gene expression profiles involved in obesity by implementing an integrated bioinformatics approach.

Materials and methods

Gene expression (GSE94752, GSE55200, and GSE48964) and DNA methylation (GSE67024 and GSE111632) datasets were obtained from the GEO database. Differentially expressed genes (DEGs) and differentially methylated genes (DMGs) in subcutaneous adipose tissue of patients with obesity were identified using GEO2R. Methylation-regulated DEGs (MeDEGs) were identified by overlapping DEGs and DMGs. The protein-protein interaction (PPI) network was constructed with the STRING database and analyzed using Cytoscape. Functional modules and hub-bottleneck genes were identified by using MCODE and CytoHubba plugins. Functional enrichment analyses were performed based on Gene Ontology terms and KEGG pathways. To prioritize and identify candidate genes for obesity, MeDEGs were compared with obesity-related genes available at the DisGeNET database.

Results

A total of 54 MeDEGs were identified after overlapping the lists of significant 274 DEGs and 11,556 DMGs. Of these, 25 were hypermethylated-low expression genes and 29 were hypomethylated-high expression genes. The PPI network showed three hub-bottleneck genes (PTGS2, TNFAIP3, and FBXL20) and one functional module. The 54 MeDEGs were mainly involved in the regulation of fibroblast growth factor production, the molecular function of arachidonic acid, and ubiquitin-protein transferase activity. Data collected from DisGeNET showed that 11 of the 54 MeDEGs were involved in obesity.

Conclusion

This study identifies new MeDEGs involved in obesity and assessed their related pathways and functions. These results data may provide a deeper understanding of methylation-mediated regulatory mechanisms of obesity.

LCK, FOXC1 and hsa-miR-146a-5p as potential immune effector molecules associated with rheumatoid arthritis

Rheumatoid arthritis (RA) is a type of systemic immune disease characterized by chronic inflammatory disease of the joints. However, the aetiology and underlying molecular events of RA are unclear. Here, we applied bioinformatics analysis to identify potential immune effector molecules involved in RA. The three microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database. We used the R software screen 115 overlapping differentially expressed genes (DEGs). Subsequently, we constructed a protein-protein interaction (PPI) network encoded by these DEGs and identified 10 genes closely associated with RA - LCK, GZMA, GZMB, CD2, LAG3, IL-15, TNFRSF4, CD247, CCR5 and CCR7. Furthermore, in the miRNA-hub gene networks, we screened out hsa-miR-146a-5p, which is the miRNA controlling the largest number of hub genes. Finally, we found some transcription factors that closely interact with hub genes, such as FOXC1, GATA2, YY1, RUNX2, SREBF1, CEBPB and NFIC. This study successfully predicted that LCK, FOXC1 and hsa-miR-146a-5p can be used as potential immune effector molecules of RA. Our study may have potential implications for future prediction of disease progression in patients with symptomatic RA, and has important significance for the pathogenesis and targeted therapy of RA.

Disease progression promotes changes in adipose tissue signatures in type 2 diabetic (db/db) mice: The potential pathophysiological role of batokines

Unlike the white adipose tissue (WAT) which mainly stores excess energy as fat, brown adipose tissue (BAT) has become physiologically important and therapeutically relevant for its prominent role in regulating energy metabolism. The current study makes use of an established animal model of type 2 diabetes (T2D) db/db mice to determine the effect of the disease progression on adipose tissue morphology and gene regulatory signatures. Results showed that WAT and BAT from db/db mice display a hypertrophied phenotype that is consistent with increased expression of the pro-inflammatory cytokine, tumor necrosis factor-alpha (Tnf-α). Moreover, BAT from both db/db and non-diabetic db/+ control mice displayed an age-related impairment in glucose homeostasis, inflammatory profile, and thermogenic regulation, as demonstrated by reduced expression of genes like glucose transporter (Glut-4), adiponectin (AdipoQ), and uncoupling protein 1 (Ucp-1). Importantly, gene expression of the batokines regulating sympathetic neurite outgrowth and vascularization, including bone morphogenic protein 8b (Bmp8b), fibroblast growth factor 21 (Fgf-21), neuregulin 4 (Nrg-4) were altered in BAT from db/db mice. Likewise, gene expression of meteorin-like (Metrnl), growth differentiation factor 15 (Gdt-15), and C-X-C motif chemokine-14 (Cxcl-14) regulating pro- and anti-inflammation were altered. This data provides some new insights into the pathophysiological mechanisms involved in BAT hypertrophy (or whitening) and the disturbances of batokines during the development and progression of T2D. However, these are only preliminary results as additional experiments are necessary to confirm these findings in other experimental models of T2D.

