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EBioMedicine ; 68: 103390, 2021 Jun.
Article in English | MEDLINE | ID: covidwho-1267655


BACKGROUND: Coronavirus Disease 2019 (Covid-19) continues to challenge the limits of our knowledge and our healthcare system. Here we sought to define the host immune response, a.k.a, the "cytokine storm" that has been implicated in fatal COVID-19 using an AI-based approach. METHOD: Over 45,000 transcriptomic datasets of viral pandemics were analyzed to extract a 166-gene signature using ACE2 as a 'seed' gene; ACE2 was rationalized because it encodes the receptor that facilitates the entry of SARS-CoV-2 (the virus that causes COVID-19) into host cells. An AI-based approach was used to explore the utility of the signature in navigating the uncharted territory of Covid-19, setting therapeutic goals, and finding therapeutic solutions. FINDINGS: The 166-gene signature was surprisingly conserved across all viral pandemics, including COVID-19, and a subset of 20-genes classified disease severity, inspiring the nomenclatures ViP and severe-ViP signatures, respectively. The ViP signatures pinpointed a paradoxical phenomenon wherein lung epithelial and myeloid cells mount an IL15 cytokine storm, and epithelial and NK cell senescence and apoptosis determine severity/fatality. Precise therapeutic goals could be formulated; these goals were met in high-dose SARS-CoV-2-challenged hamsters using either neutralizing antibodies that abrogate SARS-CoV-2•ACE2 engagement or a directly acting antiviral agent, EIDD-2801. IL15/IL15RA were elevated in the lungs of patients with fatal disease, and plasma levels of the cytokine prognosticated disease severity. INTERPRETATION: The ViP signatures provide a quantitative and qualitative framework for titrating the immune response in viral pandemics and may serve as a powerful unbiased tool to rapidly assess disease severity and vet candidate drugs. FUNDING: This work was supported by the National Institutes for Health (NIH) [grants CA151673 and GM138385 (to DS) and AI141630 (to P.G), DK107585-05S1 (SD) and AI155696 (to P.G, D.S and S.D), U19-AI142742 (to S. C, CCHI: Cooperative Centers for Human Immunology)]; Research Grants Program Office (RGPO) from the University of California Office of the President (UCOP) (R00RG2628 & R00RG2642 to P.G, D.S and S.D); the UC San Diego Sanford Stem Cell Clinical Center (to P.G, D.S and S.D); LJI Institutional Funds (to S.C); the VA San Diego Healthcare System Institutional funds (to L.C.A). GDK was supported through The American Association of Immunologists Intersect Fellowship Program for Computational Scientists and Immunologists. ONE SENTENCE SUMMARY: The host immune response in COVID-19.

Angiotensin-Converting Enzyme 2/genetics , Antiviral Agents/administration & dosage , COVID-19/genetics , Gene Expression Profiling/methods , Interleukin-15/genetics , Receptors, Interleukin-15/genetics , Virus Diseases/genetics , Animals , Antibodies, Neutralizing/administration & dosage , Antibodies, Neutralizing/pharmacology , Antiviral Agents/pharmacology , Artificial Intelligence , Autopsy , COVID-19/drug therapy , COVID-19/immunology , Cricetinae , Cytidine/administration & dosage , Cytidine/analogs & derivatives , Cytidine/pharmacology , Databases, Genetic , Disease Models, Animal , Gene Regulatory Networks/drug effects , Genetic Markers/drug effects , Humans , Hydroxylamines/administration & dosage , Hydroxylamines/pharmacology , Interleukin-15/blood , Lung/immunology , Mesocricetus , Pandemics , Receptors, Interleukin-15/blood , Virus Diseases/immunology
JCI Insight ; 6(1)2021 01 11.
Article in English | MEDLINE | ID: covidwho-1027164


Immune and inflammatory responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contribute to disease severity of coronavirus disease 2019 (COVID-19). However, the utility of specific immune-based biomarkers to predict clinical outcome remains elusive. Here, we analyzed levels of 66 soluble biomarkers in 175 Italian patients with COVID-19 ranging from mild/moderate to critical severity and assessed type I IFN-, type II IFN-, and NF-κB-dependent whole-blood transcriptional signatures. A broad inflammatory signature was observed, implicating activation of various immune and nonhematopoietic cell subsets. Discordance between IFN-α2a protein and IFNA2 transcript levels in blood suggests that type I IFNs during COVID-19 may be primarily produced by tissue-resident cells. Multivariable analysis of patients' first samples revealed 12 biomarkers (CCL2, IL-15, soluble ST2 [sST2], NGAL, sTNFRSF1A, ferritin, IL-6, S100A9, MMP-9, IL-2, sVEGFR1, IL-10) that when increased were independently associated with mortality. Multivariate analyses of longitudinal biomarker trajectories identified 8 of the aforementioned biomarkers (IL-15, IL-2, NGAL, CCL2, MMP-9, sTNFRSF1A, sST2, IL-10) and 2 additional biomarkers (lactoferrin, CXCL9) that were substantially associated with mortality when increased, while IL-1α was associated with mortality when decreased. Among these, sST2, sTNFRSF1A, IL-10, and IL-15 were consistently higher throughout the hospitalization in patients who died versus those who recovered, suggesting that these biomarkers may provide an early warning of eventual disease outcome.

COVID-19/immunology , COVID-19/mortality , Adrenal Cortex Hormones/therapeutic use , Adult , Aged , Anti-Bacterial Agents/therapeutic use , Antibodies, Monoclonal, Humanized/therapeutic use , Antiviral Agents/therapeutic use , Azithromycin/therapeutic use , Biomarkers , COVID-19/genetics , COVID-19/therapy , Calgranulin B/genetics , Calgranulin B/immunology , Case-Control Studies , Chemokine CCL2/genetics , Chemokine CCL2/immunology , Chemokine CXCL9/genetics , Chemokine CXCL9/immunology , Enzyme Inhibitors/therapeutic use , Female , Ferritins/genetics , Ferritins/immunology , Gene Expression Profiling , Humans , Hydroxychloroquine/therapeutic use , Immunologic Factors/therapeutic use , Interferon Type I/genetics , Interferon Type I/immunology , Interferon-gamma/genetics , Interferon-gamma/immunology , Interleukin-1 Receptor-Like 1 Protein/genetics , Interleukin-1 Receptor-Like 1 Protein/immunology , Interleukin-10/genetics , Interleukin-10/immunology , Interleukin-15/genetics , Interleukin-15/immunology , Interleukin-2/genetics , Interleukin-2/immunology , Interleukin-6/genetics , Interleukin-6/immunology , Lactoferrin/genetics , Lactoferrin/immunology , Lipocalin-2/genetics , Lipocalin-2/immunology , Male , Matrix Metalloproteinase 9/genetics , Matrix Metalloproteinase 9/immunology , Middle Aged , Multivariate Analysis , NF-kappa B/genetics , NF-kappa B/immunology