Integrative Analysis of Exosomal miR-452 and miR-4713 Downregulating NPY1R for the Prevention of Childhood Obesity

Identification and analysis of key genes in adipose tissue for human obesity based on bioinformatics

BACKGROUND

Obesity is a complex condition that is affected by a variety of factors, including the environment, behavior, and genetics. However, the genetic mechanisms underlying obesity remains poorly elucidated. Therefore, our study aimed at identifying key genes for human obesity using bioinformatics analysis.

METHODS

The microarray datasets of adipose tissue in humans were downloaded from the Gene Expression Omnibus (GEO) database. After the selection of differentially expressed genes (DEGs), we used Lasso regression and Support Vector Machine (SVM) algorithm to further identify the feature genes. Moreover, immune cell infiltration analysis, gene set variation analysis (GSVA), GeneCards database and transcriptional regulation analysis were conducted to study the potential mechanisms by which the feature genes may impact obesity. We utilized receiver operating characteristic (ROC) curve to analysis the diagnostic efficacy of feature genes. Finally, we verified the feature genes in cell experiments and animal experiments. The statistical analyses in validation experiments were conducted using SPSS version 28.0, and the graph were generated using GraphPad Prism 9.0 software. The bioinformatics analyses were conducted using R language (version 4.2.2), with a significance threshold of p < 0.05 used.

RESULTS

199 DEGs were selected using Limma package, and subsequently, 5 feature genes (EGR2, NPY1R, GREM1, BMP3 and COL8A1) were selected through Lasso regression and SVM algorithm. Through various bioinformatics analyses, we found some signaling pathways by which feature genes influence obesity and also revealed the crucial role of these genes in the immune microenvironment, as well as their strong correlations with obesity-related genes. Additionally, ROC curve showed that all the feature genes had good predictive and diagnostic efficiency in obesity. Finally, after validation through in vitro experiments, EGR2, NPY1R and GREM1 were identified as the key genes.

CONCLUSIONS

This study identified EGR2, GREM1 and NPY1R as the potential key genes and potential diagnostic biomarkers for obesity in humans. Moreover, EGR2 was discovered as a key gene for obesity in human adipose tissue for the first time, which may provide novel targets for diagnosing and treating obesity.

Childhood obesity, metabolic syndrome, and oxidative stress: microRNAs go on stage

The incidence of childhood obesity and metabolic syndrome has grown notably in the last years, becoming major public health burdens in developed countries. Nowadays, oxidative stress is well-recognized to be closely associated with the onset and progression of several obesity-related complications within the framework of a complex crosstalk involving other intertwined pathogenic events, such as inflammation, insulin disturbances, and dyslipidemia. Thus, understanding the molecular basis behind these oxidative dysregulations could provide new approaches for the diagnosis, prevention, and treatment of childhood obesity and associated disorders. In this respect, the transcriptomic characterization of miRNAs bares great potential because of their involvement in post-transcriptional modulation of genetic expression. Herein, we provide a comprehensive literature revision gathering state-of-the-art research into the association between childhood obesity, metabolic syndrome, and miRNAs. We put special emphasis on the potential role of miRNAs in modulating obesity-related pathogenic events, with particular focus on oxidative stress.

Study on Potential Differentially Expressed Genes in Idiopathic Pulmonary Fibrosis by Bioinformatics and Next-Generation Sequencing Data Analysis

Idiopathic pulmonary fibrosis (IPF) is a chronic progressive lung disease with reduced quality of life and earlier mortality, but its pathogenesis and key genes are still unclear. In this investigation, bioinformatics was used to deeply analyze the pathogenesis of IPF and related key genes, so as to investigate the potential molecular pathogenesis of IPF and provide guidance for clinical treatment. Next-generation sequencing dataset GSE213001 was obtained from Gene Expression Omnibus (GEO), and the differentially expressed genes (DEGs) were identified between IPF and normal control group. The DEGs between IPF and normal control group were screened with the DESeq2 package of R language. The Gene Ontology (GO) and REACTOME pathway enrichment analyses of the DEGs were performed. Using the g:Profiler, the function and pathway enrichment analyses of DEGs were performed. Then, a protein-protein interaction (PPI) network was constructed via the Integrated Interactions Database (IID) database. Cytoscape with Network Analyzer was used to identify the hub genes. miRNet and NetworkAnalyst databaseswereused to construct the targeted microRNAs (miRNAs), transcription factors (TFs), and small drug molecules. Finally, receiver operating characteristic (ROC) curve analysis was used to validate the hub genes. A total of 958 DEGs were screened out in this study, including 479 up regulated genes and 479 down regulated genes. Most of the DEGs were significantly enriched in response to stimulus, GPCR ligand binding, microtubule-based process, and defective GALNT3 causes HFTC. In combination with the results of the PPI network, miRNA-hub gene regulatory network and TF-hub gene regulatory network, hub genes including LRRK2, BMI1, EBP, MNDA, KBTBD7, KRT15, OTX1, TEKT4, SPAG8, and EFHC2 were selected. Cyclothiazide and rotigotinethe are predicted small drug molecules for IPF treatment. Our findings will contribute to identification of potential biomarkers and novel strategies for the treatment of IPF, and provide a novel strategy for clinical therapy.

