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生物信息学和系统生物学方法研究 COVID-19、流感和 HIV 对基因表达调控的影响。

Bioinformatics and system biology approach to identify the influences among COVID-19, influenza, and HIV on the regulation of gene expression.

机构信息

Microbiology Laboratory Department, Jinzhou Center for Disease Control and Prevention, Jinzhou, Liaoning, China.

Department of Immunology, School of Basic Medical Science, Jinzhou Medical University, Jinzhou, Liaoning, China.

出版信息

Front Immunol. 2024 Mar 27;15:1369311. doi: 10.3389/fimmu.2024.1369311. eCollection 2024.

Abstract

BACKGROUND

Coronavirus disease (COVID-19), caused by SARS-CoV-2, has emerged as a infectious disease, coexisting with widespread seasonal and sporadic influenza epidemics globally. Individuals living with HIV, characterized by compromised immune systems, face an elevated risk of severe outcomes and increased mortality when affected by COVID-19. Despite this connection, the molecular intricacies linking COVID-19, influenza, and HIV remain unclear. Our research endeavors to elucidate the shared pathways and molecular markers in individuals with HIV concurrently infected with COVID-19 and influenza. Furthermore, we aim to identify potential medications that may prove beneficial in managing these three interconnected illnesses.

METHODS

Sequencing data for COVID-19 (GSE157103), influenza (GSE185576), and HIV (GSE195434) were retrieved from the GEO database. Commonly expressed differentially expressed genes (DEGs) were identified across the three datasets, followed by immune infiltration analysis and diagnostic ROC analysis on the DEGs. Functional enrichment analysis was performed using GO/KEGG and Gene Set Enrichment Analysis (GSEA). Hub genes were screened through a Protein-Protein Interaction networks (PPIs) analysis among DEGs. Analysis of miRNAs, transcription factors, drug chemicals, diseases, and RNA-binding proteins was conducted based on the identified hub genes. Finally, quantitative PCR (qPCR) expression verification was undertaken for selected hub genes.

RESULTS

The analysis of the three datasets revealed a total of 22 shared DEGs, with the majority exhibiting an area under the curve value exceeding 0.7. Functional enrichment analysis with GO/KEGG and GSEA primarily highlighted signaling pathways associated with ribosomes and tumors. The ten identified hub genes included , , , , , , , , , and . Additionally, five crucial miRNAs (hsa-miR-8060, hsa-miR-6890-5p, hsa-miR-5003-3p, hsa-miR-6893-3p, and hsa-miR-6069), five essential transcription factors (CREB1, CEBPB, EGR1, EP300, and IRF1), and the top ten significant drug chemicals (estradiol, progesterone, tretinoin, calcitriol, fluorouracil, methotrexate, lipopolysaccharide, valproic acid, silicon dioxide, cyclosporine) were identified.

CONCLUSION

This research provides valuable insights into shared molecular targets, signaling pathways, drug chemicals, and potential biomarkers for individuals facing the complex intersection of COVID-19, influenza, and HIV. These findings hold promise for enhancing the precision of diagnosis and treatment for individuals with HIV co-infected with COVID-19 and influenza.

摘要

背景

由 SARS-CoV-2 引起的冠状病毒病(COVID-19)已成为一种传染病,在全球范围内与广泛的季节性和偶发性流感流行并存。患有 HIV 的个体免疫系统受损,当感染 COVID-19 时,他们面临严重后果和死亡率增加的风险。尽管存在这种联系,但 COVID-19、流感和 HIV 之间的分子复杂性仍不清楚。我们的研究旨在阐明同时感染 COVID-19 和流感的 HIV 个体中共同的途径和分子标记物。此外,我们旨在确定可能对管理这三种相互关联的疾病有益的潜在药物。

方法

从 GEO 数据库中检索 COVID-19(GSE157103)、流感(GSE185576)和 HIV(GSE195434)的测序数据。确定了三个数据集之间共同表达的差异表达基因(DEG),然后对 DEG 进行免疫浸润分析和诊断 ROC 分析。使用 GO/KEGG 和基因集富集分析(GSEA)对 DEG 进行功能富集分析。通过 DEG 之间的蛋白质-蛋白质相互作用网络(PPIs)分析筛选出枢纽基因。基于鉴定出的枢纽基因分析 miRNA、转录因子、药物化学物质、疾病和 RNA 结合蛋白。最后,对选定的枢纽基因进行定量 PCR(qPCR)表达验证。

结果

对三个数据集的分析共发现 22 个共同的 DEG,其中大多数的曲线下面积值超过 0.7。GO/KEGG 和 GSEA 的功能富集分析主要突出了与核糖体和肿瘤相关的信号通路。鉴定出的十个枢纽基因包括、、、、、、、、和。此外,还确定了五个关键的 miRNA(hsa-miR-8060、hsa-miR-6890-5p、hsa-miR-5003-3p、hsa-miR-6893-3p 和 hsa-miR-6069)、五个关键的转录因子(CREB1、CEBPB、EGR1、EP300 和 IRF1)和十个重要的药物化学物质(雌二醇、孕酮、维 A 酸、骨化三醇、氟尿嘧啶、甲氨蝶呤、脂多糖、丙戊酸、二氧化硅、环孢菌素)。

结论

这项研究为 COVID-19、流感和 HIV 同时存在的个体的共同分子靶标、信号通路、药物化学物质和潜在生物标志物提供了有价值的见解。这些发现有望提高同时感染 COVID-19 和流感的 HIV 个体的诊断和治疗的精准度。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a522/11004287/de121b25a4c0/fimmu-15-1369311-g001.jpg

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