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Key genes associated with non-alcoholic fatty liver disease and acute myocardial infarction.

ABSTRACT: BACKGROUND With the increasing research on non-alcoholic fatty liver (NAFLD) and acute myocardial infarction (AMI), many evidences show a tight correlation between NAFLD and AMI, however the underlying pathophysiology is still not clear. This study was to identify the potential hub genes and pathways related to these two diseases via bioinformatic method. MATERIAL AND METHODS Gene Expression Omnibus (GEO) dataset GSE63067 of NAFLD patients and normal controls was downloaded from GEO database. The GSE60993 and GSE66360 datasets for AMI patients and healthy controls were also obtained. Differential expression genes (DEGs) of NAFLD and AMI datasets, accompanied with common genes between them were achieved. Further GO and KEGG enrichment analysis for common genes were performed. RESULTS To obtain the pathogenesis associated with both NAFLD and AMI, protein-protein interaction (PPI) network was constructed and the top ten hub genes (TLR2, LILRB2, CXCL1, FPR1, TLR4, TYROBP, MMP9, FCER1G, CLEC4D and CCR2) were selected with CONCLUSIONS The results of this study suggesting some novel genes may play an important role in the occurrence and progression NAFLD and AMI. But more experimental researches and clinical trials need to verify.

SUBMITTER: Dai W

PROVIDER: S-EPMC7341693 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Key genes associated with non-alcoholic fatty liver disease and acute myocardial infarction.

Dai Weiran W Sun Yue Y Jiang Zhiyuan Z Du Kuan K Xia Ning N Zhong Guoqiang G

Medical science monitor : international medical journal of experimental and clinical research 20200628

BACKGROUND With the increasing research on non-alcoholic fatty liver (NAFLD) and acute myocardial infarction (AMI), many evidences show a tight correlation between NAFLD and AMI, however the underlying pathophysiology is still not clear. This study was to identify the potential hub genes and pathways related to these two diseases via bioinformatic method. MATERIAL AND METHODS Gene Expression Omnibus (GEO) dataset GSE63067 of NAFLD patients and normal controls was downloaded from GEO database. Th ...[more]

PMID: 32594092

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Project description:Background: Polycystic ovary syndrome (PCOS) is the most common metabolic and endocrinopathies disorder in women of reproductive age and non-alcoholic fatty liver (NAFLD) is one of the most common liver diseases worldwide. Previous research has indicated potential associations between PCOS and NAFLD, but the underlying pathophysiology is still not clear. The present study aims to identify the differentially expressed genes (DEGs) between PCOS and NAFLD through the bioinformatics method, and explore the associated molecular mechanisms. Methods: The microarray datasets GSE34526 and GSE63067 were downloaded from Gene Expression Omnibus (GEO) database and analyzed to obtain the DEGs between PCOS and NAFLD with the GEO2R online tool. Next, the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for the DEGs were performed. Then, the protein-protein interaction (PPI) network was constructed and the hub genes were identified using the STRING database and Cytoscape software. Finally, NetworkAnalyst was used to construct the network between the targeted microRNAs (miRNAs) and the hub genes. Results: A total of 52 genes were identified as DEGs in the above two datasets. GO and KEGG enrichment analysis indicated that DEGs are mostly enriched in immunity and inflammation related pathways. In addition, nine hub genes, including TREM1, S100A9, FPR1, NCF2, FCER1G, CCR1, S100A12, MMP9, and IL1RN were selected from the PPI network by using the cytoHubba and MCODE plug-in. Then, four miRNAs, including miR-20a-5p, miR-129-2-3p, miR-124-3p, and miR-101-3p, were predicted as possibly the key miRNAs through the miRNA-gene network construction. Conclusion: In summary, we firstly constructed a miRNA-gene regulatory network depicting interactions between the predicted miRNA and the hub genes in NAFLD and PCOS, which provides novel insights into the identification of potential biomarkers and valuable therapeutic leads for PCOS and NAFLD.

Project description:BackgroundStudies had shown that autophagy was closely related to nonalcoholic fat liver disease (NAFLD), while N6-methyladenosine (m6A) was involved in the regulation of autophagy. However, the mechanism of m6A related autophagy in NAFLD was unclear.MethodsThe NAFLD related datasets were gained via the Gene Expression Omnibus (GEO) database, and we also extracted 232 autophagy-related genes (ARGs) and 37 m6A. First, differentially expressed ARGs (DE-ARGs) and differentially expressed m6A (DE-m6A) were screened out by differential expression analysis. DE-ARGs associated with m6A were sifted out by Pearson correlation analysis, and the m6A-ARGs relationship pairs were acquired. Then, autophagic genes in m6A-ARGs pairs were analyzed for machine learning algorithms to obtain feature genes. Further, we validated the relationship between feature genes and NAFLD through quantitative real-time polymerase chain reaction (qRT-PCR), Western blot (WB). Finally, the immuno-infiltration analysis was implement, and we also constructed the TF-mRNA and drug-gene networks.ResultsThere were 19 DE-ARGs and four DE-m6A between NAFLD and normal samples. The three m6A genes and five AGRs formed the m6A-ARGs relationship pairs. Afterwards, genes obtained from machine learning algorithms were intersected to yield three feature genes (TBK1, RAB1A, and GOPC), which showed significant positive correlation with astrocytes, macrophages, smooth muscle, and showed significant negative correlation with epithelial cells, and endothelial cells. Besides, qRT-PCR and WB indicate that TBK1, RAB1A and GOPC significantly upregulated in NAFLD. Ultimately, we found that the TF-mRNA network included FOXP1-GOPC, ATF1-RAB1A and other relationship pairs, and eight therapeutic agents such as R-406 and adavosertib were predicted based on the TBK1.ConclusionThe study investigated the potential molecular mechanisms of m6A related autophagy feature genes (TBK1, RAB1A, and GOPC) in NAFLD through bioinformatic analyses and animal model validation. However, it is critical to note that these findings, although consequential, demonstrate correlations rather than cause-and-effect relationships. As such, more research is required to fully elucidate the underlying mechanisms and validate the clinical relevance of these feature genes.

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Key genes associated with non-alcoholic fatty liver disease and acute myocardial infarction.

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Key genes associated with non-alcoholic fatty liver disease and acute myocardial infarction.

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