Evidence map›Paper›PMID 32511476›Full record

ArticlemedRxiv : the preprint server for health sciences2020

Upper airway gene expression differentiates COVID-19 from other acute respiratory illnesses and reveals suppression of innate immune responses by SARS-CoV-2.

Eran Mick, Jack Kamm, Angela Oliveira Pisco, Kalani Ratnasiri, Jennifer M Babik, Carolyn S Calfee, Gloria Castañeda, Joseph L DeRisi, Angela M Detweiler, Samantha Hao and 13 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in medRxiv : the preprint server for health sciences, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 51 citations in OpenAlex.

  1. Identifying Transcriptomic Signatures and Rules for SARS-CoV-2 Infection.Frontiers in cell and developmental biology · 2020
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

23 authors at 2 institutions in 1 country.

Eran MickDivision of Infectious Diseases, University of California, San Francisco, CA, USA.
Jack KammChan Zuckerberg Biohub, San Francisco, CA, USA.
Angela Oliveira PiscoChan Zuckerberg Biohub, San Francisco, CA, USA.
Kalani RatnasiriChan Zuckerberg Biohub, San Francisco, CA, USA.
Jennifer M BabikDivision of Infectious Diseases, University of California, San Francisco, CA, USA.
Carolyn S CalfeeDivision of Pulmonary and Critical Care Medicine, University of California, San Francisco, CA, USA.
Gloria CastañedaChan Zuckerberg Biohub, San Francisco, CA, USA.
Joseph L DeRisiChan Zuckerberg Biohub, San Francisco, CA, USA.
Angela M DetweilerChan Zuckerberg Biohub, San Francisco, CA, USA.
Samantha HaoChan Zuckerberg Biohub, San Francisco, CA, USA.
Kirsten N KangelarisDivision of Hospital Medicine, University of California, San Francisco, CA, USA.
G Renuka KumarChan Zuckerberg Biohub, San Francisco, CA, USA.
Lucy M LiChan Zuckerberg Biohub, San Francisco, CA, USA.
Sabrina A MannChan Zuckerberg Biohub, San Francisco, CA, USA.
Norma NeffChan Zuckerberg Biohub, San Francisco, CA, USA.
Priya A PrasadDivision of Hospital Medicine, University of California, San Francisco, CA, USA.
Paula Hayakawa SerpaDivision of Infectious Diseases, University of California, San Francisco, CA, USA.
Sachin J ShahDivision of Hospital Medicine, University of California, San Francisco, CA, USA.
Natasha SpottiswoodeDivision of Hospital Medicine, University of California, San Francisco, CA, USA.
Michelle TanChan Zuckerberg Biohub, San Francisco, CA, USA.
Stephanie A ChristensonDivision of Pulmonary and Critical Care Medicine, University of California, San Francisco, CA, USA.
Amy KistlerChan Zuckerberg Biohub, San Francisco, CA, USA.
Charles LangelierDivision of Infectious Diseases, University of California, San Francisco, CA, USA.
University of California, San Francisco · USChan Zuckerberg Initiative (United States) · US

Funding

Precision Medicine in the Acute Respiratory Distress SyndromeR35HL140026 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI CALFEE, CAROLYN · 2018 to 2024
$6.8M
Profiling the Lung Transcriptome for Precision Diagnosis of Respiratory Infections using Host/Pathogen Metagenomic SequencingK23HL138461 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI LANGELIER, CHARLES · 2018 to 2021
$718k
NHLBI NIH HHS K23 HL138461NHLBI NIH HHS R35 HL140026
6 · The paper itself

Abstract

We studied the host transcriptional response to SARS-CoV-2 by performing metagenomic sequencing of upper airway samples in 238 patients with COVID-19, other viral or non-viral acute respiratory illnesses (ARIs). Compared to other viral ARIs, COVID-19 was characterized by a diminished innate immune response, with reduced expression of genes involved in toll-like receptor and interleukin signaling, chemokine binding, neutrophil degranulation and interactions with lymphoid cells. Patients with COVID-19 also exhibited significantly reduced proportions of neutrophils and macrophages, and increased proportions of goblet, dendritic and B-cells, compared to other viral ARIs. Using machine learning, we built 26-, 10- and 3-gene classifiers that differentiated COVID-19 from other acute respiratory illnesses with AUCs of 0.980, 0.950 and 0.871, respectively. Classifier performance was stable at low viral loads, suggesting utility in settings where direct detection of viral nucleic acid may be unsuccessful. Taken together, our results illuminate unique aspects of the host transcriptional response to SARS-CoV-2 in comparison to other respiratory viruses and demonstrate the feasibility of COVID-19 diagnostics based on patient gene expression.

Identifiers

PMID32511476
PMCPMC7273244
OpenAlexW3026084861

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.