scholarly journals IGFBP-2 as a biomarker in NAFLD improves hepatic steatosis:an integrated bioinformatics and experimental study

2021 ◽  
Author(s):  
Xu Chen ◽  
Yi Tang ◽  
Shen Chen ◽  
Wen-Hua Ling ◽  
Qing Wang
Keyword(s):  
Liver Disease ◽  
Hepatic Steatosis ◽  
Molecular Mechanisms ◽  
Gene Expression Omnibus ◽  
Ppi Network ◽  
Hub Genes ◽  
Alcoholic Fatty Liver ◽  
Simple Steatosis ◽  
Public Datasets ◽  
Geo Database

Background and aims: Non-alcoholic fatty liver disease (NAFLD) has become a common chronic liver disease in the world. Simple steatosis is the early phase of NAFLD. However, the molecular mechanisms underlying the development of steatosis have not yet been fully elucidated. Methods: Two public datasets (GSE48452 and GSE89632) through the Gene Expression Omnibus (GEO) database were used to identify differentially expressed genes (DEGs) in the development of steatosis. A total of 72 participants including 38 normal histological controls and 34 simple steatosis patients were included in this study. GO, KEGG and PPI network analysis were performed to explore the function of DEGs. The results were further confirmed in high-fat diet (HFD)-fed mice and oleate-treated HepG2 cells. Results: Total 57 DEGs including 31 up- and 26 down-regulated genes between simple steatosis patients and healthy controls were determined. GO and KEGG analysis showed that most of DEGs were enriched in the ligand-receptor signaling pathways. PPI network construction was used to identify the hub genes of the DEGs. MYC, ANXA2, GDF15, AGTR1, NAMPT, LEPR, IGFBP-2, IL1RN, MMP7 and APLNR were identified as hub genes. And IGFBP-2 expression was found to be reversely associated with hepatic steatosis, fasting insulin, HOMA-IR index and ALT levels. In HFD-fed mice, hepatic IGFBP-2 was also downregulated and negatively associated with hepatic triglyceride levels. Moreover, overexpression IGFBP-2 ameliorated the oleate induced accumulation of triglycerides in hepatocytes. Conclusions: This study identified novel gene signatures in the hepatic steatosis and will provide new understanding and molecular clues of hepatic steatosis.

scholarly journals Identification of Novel Hub Genes Through Expression Profiles Analysis in Adrenocortical Carcinoma

2020 ◽  
Author(s):  
Chenhe Yao ◽  
Xiaoling Zhao ◽  
Xuemeng Shang ◽  
Binghan Jia ◽  
Shuaijie Dou ◽  
...  
Keyword(s):  
Adrenocortical Carcinoma ◽  
Expression Profiling ◽  
Molecular Mechanisms ◽  
Cross Validation ◽  
Expression Profiles ◽  
Ppi Network ◽  
Hub Genes ◽  
Tumor Association ◽  
Prediction Of Prognosis ◽  
Geo Database

Abstract Background: Adrenocortical carcinoma (ACC) is a heterogeneous and rare malignant tumor associated with a poor prognosis. The molecular mechanisms of ACC remain elusive and more accurate biomarkers for the prediction of prognosis are needed.Methods: In this study, integrative profiling analyses were performed to identify novel hub genes in ACC to provide promising targets for future investigation. Three gene expression profiling datasets in the GEO database were used for the identification of overlapped differentially expressed genes (DEGs) following the criteria of adj.P.Value<0.05 and |log2 FC|>0.5 in ACC. Novel hub genes were screened out following a series of processes: the retrieval of DEGs with no known associations with ACC on Pubmed, then the cross-validation of expression values and significant associations with overall survival in the GEPIA2 and starBase databases, and finally the prediction of gene-tumor association in the GeneCards database.Results: Four novel hub genes were identified and two of them, TPX2 and RACGAP1, were positively correlated with the staging. Interestingly, co-expression analysis revealed that the association between TPX2 and RACGAP1 was the strongest and that the expression of HOXA5 was almost completely independent of that of RACGAP1 and TPX2. Furthermore, the PPI network consisting of four novel genes and seed genes in ACC revealed that HOXA5, TPX2, and RACGAP1 were all associated with TP53. Conclusions: This study identified four novel hub genes (TPX2, RACHAP1, HXOA5 and FMO2) that may play crucial roles in the tumorigenesis and the prediction of prognosis of ACC.

