Innate lymphoid cells and COVID-19 severity in SARS-CoV-2 infection

  1. Noah J Silverstein
  2. Yetao Wang
  3. Zachary Manickas-Hill
  4. Claudia Carbone
  5. Ann Dauphin
  6. Brittany P Boribong
  7. Maggie Loiselle
  8. Jameson Davis
  9. Maureen M Leonard
  10. Leticia Kuri-Cervantes
  11. MGH COVID-19 Collection & Processing Team
  12. Nuala J Meyer
  13. Michael R Betts
  14. Jonathan Z Li
  15. Bruce D Walker
  16. Xu G Yu
  17. Lael M Yonker
  18. Jeremy Luban

  • Curated by eLife

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    Evaluation Summary:

    The authors present an interesting approach of COVID-19 pathogenesis with emphasis on the role of innate lymphoid cells as a major correlate of the severity of COVID-19 and of the levels of inflammatory markers. The main strength of the manuscript is the novelty of approach, and the fact that the authors are the first to find this potentially interesting correlation, which brings up a number of both translational and mechanistic possibilities of significance. The limitation, of course, is the difficulty in showing a cause-and-effect relationship between the reduction in of innate lymphoid cells and the severity of COVID-19 inflammation.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their names with the authors.)

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Abstract

Risk of severe COVID-19 increases with age, is greater in males, and is associated with lymphopenia, but not with higher burden of SARS-CoV-2. It is unknown whether effects of age and sex on abundance of specific lymphoid subsets explain these correlations.

Methods:

Multiple regression was used to determine the relationship between abundance of specific blood lymphoid cell types, age, sex, requirement for hospitalization, duration of hospitalization, and elevation of blood markers of systemic inflammation, in adults hospitalized for severe COVID-19 (n = 40), treated for COVID-19 as outpatients (n = 51), and in uninfected controls (n = 86), as well as in children with COVID-19 (n = 19), recovering from COVID-19 (n = 14), MIS-C (n = 11), recovering from MIS-C (n = 7), and pediatric controls (n = 17).

Results:

This observational study found that the abundance of innate lymphoid cells (ILCs) decreases more than 7-fold over the human lifespan – T cell subsets decrease less than 2-fold – and is lower in males than in females. After accounting for effects of age and sex, ILCs, but not T cells, were lower in adults hospitalized with COVID-19, independent of lymphopenia. Among SARS-CoV-2-infected adults, the abundance of ILCs, but not of T cells, correlated inversely with odds and duration of hospitalization, and with severity of inflammation. ILCs were also uniquely decreased in pediatric COVID-19 and the numbers of these cells did not recover during follow-up. In contrast, children with MIS-C had depletion of both ILCs and T cells, and both cell types increased during follow-up. In both pediatric COVID-19 and MIS-C, ILC abundance correlated inversely with inflammation. Blood ILC mRNA and phenotype tracked closely with ILCs from lung. Importantly, blood ILCs produced amphiregulin, a protein implicated in disease tolerance and tissue homeostasis. Among controls, the percentage of ILCs that produced amphiregulin was higher in females than in males, and people hospitalized with COVID-19 had a lower percentage of ILCs that produced amphiregulin than did controls.

Conclusions:

These results suggest that, by promoting disease tolerance, homeostatic ILCs decrease morbidity and mortality associated with SARS-CoV-2 infection, and that lower ILC abundance contributes to increased COVID-19 severity with age and in males.

Funding:

This work was supported in part by the Massachusetts Consortium for Pathogen Readiness and NIH grants R37AI147868, R01AI148784, F30HD100110, 5K08HL143183.

Article activity feed

  1. Version published to 10.7554/elife.74681 on eLife
  2. eLife

    Evaluation Summary:

    The authors present an interesting approach of COVID-19 pathogenesis with emphasis on the role of innate lymphoid cells as a major correlate of the severity of COVID-19 and of the levels of inflammatory markers. The main strength of the manuscript is the novelty of approach, and the fact that the authors are the first to find this potentially interesting correlation, which brings up a number of both translational and mechanistic possibilities of significance. The limitation, of course, is the difficulty in showing a cause-and-effect relationship between the reduction in of innate lymphoid cells and the severity of COVID-19 inflammation.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #1 and Reviewer #2 agreed to share their names with the authors.)

