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基于生物信息学研究的利什曼病关键枢纽基因的鉴定及其在诊断和治疗中的潜在作用。

Determination of key hub genes in Leishmaniasis as potential factors in diagnosis and treatment based on a bioinformatics study.

机构信息

Department of Tissue Engineering, School of Advanced Technologies in Medicine, Fasa University of Medical Sciences, Fasa, Iran.

Department of Pharmacology, School of Medicine, Fasa University of Medical Sciences, Fasa, Iran.

出版信息

Sci Rep. 2024 Sep 28;14(1):22537. doi: 10.1038/s41598-024-73779-w.

DOI:10.1038/s41598-024-73779-w
PMID:39342024
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11438978/
Abstract

Leishmaniasis is an infectious disease caused by protozoan parasites from different species of leishmania. The disease is transmitted by female sandflies that carry these parasites. In this study, datasets on leishmaniasis published in the GEO database were analyzed and summarized. The analysis in all three datasets (GSE43880, GSE55664, and GSE63931) used in this study has been performed on the skin wounds of patients infected with a clinical form of leishmania (Leishmania braziliensis), and biopsies have been taken from them. To identify differentially expressed genes (DEGs) between leishmaniasis patients and controls, the robust rank aggregation (RRA) procedure was applied. We performed gene functional annotation and protein-protein interaction (PPI) network analysis to demonstrate the putative functionalities of the DEGs. The study utilized Molecular Complex Detection (MCODE), Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) to detect molecular complexes within the protein-protein interaction (PPI) network and conduct analyses on the identified functional modules. The CytoHubba plugin's results were paired with RRA analysis to determine the hub genes. Finally, the interaction between miRNAs and hub genes was predicted. Based on the RRA integrated analysis, 407 DEGs were identified (263 up-regulated genes and 144 down-regulated genes). The top three modules were listed after creating the PPI network via the MCODE plug. Seven hub genes were found using the CytoHubba app and RRA: CXCL10, GBP1, GNLY, GZMA, GZMB, NKG7, and UBD. According to our enrichment analysis, these functional modules were primarily associated with immune pathways, cytokine activity/signaling pathways, and inflammation pathways. However, a UBD hub gene is interestingly involved in the ubiquitination pathways of pathogenesis. The mirNet database predicted the hub gene's interaction with miRNAs, and results revealed that several miRNAs, including mir-146a-5p, crucial in fighting pathogenesis. The key hub genes discovered in this work may be considered as potential biomarkers in diagnosis, development of agonists/antagonist, novel vaccine design, and will greatly contribute to clinical studies in the future.

摘要

利什曼病是一种由不同种利什曼原虫引起的传染病。这种疾病通过携带这些寄生虫的雌性沙蝇传播。在这项研究中,分析并总结了 GEO 数据库中发表的利什曼病数据集。本研究中使用的所有三个数据集(GSE43880、GSE55664 和 GSE63931)的分析均在感染临床形式利什曼原虫(巴西利什曼原虫)的患者的皮肤伤口上进行,并从他们身上采集活检。为了鉴定利什曼病患者和对照之间的差异表达基因(DEGs),应用了稳健秩聚合(RRA)程序。我们进行了基因功能注释和蛋白质-蛋白质相互作用(PPI)网络分析,以证明 DEGs 的潜在功能。该研究利用分子复合物检测(MCODE)、基因本体论(GO)和京都基因与基因组百科全书(KEGG)来检测蛋白质-蛋白质相互作用(PPI)网络中的分子复合物,并对鉴定的功能模块进行分析。CytoHubba 插件的结果与 RRA 分析配对,以确定枢纽基因。最后,预测了 miRNA 和枢纽基因之间的相互作用。基于 RRA 综合分析,鉴定出 407 个 DEGs(263 个上调基因和 144 个下调基因)。通过 MCODE 插件创建 PPI 网络后,列出了前三个模块。使用 CytoHubba 应用程序和 RRA 发现了七个枢纽基因:CXCL10、GBP1、GNLY、GZMA、GZMB、NKG7 和 UBD。根据我们的富集分析,这些功能模块主要与免疫途径、细胞因子活性/信号通路和炎症通路相关。然而,一个 UBD 枢纽基因有趣地参与了发病机制的泛素化途径。mirNet 数据库预测了枢纽基因与 miRNA 的相互作用,结果表明,一些 miRNA,包括在对抗发病机制中至关重要的 mir-146a-5p,可能与这些基因相互作用。本工作中发现的关键枢纽基因可能被视为诊断、激动剂/拮抗剂开发、新型疫苗设计的潜在生物标志物,并将为未来的临床研究做出巨大贡献。

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本文引用的文献

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Preparation and characterization of artemether-loaded niosomes in Leishmania major-induced cutaneous leishmaniasis.载青蒿琥酯的尼莫司汀脂质体的制备及表征在利什曼原虫诱导的皮肤利什曼病中的应用。
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Experimental structure based drug design (SBDD) applications for anti-leishmanial drugs: A paradigm shift?
基于实验结构的药物设计(SBDD)在抗利什曼病药物中的应用:范式转变?
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CXCL10 May Be Responsible for Susceptibility to Pulmonary Embolism in COVID-19 Patients.CXCL10可能是COVID-19患者易患肺栓塞的原因。
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