Identification of Oxidative Stress-Related Biomarkers in Diabetic Kidney Disease

Background

Diabetic kidney disease (DKD) is a leading cause of end-stage renal disease throughout the world. In kidney disease, oxidative stress has been linked to both antioxidant depletions and increased reactive oxygen species (ROS) production. Thus, the objective of this study was to identify biomarkers related to oxidative stress in DKD.

Methods

The gene expression profile of the DKD was extracted from the Gene Expression Omnibus (GEO) database. The identification of the differentially expressed genes (DEGs) was performed using the "limma" R package, and weighted gene coexpression network analysis (WGCNA) was used to find the gene modules that were most related to DKD. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed using "Org.Hs.eg.db" R package. The protein-protein interaction (PPI) network was constructed using the STRING database. The hub genes were identified by the Molecular Complex Detection (MCODE) plug-in of Cytoscape software. The diagnostic capacity of hub genes was verified using the receiver operating characteristic (ROC) curve. Correlations between diagnostic genes were analyzed using the "corrplot" package. In addition, the miRNA gene transcription factor (TF) network was used to explain the regulatory mechanism of hub genes in DKD.

Results

DEGs analysis and WGCNA-identified 160 key genes were identified in DKD patients. Among them, nine oxidative stress-related genes were identified as candidate hub genes for DKD. Using the PPI network, five hub genes, NR4A2, DUSP1, FOS, JUN, and PTGS2, were subsequently identified. All the hub genes were downregulated in DKD and had a high diagnostic value of DKD. The regulatory mechanism of hub genes was analyzed from the miRNA gene-TF network.

Conclusion

Our study identified NR4A2, DUSP1, FOS, JUN, and PTGS2 as hub genes of DKD. These genes may serve as potential therapeutic targets for DKD patients.

Regulatory network of metformin on adipogenesis determined by combining high-throughput sequencing and GEO database

Adipose differentiation and excessive lipid accumulation are the important characteristics of obesity. Metformin, as a classic hypoglycaemic drug, has been proved to reduce body weight in type 2 diabetes, the specific mechanism has not been completely clear. A few studies have explored its effect on adipogenesis in vitro, but the existing experimental results are ambiguous. 3T3-L1 preadipocytes were used to explore the effects of metformin on the morphological and physiological changes of lipid droplets during adipogenesis. A high throughput sequencing was used to examine the effects of metformin on the transcriptome of adipogenesis. Considering the inevitable errors among independent experiments, we performed integrated bioinformatics analysis to identify important genes involved in adipogenesis and reveal potential molecular mechanisms. During the process of adipogenesis, metformin visibly relieved the morphological and functional changes. In addition, metformin reverses the expression pattern of genes related to adipogenesis at the transcriptome level. Combining with integrated bioinformatics analyses to further identify the potential targeted genes regulated by metformin during adipogenesis. The present study identified novel changes in the transcriptome of metformin in the process of adipogenesis that might shed light on the underlying mechanism by which metformin impedes the progression of obesity.

