Evidence map›Paper›PMID 35734088›Full record

ArticlebioRxiv : the preprint server for biology2022

The Omicron variant BA.1.1 presents a lower pathogenicity than B.1 D614G and Delta variants in a feline model of SARS-CoV-2 infection.

Mathias Martins, Gabriela M do Nascimento, Mohammed Nooruzzaman, Fangfeng Yuan, Chi Chen, Leonardo C Caserta, Andrew D Miller, Gary R Whittaker, Ying Fang, Diego G Diel

Open access · greenAbstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed, 7 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

10 authors at 2 institutions in 1 country.

Mathias MartinsDepartment of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America.
Gabriela M do NascimentoDepartment of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America.
Mohammed NooruzzamanDepartment of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America.
Fangfeng YuanDepartment of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
Chi ChenDepartment of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
Leonardo C CasertaDepartment of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America.
Andrew D MillerDepartment of Biomedical Sciences, Section of Anatomic Pathology, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America.
Gary R WhittakerDepartment of Microbiology and Immunology, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America.
Ying FangDepartment of Pathobiology, College of Veterinary Medicine, University of Illinois at Urbana-Champaign, Urbana, Illinois, United States of America.
Diego G DielDepartment of Population Medicine and Diagnostic Sciences, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America.
Cornell University · USUniversity of Illinois Urbana-Champaign · US

Funding

Novel diagnostic tools and animal model system for study human/animal interface of COVID-19R01AI166791 · NIAID · UNIVERSITY OF ILLINOIS AT URBANA-CHAMPAIGN · PI DIEL, DIEGO G, FANG, YING · 2021 to 2024
$3.1M
NIAID NIH HHS R01 AI166791
6 · The paper itself

Abstract

Omicron (B.1.1.529) is the most recent SARS-CoV-2 variant of concern (VOC), which emerged in late 2021 and rapidly achieved global predominance in early 2022. In this study, we compared the infection dynamics, tissue tropism and pathogenesis and pathogenicity of SARS-CoV-2 D614G (B.1), Delta (B.1.617.2) and Omicron BA.1.1 sublineage (B.1.1.529) variants in a highly susceptible feline model of infection. While D614G- and Delta-inoculated cats became lethargic, and showed increased body temperatures between days 1 and 3 post-infection (pi), Omicron-inoculated cats remained subclinical and, similar to control animals, gained weight throughout the 14-day experimental period. Intranasal inoculation of cats with D614G- and the Delta variants resulted in high infectious virus shedding in nasal secretions (up to 6.3 log10 TCID Author Summary: The SARS-CoV-2 Omicron (B.1.1.529) variant of concern (VOC) emerged in South Africa late in 2021 and rapidly spread across the world causing a significant increase in the number of infections. Importantly, this variant was also associated with an increased risk of reinfections. However, the number of hospitalizations and deaths due to COVID-19 did not follow the same trends. These early observations, suggested effective protection conferred by immunizations and/or overall lower virulence of the highly mutated variant virus. In this study we present novel evidence demonstrating that the Omicron BA.1.1 variant of concern (VOC) presents a lower pathogenicity when compared to D614G- or Delta variants in cats. Clinical, virological and pathological evaluations revealed lower disease severity, viral replication and lung pathology in Omicron-infected cats when compared to D614G and Delta variant inoculated animals, confirming that Omicron BA.1.1 is less pathogenic in a highly susceptible feline model of infection.

Identifiers

PMID35734088
PMCPMC9216722
OpenAlexW4282959428

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.