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通过综合分析鉴定登革热的与阶段相关和严重程度相关的生物标志物,并探索免疫全景。

Identification of stage-related and severity-related biomarkers and exploration of immune landscape for Dengue by comprehensive analyses.

机构信息

Institute of Medical Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Kunming, 650118, People's Republic of China.

Kunming Medical University, Kunming, 650500, People's Republic of China.

出版信息

Virol J. 2022 Aug 2;19(1):130. doi: 10.1186/s12985-022-01853-8.

DOI:10.1186/s12985-022-01853-8
PMID:35918744
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9344228/
Abstract

BACKGROUND

At present, there are still no specific therapeutic drugs and appropriate vaccines for Dengue. Therefore, it is important to explore distinct clinical diagnostic indicators.

METHODS

In this study, we combined differentially expressed genes (DEGs) analysis, weighted co-expression network analysis (WGCNA) and Receiver Operator Characteristic Curve (ROC) to screen a stable and robust biomarker with diagnosis value for Dengue patients. CIBERSORT was used to evaluate immune landscape of Dengue patients. Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene set enrichment analysis (GSEA) were applied to explore potential functions of hub genes.

RESULTS

CD38 and Plasma cells have excellent Area Under the Curve (AUC) in distinguishing clinical stages for Dengue patients, and activated memory CD4+ T cells and Monocytes have good AUC for this function. ZNF595 has acceptable AUC in discriminating dengue hemorrhagic fever (DHF) from dengue fever (DF) in whole acute stages. Analyzing any serotype, we can obtain consistent results. Negative inhibition of viral replication based on GO, KEGG and GSEA analysis results, up-regulated autophagy genes and the impairing immune system are potential reasons resulting in DHF.

CONCLUSIONS

CD38, Plasma cells, activated memory CD4+ T cells and Monocytes can be used to distinguish clinical stages for dengue patients, and ZNF595 can be used to discriminate DHF from DF, regardless of serotypes.

摘要

背景

目前,登革热尚无特效治疗药物和适宜疫苗,因此,探索特异的临床诊断指标十分重要。

方法

本研究采用差异表达基因分析、加权基因共表达网络分析(WGCNA)和受试者工作特征曲线(ROC)相结合的方法,筛选具有诊断价值的登革热患者稳定而可靠的生物标志物。采用 CIBERSORT 评估登革热患者的免疫图谱。通过基因本体论(GO)富集、京都基因与基因组百科全书(KEGG)分析和基因集富集分析(GSEA)探讨关键基因的潜在功能。

结果

CD38 和浆细胞在区分登革热患者的临床分期方面具有极佳的曲线下面积(AUC),而激活的记忆 CD4+T 细胞和单核细胞在该功能方面具有良好的 AUC。ZNF595 在整个急性发病期鉴别登革出血热(DHF)和登革热(DF)方面具有可接受的 AUC。分析任何血清型均可得到一致的结果。GO、KEGG 和 GSEA 分析结果提示负性抑制病毒复制、上调自噬基因和损害免疫系统可能是导致 DHF 的原因。

结论

CD38、浆细胞、激活的记忆 CD4+T 细胞和单核细胞可用于区分登革热患者的临床分期,而 ZNF595 可用于鉴别 DHF 与 DF,与血清型无关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/7d3370334de2/12985_2022_1853_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/731c9309698c/12985_2022_1853_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/18f48b9e9a0c/12985_2022_1853_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/4ebbd3f5cbf5/12985_2022_1853_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/deebbc3af968/12985_2022_1853_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/f8bd24daae1b/12985_2022_1853_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/a33914be1d87/12985_2022_1853_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/ac50e5a5424c/12985_2022_1853_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/7d3370334de2/12985_2022_1853_Fig8_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/731c9309698c/12985_2022_1853_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/18f48b9e9a0c/12985_2022_1853_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/4ebbd3f5cbf5/12985_2022_1853_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/deebbc3af968/12985_2022_1853_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/f8bd24daae1b/12985_2022_1853_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/a33914be1d87/12985_2022_1853_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/ac50e5a5424c/12985_2022_1853_Fig7_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3e3f/9344724/7d3370334de2/12985_2022_1853_Fig8_HTML.jpg

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