Differential Gene Expression of Subcutaneous Adipose Tissue among Lean, Obese, and after RYGB (Different Timepoints): Systematic Review and Analysis

The main roles of adipose tissue include triglycerides storage and adipokine secretion, which regulate energy balance and inflammation status. In obesity, adipocyte dysfunction leads to proinflammatory cytokine production and insulin resistance. Bariatric surgery is the most effective treatment for obesity, the gold-standard technique being Roux-en-Y gastric bypass (RYGB). Since metabolic improvements after RYGB are clear, a better understanding of adipose tissue molecular modifications could be derived from this study. Thus, the aim of this systematic review was to find differentially expressed genes in subcutaneous adipose tissue of lean, obese and post-RYGB (distinct timepoints). To address this objective, publications from 2015-2022 reporting gene expression (candidate genes or transcriptomic approach) of subcutaneous adipose tissue from lean and obese individuals before and after RGYB were searched in PubMed, Elsevier, and Springer Link. Excluded publications were reviews, studies analyzing serum, other types of tissues, or bariatric procedures. A risk-of-bias summary was created for each paper using Robvis, to finally include 17 studies. Differentially expressed genes in post-RYGB vs. obese and lean vs. obese were obtained and the intersection among these groups was used for analysis and gene classification by metabolic pathway. Results showed that the lean state as well as the post-RYGB is similar in terms of increased expression of insulin-sensitizing molecules, inducing lipogenesis over lipolysis and downregulating leukocyte activation, cytokine production and other factors that promote inflammation. Thus, massive weight loss and metabolic improvements after RYGB are accompanied by gene expression modifications reverting the "adipocyte dysfunction" phenomenon observed in obesity conditions.

Identification of hub genes and candidate herbal treatment in obesity through integrated bioinformatic analysis and reverse network pharmacology

Obesity is a global epidemic elevating the risk of various metabolic disorders. As there is a lack of effective drugs to treat obesity, we combined bioinformatics and reverse network pharmacology in this study to identify effective herbs to treat obesity. We identified 1011 differentially expressed genes (DEGs) of adipose tissue after weight loss by analyzing five expression profiles (GSE103766, GSE35411, GSE112307, GSE43471, and GSE35710) from the Gene Expression Omnibus (GEO) database. We identified 27 hub genes from the protein-protein interaction (PPI) network by performing MCODE using the Search Tool for the Retrieval of Interacting Genes (STRING) database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses revealed that these hub genes have roles in the extracellular matrix-receptor interaction, cholesterol metabolism, PI3K-Akt signaling pathway, etc. Ten herbs (Aloe, Portulacae Herba, Mori Follum, Silybum Marianum, Phyllanthi Fructus, Pollen Typhae, Ginkgo Semen, Leonuri Herba, Eriobotryae Folium, and Litseae Fructus) targeting the nine hub genes (COL1A1, MMP2, MMP9, SPP1, DNMT3B, MMP7, CETP, COL1A2, and MUC1) using six ingredients were identified as the key herbs. Quercetin and (-)-epigallocatechin-3-gallate were determined to be the key ingredients. Lastly, Ingredients-Targets, Herbs-Ingredients-Targets, and Herbs-Taste-Meridian Tropism networks were constructed using Cytoscape to elucidate this complex relationship. This study could help identify promising therapeutic targets and drugs to treat obesity.

Lipid Peroxidation in Obesity: Can Bariatric Surgery Help?

Obesity and chronic oxidative stress, often being associated with each other in a vicious circle, are important factors of chronic diseases. Although it was usually considered to accompany aging and wealth, global trends show the increase in obesity among children even in Third World countries. Being manifested by an imbalance between energy consumption and food intake, obesity is characterized by an excessive or abnormal fat accumulation, impaired redox homeostasis and metabolic changes often associated with the self-catalyzed lipid peroxidation generating 4-hydroxynonenal, pluripotent bioactive peroxidation product of polyunsaturated fatty acids. Conservative methods targeting obesity produced only modest and transient results in the treatment of morbid obesity. Therefore, in recent years, surgery, primarily bariatric, became an attractive treatment for morbid obesity. Since adipose tissue is well known as a stress organ with pronounced endocrine functions, surgery results in redox balance and metabolic improvement of the entire organism. The source of bioactive lipids and lipid-soluble antioxidants, and the complex pathophysiology of lipid peroxidation should thus be considered from the aspects of personalized and integrative biomedicine to treat obesity in an appropriate way.

