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

ABSTRACT: We explored potential biomarkers and molecular mechanisms regarding multiple benefits after bariatric surgery. Differentially expressed genes (DEGs) for subcutaneous adipose tissue (AT) after bariatric surgery were identified by analyzing two expression profiles from the GEO. Subsequently, enrichment analysis, GSEA, PPI network, and gene-microRNAs and gene-TFs networks were interrogated to identify hub genes and associated pathways. Co-expressed DEGs included one that was up-regulated and 22 that were down-regulated genes. The enrichment analyses indicated that down-regulated DEGs were significantly involved in inflammatory responses. GSEA provided comprehensive evidence that most genes enriched in pro-inflammation pathways, while gene-sets after surgery enriched in metabolism. We identified nine hub genes in the PPI network, most of which were validated as highly expressed and hypomethylated in obesity by Attie Lab Diabetes and DiseaseMeth databases, respectively. DGIdb was also applied to predict potential therapeutic agents that might reverse abnormally high hub gene expression. Bariatric surgery induces a significant shift from an obese pro-inflammatory state to an anti-inflammatory state, with improvement in adipocyte metabolic function - representing key mechanisms whereby AT function improves after bariatric surgery. Our study deepens a mechanistic understanding of the benefits of bariatric surgery and provides potential biomarkers or treatment targets for further research.

SUBMITTER: Liu Y

PROVIDER: S-EPMC7469525 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Bariatric surgery and other therapeutic options for obese patients are often evaluated by the loss of weight, reduction of comorbidities or improved quality of life. However, little is currently known about potential therapy-related changes in the adipose tissue of obese patients. The aim of this study was therefore to quantify fat fraction (FF) and T1 relaxation time by magnetic resonance imaging (MRI) after Roux-en-Y gastric bypass surgery and compare the resulting values with the preoperative ones. Corresponding MRI data were available from 23 patients (16 females and 7 males) that had undergone MRI before (M0) and one month after (M1) bariatric surgery. Patients were 22-59 years old (mean age 44.3 years) and their BMI ranged from 35.7-54.6 kg/m2 (mean BMI 44.6 kg/m2) at M0. Total visceral AT volumes (VVAT-T, in L) were measured by semi-automatic segmentation of axial MRI images acquired between diaphragm and femoral heads. MRI FF and T1 relaxation times were measured in well-defined regions of visceral (VAT) and subcutaneous (SAT) adipose tissue using two custom-made analysis tools. Average BMI values were 45.4 kg/m2 at time point M0 and 42.4 kg/m2 at M1. Corresponding VVAT-T values were 5.94 L and 5.33 L. Intraindividual differences in both BMI and VVAT-T were highly significant (p<0.001). Average relaxation times T1VAT were 303.7 ms at M0 and 316.9 ms at M1 (p<0.001). Corresponding T1SAT times were 283.2 ms and 280.7 ms (p = 0.137). Similarly, FFVAT differences (M0: 85.7%, M1: 83.4%) were significant (p <0.01) whereas FFSAT differences (M0: 86.1, M1: 85.9%) were not significant (p = 0.517). In conclusion, bariatric surgery is apparently not only related to a significant reduction in common parameters of adipose tissue distribution, here BMI and total visceral fat volume, but also significant changes in T1 relaxation time and fat fraction of visceral adipose tissue. Such quantitative MRI measures may potentially serve as independent biomarkers for longitudinal and cross-sectional measurements in obese patients.

Project description:BackgroundBariatric surgery is associated to improvements in obesity-associated comorbidities thought to be mediated by a decrease of adipose inflammation. However, the molecular mechanisms behind these beneficial effects are poorly understood.Methodology/principal findingsWe analyzed RNA-seq expression profiles in adipose tissue from 22 obese women before and 3 months after surgery. Of 15,972 detected genes, 1214 were differentially expressed after surgery at a 5% false discovery rate. Upregulated genes were mostly involved in the basal cellular machinery. Downregulated genes were enriched in metabolic functions of adipose tissue. At baseline, 26 modules of coexpressed genes were identified. The four most stable modules reflected the innate and adaptive immune responses of adipose tissue. A first module reflecting a non-specific signature of innate immune cells, mainly macrophages, was highly conserved after surgery with the exception of DUSP2 and CD300C. A second module reflected the adaptive immune response elicited by T lymphocytes; after surgery, a disconnection was observed between genes involved in T-cell signaling and mediators of the signal transduction such as CXCR1, CXCR2, GPR97, CCR7 and IL7R. A third module reflected neutrophil-mediated inflammation; after surgery, several genes were dissociated from the module, including S100A8, S100A12, CD300E, VNN2, TUBB1 and FAM65B. We also identified a dense network of 19 genes involved in the interferon-signaling pathway which was strongly preserved after surgery, with the exception of DDX60, an antiviral factor involved in RIG-I-mediated interferon signaling. A similar loss of connection was observed in lean mice compared to their obese counterparts.Conclusions/significanceThese results suggest that improvements of the inflammatory state following surgery might be explained by a disruption of immuno-inflammatory cascades involving a few crucial molecules which could serve as potential therapeutic targets.

