生物学杂志

生物学杂志 ›› 2022, Vol. 39 ›› Issue (5): 13-.doi: 10.3969/j.issn.2095-1736.2022.05.013

• 研究报告 • 上一篇    下一篇

外周血基因表达谱探测新型冠状病毒肺炎潜在诊断标志物

  

  1. 中国科学院大学 宁波生命与健康产业研究院， 宁波 315100
  • 出版日期:2022-10-18 发布日期:2022-10-18
  • 通讯作者: 张顺，硕士，副主任技师，研究方向为检测及治疗、生物治疗、分子生物学，E-mail：zhangshun@ucas.as.cn；蔡挺，硕士，主任医师、教授、博士研究生导师，研究方向为内科学、急诊科学，E-mail：cating@ucas.as.cn
  • 作者简介:张思嘉，硕士，研究方向为生物信息学，E-mail：zs13616hm@163.com
  • 基金资助:
    华美研究基金-基于代谢组学的新冠肺炎诊断和预后评价项目（2020HMZD23)； 浙江省医药卫生新品技术研发项目（2021PY021)； 宁波市科技重大专项-新型冠状病毒肺炎疫情防控应急科技攻关项目（2020C50001)

Exploration of potential diagnostic markers for COVID-19 based on peripheral blood gene expression profile

  1. Ningbo Institute of Life and Health Industry, University of Chinese Academy of Sciences, Ningbo 315100, China
  • Online:2022-10-18 Published:2022-10-18

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摘要： 使用基因表达数据库（gene expression ominibus, GEO）芯片数据GSE161731，利用差异表达分析、Lasso回归等方法，筛选区分早期COVID-19患者的关键基因，应用ROC曲线评价关键基因的早期COVID-19患者诊断准确性。基于权重基因共表达网络分析(WGCNA)构建的共表达网络，筛选出不同疾病组对应的关键基因。KEGG富集分析用于阐释基因模块的功能和相关信号通路。共获得509个差异基因，并初步筛选出17种早期COVID-19患者潜在诊断标志物，包括YBL2、PKMYT1、HJURP、TCN2、TTC24、ESPL1、GZMK、RPA3、ATP5F1E、CD2、ZAP70、IL15RA、NFYB、CIAO2A、PLRG1、GPATCH11和MRPL33。KEGG结果显示差异基因主要与细胞周期、T细胞免疫、氧化磷酸化有关。WGCNA分析确定的COVID-19特异性基因模块，主要参与核糖体蛋白的合成、氧化磷酸化等生理活动。

关键词: COVID-19, 外周血, 生物信息学分析, 转录组

Abstract: The dataset GSE161731 was downloaded from the Gene Expression Omnibus(GEO) database. Variation analysis and Lasso regression were used to search for the key genes which can distinguish early COVID-19 patients. Diagnostic efficacy was evaluated by ROC curve. Biomarkers of different disease groups were confirmed by co-expression network constructed (WGCNA). KEGG enrichment analysis was applied to explain the function of gene modules and related signal pathways. A total of 509 differential genes were screened, and 17 potential diagnostic markers for early-stage COVID-19 patients were identified including MYBL2, PKMYT1, HJURP, TCN2, TTC24, ESPL1, GZMK, RPA3, ATP5F1E, CD2, ZAP70, IL15RA, NFYB, CIAO2A, PLRG1, GPATCH11 and MRPL33. KEGG results showed that these differentially expressed genes were mainly related to cell cycle, T cell immunity, and oxidative phosphorylation. The COVID-19 specific gene modules identified by WGCNA analysis were mainly involved in physiological activities such as protein synthesis and ribosomes oxidative phosphorylation.

Key words: COVID-19, peripheral blood, bioinformatics analysis, transcriptome signature

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