Systems biology approach reveals a common molecular basis for COVID-19 and non-alcoholic fatty liver disease (NAFLD).
Ontology highlight
ABSTRACT: Background
Patients with non-alcoholic fatty liver disease (NAFLD) may be more susceptible to coronavirus disease 2019 (COVID-19) and even more likely to suffer from severe COVID-19. Whether there is a common molecular pathological basis for COVID-19 and NAFLD remains to be identified. The present study aimed to elucidate the transcriptional alterations shared by COVID-19 and NAFLD and to identify potential compounds targeting both diseases.Methods
Differentially expressed genes (DEGs) for COVID-19 and NAFLD were extracted from the GSE147507 and GSE89632 datasets, and common DEGs were identified using the Venn diagram. Subsequently, we constructed a protein-protein interaction (PPI) network based on the common DEGs and extracted hub genes. Then, we performed gene ontology (GO) and pathway analysis of common DEGs. In addition, transcription factors (TFs) and miRNAs regulatory networks were constructed, and drug candidates were identified.Results
We identified a total of 62 common DEGs for COVID-19 and NAFLD. The 10 hub genes extracted based on the PPI network were IL6, IL1B, PTGS2, JUN, FOS, ATF3, SOCS3, CSF3, NFKB2, and HBEGF. In addition, we also constructed TFs-DEGs, miRNAs-DEGs, and protein-drug interaction networks, demonstrating the complex regulatory relationships of common DEGs.Conclusion
We successfully extracted 10 hub genes that could be used as novel therapeutic targets for COVID-19 and NAFLD. In addition, based on common DEGs, we propose some potential drugs that may benefit patients with COVID-19 and NAFLD.
SUBMITTER: Jiang ST
PROVIDER: S-EPMC9664052 | biostudies-literature | 2022 Nov
REPOSITORIES: biostudies-literature
Publications
Systems biology approach reveals a common molecular basis for COVID-19 and non-alcoholic fatty liver disease (NAFLD).
Jiang Shi-Tao ST Liu Yao-Ge YG Zhang Lei L Sang Xin-Ting XT Xu Yi-Yao YY Lu Xin X
European journal of medical research 20221115 1
<h4>Background</h4>Patients with non-alcoholic fatty liver disease (NAFLD) may be more susceptible to coronavirus disease 2019 (COVID-19) and even more likely to suffer from severe COVID-19. Whether there is a common molecular pathological basis for COVID-19 and NAFLD remains to be identified. The present study aimed to elucidate the transcriptional alterations shared by COVID-19 and NAFLD and to identify potential compounds targeting both diseases.<h4>Methods</h4>Differentially expressed genes ...[more]
Similar Datasets
Project description:The abnormal accumulation of fat in the liver is often related either to metabolic risk factors associated with metabolic syndrome in the absence of alcohol consumption (nonalcoholic fatty liver disease, NAFLD) or to chronic alcohol consumption (alcoholic fatty liver disease, AFLD). Clinical and histological studies suggest that NAFLD and AFLD share pathogenic mechanisms. Nevertheless, current data are still inconclusive as to whether the underlying biological process and disease pathways of NAFLD and AFLD are alike. Our primary aim was to integrate omics and physiological data to answer the question of whether NAFLD and AFLD share molecular processes that lead to disease development. We also explored the extent to which insulin resistance (IR) is a distinctive feature of NAFLD. To answer these questions, we used systems biology approaches, such as gene enrichment analysis, protein-protein interaction networks, and gene prioritization, based on multi-level data extracted by computational data mining. We observed that the leading disease pathways associated with NAFLD did not significantly differ from those of AFLD. However, systems biology revealed the importance of each molecular process behind each of the two diseases, and dissected distinctive molecular NAFLD and AFLD-signatures. Comparative co-analysis of NAFLD and AFLD clarified the participation of NAFLD, but not AFLD, in cardiovascular disease, and showed that insulin signaling is impaired in fatty liver regardless of the noxa, but the putative regulatory mechanisms associated with NAFLD seem to encompass a complex network of genes and proteins, plausible of epigenetic modifications. Gene prioritization showed a cancer-related functional map that suggests that the fatty transformation of the liver tissue is regardless of the cause, an emerging mechanism of ubiquitous oncogenic activation. In conclusion, similar underlying disease mechanisms lead to NAFLD and AFLD, but specific ones depict a particular disease signature that has a different impact on the systemic context.
