Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients.
Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients.
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血液转录组中疾病严重程度特异性的中性粒细胞特异性信号分层了199例患者。
DOI：
10.1186/s13073-020-00823-5
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发表时间：
2021-01-13
期刊：
影响因子：
12.3
通讯作者：
German COVID-19 Omics Initiative (DeCOI)
中科院分区：
文献类型：
--
作者：
Aschenbrenner AC;Mouktaroudi M;Krämer B;Oestreich M;Antonakos N;Nuesch-Germano M;Gkizeli K;Bonaguro L;Reusch N;Baßler K;Saridaki M;Knoll R;Pecht T;Kapellos TS;Doulou S;Kröger C;Herbert M;Holsten L;Horne A;Gemünd ID;Rovina N;Agrawal S;Dahm K;van Uelft M;Drews A;Lenkeit L;Bruse N;Gerretsen J;Gierlich J;Becker M;Händler K;Kraut M;Theis H;Mengiste S;De Domenico E;Schulte-Schrepping J;Seep L;Raabe J;Hoffmeister C;ToVinh M;Keitel V;Rieke G;Talevi V;Skowasch D;Aziz NA;Pickkers P;van de Veerdonk FL;Netea MG;Schultze JL;Kox M;Breteler MMB;Nattermann J;Koutsoukou A;Giamarellos-Bourboulis EJ;Ulas T;German COVID-19 Omics Initiative (DeCOI)
SARS-COV-2大流行目前正在导致世界各地的Covid-19患者数量越来越多。临床表现范围从无症状，轻度呼吸道感染到严重的急性呼吸窘迫综合征，呼吸衰竭和死亡。在严重情况下，有关免疫系统失调的报告要求更好地表征和了解免疫系统的变化。
为了剖析共vid-19驱动的免疫宿主反应，我们从轻度和严重的Covid-19患者中进行了全血细胞转录组和粒细胞制剂的RNA-SEQ，并使用常规和数据驱动的共表达组合进行了数据分析数据分析。此外，使用公开数据来显示COVID-19与其他疾病的区别。根据数据驱动的发现，使用反向药物靶标预测来鉴定已知或新颖的候选药物。
在这里，我们介绍了39名Covid-19患者和10名对照供体的全血记录组，可实现基于分子表型的数据驱动分层。嗜中性粒细胞激活相关的特征显着富含严重的患者组，这是从30个独立的第二个队列以及来自30个独立的第二个队列的全血记录中佐证的，以及来自16名COVID-19患者的第三个队列中的粒细胞样品（44个样本）。比较共同199的血液转录组与来自12种不同病毒感染，炎症性疾病和独立对照样本的3100多种样品的收集的比较，显示了Covid-19的高度特异性转录组特征。此外，分层转录组预测了靶向宿主全身免疫反应失调的患者亚组特异性药物候选。
我们的研究提供了不同的分子亚组或表型的新见解，这些见解不简单地用临床参数解释。我们表明，整个血液转录组对于COVID-19的信息非常有用，因为它们捕获了粒细胞，这些粒细胞是疾病严重程度的主要驱动因素。
在线版本中包含10.1186/s13073-020-00823-5的补充材料。
The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system. In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings. Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host. Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity. The online version contains supplementary material available at 10.1186/s13073-020-00823-5.
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影响因子：
3.7
作者：
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通讯作者：
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DOI：
10.1126/science.abc6261
发表时间：
2020-09-04
期刊：
Science (New York, N.Y.)
影响因子：
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影响因子：
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作者：
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影响因子：
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影响因子：
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作者：
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通讯作者：
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