Introduction. Novel coronavirus pneumonia (COVID-19) is an acute respiratory disease caused by the novel coronavirus SARS-CoV-2. Severe and critical illness, especially secondary bacterial infection (SBI) cases, accounts for the vast majority of COVID-19-related deaths. However, the relevant biological indicators of COVID-19 and SBI are still unclear, which significantly limits the timely diagnosis and treatment. Methods. The differentially expressed genes (DEGs) between severe COVID-19 patients with SBI and without SBI were screened through the analysis of GSE168017 and GSE168018 datasets. By performing Gene Ontology (GO) enrichment analysis for significant DEGs, significant biological processes, cellular components, and molecular functions were selected. To understand the high-level functions and utilities of the biological system, the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed. By analyzing protein-protein interaction (PPI) and key subnetworks, the core DEGs were found. Results. 85 DEGs were upregulated, and 436 DEGs were downregulated. The CD14 expression was significantly increased in the SBI group of severe COVID-19 patients (). The area under the curve (AUC) of CD14 in the SBI group in severe COVID-19 patients was 0.9429. The presepsin expression was significantly higher in moderate to severe COVID-19 patients (). Presepsin has a diagnostic value for moderate to severe COVID-19 with the AUC of 0.9732. The presepsin expression of COVID-19 patients in the nonsurvivors was significantly higher than that in the survivors (). Conclusion. Presepsin predicts severity and SBI in COVID-19 and may be associated with prognosis in COVID-19.

中文翻译：

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Presepsin 通过生物信息学分析预测 COVID-19 的严重程度和继发细菌感染


介绍。新型冠状病毒肺炎（COVID-19）是由新型冠状病毒 SARS-CoV-2 引起的急性呼吸道疾病。严重和危重疾病，特别是继发细菌感染 (SBI) 病例，占 COVID-19 相关死亡的绝大多数。然而，COVID-19和SBI的相关生物学指标仍不清楚，这极大地限制了及时诊断和治疗。方法。通过GSE168017和GSE168018数据集的分析，筛选出患有SBI和不患有SBI的重症COVID-19患者之间的差异表达基因（DEG）。通过对重要的 DEG 进行基因本体 (GO) 富集分析，选择了重要的生物过程、细胞成分和分子功能。为了了解生物系统的高级功能和效用，进行了京都基因和基因组百科全书（KEGG）途径富集分析。通过分析蛋白质-蛋白质相互作用（PPI）和关键子网络，找到了核心DEG。结果。 85 个 DEG 上调，436 个 DEG 下调。重症COVID-19患者SBI组CD14表达显着升高（ ）。 SBI组重症COVID-19患者CD14的曲线下面积（AUC）为0.9429。中度至重度 COVID-19 患者中 presepsin 的表达显着较高（ ）。Presepsin 对中度至重度 COVID-19 有诊断价值，AUC 为 0.9732。 COVID-19患者非幸存者中的presepsin表达显着高于幸存者（）。结论。 Presepsin 可预测 COVID-19 的严重程度和 SBI，并可能与 COVID-19 的预后相关。