Identification of diagnostic biomarkers and mitochondrial metabolic characteristics in sepsis-associated acute kidney injury.

IF 3.4 3区 医学 Q2 MEDICINE, RESEARCH & EXPERIMENTAL
Yichun Xia, Yiming Qian, Guanyu Hu, Yuehong Pu, Jian Guo
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引用次数: 0

Abstract

Background: This study intended to explore the molecular mechanisms and the mitochondrial metabolic characteristics of sepsis-associated acute kidney injury (S-AKI) through bioinformatics analysis and experimental validation.

Methods: The datasets of S-AKI were acquired from the GEO database while mitochondrial related genes (MRGs) were procured utilizing MitoCarta3.0 database. The "limma" R package was used to screen the differentially expressed genes (DEGs). Weighted Gene Correlation Network Analysis identified the co-expressed gene modules. GO, together with KEGG, was applied for enrichment analysis. A PPI network was constructed using the STRING database. The LASSO algorithm was adopted to screen prognostic predictors of S-AKI. The correlation between immune cells and diagnostic biomarkers was reflected through immune cell infiltration analysis utilizing CIBERSORT. In cellular experiments, the CCK-8 assay detected the cell viability. RT-qPCR and western blot assessed PMPCA and PMPCB expressions. The release of inflammatory cytokines and oxidative stress markers was assessed using ELISA and corresponding assay kits. Western blot assessed the expressions of proteins implicated in mitochondrial function.

Results: 163 intersected genes between DEGs and MRGs were screened. 103 key genes were acquired via the intersection of module genes with the 163 MRDEGs and 10 hub genes were determined. Functional enrichment analysis disclosed that the key genes were primarily enriched in mitochondrial metabolic pathways. Five significant immune cells showing differences between S-AKI and controls were identified. Correlation analysis displayed a negative association of Gpx4 with resting NK cells, its positive association with M2 macrophages as well as a negative association of Amacr with Th17 Cells. Three independent diagnostic biomarkers Gpx4, PMPCB and Amacr for S-AKI were determined. The validation cellular experiments showed that PMPCB overexpression could alleviate LPS-induced oxidative stress, inflammation and viability damage in HK-2 cells.

Conclusions: This work determined three independent diagnostic biomarkers in S-AKI, which might shed novel insight into its diagnosis and treatment.

脓毒症相关急性肾损伤诊断生物标志物和线粒体代谢特征的鉴定
背景:本研究旨在通过生物信息学分析和实验验证,探讨脓毒症相关急性肾损伤(S-AKI)的分子机制和线粒体代谢特征。方法:从GEO数据库获取S-AKI数据集,利用MitoCarta3.0数据库获取线粒体相关基因(MRGs)。采用“limma”R包筛选差异表达基因(DEGs)。加权基因相关网络分析确定了共表达的基因模块。使用GO和KEGG进行富集分析。利用STRING数据库构建了PPI网络。采用LASSO算法筛选S-AKI预后预测因子。利用CIBERSORT进行免疫细胞浸润分析,反映免疫细胞与诊断性生物标志物之间的相关性。在细胞实验中,CCK-8法检测细胞活力。RT-qPCR和western blot检测PMPCA和PMPCB的表达。采用ELISA和相应的检测试剂盒评估炎症细胞因子和氧化应激标志物的释放。Western blot检测与线粒体功能相关的蛋白表达。结果:共筛选到163个deg与mrg之间的交叉基因。163个MRDEGs通过模块基因交叉获得103个关键基因,并确定了10个枢纽基因。功能富集分析表明,关键基因主要富集于线粒体代谢途径。在S-AKI和对照组之间鉴定出5个显著的免疫细胞。相关分析显示Gpx4与静息NK细胞呈负相关,与M2巨噬细胞呈正相关,而Amacr与Th17细胞呈负相关。测定S-AKI的三个独立诊断生物标志物Gpx4、PMPCB和Amacr。验证性细胞实验表明,PMPCB过表达可减轻lps诱导的HK-2细胞氧化应激、炎症和活力损伤。结论:本研究确定了3个独立的S-AKI诊断生物标志物,为S-AKI的诊断和治疗提供了新的思路。
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来源期刊
European Journal of Medical Research
European Journal of Medical Research 医学-医学:研究与实验
CiteScore
3.20
自引率
0.00%
发文量
247
审稿时长
>12 weeks
期刊介绍: European Journal of Medical Research publishes translational and clinical research of international interest across all medical disciplines, enabling clinicians and other researchers to learn about developments and innovations within these disciplines and across the boundaries between disciplines. The journal publishes high quality research and reviews and aims to ensure that the results of all well-conducted research are published, regardless of their outcome.
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