Network pharmacology combined with GEO database identifying the mechanisms and molecular targets of Polygoni Cuspidati Rhizoma on Peri-implants

Peri-implants is a chronic disease leads to the bone resorption and loss of implants. Polygoni Cuspidati Rhizoma (PCRER), a traditional Chinese herbal has been used to treat diseases of bone metabolism. However, its mechanism of anti-bone absorption still remains unknown. We aimed to identify its molecular target and the mechanism involved in PCRER potential treatment theory to Peri-implants by network pharmacology. The active ingredients of PCRER and potential disease-related targets were retrieved from TCMSP, Swiss Target Prediction, SEA databases and then combined with the Peri-implants disease differential genes obtained in the GEO microarray database. The crossed genes were used to protein–protein interaction (PPI) construction and Gene Ontology (GO) and KEGG enrichment analysis. Using STRING database and Cytoscape plug-in to build protein interaction network and screen the hub genes and verified through molecular docking by AutoDock vina software. A total of 13 active compounds and 90 cross targets of PCRER were selected for analysis. The GO and KEGG enrichment analysis indicated that the anti-Peri-implants targets of PCRER mainly play a role in the response in IL-17 signaling, Calcium signaling pathway, Toll-like receptor signaling pathway, TNF signaling pathway among others. And CytoHubba screened ten hub genes (MMP9, IL6, MPO, IL1B, SELL, IFNG, CXCL8, CXCL2, PTPRC, PECAM1). Finally, the molecular docking results indicated the good binding ability with active compounds and hub genes. PCRER’s core components are expected to be effective drugs to treat Peri-implants by anti-inflammation, promotes bone metabolism. Our study provides new thoughts into the development of natural medicine for the prevention and treatment of Peri-implants.

Promising novel biomarkers and candidate drugs or herbs in Osteoarthritis: Evidence from bioinformatics analysis of high‐throughput data

Background:

The most common joint illness is osteoarthritis (OA). The goal of this work was to find changes in gene signatures between normal knee joints and OA tissue samples and look for prospective gene targets for OA.

Methods:

The gene expression profiles of GSE12021, GSE51588, and GSE55457 were downloaded from Gene Expression Omnibus (GEO). Total 64 samples (40 OA and 24 standard control samples) were used. The limma program was used to find differentially expressed genes (DEGs) in OA versus NC. Functional annotation and protein-protein interaction (PPI) network construction of OA-specific DEGs were performed. Finally, the candidate drugs and herbs as potential drugs to treat OA were predicted in the DGIdb and TCMIO databases.

Results:

19 upregulated and 27 downregulated DEGs between OA and NC samples. DEGs such as PTN, COMP, NELL1 and MN1 have shown a significant correlation with OA and are expected to become new biomarkers. Cellular senescence,Positive regulation of ossification and Vascular endothelial growth factor (VEGF) were significantly enriched for OA‐specific DEGs.In cell composition analysis, DEGs were also found to be highly enriched in the cytosol.We have identified a total of 68 types of drugs or molecular compounds that are promising to reverse OA-related DEGs.Honeycomb and cinnamon oil have the possibility of treating OA.

Conclusion:

Our findings suggest new biomarkers that can be used to diagnose OA. Furthermore, we tried to find drugs and traditional Chinese medicine that may improve the progress of OA. This research may improve the identification and treatment of these uncontrollable chronic diseases.

A novel immune-related genes signature after bariatric surgery is histologically associated with non-alcoholic fatty liver disease

Increasing evidence shows that immune-related genes (IRGs) play an important role in bariatric surgery (BS). We identified differentially expressed immune-related genes (DEIRGs) of adipose tissue after BS by analysing the two expression profiles of GEO (GSE59034 and GSE29409). Subsequently, enrichment analysis, GSEA and PPI networks were examined to identify the hub IRGs and related pathways. The performance of the signature was evaluated by area under the curve (AUC) of the receiver operating characteristic (ROC). CIBERSORT algorithm was used to evaluate the relative abundance of infiltrated immune cells.42 DEIRGs were found between the GSE59034 and GSE29409 datasets. The AUC of the signature was 0.904 and 0.865 in the GSE58979 and GSE48452, respectively. Interestingly, the signature also showed good performance in diagnosing non-alcoholic fatty liver disease (NAFLD) (AUC was 0.834 and 0.800, respectively). The number of neutrophils, macrophages M2, macrophages M0 and dendritic cells activated decreased significantly. After BS, the infiltration of T cells regulatory, monocytes, mast cells resting and plasma cells in adipose tissue increased. The novel proposed IRGs signature reveals the underlying immune mechanism of BS and is a promising biomarker for distinguishing the severity of NAFLD. This will provide new insights into strategies for treating obesity and NAFLD.

