Ng Dianna L, Granados Andrea C, Santos Yale A, Servellita Venice, Goldgof Gregory M, Meydan Cem, Sotomayor-Gonzalez Alicia, Levine Andrew G, Balcerek Joanna, Han Lucy M, Akagi Naomi, Truong Kent, Neumann Neil M, Nguyen David N, Bapat Sagar P, Cheng Jing, Martin Claudia Sanchez-San, Federman Scot, Foox Jonathan, Gopez Allan, Li Tony, Chan Ray, Chu Cynthia S, Wabl Chiara A, Gliwa Amelia S, Reyes Kevin, Pan Chao-Yang, Guevara Hugo, Wadford Debra, Miller Steve, Mason Christopher E, Chiu Charles Y
Department of Pathology, University of California, San Francisco, San Francisco, CA, USA.
Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA.
Sci Adv. 2021 Feb 3;7(6). doi: 10.1126/sciadv.abe5984. Print 2021 Feb.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease-19 (COVID-19), has emerged as the cause of a global pandemic. We used RNA sequencing to analyze 286 nasopharyngeal (NP) swab and 53 whole-blood (WB) samples from 333 patients with COVID-19 and controls. Overall, a muted immune response was observed in COVID-19 relative to other infections (influenza, other seasonal coronaviruses, and bacterial sepsis), with paradoxical down-regulation of several key differentially expressed genes. Hospitalized patients and outpatients exhibited up-regulation of interferon-associated pathways, although heightened and more robust inflammatory responses were observed in hospitalized patients with more clinically severe illness. Two-layer machine learning-based host classifiers consisting of complete (>1000 genes), medium (<100), and small (<20) gene biomarker panels identified COVID-19 disease with 85.1-86.5% accuracy when benchmarked using an independent test set. SARS-CoV-2 infection has a distinct biosignature that differs between NP swabs and WB and can be leveraged for COVID-19 diagnosis.
严重急性呼吸综合征冠状病毒2（SARS-CoV-2）引发了冠状病毒病19（COVID-19），已成为全球大流行的病因。我们使用RNA测序分析了来自333例COVID-19患者和对照的286份鼻咽（NP）拭子和53份全血（WB）样本。总体而言，与其他感染（流感、其他季节性冠状病毒和细菌性败血症）相比，COVID-19患者的免疫反应较为微弱，同时一些关键差异表达基因出现了反常的下调。住院患者和门诊患者的干扰素相关通路均有上调，不过在临床症状更严重的住院患者中观察到了更强且更活跃的炎症反应。由完整（>1000个基因）、中等（<100个）和小型（<20个）基因生物标志物面板组成的基于两层机器学习的宿主分类器，在使用独立测试集进行基准测试时，识别COVID-19疾病的准确率为85.1-86.5%。SARS-CoV-2感染具有独特的生物特征，在NP拭子和WB之间存在差异，可用于COVID-19的诊断。
