Table 2_Identification of potential hub genes and drugs in septic kidney injury: a bioinformatic analysis with preliminary experimental validation.docx

BackgroundSepsis-associated kidney injury (SAKI) is a prevalent complication in intensive care unit (ICU) patients with sepsis. Diagnosis currently relies on clinical assessment, urine output, and serum creatinine levels, yet effective clinical treatments remain scarce. Our objectives are to explore prospective, targeted medications for the treatment of septic kidney injury and to employ bioinformatics to identify key genes and pathways that may be implicated in the pathogenesis of SAKI.
MethodsWe utilized the GEO database for differential gene screening. Related genes of septic kidney injury were identified through Pubmed2Ensembl, followed by annotation and visualization of gene ontology biological processes and KEGG pathways using DAVID. Protein–protein interactions were analyzed with the STRING database, and hub genes were identified using Cytoscape software. Candidate genes were further validated through Metascape. The CTD database was employed to uncover the relationship between hub genes and acute kidney injury (AKI). CIBERSORT was applied to evaluate the infiltration of immune cells and their association with hub genes. Hub genes were experimentally verified through qPCR detection. Lastly, the Drug–Gene Interaction Database (DGIdb) was utilized to identify drug–gene interactions.
ResultsSix genes, including TNF, CXCL8, IL-6, IL-1β, IL-2, and IL-10, were associated with three major signaling pathways: the COVID-19 adverse outcome pathway, an overview of pro-inflammatory and pro-fibrotic mediators, and the interleukin-10 signaling pathway. Additionally, 12 targeted drugs were identified as potential therapeutic agents.

脓毒症相关性肾损伤（Sepsis-associated kidney injury, SAKI）是重症监护病房（intensive care unit, ICU）脓毒症患者的常见并发症。当前其诊断仍依赖临床评估、尿量及血清肌酐水平，但有效的临床治疗手段仍较为匮乏。本研究旨在探索治疗脓毒症肾损伤的前瞻性靶向药物，并借助生物信息学手段挖掘可能参与SAKI发病机制的关键基因与通路。
方法 本研究利用GEO数据库开展差异基因筛选。通过Pubmed2Ensembl工具鉴定脓毒症肾损伤相关基因，随后使用DAVID对基因本体（Gene Ontology, GO）生物过程及KEGG通路进行注释与可视化。借助STRING数据库分析蛋白质-蛋白质相互作用（protein–protein interactions, PPI），并通过Cytoscape软件筛选核心基因（hub genes）。通过Metascape对候选基因进行进一步验证。采用CTD数据库探究核心基因与急性肾损伤（acute kidney injury, AKI）的关联。利用CIBERSORT评估免疫细胞浸润情况及其与核心基因的相关性。通过实时荧光定量PCR（quantitative real-time polymerase chain reaction, qPCR）检测对核心基因进行实验验证。最后，借助药物-基因相互作用数据库（Drug–Gene Interaction Database, DGIdb）挖掘药物-基因相互作用关系。
结果 共筛选得到TNF、CXCL8、IL-6、IL-1β、IL-2及IL-10共6个基因，它们与3条主要信号通路相关：新型冠状病毒肺炎（Corona Virus Disease 2019, COVID-19）不良预后通路、促炎与促纤维化介质概述以及白细胞介素-10信号通路。此外，本研究还鉴定出12种靶向药物作为潜在治疗制剂。