| S-EPMC3596348 | biostudies-literature
Project description:With an estimated prevalence of about 30% in western countries non-alcoholic fatty liver disease (NAFLD) is a major public health issue [PMID: 18956290]. NAFLD is associated with the metabolic syndrome of insulin resistance, obesity, glucose intolerance. Although many studies are pointing to an induction of insulin resistance by NAFLD causality between both phenotypes is not fully clarified. Furthermore, mechanisms leading to strongly differing progression of NAFLD have to be elucidated which range from mild steatosis up to severe steatohepatitis. Steatohepatitis might even result in liver cirrhosis and hepatocellular carcinoma. Additional complexity is introduced into the understanding of the disease by recent studies providing evidence for a direct development of carcinoma from steatosis without the formerly assumed intermediary phase of cirrhosis. Here, we investigate liver samples from patients with varying severities of steatosis in an integrative approach employing transcriptomics, serum biomarker profling, metabolomics data and systems biology models. Total RNA obtained from hepatocytes derived from nine obese patients with distinct grades of steatosis. This dataset is part of the TransQST collection.
2015-11-01 | E-GEOD-46300 | biostudies-arrayexpress
Project description:With an estimated prevalence of about 30% in western countries non-alcoholic fatty liver disease (NAFLD) is a major public health issue [PMID: 18956290]. NAFLD is associated with the metabolic syndrome of insulin resistance, obesity, glucose intolerance. Although many studies are pointing to an induction of insulin resistance by NAFLD causality between both phenotypes is not fully clarified. Furthermore, mechanisms leading to strongly differing progression of NAFLD have to be elucidated which range from mild steatosis up to severe steatohepatitis. Steatohepatitis might even result in liver cirrhosis and hepatocellular carcinoma. Additional complexity is introduced into the understanding of the disease by recent studies providing evidence for a direct development of carcinoma from steatosis without the formerly assumed intermediary phase of cirrhosis. Here, we investigate liver samples from patients with varying severities of steatosis in an integrative approach employing transcriptomics, serum biomarker profling, metabolomics data and systems biology models.
2015-11-01 | GSE46300 | GEO
Project description:Non-alcoholic fatty liver disease (NAFLD) is now the most frequent global chronic liver disease. Individuals with NAFLD exhibited an increased risk of all-cause mortality driven by extrahepatic cancers and liver and cardiovascular disease. Once the disease is established, women have a higher risk of disease progression and worse outcome. It is therefore critical to deepen the current knowledge on the pathophysiology of NAFLD in women. Here, we used a systems biology approach to investigate the contribution of different organs to this disease. We analyzed transcriptomics profiles of liver and adipose tissues, fecal metagenomes, and plasma metabolomes of 55 women with and without NAFLD. We observed differences in metabolites, expression of human genes, and gut microbial features between the groups and revealed that there is substantial crosstalk between these different omics sets. Multi-omics analysis of individuals with NAFLD may provide novel strategies to study the pathophysiology of NAFLD in humans.
