Identification of key candidate biomarkers for severe influenza infection by integrated bioinformatical analysis and initial clinical validation.
Identification of key candidate biomarkers for severe influenza infection by integrated bioinformatical analysis and initial clinical validation.
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通过综合生物信息分析和初步临床验证确定严重流感感染的关键候选生物标记物。
DOI：
10.1111/jcmm.16275
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发表时间：
2021-03
影响因子：
5.3
通讯作者：
Cao B
中科院分区：
文献类型：
--
作者：
Liu S;Huang Z;Deng X;Zou X;Li H;Mu S;Cao B
早期识别和干预严重流感病例的关键障碍之一是缺乏可靠的免疫指标。在这项研究中，我们在一个合格的流感GEO数据集（GSE 111368）中利用结合加权基因共表达网络分析的差异表达基因筛选来鉴定与临床严重程度相关的枢纽基因。共鉴定出10个基因（PBI、MMP 8、TCN 1、RETN、OLFM 4、ELANE、LTF、LCN 2、DEFA 4和HP）。基因集富集分析（GSEA）显示，这些基因与抗菌反应和中性粒细胞活性密切相关。为了进一步评估这些基因对疾病发展的诊断/预后的能力，我们采用（a）另一个新的独立数据集（GSE 101702）和（B）从住院流感患者收集的血浆样品进行双重验证。我们发现10个枢纽基因与疾病严重程度高度相关。特别是，血浆中的BPI和MMP 8编码蛋白在严重和死亡病例中获得更高的表达，这表明不利的疾病发展并提示令人沮丧的预后。这些发现为严重流感的发病机制提供了新的见解，并确定了两个上级传统临床指标的重要候选基因。这些候选基因或编码蛋白可作为临床诊断的生物标志物和治疗重症流感的靶点。
One of the key barriers for early identification and intervention of severe influenza cases is a lack of reliable immunologic indicators. In this study, we utilized differentially expressed genes screening incorporating weighted gene co‐expression network analysis in one eligible influenza GEO data set (GSE111368) to identify hub genes associated with clinical severity. A total of 10 genes (PBI, MMP8, TCN1, RETN, OLFM4, ELANE, LTF, LCN2, DEFA4 and HP) were identified. Gene set enrichment analysis (GSEA) for single hub gene revealed that these genes had a close association with antimicrobial response and neutrophils activity. To further evaluate these genes' ability for diagnosis/prognosis of disease developments, we adopted double validation with (a) another new independent data set (GSE101702); and (b) plasma samples collected from hospitalized influenza patients. We found that 10 hub genes presented highly correlation with disease severity. In particular, BPI and MMP8 encoding proteins in plasma achieved higher expression in severe and dead cases, which indicated an adverse disease development and suggested a frustrating prognosis. These findings provide new insight into severe influenza pathogenesis and identify two significant candidate genes that were superior to the conventional clinical indicators. These candidate genes or encoding proteins could be biomarker for clinical diagnosis and therapeutic targets for severe influenza infection.
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WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
DOI：
10.1074/jbc.m117.776112
发表时间：
2017-03-24
期刊：
The Journal of biological chemistry
影响因子：
--
作者：
Fan Y;Mok CK;Chan MC;Zhang Y;Nal B;Kien F;Bruzzone R;Sanyal S
通讯作者：
Sanyal S
影响因子：
5.3
作者：
Liu S;Huang Z;Deng X;Zou X;Li H;Mu S;Cao B
通讯作者：
Cao B
影响因子：
15.1
作者：
Parnell, Grant P.;McLean, Anthony S.;Tang, Benjamin M.
通讯作者：
Tang, Benjamin M.
影响因子：
5.8
作者：
McCormick, Allison;Heesemann, Leonie;Ebel, Frank
通讯作者：
Ebel, Frank