The Regulatory Role of MicroRNAs in Obesity and Obesity-Derived Ailments

Obesity is a condition that is characterized by the presence of excessive adipose tissue in the body. Obesity has become one of the main health concerns worldwide since it can lead to other chronic ailments, such as type 2 diabetes or fatty liver disease, and it could be an aggravating factor in infections. MicroRNAs (miRNAs) are small, non-coding RNA molecules that regulate gene expression and can play an important role in controlling crucial biological processes involved in the onset of obesity, such as lipogenesis, adipogenesis, lipid metabolism, or the regulation of cytokines and chemokines. Moreover, chemical compounds present in food or food packaging can alter miRNA expression and regulate the aforementioned biological mechanisms related to diabetes onset and progression. Furthermore, therapies, such as bariatric surgery and aerobic exercise training, can also influence the expression profile of miRNAs in obesity. Therefore, the present review provides insight into the current research on the role of miRNAs in obesity and obesity-derived ailments, intending to develop novel therapies to effectively manage these disorders.

Alzheimer's disease-associated inflammatory pathways might contribute to osteoporosis through the interaction between PROK2 and CSF3

This study aimed to explore the potential molecular pathways and targets of Alzheimer's disease leading to osteoporosis using bioinformatics tools. The Alzheimer's and osteoporosis microarray gene expression data were retrieved from the Gene Expression Omnibus, and differentially expressed genes in the blood microenvironment related to Alzheimer's disease and osteoporosis were identified. The intersection of the three datasets (GSE97760, GSE168813, and GSE62402) was used to obtain 21 co-expressed targets in the peripheral blood samples in patients with Alzheimer's disease and osteoporosis. Based on the degree algorithm, the top 10 potential core target genes related to these diseases were identified, which included CLEC4D, PROK2, SIGLEC7, PDGFB, PTCRA, ECH1, etc. Two differentially expressed mRNAs, Prokineticin 2 (PROK2) and three colony-stimulating factor 3 (CSF3), were screened in the GSE62402 dataset associated with osteoporosis. Protein–protein rigid docking with ZDOCK revealed that PROK2 and CSF3 could form a stable protein docking model. The interaction of PROK2 and CSF3, core genes related to osteoporosis inflammation, plays an important role in the mechanism of osteoporosis in patients with Alzheimer's. Therefore, abnormalities or alterations in the inflammatory pathways in the peripheral blood samples of Alzheimer's patients may affect the course of osteoporosis.

Exercise improves choroid plexus epithelial cells metabolism to prevent glial cell-associated neurodegeneration

Recent studies have shown that physical activities can prevent aging-related neurodegeneration. Exercise improves the metabolic landscape of the body. However, the role of these differential metabolites in preventing neurovascular unit degeneration (NVU) is still unclear. Here, we performed single-cell analysis of brain tissue from young and old mice. Normalized mutual information (NMI) was used to measure heterogeneity between each pair of cells using the non-negative Matrix Factorization (NMF) method. Astrocytes and choroid plexus epithelial cells (CPC), two types of CNS glial cells, differed significantly in heterogeneity depending on their aging status and intercellular interactions. The MetaboAnalyst 5.0 database and the scMetabolism package were used to analyze and calculate the differential metabolic pathways associated with aging in the CPC. These mRNAs and corresponding proteins were involved in the metabolites (R)-3-Hydroxybutyric acid, 2-Hydroxyglutarate, 2-Ketobutyric acid, 3-Hydroxyanthranilic acid, Fumaric acid, L-Leucine, and Oxidized glutathione pathways in CPC. Our results showed that CPC age heterogeneity-associated proteins (ECHS1, GSTT1, HSD17B10, LDHA, and LDHB) might be directly targeted by the metabolite of oxidized glutathione (GSSG). Further molecular dynamics and free-energy simulations confirmed the insight into GSSG's targeting function and free-energy barrier on these CPC age heterogeneity-associated proteins. By inhibiting these proteins in CPC, GSSG inhibits brain energy metabolism, whereas exercise improves the metabolic pathway activity of CPC in NVU by regulating GSSG homeostasis. In order to develop drugs targeting neurodegenerative diseases, further studies are needed to understand how physical exercise enhances NVU function and metabolism by modulating CPC-glial cell interactions.