Transcriptional Profiling and Machine Learning Unveil a Concordant Biosignature of Type I Interferon-Inducible Host Response Across Nasal Swab and Pulmonary Tissue for COVID-19 Diagnosis.
Transcriptional Profiling and Machine Learning Unveil a Concordant Biosignature of Type I Interferon-Inducible Host Response Across Nasal Swab and Pulmonary Tissue for COVID-19 Diagnosis.
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转录分析和机器学习揭示了I型I型干扰素诱导型宿主反应的一致生物签名，用于鼻拭子和肺组织，以进行19009诊断。
DOI：
10.3389/fimmu.2021.733171
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发表时间：
2021
影响因子：
7.3
通讯作者：
Feng Y
中科院分区：
文献类型：
--
作者：
Zhang C;Feng YG;Tam C;Wang N;Feng Y
COVID-19是由SARS-CoV-2病毒引起的全球性大流行病，具有高死亡率和高发病率。有限的诊断方法阻碍了感染控制。由于主要通过RT-PCR直接检测病毒可能导致假阴性结果，因此宿主反应依赖性检测可作为改善COVID-19诊断的补充方法。我们的研究发现了一个高度保留的I型干扰素（IFN-I）依赖基因的转录谱，用于COVID-19的互补诊断。采用计算语言R依赖的机器学习来挖掘SARS-CoV-2和其他呼吸道感染感染的异质样本中高度保守的转录谱（RNA测序）。转录组学/高通量测序数据从NCBI-GEO数据集（GSE 32155、GSE 147507、GSE 150316、GSE 162835、GSE 163151、GSE 171668、GSE 182569）检索。同源性分析的数学方法如下：调整兰德指数相关的相似性分析，几何和多维数据解释，UpsetR，t-分布随机邻居嵌入（t-SNE），和加权基因共表达网络分析（WGCNA）。此外，干扰素组数据库用于预测具有IFN-I启动子结合位点的转录因子与用于COVID-19诊断的关键IFN-I基因。在本研究中，我们在SARS-CoV-2感染的鼻拭子和死后肺组织之间鉴定了一个高度保守的基因模块，该模块调节IFN-I信号传导用于COVID-19互补诊断，其中以下14个IFN-I刺激的基因高度保守，包括BST 2、IFIT 1、IFIT 2、IFIT 3、IFITM 1、ISG 15、MX 1、MX2、OAS 1、OAS 2、OAS 3、OASL、RSAD 2和STAT 1。COVID-19的分层严重程度也可以通过这14个IFN-I基因的转录水平来识别。通过对NCBI-GEO检索到的RNA-seq数据进行转录和计算分析，我们在SARS-CoV-2感染的鼻拭子和死后肺组织中鉴定了高度保留的14个基因转录谱，其调节IFN-I信号传导。这种涉及IFN-I相关宿主反应的保守生物特征可用于COVID-19诊断。
COVID-19, caused by SARS-CoV-2 virus, is a global pandemic with high mortality and morbidity. Limited diagnostic methods hampered the infection control. Since the direct detection of virus mainly by RT-PCR may cause false-negative outcome, host response-dependent testing may serve as a complementary approach for improving COVID-19 diagnosis. Our study discovered a highly-preserved transcriptional profile of Type I interferon (IFN-I)-dependent genes for COVID-19 complementary diagnosis. Computational language R-dependent machine learning was adopted for mining highly-conserved transcriptional profile (RNA-sequencing) across heterogeneous samples infected by SARS-CoV-2 and other respiratory infections. The transcriptomics/high-throughput sequencing data were retrieved from NCBI-GEO datasets (GSE32155, GSE147507, GSE150316, GSE162835, GSE163151, GSE171668, GSE182569). Mathematical approaches for homological analysis were as follows: adjusted rand index-related similarity analysis, geometric and multi-dimensional data interpretation, UpsetR, t-distributed Stochastic Neighbor Embedding (t-SNE), and Weighted Gene Co-expression Network Analysis (WGCNA). Besides, Interferome Database was used for predicting the transcriptional factors possessing IFN-I promoter-binding sites to the key IFN-I genes for COVID-19 diagnosis. In this study, we identified a highly-preserved gene module between SARS-CoV-2 infected nasal swab and postmortem lung tissue regulating IFN-I signaling for COVID-19 complementary diagnosis, in which the following 14 IFN-I-stimulated genes are highly-conserved, including BST2, IFIT1, IFIT2, IFIT3, IFITM1, ISG15, MX1, MX2, OAS1, OAS2, OAS3, OASL, RSAD2, and STAT1. The stratified severity of COVID-19 may also be identified by the transcriptional level of these 14 IFN-I genes. Using transcriptional and computational analysis on RNA-seq data retrieved from NCBI-GEO, we identified a highly-preserved 14-gene transcriptional profile regulating IFN-I signaling in nasal swab and postmortem lung tissue infected by SARS-CoV-2. Such a conserved biosignature involved in IFN-I-related host response may be leveraged for COVID-19 diagnosis.
