Upper airway gene expression reveals suppressed immune responses to SARS-CoV-2 compared with other respiratory viruses
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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.
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SciScore for 10.1101/2020.05.18.20105171: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Experimental Models: Cell Lines Sentences Resources To control for background contamination, we included negative controls (water and HeLa cell RNA) as well as positive controls (spike-in RNA standards from the External RNA Controls Consortium (ERCC))1. HeLasuggested: CLS Cat# 300194/p772_HeLa, RRID:CVCL_0030)Software and Algorithms Sentences Resources Detection of other respiratory pathogenic viruses by mNGS: All samples were processed through the IDSeq pipeline5,6, which performs reference based alignment at both the nucleotide and amino acid level against sequences in the National Center for Biotechnology Information (NCBI) … SciScore for 10.1101/2020.05.18.20105171: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Experimental Models: Cell Lines Sentences Resources To control for background contamination, we included negative controls (water and HeLa cell RNA) as well as positive controls (spike-in RNA standards from the External RNA Controls Consortium (ERCC))1. HeLasuggested: CLS Cat# 300194/p772_HeLa, RRID:CVCL_0030)Software and Algorithms Sentences Resources Detection of other respiratory pathogenic viruses by mNGS: All samples were processed through the IDSeq pipeline5,6, which performs reference based alignment at both the nucleotide and amino acid level against sequences in the National Center for Biotechnology Information (NCBI) nucleotide (NT) and non-redundant (NR) databases, followed by assembly of the reads matching each taxon detected. IDSeqsuggested: (IDseq, RRID:SCR_019038)analysis: Gene set enrichment analyses13 were performed using the fgseaMultilevel function in the R package fgsea14 on REACTOME15 pathways with a minimum size of 10 genes and a maximum size of 1,000. Gene set enrichmentsuggested: (Gene Set Enrichment Analysis, RRID:SCR_003199)Results from OddPub: Thank you for sharing your code and data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:We also leveraged these data to develop an accurate, clinically practical, COVID-19 diagnostic classifier that may help overcome the limitations of direct detection of viral nucleic acid. Future prospective studies in a larger cohort will be needed to validate these findings, determine the prognostic value of host signatures, and assess the performance of integrated host/viral diagnostic assays.
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
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