Novel insights into the molecular mechanisms of sepsis-associated acute kidney injury: an integrative study of GBP2, PSMB8, PSMB9 genes and immune microenvironment characteristics.
Haiting Ye, Xiang Zhang, Pengyan Li, Mei Wang, Ruolan Liu, Dingping Yang
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引用次数: 0
Abstract
Background: Sepsis-associated acute kidney injury (SA-AKI) is a prevalent and severe complication of sepsis, but its complex pathogenesis remains unclear. This study aims to identify potential biomarkers for SA-AKI by elucidating its molecular mechanisms through bioinformatics methods.
Methods: Transcriptional data related to SA-AKI were obtained from the Gene Expression Omnibus (GEO) database. We used differentially expressed genes (DEGs) and weighted gene co-expression network analysis (WGCNA) to identify characteristic genes associated with SA-AKI and conducted enrichment analyses. Hub genes were determined using protein-protein interaction (PPI) network analysis and the Least Absolute Shrinkage and Selection Operator (LASSO). Additionally, ROC curves were plotted to assess the diagnostic value of these core genes. Immune cell infiltration was analyzed using the CIBERSORT algorithm, and potential associations between the hub genes and clinicopathological features were explored based on the Nephroseq database. Finally, a murine model of SA-AKI was induced with lipopolysaccharide (LPS) to validate the findings, and mRNA abundance and protein production levels of pivotal genes were confirmed via RT-qPCR, Western blotting, and immunohistochemical methods.
Results: We identified 268 characteristic genes associated with SA-AKI that are enriched in immune and inflammation-related pathways. Utilizing machine learning techniques, three key genes were screened: GBP2, PSMB8 and PSMB9. The expression patterns of these three genes were well-validated through animal experiments and databases. Correlation between these genes and clinical indicators was confirmed using the Nephroseq database. Furthermore, immune infiltration analysis provided additional insights into their potential functions.
Conclusion: GBP2, PSMB8, and PSMB9 are promising candidate genes for SA-AKI, providing a novel perspective on its pathological mechanisms. Further exploration of the biological roles of these genes in the pathogenesis of SA-AKI is needed in the future.
背景:脓毒症相关急性肾损伤(SA-AKI)是脓毒症的一种常见且严重的并发症,但其复杂的发病机制尚不清楚。本研究旨在通过生物信息学方法阐明SA-AKI的分子机制,寻找潜在的生物标志物。方法:从Gene Expression Omnibus (GEO)数据库中获取SA-AKI相关转录数据。我们使用差异表达基因(DEGs)和加权基因共表达网络分析(WGCNA)来鉴定与SA-AKI相关的特征基因,并进行富集分析。利用蛋白相互作用(PPI)网络分析和最小绝对收缩和选择算子(LASSO)确定枢纽基因。此外,绘制ROC曲线以评估这些核心基因的诊断价值。使用CIBERSORT算法分析免疫细胞浸润,并基于Nephroseq数据库探索枢纽基因与临床病理特征之间的潜在关联。最后,用脂多糖(LPS)诱导SA-AKI小鼠模型验证研究结果,并通过RT-qPCR、Western blotting和免疫组织化学方法确认关键基因的mRNA丰度和蛋白产生水平。结果:我们确定了268个与SA-AKI相关的特征基因,这些基因在免疫和炎症相关途径中富集。利用机器学习技术,筛选了三个关键基因:GBP2、PSMB8和PSMB9。这三个基因的表达模式通过动物实验和数据库得到了很好的验证。使用Nephroseq数据库证实这些基因与临床指标之间的相关性。此外,免疫浸润分析为其潜在功能提供了额外的见解。结论:GBP2、PSMB8和PSMB9是SA-AKI的候选基因,为其病理机制提供了新的视角。未来需要进一步探索这些基因在SA-AKI发病机制中的生物学作用。
期刊介绍:
BMC Nephrology is an open access journal publishing original peer-reviewed research articles in all aspects of the prevention, diagnosis and management of kidney and associated disorders, as well as related molecular genetics, pathophysiology, and epidemiology.