{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,25]],"date-time":"2026-08-25T01:13:26Z","timestamp":1787620406153,"version":"build-2736575974"},"reference-count":41,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T00:00:00Z","timestamp":1684195200000},"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. Immunol."],"abstract":"<jats:p>Background Severe coronavirus disease 2019 (COVID -19) has led to severe pneumonia or acute respiratory distress syndrome (ARDS) worldwide. we have noted that many critically ill patients with COVID-19 present with typical sepsis-related clinical manifestations, including multiple organ dysfunction syndrome, coagulopathy, and septic shock. The molecular mechanisms that underlie COVID-19, ARDS and sepsis are not well understood. The objectives of this study were to analyze potential molecular mechanisms and identify potential drugs for the treatment of COVID-19, ARDS and sepsis using bioinformatics and a systems biology approach. Methods Three RNA-seq datasets (GSE171110, GSE76293 and GSE137342) from Gene Expression Omnibus (GEO) were employed to detect mutual differentially expressed genes (DEGs) for the patients with the COVID-19, ARDS and sepsis for functional enrichment, pathway analysis, and candidate drugs analysis. Results We obtained 110 common DEGs among COVID-19, ARDS and sepsis. ARG1, FCGR1A, MPO, and TLR5 are the most influential hub genes. The infection and immune-related pathways and functions are the main pathways and molecular functions of these three diseases. FOXC1, YY1, GATA2, FOXL, STAT1 and STAT3 are important TFs for COVID-19. mir-335-5p, miR-335-5p and hsa-mir-26a-5p were associated with COVID-19. Finally, the hub genes retrieved from the DSigDB database indicate multiple drug molecules and drug-targets interaction. Conclusion We performed a functional analysis under ontology terms and pathway analysis and found some common associations among COVID-19, ARDS and sepsis. Transcription factors\u2013genes interaction, protein\u2013drug interactions, and DEGs-miRNAs coregulatory network with common DEGs were also identified on the datasets. We believe that the candidate drugs obtained in this study may contribute to the effective treatment of COVID-19.<\/jats:p>","DOI":"10.3389\/fimmu.2023.1152186","type":"journal-article","created":{"date-parts":[[2023,5,16]],"date-time":"2023-05-16T05:38:18Z","timestamp":1684215498000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":16,"title":["Bioinformatics and system biology approach to identify the influences among COVID-19, ARDS and sepsis"],"prefix":"10.3389","volume":"14","author":[{"given":"Peiyu","family":"Li","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tao","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiming","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xingui","family":"Dai","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bin","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhen","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhiwang","family":"Li","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2023,5,16]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(20)30251-8","article-title":"Genomic characterisation and epidemiology of 2019 novel coronavirus: implications for virus origins and receptor binding","volume":"395","author":"Lu","year":"2020","journal-title":"Lancet"},{"key":"B2","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-020-2739-1","article-title":"The coding capacity of SARS-CoV-2","volume":"589","author":"Finkel","year":"2021","journal-title":"Nature"},{"key":"B3","doi-asserted-by":"publisher","DOI":"10.3389\/fimmu.2022.860676","article-title":"Bioinformatics and system biology approach to identify the influences of COVID-19 on rheumatoid arthritis","volume":"13","author":"Hu","year":"2022","journal-title":"Front Immunol"},{"key":"B4","doi-asserted-by":"publisher","DOI":"10.1016\/S2213-2600(20)30217-4","article-title":"Immunotherapies for COVID-19: lessons learned from sepsis","volume":"8","author":"Remy","year":"2020","journal-title":"Lancet Respir Med"},{"key":"B5","doi-asserted-by":"publisher","DOI":"10.1038\/s41422-021-00523-8","article-title":"A cohort autopsy study defines COVID-19 systemic pathogenesis","volume":"31","author":"Yao","year":"2021","journal-title":"Cell Res"},{"key":"B6","doi-asserted-by":"publisher","DOI":"10.3906\/sag-2108-239","article-title":"COVID-19 and sepsis","volume":"51","author":"Kocak","year":"2021","journal-title":"Turk J Med Sci"},{"key":"B7","author":"Shane","year":"2017"},{"key":"B8","author":"Chen","year":"2019"},{"key":"B9","doi-asserted-by":"publisher","DOI":"10.3760\/cma.j.issn.","article-title":"[Definition and dignosis of sepsis 3.0]","volume":"55","author":"Guo","year":"2016","journal-title":"Zhonghua Nei Ke Za Zhi"},{"key":"B10","doi-asserted-by":"publisher","DOI":"10.1001\/jama.2016.0287","article-title":"The third international consensus definitions for sepsis and septic shock (Sepsis-3)","volume":"315","author":"Singer","year":"2016","journal-title":"JAMA"},{"key":"B11","doi-asserted-by":"publisher","first-page":"6362344","DOI":"10.1155\/2022\/6362344","article-title":"Classic signaling pathways in alveolar injury and repair involved in sepsis-induced ALI\/ARDS: new research progress and prospect","author":"Li","year":"2022","journal-title":"Dis Markers 2022."},{"key":"B12","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gku1179","article-title":"Gene Ontology Consortium. 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