scholarly journals Gene Differential Expression and Interaction Networks Illustrate the Biomarkers and Molecular Mechanisms of Atherosclerotic Cerebral Infarction

2022 ◽  
Vol 2022 ◽  
pp. 1-8
Author(s):  
Benzhuo Zhang ◽  
Wei Huang ◽  
Mingquan Yi ◽  
Chunxu Xing
Keyword(s):  
Network Analysis ◽  
Cerebral Infarction ◽  
Antigen Processing ◽  
Molecular Mechanisms ◽  
Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Neutrophil Activation ◽  
Receptor Interaction ◽  
Ppi Network ◽  
Geo Database

Atherosclerotic cerebral infarction (ACI) seriously threatens the health of the senile patients, and the strategies are urgent for the diagnosis and treatment of ACI. This study investigated the mRNA profiling of the patients with ischemic stroke and atherosclerosis via excavating the datasets in the GEO database and attempted to reveal the biomarkers and molecular mechanism of ACI. In this study, GES16561 and GES100927 were obtained from Gene Expression Omnibus (GEO) database, and the related differentially expressed genes (DEGs) were analyzed with R language. Furthermore, the DEGs were analyzed with Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Besides, the protein-protein interaction (PPI) network of DEGs was analyzed by STRING database and Cytoscape. The results showed that 133 downregulated DEGs and 234 upregulated DEGs were found in GES16561, 25 downregulated DEGs and 104 upregulated DEGs were found in GSE100927, and 6 common genes were found in GES16561 and GES100927. GO enrichment analysis showed that the functional models of the common genes were involved in neutrophil activation, neutrophil degranulation, neutrophil activation, and immune response. KEGG enrichment analysis showed that the DEGs in both GSE100927 and GSE16561 were connected with the pathways including Cell adhesion molecules (CAMs), Cytokine-cytokine receptor interaction, Phagosome, Antigen processing and presentation, and Staphylococcus aureus infection. The PPI network analysis showed that 9 common DEGs were found in GSE100927 and GSE16561, and a cluster with 6 nodes and 12 edges was also identified by PPI network analysis. In conclusion, this study suggested that FCGR3A and MAPK pathways were connected with ACI.

scholarly journals Identification of Pulpitis-Related Potential Biomarkers Using Bioinformatics Approach

2021 ◽  
Vol 2021 ◽  
pp. 1-12
Author(s):  
Bingchang Xin ◽  
Yuxiang Lin ◽  
He Tian ◽  
Jia Song ◽  
Liwei Zhang ◽  
...  
Keyword(s):  
Inflammatory Reaction ◽  
Gene Expression Omnibus ◽  
Ppi Network ◽  
Hub Genes ◽  
Pulp Tissue ◽  
Network Nodes ◽  
Protein Protein Interaction ◽  
Pathogen Elimination ◽  
Potential Biomarkers ◽  
Geo Database

Inflammatory reaction of pulp tissue plays a role in the pathogen elimination and tissue repair. The evaluation of severity of pulpitis can serve an instructive function in therapeutic scheme. However, there are many limitations in the traditional evaluation methods for the severity of pulpitis. Based on the Gene Expression Omnibus (GEO) database, our study discovered 843 differentially expressed genes (DEGs) related to pulpitis. Afterwards, we constructed a protein-protein interaction (PPI) network of DEGs and used MCODE plugin to determine the key functional subset. Meanwhile, genes in the key functional subset were subjected to GO and KEGG enrichment analyses. The result showed that genes were mainly enriched in inflammatory reaction-related functions. Next, we screened out intersections of PPI network nodes and pulpitis-related genes. Then, 20 genes were obtained as seed genes. In the PPI network, 50 genes that had the highest correlation with seed genes were screened out using random walk with restart (RWR). Furthermore, 4 pulpitis-related hub genes were obtained from the intersection of the top 50 genes and genes in the key functional subset. Finally, GeneMANIA was utilized to predict genes coexpressed with hub genes, and expression levels of the 4 hub genes in normal and pulpitis groups were analyzed based on GEO data. The result demonstrated that the 4 hub genes were mainly coexpressed with chemokine-related genes and were remarkably upregulated in the pulpitis group. In short, we eventually determined 4 potential biomarkers of pulpitis.

scholarly journals Understanding lipotoxicity in NAFLD pathogenesis: is CD36 a key driver?