| S-EPMC9382345 | biostudies-literature
Project description:Background Osteosarcoma (OS) is the most common malignant bone tumor in children and adolescents. The survival rate of patients with metastatic disease remains very dismal. Nevertheless, metastasis is a complex process and a single-level analysis is not likely to identify its key biological determinants. In this study, we used a systems biology approach to identify common metastatic pathways that are jointly supported by both mRNA and protein expression data in two distinct human metastatic OS models. Results mRNA expression microarray and N-linked glycoproteomic analyses were performed on two commonly used isogenic pairs of human metastatic OS cell lines, namely HOS/143B and SaOS-2/LM7. Pathway analysis of the differentially regulated genes and glycoproteins separately revealed pathways associated to metastasis including cell cycle regulation, immune response, and epithelial-to-mesenchymal-transition. However, no common significant pathway was found at both genomic and proteomic levels between the two metastatic models, suggesting a very different biological nature of the cell lines. To address this issue, we used a topological significance analysis based on a “shortest path” algorithm to identify topological nodes, which uncovered additional biological information with respect to the genomic and glycoproteomic profiles but remained hidden from the direct analyses. Pathway analysis of the significant topological nodes revealed a striking concordance between the models and identified significant common pathways, including “Cytoskeleton remodeling/TGF/WNT”, “Cytoskeleton remodeling/Cytoskeleton remodeling”, and “Cell adhesion/Chemokines and adhesion”. Of these, the “Cytoskeleton remodeling/TGF/WNT” was the top ranked common pathway from the topological analysis of the genomic and proteomic profiles in the two metastatic models. The up-regulation of proteins in the “Cytoskeleton remodeling/TGF/WNT” pathway in the SaOS-2/LM7 and HOS/143B models was further validated using an orthogonal Reverse Phase Protein Array platform. Conclusions In this study, we used a systems biology approach by integrating genomic and proteomic data to identify key and common metastatic mechanisms in OS. The use of the topological analysis revealed hidden biological pathways that are known to play critical roles in metastasis. Wnt signaling has been previously implicated in OS and other tumors, and inhibitors of Wnt signaling pathways are available for clinical testing. Further characterization of this common pathway and other topological pathways identified from this study may lead to a novel therapeutic strategy for the treatment of metastatic OS.
2012-04-25 | GSE37552 | GEO
Project description:Background Osteosarcoma (OS) is the most common malignant bone tumor in children and adolescents. The survival rate of patients with metastatic disease remains very dismal. Nevertheless, metastasis is a complex process and a single-level analysis is not likely to identify its key biological determinants. In this study, we used a systems biology approach to identify common metastatic pathways that are jointly supported by both mRNA and protein expression data in two distinct human metastatic OS models. Results mRNA expression microarray and N-linked glycoproteomic analyses were performed on two commonly used isogenic pairs of human metastatic OS cell lines, namely HOS/143B and SaOS-2/LM7. Pathway analysis of the differentially regulated genes and glycoproteins separately revealed pathways associated to metastasis including cell cycle regulation, immune response, and epithelial-to-mesenchymal-transition. However, no common significant pathway was found at both genomic and proteomic levels between the two metastatic models, suggesting a very different biological nature of the cell lines. To address this issue, we used a topological significance analysis based on a “shortest path” algorithm to identify topological nodes, which uncovered additional biological information with respect to the genomic and glycoproteomic profiles but remained hidden from the direct analyses. Pathway analysis of the significant topological nodes revealed a striking concordance between the models and identified significant common pathways, including “Cytoskeleton remodeling/TGF/WNT”, “Cytoskeleton remodeling/Cytoskeleton remodeling”, and “Cell adhesion/Chemokines and adhesion”. Of these, the “Cytoskeleton remodeling/TGF/WNT” was the top ranked common pathway from the topological analysis of the genomic and proteomic profiles in the two metastatic models. The up-regulation of proteins in the “Cytoskeleton remodeling/TGF/WNT” pathway in the SaOS-2/LM7 and HOS/143B models was further validated using an orthogonal Reverse Phase Protein Array platform. Conclusions In this study, we used a systems biology approach by integrating genomic and proteomic data to identify key and common metastatic mechanisms in OS. The use of the topological analysis revealed hidden biological pathways that are known to play critical roles in metastasis. Wnt signaling has been previously implicated in OS and other tumors, and inhibitors of Wnt signaling pathways are available for clinical testing. Further characterization of this common pathway and other topological pathways identified from this study may lead to a novel therapeutic strategy for the treatment of metastatic OS. In this study we analyzed two human metastatic OS cell lines and their parental non-metastatic lines. The two human metastatic OS cell line models were HOS/143B and SaOS-2/LM7. The HOS cell line, originally known as M.T. and later as TE-85, was derived from an OS of a 13 year-old girl. The 143B metastatic subline was generated from HOS by a Ki-RAS oncogene transformation [Rhim, J.S., et al., Characterization of human cells transformed in vitro by N-methyl-N'-nitro-N-nitrosoguanidine. Int J Cancer, 1977. 19(4): p. 505-10.]. The SaOS-2 cell was derived from an OS of an 11 year-old girl, and its metastatic subline LM7, was developed by multiple in vivo selection of SaOS-2 cells in mice with pulmonary metastases [Jia, S.F., L.L. Worth, and E.S. Kleinerman, A nude mouse model of human osteosarcoma lung metastases for evaluating new therapeutic strategies. Clin Exp Metastasis, 1999. 17(6): p. 501-6.]. No replicates were included.
