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基于生物信息学方法的急性肾损伤相关关键微小RNA分子分析

Analysis of key microRNA molecules associated with acute kidney injury based on bioinformatics method.

作者信息

Liu Dongzhi, Zhang Xiaoyang, Xu Jialin, Chen Chuang, Shao Hongyi, Chen Xingxiang, Wu Dayong, Ma Qiang, Wang Wenmin, Wang Yan

机构信息

Department of Critical Care Medicine, Shaoxing Central Hospital, Shaoxing, Zhejiang, China.

The Yangtze River Delta Biological Medicine Research and Development Center of Zhejiang Province, Yangtze Delta Region Institution of Tsinghua University, Hangzhou, Zhejiang, China.

出版信息

Medicine (Baltimore). 2025 Mar 7;104(10):e41785. doi: 10.1097/MD.0000000000041785.

Abstract

RATIONALE

Acute kidney injury (AKI) is a critical condition with limited early detection biomarkers and therapeutic options. This study aims to identify differentially expressed genes and potential microRNAs (miRNAs) as detection and therapeutic targets for AKI using bioinformatics-based analysis.

PATIENT CONCERNS

The study focuses on AKI as a major health concern with a need for improved biomarkers to monitor and treat this condition effectively.

DIAGNOSES

The bioinformatics analysis was conducted on the Gene Expression Omnibus database to identify key differentially expressed genes related to AKI. Additionally, potential miRNAs associated with these genes were predicted to provide further insight into AKI diagnosis and therapeutic strategies.

INTERVENTIONS

Raw chip data from the Gene Expression Omnibus database were analyzed using coexpression complex analysis of weighted genes to identify differentially expressed genes associated with AKI. Gene set enrichment analysis and gene ontology analyses were performed to examine the pathways involved. A gene-miRNA regulatory network was constructed to explore potential therapeutic targets.

OUTCOMES

A total of 277 differentially expressed genes were identified, with 200 genes upregulated and 77 downregulated. Significant enrichment pathways included neuroactive ligand-receptor interactions, Leishmania infection, prion disease, and electrocardiogram receptor interactions. Key enriched pathways from the Kyoto Encyclopedia of Genes and Genomes included the cytokine receptor binding pathway, chemokine signaling pathway, phosphatidylinositol-3-kinase/protein kinase B signaling pathway, and nuclear transcription factor kappa B signaling pathway. Ten hub genes, namely intercellular adhesion molecule 1 (ICAM1), C-X-C chemokine ligand 8 (CXCL8), toll-like receptor 2 (TLR2), selectin L (SELL), cytotoxic T lymphocyte-associated antigen (CTLA4), cell differentiation antigen 69 (CD69), disaccharide proteoglycan (BGN), C-X-C chemokine ligand 13 (CXCL13), metalloproteinase inhibitor 1 (TIMP1), and chemokine receptor 4 (CXCR4), were identified. Twelve critical miRNAs, namely hsa-miR-335-5p, hsa-miR-92a-3p, hsa-miR-146a-5p, hsa-miR-155-5p, hsa-miR-4426, hsa-miR-26b-5p, hsa-miR-4462b, hsa-miR-4647, hsa-miR-32-5p, hsa-miR-92b-3p, hsa-miR-98-5p, and hsa-miR-93-5p, were also identified.

LESSONS

This bioinformatics analysis highlights 277 differentially expressed genes and 12 potential miRNAs that may serve as biomarkers for AKI detection and therapy. These findings contribute to a better understanding of the molecular mechanisms underlying AKI and offer promising targets for future diagnostic and therapeutic strategies.

摘要

原理

急性肾损伤(AKI)是一种危急病症,早期检测生物标志物和治疗选择有限。本研究旨在通过基于生物信息学的分析,鉴定差异表达基因和潜在的微小RNA(miRNA)作为AKI的检测和治疗靶点。

患者关注

该研究将AKI作为主要的健康问题,需要改进生物标志物以有效监测和治疗这种病症。

诊断

在基因表达综合数据库上进行生物信息学分析,以鉴定与AKI相关的关键差异表达基因。此外,预测与这些基因相关的潜在miRNA,以进一步深入了解AKI的诊断和治疗策略。

干预措施

使用加权基因的共表达复合体分析对来自基因表达综合数据库的原始芯片数据进行分析,以鉴定与AKI相关的差异表达基因。进行基因集富集分析和基因本体分析,以检查涉及的途径。构建基因-miRNA调控网络以探索潜在的治疗靶点。

结果

共鉴定出277个差异表达基因,其中200个基因上调,77个基因下调。显著富集的途径包括神经活性配体-受体相互作用、利什曼原虫感染、朊病毒病和心电图受体相互作用。京都基因与基因组百科全书中的关键富集途径包括细胞因子受体结合途径、趋化因子信号通路、磷脂酰肌醇-3-激酶/蛋白激酶B信号通路和核转录因子κB信号通路。还鉴定出10个枢纽基因,即细胞间粘附分子1(ICAM1)、C-X-C趋化因子配体8(CXCL8)、Toll样受体2(TLR2)、选择素L(SELL)、细胞毒性T淋巴细胞相关抗原(CTLA4)、细胞分化抗原69(CD69)、双糖蛋白聚糖(BGN)、C-X-C趋化因子配体13(CXCL13)、金属蛋白酶抑制剂1(TIMP1)和趋化因子受体4(CXCR4)。还鉴定出12个关键miRNA,即hsa-miR-335-5p、hsa-miR-92a-3p、hsa-miR-146a-5p、hsa-miR-155-5p、hsa-miR-4426、hsa-miR-26b-5p、hsa-miR-4462b、hsa-miR-4647、hsa-miR-32-5p、hsa-miR-92b-3p、hsa-miR-98-5p和hsa-miR-93-5p。

经验教训

这项生物信息学分析突出了277个差异表达基因和12个潜在的miRNA,它们可能作为AKI检测和治疗的生物标志物。这些发现有助于更好地理解AKI的分子机制,并为未来的诊断和治疗策略提供有前景的靶点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dee8/11902973/e8a71cbc4a53/medi-104-e41785-g001.jpg

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