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Record W4403145045 · doi:10.1101/2024.10.03.616431

Delayed viral clearance and altered inflammatory responses resulted in increased severity of SARS-CoV-2 infection in aged mice

2024· preprint· en· W4403145045 on OpenAlexaff
Émile Lacasse, Isabelle Dubuc, Leslie Gudimard, Ana Cláudia dos Santos Pereira Andrade, Annie Gravel, Karine Greffard, Alexandre Chamberland, Camille Oger, Jean‐Marie Galano, Thierry Durand, Éric Philipe, Marie‐Renée Blanchet, Jean‐François Bilodeau, Louis Flamand

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsInstitut universitaire de cardiologie et de pneumologie de QuébecUniversité LavalCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Coronavirus disease 2019 (COVID-19)Viral infectionVirologyImmunology2019-20 coronavirus outbreakMedicineInflammationViral loadVirusInternal medicineOutbreakInfectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

Abstract Since the onset of the COVID-19 pandemic, advanced age has emerged as a major predictor of disease severity. Epidemiological investigations consistently demonstrate an overrepresentation of the elderly in COVID-19 hospitalizations and fatalities. Despite this, a comprehensive understanding of the molecular mechanisms explaining how old age constitutes a critical risk factor remains elusive. To unravel this, we designed an animal study, juxtaposing the course of COVID-19 in young adults (2 months) and geriatric (15-22 months) mice. Both groups of K18(hACE2) mice were intranasally exposed to 500 TCID 50 of the SARS-CoV-2 Delta variant with a variety of outcomes assessed on days 3, 5, and 7 post-infections (DPI). Analyses included pulmonary cytokines, RNA, viral loads, lipidomic profiles, and histological assessments, with a concurrent evaluation of the percentage of mice reaching humane endpoints. The findings unveiled notable distinctions between the two groups, with aged mice exhibiting impaired viral clearance at 7 DPI, correlating with diminished survival rates together with an absence of weight loss recovery at 6-7 DPI. Additionally, elderly-infected mice exhibited a deficient Th1 response characterized by diminished productions of IFNg, CCL2, CCL3, and CXCL9 relative to younger mice. Furthermore, mass-spectrometry analysis of the lung lipidome indicated altered expression of several lipids with immunomodulatory and pro-resolution effects in aged mice such as Resolvin, HOTrEs, and NeuroP, but also DiHOMEs-related ARDS. Collectively, disease severity implies a dysregulation of the antiviral response in elderly-infected mice relative to younger mice, resulting in compromised viral clearance and a more unfavorable prognosis. This underscores the potential efficacy of immunomodulatory treatments for elderly subjects experiencing symptoms of severe COVID-19. Author summary In this study, we investigated why older age is linked to more severe COVID-19 outcomes by comparing the progression of the disease in young (2 months) and elderly (15-22 months) K18(hACE2) mice infected with the SARS-CoV-2 Delta variant. After exposing both groups to the virus, we assessed various factors such as viral loads, immune responses, and lipid profiles in the lungs at different time points. Our findings revealed that elderly mice struggled to clear the virus by day 7 post-infection, leading to higher mortality rates and poorer recovery compared to younger mice. Aged mice showed weaker immune responses, with reduced production of key antiviral proteins like IFNg and certain chemokines. Lipid analysis also highlighted differences in molecules involved in immune regulation and lung protection, such as decreased levels of pro-resolving lipids and increased lipids associated with lung injury. These results suggest that older mice have a compromised antiviral defense, which could inform new therapeutic approaches for elderly patients with severe COVID-19.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.001

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 head0.036
GPT teacher head0.344
Teacher spread0.309 · 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 designBench or experimental
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

Citations0
Published2024
Admission routes1
Has abstractyes

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