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Record W3093850884 · doi:10.1101/2020.10.15.20208041

Analysis of respiratory and systemic immune responses in COVID-19 reveals mechanisms of disease pathogenesis

2020· preprint· en· W3093850884 on OpenAlexfundno aff
Peter A. Szabo, Pranay Dogra, Joshua I. Gray, Steven B. Wells, Thomas J. Connors, Stuart P. Weisberg, Izabela Krupska, Rei Matsumoto, Maya M.L. Poon, Emma Idzikowski, Sinead E. Morris, Chloé Pasin, Andrew J. Yates, Amy Ku, Michael Chait, Julia Davis‐Porada, Jing Zhou, Matthew Steinle, Sean Mackay, Anjali Saqi, Matthew R. Baldwin, Peter A. Sims, Donna L. Färber

Bibliographic record

VenuemedRxiv · 2020
Typepreprint
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsnot available
FundersNational Cancer InstituteCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsImmunologyPathogenesisImmune systemMonocyteCD163CCL2CCR2Respiratory tractBiologyAcquired immune systemLungImmunityMacrophageRespiratory systemMedicineChemokineChemokine receptorInternal medicineIn vitro

Abstract

fetched live from OpenAlex

SUMMARY Immune responses to respiratory viruses like SARS-CoV-2 originate and function in the lung, yet assessments of human immunity are often limited to blood. Here, we conducted longitudinal, high-dimensional profiling of paired airway and blood samples from patients with severe COVID-19, revealing immune processes in the respiratory tract linked to disease pathogenesis. Survival from severe disease was associated with increased CD4 + T cells and decreased monocyte/macrophage frequencies in the airway, but not in blood. Airway T cells and macrophages exhibited tissue-resident phenotypes and activation signatures, including high level expression and secretion of monocyte chemoattractants CCL2 and CCL3 by airway macrophages. By contrast, monocytes in blood expressed the CCL2-receptor CCR2 and aberrant CD163 + and immature phenotypes. Extensive accumulation of CD163 + monocyte/macrophages within alveolar spaces in COVID-19 lung autopsies suggested recruitment from circulation. Our findings provide evidence that COVID-19 pathogenesis is driven by respiratory immunity, and rationale for site-specific treatment and prevention strategies.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.145
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.145
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.097
GPT teacher head0.423
Teacher spread0.326 · 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 teacher head, not a consensus.

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

Citations25
Published2020
Admission routes1
Has abstractyes

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