Systems biological assessment of immunity to mild versus severe COVID-19 infection in humans
Open accessAbstract
Immune profiling of COVID-19 patients: Coronavirus disease 2019 (COVID-19) has affected millions of people globally, yet how the human immune system responds to and influences COVID-19 severity remains unclear. Mathew et al. present a comprehensive atlas of immune modulation associated with COVID-19. They performed high-dimensional flow cytometry of hospitalized COVID-19 patients and found three prominent and distinct immunotypes that are related to disease severity and clinical parameters. Arunachalam et al. report a systems biology approach to assess the immune system of COVID-19 patients with mild-to-severe disease. These studies provide a compendium of immune cell information and roadmaps for potential therapeutic interventions. Science , this issue p. eabc8511 , p. 1210
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Type I and III interferon responses are the most important innate antiviral responses against SARS-CoV-2 according to model systems.
“Evidence from model systems indicate that type I and III IFN responses are most important”
From COVID-19 and the human innate immune system (2021) · cites this paper as [7]
COVID-19 patients showed a lack of expression of genes encoding type I IFNs in PBMCs and an early but transient wave of ISG expression in blood-derived immune cells, which correlated with an early burst of IFNα likely of lung origin.
“These observations were further extended by illustrating a lack of expression of genes encoding type I IFNs in peripheral blood mononuclear cells (PBMCs) of COVID-19 patients and an early but transient wave of ISG expression in blood-derived immune cells, which correlated with an early burst of IFNα, likely of lung origin (Arunachalam et al., 2020).”
From COVID-19 and the human innate immune system (2021) · cites this paper as Arunachalam et al., 2020
pDCs are reduced and functionally impaired in COVID-19, suggesting the lung is a source of elevated plasma type I IFNs early in infection.
“suggesting the lung as a source for the elevated plasma levels of type I IFNs early on infection”
From COVID-19 and the human innate immune system (2021) · cites this paper as Arunachalam et al., 2020
SARS-CoV-2 is unusually effective at evading or delaying early innate immune responses, including type I and type III IFNs, in vitro and in humans.
“In a SARS-CoV-2 infection, the virus is particularly effective at avoiding or delaying triggering intracellular innate immune responses associated with type I and type III IFNs in vitro (Blanco-Melo et al., 2020) and in humans (Arunachalam et al., 2020; Bastard et al., 2020; Blanco-Melo et al., 2020; Laing et al., 2020).”
From Adaptive immunity to SARS-CoV-2 and COVID-19 (2021) · cites this paper as Arunachalam et al., 2020
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- Authors
- Arunachalam, P. S., Wimmers, F., Mok, C. K. P., Perera, R. A. P. M., Scott, M., Hagan, T., Sigal, N., Feng, Y., Bristow, L., Tak-Yin Tsang, O., Wagh, D., Coller, J., Pellegrini, K. L., Kazmin, D., Alaaeddine, G., Leung, W. S., Chan, J. M. C., Chik, T. S. H., Choi, C. Y. C., Huerta, C., Paine McCullough, M., Lv, H., Anderson, E., Edupuganti, S., Upadhyay, A. A., Bosinger, S. E., Maecker, H. T., Khatri, P., Rouphael, N., Peiris, M., & Pulendran, B.
- Affiliations
- Stanford Medicine (US)
- HKU-Pasteur Research Pole (HK)
- University of Hong Kong (HK)
- Emory University (US)
- Infectious Diseases Centre, Princess Margaret Hospital, Hospital Authority of Hong Kong, Hong Kong.
- Emory National Primate Research Center (US)
- Hospital Authority (HK)
- Hope Clinic of the Emory Vaccine Center, Department of Medicine, Division of Infectious Diseases, Emory University School of Medicine, Decatur, GA 30030, USA.
- Corresponding author
- Arunachalam, Prabhu S.
- Wimmers, Florian
- Mok, Chris Ka Pun
- Perera, Ranawaka A. P. M.
- Scott, Madeleine
- Hagan, Thomas
- Sigal, Natalia
- Feng, Yupeng
- Pulendran, Bali
- ORCID
- Arunachalam, Prabhu S.
- Wimmers, Florian
- Mok, Chris Ka Pun
- Perera, Ranawaka A. P. M.
- Scott, Madeleine
- Hagan, Thomas
- Sigal, Natalia
- Feng, Yupeng
- Bristow, Laurel
- Wagh, Dhananjay
- Pellegrini, Kathryn L.
- Kazmin, Dmitri
- Alaaeddine, Ghina
- Leung, Wai Shing
- Chik, Thomas Shiu Hong
- Choi, Chris Yau Chung
- Lv, Huibin
- Anderson, Evan
- Edupuganti, Srilatha
- Upadhyay, Amit A.
- Bosinger, Steve E.
- Maecker, Holden Terry
- Khatri, Purvesh
- Rouphael, Nadine
- Peiris, Malik
- Pulendran, Bali
- Venue
- Science
- Published
- 2020-09-04
- Volume
- 369
- Issue
- 6508
- Pages
- 1210-1220
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC7665312
- OpenAlex
- W3047880178
- Cited by
- 1,186
- References
- 43
- Citations by year
- 2026: 52 · 2025: 95 · 2024: 141 · 2023: 191 · 2022: 269 · 2021: 360 · 2020: 77
- FWCI
- 29.55
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Science (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- National Institutes of Health (U19AI090023)
- Topics
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 and COVID-19 Research
- Life Sciences › Immunology and Microbiology › Immunology › interferon and immune responses
- Keywords
- COVID-19 pandemic, SARS-CoV-2, disease severity, immune response, HLA-DR, myeloid cells, inflammatory cytokines, mTOR signaling, plasmacytoid dendritic cells, interferon-alpha, type I interferon, S100A12, TNFSF14, oncostatin M, bacterial products, IFN-stimulated genes, single-cell transcriptomics, peripheral blood mononuclear cells
- MeSH terms
- Betacoronavirus, COVID-19, SARS-CoV-2, Dendritic Cells, DNA, Bacterial, Female, Flow Cytometry, HLA-DR Antigens, Humans, Immunity, Immunity, Innate, Immunoglobulins, Interferon Type I, Leukocytes, Mononuclear, Lipopolysaccharides, Male, Pneumonia, Viral, Transcription, Genetic, Signal Transduction, Cytokines, Coronavirus Infections, Inflammation Mediators, Myeloid Cells, Systems Biology, TOR Serine-Threonine Kinases, Pandemics, Single-Cell Analysis, Transcriptome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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