Abstract：
:SARS-CoV-2 infection is characterized by peak viral load in the upper airway prior to or at the time of symptom onset, an unusual feature that has enabled widespread transmission of the virus and precipitated a global pandemic. How SARS-CoV-2 is able to achieve high titer in the absence of symptoms remains unclear. Here, we examine the upper airway host transcriptional response in patients with COVID-19 (n = 93), other viral (n = 41) or non-viral (n = 100) acute respiratory illnesses (ARIs). Compared with other viral ARIs, COVID-19 is characterized by a pronounced interferon response but attenuated activation of other innate immune pathways, including toll-like receptor, interleukin and chemokine signaling. The IL-1 and NLRP3 inflammasome pathways are markedly less responsive to SARS-CoV-2, commensurate with a signature of diminished neutrophil and macrophage recruitment. This pattern resembles previously described distinctions between symptomatic and asymptomatic viral infections and may partly explain the propensity for pre-symptomatic transmission in COVID-19. We further use machine learning to build 27-, 10- and 3-gene classifiers that differentiate COVID-19 from other ARIs with AUROCs of 0.981, 0.954 and 0.885, respectively. Classifier performance is stable across a wide range of viral load, suggesting utility in mitigating false positive or false negative results of direct SARS-CoV-2 tests.
journal_name
Nat Communjournal_title
Nature communicationsauthors
Mick E,Kamm J,Pisco AO,Ratnasiri K,Babik JM,Castañeda G,DeRisi JL,Detweiler AM,Hao SL,Kangelaris KN,Kumar GR,Li LM,Mann SA,Neff N,Prasad PA,Serpa PH,Shah SJ,Spottiswoode N,Tan M,Calfee CS,Christenson SA,Kistlerdoi
10.1038/s41467-020-19587-ysubject
Has Abstractpub_date
2020-11-17 00:00:00pages
5854issue
1issn
2041-1723pii
10.1038/s41467-020-19587-yjournal_volume
11pub_type
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