Nasrin Amiri-Dashatan, Mehdi Koushki, Masoumeh Farahani, Somayeh Chahkandi, Mohammad Salehi, Hossein Chiti, Zohreh Amarloo, Aliasghar Keramatinia, Mohsen Norouzinia
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引用次数: 0
Abstract
Aim: This research aimed to identify the possible links between Non-alcoholic fatty liver disease (NAFLD) and gestational diabetes mellitus (GDM) by examining shared genes and pathways through the use of bioinformatics tools.
Background: NAFLD presents several potential risk factors for the onset of GDM.
Methods: We downloaded relevant microarray datasets from the Gene Expression Omnibus (GEO) database for screening common differentially expressed genes (DEGs) between NAFLD and GDM by GEO2R. Then, we used gene ontology analysis to explore the biological processes and KEGG pathways of NAFLD and GDM occurrence. The hub genes of each disease were screened by analysis of the PPI network, and the common hub genes were identified. We designed a co-expression network and miRNA hub gene regulatory network for selected hub genes by using GeneMANIA and miRNet platforms, respectively.
Results: We identified 521 and 185 DEGs for NAFLD and GDM, respectively. 10 shared genes (FOS, CD22, AMZ1, ANGPT2, ATP1B2, STAB2, EGR1, MMP9, CXCL9, and LCN2) were screened among DEGs of two diseases, with analysis revealing enrichment in pathways such as IL-7 and TNF signaling pathways. Then, common hub genes (FOS, MMP9, and CXCL9) were identified via PPI network analysis, which were strongly correlated with both diseases. In addition, has-mir-34a-5p and has-mir-335-5p were detected as shared miRs that target hubs.
Conclusion: We found 3 shared hub genes involved in NAFLD and GDM. Our research established a connection between the two diseases and could aid in formulating possible intervention strategies aimed at addressing both disorders by utilizing these risk factors.
目的：本研究旨在通过使用生物信息学工具检查共享基因和途径，确定非酒精性脂肪性肝病（NAFLD）和妊娠糖尿病（GDM）之间可能的联系。背景：NAFLD是GDM发病的几个潜在危险因素。方法：从Gene Expression Omnibus （GEO）数据库下载相关微阵列数据集，利用GEO2R筛选NAFLD和GDM之间的共同差异表达基因（DEGs）。然后，我们利用基因本体分析探讨NAFLD和GDM发生的生物学过程和KEGG通路。通过对PPI网络的分析，筛选各疾病的枢纽基因，鉴定出共同的枢纽基因。我们分别利用GeneMANIA和miRNet平台设计了选定枢纽基因的共表达网络和miRNA枢纽基因调控网络。结果：我们分别鉴定出521和185 deg为NAFLD和GDM。在两种疾病的deg中筛选了10个共享基因（FOS、CD22、AMZ1、ANGPT2、ATP1B2、STAB2、EGR1、MMP9、CXCL9和LCN2），分析显示在IL-7和TNF信号通路等途径中富集。然后，通过PPI网络分析确定了与两种疾病密切相关的共同枢纽基因（FOS、MMP9和CXCL9）。此外，检测到has-mir-34a-5p和has-mir-335-5p是靶向枢纽的共享mir。结论：我们发现了3个与NAFLD和GDM相关的共享中枢基因。我们的研究建立了两种疾病之间的联系，可以帮助制定可能的干预策略，旨在通过利用这些危险因素来解决这两种疾病。
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