2020 ◽  
Vol 11 (9) ◽  
Author(s):  
Patricia Rada ◽  
Águeda González-Rodríguez ◽  
Carmelo García-Monzón ◽  
Ángela M. Valverde
Keyword(s):  
Fatty Acid ◽  
Liver Disease ◽  
Hepatic Steatosis ◽  
Molecular Mechanisms ◽  
Histological Grade ◽  
Soluble Form ◽  
Alcoholic Fatty Liver ◽  
Fatty Acid Translocase ◽  
Promising Therapeutic Approach ◽  
Hepatic Lipotoxicity

Abstract Non-alcoholic fatty liver disease (NAFLD) is the most common cause of chronic liver disease worldwide. NAFLD stages range from simple steatosis (NAFL) to non-alcoholic steatohepatitis (NASH) which can progress to cirrhosis and hepatocellular carcinoma. One of the crucial events clearly involved in NAFLD progression is the lipotoxicity resulting from an excessive fatty acid (FFA) influx to hepatocytes. Hepatic lipotoxicity occurs when the capacity of the hepatocyte to manage and export FFAs as triglycerides (TGs) is overwhelmed. This review provides succinct insights into the molecular mechanisms responsible for lipotoxicity in NAFLD, including ER and oxidative stress, autophagy, lipoapotosis and inflammation. In addition, we highlight the role of CD36/FAT fatty acid translocase in NAFLD pathogenesis. Up-to-date, it is well known that CD36 increases FFA uptake and, in the liver, it drives hepatosteatosis onset and might contribute to its progression to NASH. Clinical studies have reinforced the significance of CD36 by showing increased content in the liver of NAFLD patients. Interestingly, circulating levels of a soluble form of CD36 (sCD36) are abnormally elevated in NAFLD patients and positively correlate with the histological grade of hepatic steatosis. In fact, the induction of CD36 translocation to the plasma membrane of the hepatocytes may be a determining factor in the physiopathology of hepatic steatosis in NAFLD patients. Given all these data, targeting the fatty acid translocase CD36 or some of its functional regulators may be a promising therapeutic approach for the prevention and treatment of NAFLD.

scholarly journals FRI0584 SCREENING AND IDENTIFICATION OF BIOMARKERS IN MYOSITIS

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 896-897
Author(s):  
W. Liu ◽  
X. Zhang
Keyword(s):  
Gene Expression ◽  
Interstitial Lung Disease ◽  
Lung Disease ◽  
Molecular Mechanisms ◽  
Interaction Network ◽  
Gene Expression Omnibus ◽  
Hub Genes ◽  
Protein Protein Interaction ◽  
Protein Protein Interaction Network ◽  
Geo Database

Background:Myositis, including dermatomyositis and polymyositis, is autoimmune disorders that is characterized by muscle degeneration in the proximal extremities, with the complications of weakness of muscles, interstitial lung disease and vascular lesions, even leading to death in an acute progressive process[1,2]. However, the molecular mechanisms of myositis are rarely understood.Objectives:Identify the candidate genes in myositis.Methods:Microarray datasets GSE128470, GSE48280 and GSE39454 were extracted from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) and function enrichment analyses were conducted. The protein-protein interaction network and the analyses of hub genes were performed with STRING and Cytoscape.Results:There were 98 DEGs, of which the function and pathways enrichment analyses showed defense response, immune response, response to virus, inflammatory response, response to wounding, cell adhesion, cell proliferation, cell death and macromolecule metabolic process. 20 hub genes were identified, of which 7 including IRF9 TRIM22 MX2 IFITM1 IFI6 IFI44 IFI44L had not been reported in the literature, related to the response to virus, immune response, transcription from RNA polymerase II promoter, cell apoptosis, cell death. The verification analysis about the 7 genes in GSE128314 showed significant differences in myositis.Conclusion:In conclusion, DEGs and hub genes identified in our study showed the potential molecular mechanisms in myositis, providing the helpful targets for diagnosis and clinical strategy of myositis.References:[1] Wu H, Geng D, Xu J. An approach to the development of interstitial lung disease in dermatomyositis: a study of 230 cases in China[J]. Journal of International Medical Research. 2013;41(2):493–501.[2] Fathi M, Dastmalchi M, Rasmussen E, Lundberg IE, Tornling G. Interstitial lung disease, a common manifestation of newly diagnosed polymyositis and dermatomyositis[J]. Annals of the Rheumatic Diseases. 2004;63(3):297–301.Figure 1.The protein-protein interaction network of 20 hub genesFigure 2.7 genes in GSE128314 showed significant differences in myositisAcknowledgments:The authors acknowledge the efforts of the Gene Expression Omnibus (GEO) database. The interpretation and reporting of these data are the sole responsibility of the authors.Disclosure of Interests:None declared

