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Record W4386496927 · doi:10.1128/spectrum.01256-23

Analysis of SARS-CoV-2 isolates, namely the Wuhan strain, Delta variant, and Omicron variant, identifies differential immune profiles

2023· article· en· W4386496927 on OpenAlexafffund
Shima Shahbaz, Najmeh Bozorgmehr, Julia Lu, Mohammed Osman, Wendy Sligl, D. Lorne Tyrrell, Shokrollah Elahi

Bibliographic record

VenueMicrobiology Spectrum · 2023
Typearticle
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsAlberta Glycomics CentreWomen and Children’s Health Research InstituteUniversity of Alberta
FundersCanadian Institutes of Health ResearchUniversity of AlbertaGovernment of Canada
KeywordsImmune systemBiologyChemokineProinflammatory cytokineStrain (injury)PathogenesisCD8GalectinPhenotypeImmunologyT cellVirologyInflammationGeneGenetics

Abstract

fetched live from OpenAlex

ABSTRACT There is an urgent need to better understand the impact of different severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants on immune response and disease dynamics to facilitate better intervention strategies. Here, we show that SARS-CoV-2 variants differentially affect host immune responses. The magnitude and quantity of cytokines and chemokines were comparable in those infected with the Wuhan strain and the Delta variant. However, individuals infected with the Omicron variant had significantly lower levels of these mediators. We also found an elevation of plasma galectins (Gal-3, Gal-8, and Gal-9) in infected individuals, in particular, in those with the original strain. Soluble galectins exert a proinflammatory role in COVID-19 pathogenesis. This was illustrated by their correlation with the plasma levels of sCD14, sCD163, enhanced TNF-α/IL-6 secretion, and increased SARS-CoV-2 infectivity in vitro . Moreover, we observed enhanced CD4 + and CD8 + T cell activation in Wuhan strain-infected individuals. Surprisingly, there was a more pronounced T cell activation in those infected with the Omicron in comparison to the Delta variant. In line with T cell activation status, we observed a more pronounced expansion of T cells expressing different co-inhibitory receptors in patients infected with the Wuhan strain, followed by the Omicron and Delta variants. Individuals infected with the Wuhan strain or the Omicron variant had a similar pattern of plasma soluble immune checkpoints. Our results imply that a milder innate immune response might be beneficial and protective in those infected with the Omicron variant. Our results provide a novel insight into the differential impact of SARS-CoV-2 variants on host immunity. IMPORTANCE There is a need to better understand how different SARS-CoV-2 variants influence the immune system and disease dynamics to facilitate the development of better vaccines and therapies. We compared immune responses in 140 SARS-CoV-2-infected individuals with the Wuhan strain, the Delta variant, or the Omicron variant. All these patients were admitted to the intensive care unit and were SARS-CoV-2 vaccination naïve. We found that SARS-CoV-2 variants differentially affect the host immune response. This was done by measuring soluble biomarkers in their plasma and examining different immune cells. Overall, we found that the magnitude of cytokine storm in individuals infected with the Wuhan strain or the Delta variant was greater than in those infected with the Omicron variant. In light of enhanced cytokine release syndrome in individuals infected with the Wuhan strain or the Delta variant, we believe that a milder innate immune response might be beneficial and protective in those infected with the Omicron variant.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.309
Teacher spread0.281 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations38
Published2023
Admission routes2
Has abstractyes

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