Multi-objective optimization identifies a specific and interpretable COVID-19 host response signature.

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY Cell Systems Pub Date : 2022-12-21 DOI:10.1016/j.cels.2022.11.008
Antonio Cappuccio, Daniel G Chawla, Xi Chen, Aliza B Rubenstein, Wan Sze Cheng, Weiguang Mao, Thomas W Burke, Ephraim L Tsalik, Elizabeth Petzold, Ricardo Henao, Micah T McClain, Christopher W Woods, Maria Chikina, Olga G Troyanskaya, Stuart C Sealfon, Steven H Kleinstein, Elena Zaslavsky
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引用次数: 2

Abstract

The identification of a COVID-19 host response signature in blood can increase the understanding of SARS-CoV-2 pathogenesis and improve diagnostic tools. Applying a multi-objective optimization framework to both massive public and new multi-omics data, we identified a COVID-19 signature regulated at both transcriptional and epigenetic levels. We validated the signature's robustness in multiple independent COVID-19 cohorts. Using public data from 8,630 subjects and 53 conditions, we demonstrated no cross-reactivity with other viral and bacterial infections, COVID-19 comorbidities, or confounders. In contrast, previously reported COVID-19 signatures were associated with significant cross-reactivity. The signature's interpretation, based on cell-type deconvolution and single-cell data analysis, revealed prominent yet complementary roles for plasmablasts and memory T cells. Although the signal from plasmablasts mediated COVID-19 detection, the signal from memory T cells controlled against cross-reactivity with other viral infections. This framework identified a robust, interpretable COVID-19 signature and is broadly applicable in other disease contexts. A record of this paper's transparent peer review process is included in the supplemental information.

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多目标优化识别特定且可解释的COVID-19宿主反应特征。
在血液中发现COVID-19宿主反应特征可以增加对SARS-CoV-2发病机制的认识,并改进诊断工具。将多目标优化框架应用于大量公共数据和新的多组学数据,我们确定了一个在转录和表观遗传水平上受调控的COVID-19特征。我们在多个独立的COVID-19队列中验证了该特征的稳健性。使用来自8,630名受试者和53种情况的公开数据,我们证明与其他病毒和细菌感染、COVID-19合并症或混杂因素没有交叉反应。相比之下,先前报道的COVID-19特征与显著的交叉反应性相关。基于细胞类型反褶积和单细胞数据分析的特征解释揭示了浆母细胞和记忆T细胞的突出而互补的作用。尽管来自浆母细胞的信号介导了COVID-19的检测,但来自记忆T细胞的信号控制了与其他病毒感染的交叉反应。该框架确定了一个强大的、可解释的COVID-19特征,并广泛适用于其他疾病情况。本文的透明同行评议过程记录包含在补充信息中。
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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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