scholarly journals Bioinformatics analysis of microarray data to identify the candidate biomarkers of lung adenocarcinoma

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7313 ◽  
Author(s):  
Tingting Guo ◽  
Hongtao Ma ◽  
Yubai Zhou
Keyword(s):  
Survival Analysis ◽  
Lung Adenocarcinoma ◽  
Molecular Mechanisms ◽  
Prion Diseases ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Hub Genes

Background Lung adenocarcinoma (LUAD) is the major subtype of lung cancer and the most lethal malignant disease worldwide. However, the molecular mechanisms underlying LUAD are not fully understood. Methods Four datasets (GSE118370, GSE85841, GSE43458 and GSE32863) were obtained from the gene expression omnibus (GEO). Identification of differentially expressed genes (DEGs) and functional enrichment analysis were performed using the limma and clusterProfiler packages, respectively. A protein–protein interaction (PPI) network was constructed via Search Tool for the Retrieval of Interacting Genes (STRING) database, and the module analysis was performed by Cytoscape. Then, overall survival analysis was performed using the Kaplan–Meier curve, and prognostic candidate biomarkers were further analyzed using the Oncomine database. Results Totally, 349 DEGs were identified, including 275 downregulated and 74 upregulated genes which were significantly enriched in the biological process of extracellular structure organization, leukocyte migration and response to peptide. The mainly enriched pathways were complement and coagulation cascades, malaria and prion diseases. By extracting key modules from the PPI network, 11 hub genes were screened out. Survival analysis showed that except VSIG4, other hub genes may be involved in the development of LUAD, in which MYH10, METTL7A, FCER1G and TMOD1 have not been reported previously to correlated with LUAD. Briefly, novel hub genes identified in this study will help to deepen our understanding of the molecular mechanisms of LUAD carcinogenesis and progression, and to discover candidate targets for early detection and treatment of LUAD.

The Relevance of Noninvasive Tools To Assess Fibrosis in Non-Alcoholic Fatty Liver Disease

2020 ◽  
Vol 26 (32) ◽  
pp. 3928-3938
Author(s):  
Grazia Pennisi ◽  
Ciro Celsa ◽  
Antonina Giammanco ◽  
Federica Spatola ◽  
Salvatore Petta
Keyword(s):  
Liver Disease ◽  
Liver Biopsy ◽  
Fatty Liver ◽  
Fatty Liver Disease ◽  
Assessment Tools ◽  
Hepatic Decompensation ◽  
Alcoholic Fatty Liver ◽  
Simple Steatosis ◽  
Life Threatening ◽  
Alcoholic Fatty Liver Disease

Non-alcoholic fatty liver disease (NAFLD) is a growing cause of chronic liver diseases worldwide, involving about 25% of people. NAFLD incorporates a large spectrum of pathological conditions, from simple steatosis to non-alcoholic steatohepatitis (NASH), cirrhosis and its complications include hepatic decompensation and hepatocellular carcinoma (HCC). This progression occurs, over many years, in an asymptomatic way, until advanced fibrosis appears. Thus, the differentiation of NASH from simple steatosis and identification of advanced hepatic fibrosis are key issues. To date, the histological assessment of fibrosis with liver biopsy is the gold standard, but obviously, invasiveness is the greater threshold. In addition, rare but potentially life-threatening complications, poor acceptability, sampling variability and cost maybe restrict its use. Furthermore, due to the epidemic of NAFLD worldwide and several limitations of liver biopsy evaluation, noninvasive assessment tools to detect fibrosis in NAFLD patients are needed.

Sign in / Sign up

Export Citation Format

Share Document