2012-04-24 | E-GEOD-37552 | biostudies-arrayexpress
Project description:Osteosarcoma (OS) is the most common malignant bone tumor in children and adolescents. The survival rate of patients with metastatic disease remains very dismal. Nevertheless, metastasis is a complex process and a single-level analysis is not likely to identify its key biological determinants. In this study, we used a systems biology approach to identify common metastatic pathways that are jointly supported by both mRNA and protein expression data in two distinct human metastatic OS models.mRNA expression microarray and N-linked glycoproteomic analyses were performed on two commonly used isogenic pairs of human metastatic OS cell lines, namely HOS/143B and SaOS-2/LM7. Pathway analysis of the differentially regulated genes and glycoproteins separately revealed pathways associated to metastasis including cell cycle regulation, immune response, and epithelial-to-mesenchymal-transition. However, no common significant pathway was found at both genomic and proteomic levels between the two metastatic models, suggesting a very different biological nature of the cell lines. To address this issue, we used a topological significance analysis based on a "shortest-path" algorithm to identify topological nodes, which uncovered additional biological information with respect to the genomic and glycoproteomic profiles but remained hidden from the direct analyses. Pathway analysis of the significant topological nodes revealed a striking concordance between the models and identified significant common pathways, including "Cytoskeleton remodeling/TGF/WNT", "Cytoskeleton remodeling/Cytoskeleton remodeling", and "Cell adhesion/Chemokines and adhesion". Of these, the "Cytoskeleton remodeling/TGF/WNT" was the top ranked common pathway from the topological analysis of the genomic and proteomic profiles in the two metastatic models. The up-regulation of proteins in the "Cytoskeleton remodeling/TGF/WNT" pathway in the SaOS-2/LM7 and HOS/143B models was further validated using an orthogonal Reverse Phase Protein Array platform.In this study, we used a systems biology approach by integrating genomic and proteomic data to identify key and common metastatic mechanisms in OS. The use of the topological analysis revealed hidden biological pathways that are known to play critical roles in metastasis. Wnt signaling has been previously implicated in OS and other tumors, and inhibitors of Wnt signaling pathways are available for clinical testing. Further characterization of this common pathway and other topological pathways identified from this study may lead to a novel therapeutic strategy for the treatment of metastatic OS.
| S-EPMC3431263 | biostudies-literature
Project description:BackgroundMetabolic dysfunction-associated steatohepatitis (MASH) is characterized by liver inflammation and damage caused by a buildup of fat in the liver. Hepatitis C, caused by hepatitis C virus (HCV), is a disease that can lead to liver cirrhosis, liver cancer, and liver failure. MASH and hepatitis C are the common causes of liver cirrhosis and hepatocellular carcinoma. Several studies have shown that hepatic steatosis is also a common histological feature of liver in HCV infected patients. However, the common molecular basis for MASH and hepatitis C remains poorly understood.MethodsFirstly, differentially expressed genes (DEGs) for MASH and hepatitis C were extracted from the GSE89632, GSE164760 and GSE14323 datasets. Subsequently, the common DEGs shared among these datasets were determined using the Venn diagram. Next, a protein-protein interaction (PPI) network was constructed based on the common DEGs and the hub genes were extracted. Then, gene ontology (GO) and pathway analysis of the common DEGs were performed. Furthermore, transcription factors (TFs) and miRNAs regulatory networks were constructed, and drug candidates were identified. After the MASH and hepatitis C cell model was treated with predicted drug, the expression levels of the signature genes were measured by qRT-PCR and ELISA.Results866 common DEGs were identified in MASH and hepatitis C. The GO analysis showed that the most significantly enriched biological process of the DEGs was the positive regulation of cytokine production. 10 hub genes, including STAT1, CCL2, ITGAM, PTPRC, CXCL9, IL15, SELL, VCAM1, TLR4 and CCL5, were selected from the PPI network. By constructing the TF-gene and miRNA-gene network, most prominent TFs and miRNAs were screened out. Potential drugs screening shows that Budesonide and Dinoprostone may benefit patients, and cellular experiments showed that Budesonide effectively inhibited the expression of genes related to glycolipid metabolism, fibrosis, and inflammatory factors.ConclusionWe extracted 10 hub genes between MASH and hepatitis C, and performed a series of analyses on the genes. Molecular docking and in vitro studies have revealed that Budesonide can effectively suppress the progression of MASH and hepatitis C. This study can provide novel insights into the potential drug targets and biomarkers for MASH and hepatitis C.