Project description:BackgroundHeart failure (HF) is the most common potential cause of death, causing a huge health and economic burden all over the world. So far, some impressive progress has been made in the study of pathogenesis. However, the underlying molecular mechanisms leading to this disease remain to be fully elucidated.MethodsThe microarray data sets of GSE76701, GSE21610 and GSE8331 were retrieved from the gene expression comprehensive database (GEO). After merging all microarray data and adjusting batch effects, differentially expressed genes (DEG) were determined. Functional enrichment analysis was performed based on Gene Ontology (GO) resources, Kyoto Encyclopedia of Genes and Genomes (KEGG) resources, gene set enrichment analysis (GSEA), response pathway database and Disease Ontology (DO). Protein protein interaction (PPI) network was constructed using string database. Combined with the above important bioinformatics information, the potential key genes were selected. The comparative toxicological genomics database (CTD) is used to explore the interaction between potential key genes and HF.ResultsWe identified 38 patients with heart failure and 16 normal controls. There were 315 DEGs among HF samples, including 278 up-regulated genes and 37 down-regulated genes. Pathway enrichment analysis showed that most DEGs were significantly enriched in BMP signal pathway, transmembrane receptor protein serine/threonine kinase signal pathway, extracellular matrix, basement membrane, glycosaminoglycan binding, sulfur compound binding and so on. Similarly, GSEA enrichment analysis showed that DEGs were mainly enriched in extracellular matrix and extracellular matrix related proteins. BBS9, CHRD, BMP4, MYH6, NPPA and CCL5 are central genes in PPI networks and modules.ConclusionsThe enrichment pathway of DEGs and GO may reveal the molecular mechanism of HF. Among them, target genes EIF1AY, RPS4Y1, USP9Y, KDM5D, DDX3Y, NPPA, HBB, TSIX, LOC28556 and XIST are expected to become new targets for heart failure. Our findings provide potential biomarkers or therapeutic targets for the further study of heart failure and contribute to the development of advanced prediction, diagnosis and treatment strategies.

Project description:Background: Non-obstructive azoospermia (NOA) is the most severe form of male infertility. Currently, the molecular mechanisms underlying NOA pathology have not yet been elucidated. Hence, elucidation of the mechanisms of NOA and exploration of potential biomarkers are essential for accurate diagnosis and treatment of this disease. In the present study, we aimed to screen for biomarkers and pathways involved in NOA and reveal their potential molecular mechanisms using integrated bioinformatics. Methods: We downloaded two gene expression datasets from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in NOA and matched the control group tissues were identified using the limma package in R software. Subsequently, Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), gene set enrichment analysis (GSEA), protein-protein interaction (PPI) network, gene-microRNAs network, and transcription factor (TF)-hub genes regulatory network analyses were performed to identify hub genes and associated pathways. Finally, we conducted immune infiltration analysis using CIBERSORT to evaluate the relationship between the hub genes and the NOA immune infiltration levels. Results: We identified 698 common DEGs, including 87 commonly upregulated and 611 commonly downregulated genes in the two datasets. GO analysis indicated that the most significantly enriched gene was protein polyglycylation, and KEGG pathway analysis revealed that the DEGs were most significantly enriched in taste transduction and pancreatic secretion signaling pathways. GSEA showed that DEGs affected the biological functions of the ribosome, focaladhesion, and protein_expor. We further identified the top 31 hub genes from the PPI network, and friends analysis of hub genes in the PPI network showed that NR4A2 had the highest score. In addition, immune infiltration analysis found that CD8+ T cells and plasma cells were significantly correlated with ODF3 expression, whereas naive B cells, plasma cells, monocytes, M2 macrophages, and resting mast cells showed significant variation in the NR4A2 gene expression group, and there were differences in T cell regulatory immune cell infiltration in the FOS gene expression groups. Conclusion: The present study successfully constructed a regulatory network of DEGs between NOA and normal controls and screened three hub genes using integrative bioinformatics analysis. In addition, our results suggest that functional changes in several immune cells in the immune microenvironment may play an important role in spermatogenesis. Our results provide a novel understanding of the molecular mechanisms of NOA and offer potential biomarkers for its diagnosis and treatment.

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

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