Surgery for Obesity and Weight-Related Diseases Changes the Inflammatory Profile in Women with Severe Obesity: a Randomized Controlled Clinical Trial

INTRODUCTION/PURPOSE

Obesity increases significantly every year worldwide. Since 1980, the prevalence of individuals with obesity has practically doubled. Obesity plays an important role in the pathophysiology of diseases that arise from a complex interaction of nutritional, genetic, and metabolic factors, characterizing a chronic inflammatory state. This study aimed to verify the systemic inflammatory response through the analysis of IGF-1, IL-23, and resistin levels and the lipid profile in severely obese women undergoing surgery for obesity and weight-related diseases.

MATERIALS AND METHODS

This randomized controlled clinical trial includes female patients clinically diagnosed with severe obesity with an indication for bariatric surgery.

RESULTS

In the initial evaluation, no significant difference was observed between the control (CG) and bariatric surgery (BSG) groups. The weight, BMI, systolic and diastolic blood pressures, total cholesterol, LDL, HDL, total non-HDL cholesterol, and glucose in BSG patients showed a significant change after surgery. Pre- and post-surgery levels of resistin, IGF-1, and IL-23 showed a significant difference in the BSG group, but only IL-23 was changed after 6 months in the CG.

CONCLUSION

The results of this study confirmed that weight loss induced by surgery for obesity and weight-related diseases improved the lipid profile and reduced the chronic inflammatory status in women with severe obesity.

Screening and identification of NOTCH1, CDKN2A, and NOS3 as differentially expressed autophagy-related genes in erectile dysfunction

Background

Loss of function of key autophagy genes are associated with a variety of diseases. However specific role of autophagy-related genes in erectile dysfunction ED remains unclear. This study explores the autophagy-related differentially expressed genes (ARGs) profiles and related molecular mechanisms in Corpus Cavernosum endothelial dysfunction, which is a leading cause of ED.

Methods

The Gene Expression Omnibus (GEO) database was used to identify the key genes and pathways. Differentially expressed genes (DEGs) were mined using the limma package in R language. Next, ARGs were obtained by matching DEGs and autophagy-related genes from GeneCard using Venn diagrams. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of ARGs were described using clusterProfiler and org.Hs.eg.db in R. Moreover, hub ARGs were screened out through protein-protein interaction (PPI), gene-microRNAs, and gene-transcription factors (TFs) networks then visualized using Cytoscape. Of note, the rat model of diabetic ED was established to validate some hub ARGs with qRT-PCR and Western blots.

Results

Twenty ARGs were identified from four ED samples and eight non-ED samples. GO analysis revealed that molecular functions (MF) of upregulated ARGs were mainly enriched in nuclear receptor activity. Also, MF of downregulated ARGs were mainly enriched in oxidoreductase activity, acting on NAD(P)H and heme proteins as acceptors. Moreover, six hub ARGs were identified by setting high degrees in the network. Additionally, hsa-mir-24-3p and hsa-mir-335-5p might play a central role in several ARGs regulation, and the transcription factors-hub genes network was centered with 13 ARGs. The experimental results further showed that the expression of Notch1, NOS3, and CDKN2A in the diabetic ED group was downregulated compared to the control.

Conclusions

Our study deepens the autophagy-related mechanistic understanding of endothelial dysfunction of ED. NOTCH1, CDKN2A, and NOS3 are involved in the regulation of endothelial dysfunction and may be potential therapeutic targets for ED by modulating autophagy.