{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,22]],"date-time":"2025-10-22T05:24:33Z","timestamp":1761110673923,"version":"3.41.2"},"reference-count":84,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T00:00:00Z","timestamp":1687132800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Mol. Biosci."],"abstract":"<jats:p><jats:bold>Introduction:<\/jats:bold> Coronavirus disease 2019 (COVID-19) has become a global pandemic and poses a serious threat to human health. Many studies have shown that pre-existing nonalcoholic steatohepatitis (NASH) can worsen the clinical symptoms in patients suffering from COVID-19. However, the potential molecular mechanisms between NASH and COVID-19 remain unclear. To this end, key molecules and pathways between COVID-19 and NASH were herein explored by bioinformatic analysis.<\/jats:p><jats:p><jats:bold>Methods:<\/jats:bold> The common differentially expressed genes (DEGs) between NASH and COVID-19 were obtained by differential gene analysis. Enrichment analysis and protein-protein interaction (PPI) network analysis were carried out using the obtained common DEGs. The key modules and hub genes in PPI network were obtained by using the plug-in of Cytoscape software. Subsequently, the hub genes were verified using datasets of NASH (GSE180882) and COVID-19 (GSE150316), and further evaluated by principal component analysis (PCA) and receiver operating characteristic (ROC). Finally, the verified hub genes were analyzed by single-sample gene set enrichment analysis (ssGSEA) and NetworkAnalyst was used for the analysis of transcription factor (TF)-gene interactions, TF-microRNAs (miRNA) coregulatory network, and Protein-chemical Interactions.<\/jats:p><jats:p><jats:bold>Results:<\/jats:bold> A total of 120 DEGs between NASH and COVID-19 datasets were obtained, and the PPI network was constructed. Two key modules were obtained via the PPI network, and enrichment analysis of the key modules revealed the common association between NASH and COVID-19. In total, 16 hub genes were obtained by five algorithms, and six of them, namely, Kruppel-like factor 6 (KLF6), early growth response 1 (EGR1), growth arrest and DNA-damage-inducible 45 beta (GADD45B), JUNB, FOS, and FOS-like antigen 1 (FOSL1) were confirmed to be closely related to NASH and COVID-19. Finally, the relationship between hub genes and related pathways was analyzed, and the interaction network of six hub genes was constructed with TFs, miRNAs, and compounds.<\/jats:p><jats:p><jats:bold>Conclusion:<\/jats:bold> This study identified six hub genes related to COVID-19 and NASH, providing a new perspective for disease diagnosis and drug development.<\/jats:p>","DOI":"10.3389\/fmolb.2023.1164220","type":"journal-article","created":{"date-parts":[[2023,6,19]],"date-time":"2023-06-19T07:46:44Z","timestamp":1687160804000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Bioinformatic and systems biology approach revealing the shared genes and molecular mechanisms between COVID-19 and non-alcoholic hepatitis"],"prefix":"10.3389","volume":"10","author":[{"given":"Huishuang","family":"Lu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jiaxiu","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yalan","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jin","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yaxin","family":"An","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Wei","family":"Du","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuefei","family":"Cai","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1965","published-online":{"date-parts":[[2023,6,19]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"4653","DOI":"10.1038\/onc.2016.2","article-title":"A novel KLF6-Rho GTPase axis regulates hepatocellular carcinoma cell migration and dissemination","volume":"35","author":"Ahronian","year":"2016","journal-title":"Oncogene"},{"key":"B2","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1016\/j.it.2017.01.006","article-title":"IL-17 signaling: The Yin and the yang","volume":"38","author":"Amatya","year":"2017","journal-title":"Trends Immunol."},{"key":"B3","doi-asserted-by":"publisher","first-page":"350","DOI":"10.1002\/hep.28709","article-title":"Bile acids and nonalcoholic fatty liver disease: Molecular insights and therapeutic perspectives","volume":"65","author":"Arab","year":"2017","journal-title":"Hepatology"},{"key":"B4","doi-asserted-by":"publisher","first-page":"529","DOI":"10.1016\/S2468-1253(20)30084-4","article-title":"COVID-19 and the liver: Little cause for concern","volume":"5","author":"Bangash","year":"2020","journal-title":"lancet Gastroenterology hepatology"},{"key":"B5","doi-asserted-by":"publisher","first-page":"30","DOI":"10.1111\/j.1753-4887.2009.00253.x","article-title":"Low zinc status: A new risk factor for pneumonia in the elderly?","volume":"68","author":"Barnett","year":"2010","journal-title":"Nutr. 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