基于生物信息学方法筛选脓毒症患者死亡的关键基因

doi:10.20047/j.issn1673-7210.2023.32.01

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Abstract Objective To screen and analyze the key genes for death in sepsis patients by bioinformatics method, and to provide a new idea for the basic research of sepsis. Methods The gene pool related to sepsis was searched in GEO database by computer, and the database GSE54514 with peripheral blood gene profile of sepsis patients was selected, and then differential gene analysis, including GO and KEGG enrichment analysis, was performed. The protein protein interaction (PPI) network of differential genes was established using the STRING database, and finally Cytoscape software was used to analyze the interactions of differential genes and screen out the top ten genes that may be associated with death in sepsis patients. After that, the differential genes of sepsis patients and healthy people were screened through another sepsis gene profile GSE137342, and the common differential genes of the two parts of differential genes were found out, and then analyzed in detail. Results There were 184 differential genes (92 up-regulated genes and 92 down-regulated genes) between the patients who died of sepsis and those who did not die of sepsis detected by GSE54514, and the differences were statistically significant (P＜0.05). The results of GO enrichment analysis suggested that the biological processes of these differential genes were mainly concentrated in the generation of precursor metabolites and energy, negative regulation of protein complex assembly, ATP metabolism, and so on. The cell components were mainly concentrated in the adhesive plaque, cyst cavity, cytoplasmic cyst cavity, and so on. The molecular functions were mainly concentrated in cadherin binding, ribosome structural components, integrin binding, and so on. KEGG enrichment analysis indicated that these differential gene pathways were mainly enriched in diabetic cardiomyopathy, ribosome, and so on. The PPI network was used to identify the top ten key genes associated with death in patients with sepsis, including RPS17, RPS15A, RPL27, RPS27, FAU, etc. According to GSE137342, 623 differential genes (seven up-regulated genes and 616 down-regulated genes) were detected between sepsis patients and healthy people, and the differences were statistically significant (P＜0.05). The two databases shared 16 differential genes. Compared with the top ten key genes related to the death of sepsis patients, it was found that RPL27, RPS27, and FAU were the common differential genes. Conclusion RPL27, RPS27, and FAU may be involved in the pathophysiological process of sepsis development and prognosis, and are closely related to the death outcome of sepsis patients.

Key words： Bioinformatics analysis Sepsis Death Differential gene Key gene

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	TAN Mingming1 ZHANG Jinming1 DENG Yisi1 ZHAO Fengli2 LUO Yuanyuan2

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TAN Mingming1 ZHANG Jinming1 DENG Yisi1 ZHAO Fengli2 LUO Yuanyuan2. Screening of key genes for death in sepsis patients based on bioinformatics method[J]. 中国医药导报, 2023, 20(32): 4-10.

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https://www.yiyaodaobao.com.cn/EN/10.20047/j.issn1673-7210.2023.32.01 OR https://www.yiyaodaobao.com.cn/EN/Y2023/V20/I32/4

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