| S-EPMC11599856 | biostudies-literature
Project description:Nonalcoholic fatty liver disease (NAFLD) has become a major public health issue as its progression increases risks of multisystem morbidity and mortality. Recent evidence indicates a more complex relationship between hypertension and NAFLD than previously thought. In this study, a comprehensive literature search was used to gather information supporting the comorbidity phenomenon of hypertension and NAFLD. Then, systems biology approach was applied to identify the potential genes and mechanisms simultaneously associated with hypertension and NAFLD. With the help of protein-protein interaction network-based algorithm, we found that the distance between hypertension and NAFLD was much less than random ones. Sixty-four shared genes of hypertension and NAFLD modules were identified as core genes. Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analysis indicated that some inflammatory, metabolic and endocrine signals were related to the potential biological functions of core genes. More importantly, drugs used to treat cardiovascular diseases, hypertension, hyperlipidemia, inflammatory diseases and depression could be potential therapeutics against hypertension-NAFLD co-occurrence. After analyzing public OMICs data, ALDH1A1 was identified as a potential therapeutic target, without being affected by reverse causality. These findings give a clue for the potential mechanisms of comorbidity of hypertension and NAFLD and highlight the multiple target-therapeutic strategy of NAFLD for future clinical research.
| S-EPMC8806441 | biostudies-literature
Project description:Irisin is a cytokine involved in many metabolic pathways occurring, among others, in muscles, adipose tissue and liver. Thus, fluctuations in irisin levels are suggested to be related to metabolic diseases. Therefore, the purpose of our study was to evaluate whether irisin may be associated with non-alcoholic fatty liver disease (NAFLD). A total of 138 patients (70/68 male/female, mean age 65.61 ± 10.44 years) were enrolled in the study. The patients were assigned to the NAFLD group (n = 72, including 46 patients with type 2 diabetes (T2DM]) and the group without NAFLD (n = 66, 31 patients with T2DM). NAFLD was diagnosed based on ultrasound examination, Hepatic Steatosis Index (HSI) and Fatty Liver Index. Baseline anthropometric, blood pressure and biochemical parameters were collected. The serum irisin level was determined using an ELISA test. We observed that NAFLD was associated with an increased concentration of irisin. Moreover, Spearman correlations and linear regression analysis revealed that irisin level correlates with some anthropometric and biochemical parameters such as body mass index, glycated hemoglobin, aspartic aminotransferase, creatinine and urea. Logistic regression analysis depicted that odds for NAFLD increase 1.17 times for each 1 μg/mL rise of irisin concentration. Finally, ROC analysis showed that the concentration of irisin possesses a discriminate capacity for NAFLD and optimal cut points concentration could be designed. The risk of NAFLD in the subgroup with irisin concentration above 3.235 μg/mL was 4.57 times higher than in patients with the lower concentration of irisin. To conclude, the obtained results suggest that irisin concentration is associated with some anthropometric and biochemical parameters and should be further investigated toward its usage as a diagnostic biomarker of NAFLD.
| S-EPMC9496390 | biostudies-literature