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影响因子：
16
作者：
Martin-Sancho L;Lewinski MK;Pache L;Stoneham CA;Yin X;Becker ME;Pratt D;Churas C;Rosenthal SB;Liu S;Weston S;De Jesus PD;O'Neill AM;Gounder AP;Nguyen C;Pu Y;Curry HM;Oom AL;Miorin L;Rodriguez-Frandsen A;Zheng F;Wu C;Xiong Y;Urbanowski M;Shaw ML;Chang MW;Benner C;Hope TJ;Frieman MB;García-Sastre A;Ideker T;Hultquist JF;Guatelli J;Chanda SK
通讯作者：
Chanda SK
影响因子：
7.8
作者：
Fleming SB
通讯作者：
Fleming SB
影响因子：
--
作者：
Botía JA;Vandrovcova J;Forabosco P;Guelfi S;D'Sa K;United Kingdom Brain Expression Consortium;Hardy J;Lewis CM;Ryten M;Weale ME
通讯作者：
Weale ME
危及生命的Covid-19患者中针对I型IFN的自身抗体。
DOI：
10.1126/science.abd4585
发表时间：
2020-10-23
期刊：
Science (New York, N.Y.)
影响因子：
--
作者：
Bastard P;Rosen LB;Zhang Q;Michailidis E;Hoffmann HH;Zhang Y;Dorgham K;Philippot Q;Rosain J;Béziat V;Manry J;Shaw E;Haljasmägi L;Peterson P;Lorenzo L;Bizien L;Trouillet-Assant S;Dobbs K;de Jesus AA;Belot A;Kallaste A;Catherinot E;Tandjaoui-Lambiotte Y;Le Pen J;Kerner G;Bigio B;Seeleuthner Y;Yang R;Bolze A;Spaan AN;Delmonte OM;Abers MS;Aiuti A;Casari G;Lampasona V;Piemonti L;Ciceri F;Bilguvar K;Lifton RP;Vasse M;Smadja DM;Migaud M;Hadjadj J;Terrier B;Duffy D;Quintana-Murci L;van de Beek D;Roussel L;Vinh DC;Tangye SG;Haerynck F;Dalmau D;Martinez-Picado J;Brodin P;Nussenzweig MC;Boisson-Dupuis S;Rodríguez-Gallego C;Vogt G;Mogensen TH;Oler AJ;Gu J;Burbelo PD;Cohen JI;Biondi A;Bettini LR;D'Angio M;Bonfanti P;Rossignol P;Mayaux J;Rieux-Laucat F;Husebye ES;Fusco F;Ursini MV;Imberti L;Sottini A;Paghera S;Quiros-Roldan E;Rossi C;Castagnoli R;Montagna D;Licari A;Marseglia GL;Duval X;Ghosn J;HGID Lab;NIAID-USUHS Immune Response to COVID Group;COVID Clinicians;COVID-STORM Clinicians;Imagine COVID Group;French COVID Cohort Study Group;Milieu Intérieur Consortium;CoV-Contact Cohort;Amsterdam UMC Covid-19 Biobank;COVID Human Genetic Effort;Tsang JS;Goldbach-Mansky R;Kisand K;Lionakis MS;Puel A;Zhang SY;Holland SM;Gorochov G;Jouanguy E;Rice CM;Cobat A;Notarangelo LD;Abel L;Su HC;Casanova JL
通讯作者：
Casanova JL
影响因子：
3.6
作者：
Jha PK;Vijay A;Halu A;Uchida S;Aikawa M
通讯作者：
Aikawa M