  3. eLife

    Reviewer #1 (Public Review):

    The authors present an interesting approach of COVID-19 pathogenesis with emphasis on the role of innate lymphoid cells as the main driver of lymphopenia in severe COVID-19.

    The main strength of the manuscript is the novelty of approach being the first on that field. The main weaknesses are the difficulty in showing that the depletion of innate lymphoid cells is culprit for the lymphopenia of severe COVID-19 and of the subsequent hypoglobulinemia and the lack of further information on cytokine production capacity from these cells.

  4. eLife

    Reviewer #2 (Public Review):

    In this manuscript the authors describe very rationally the hypothesis of association of ILC with age- and sex-dependent COVID-19 severity and moreover, through a series of well-designed experiments in both adults and children justify such a link. The manuscript is of great interest and the authors are to be congratulated for their meticulous approach. I only have some minor comments as follows. The authors should clarify when exactly blood sampling took place (at admission? during hospitalization? Before any treatment start?) as in Table 1 median duration of symptoms is about 20 days, quiet a long period; normally patients are admitted after the first week. If not at admission administered therapy especially corticosteroids may influence flow cytometry results. If therapy was administered this has to be part of the regression results in Table 3. A second minor comment is the absence in presentation of comorbidities as they can perhaps also influence results. If these data are unavailable, this is for sure a limitation and should be discussed.

  5. eLife

    Reviewer #3 (Public Review):

    This study investigates the association between age, sex, the frequency of specific blood lymphocyte subsets, and COVID disease severity. In uninfected controls, they show a very clear link between age and changing lymphocyte frequencies in blood. This reveals a strong association between age and the frequency of total ILCs in blood and of so-called ILC-precursors (ILCp), which are highest at birth and decrease approximately twofold every 20 years. In addition, CD4 and CD8 T-cells were significantly lower in the oldest age category, while CD16+ NK cells appeared to increase with age. The authors also reveal a lower frequency of circulating ILCs in males than females, although the ranges are highly overlapping and the effect is weakly significant. By contrast, the lower CD4 count in males is striking and highly significant.

    In SARS-CoV2 infected adults, as reported widely, infections were highest in young adults, and mortality was highest in the elderly and increased approximately 1 log for each 20 year age group. Linear regression revealed that age, sex, and ILC and NK cell frequency were inversely correlated with hospitalization, and the association between ILC and NK frequency was retained when age and sex were adjusted for. Subsequent multiple logistic regression analysis showed that adjusting for age, sex, and symptom duration, only ILC frequency was significantly associated with an increased risk of hospitalization, the duration of hospital stay, and an increase in CRP. The same association between ILC frequency, but not other lymphocytes, and COVID was observed in an additional paediatric cohort. However, in rare Paediatric cases who developed MIS-C, both ILCs and T cells were significantly reduced. To link blood ILCs to what is happening on the lung, bioinformatic analysis of sequence data generated from sorted blood ILCS in compared to that of published gut and lung ILC datasets. Although, the authors argue this shows blood ILCs are transcriptionally more closely aligned to lung ILCs, the validity of this analysis is hard to judge without more detail and, as the data does not come from COVID subjects, its value in supporting the manuscript is unclear. Finally, ILCs from uninfected males produced less amphiregulin, important in lung homeostasis and repair.

    The loss of ILCs from circulation has been shown in several diseases, including HIV, TB, and COVID, as has the association between circulating ILCs and age. The strength of this manuscript is in using multiple regression to show that the association between ILC loss and disease severity is retained when age is controlled for, as age is such an important factor in COVID. However, the overall conclusion that elevated circulating ILCs support disease tolerance, while interesting, is not directly supported by any data. For example, a reduction in blood ILCs may indicate the recruitment of these cells to the lung, as has been shown for TB (Ardain et al Nature 2019). In which case, an increased frequency of blood ILCs may not be protective per se, but just reflective of less lung involvement. Therefore, I suggest the title and abstract be altered to reflect the data presented more directly.

  6. Version published to 10.1101/2021.01.14.21249839v4 on medRxiv
  7. Version published to 10.1101/2021.01.14.21249839v3 on medRxiv
  8. Version published to 10.1101/2021.01.14.21249839v2 on medRxiv
  9. ScreenIT

    SciScore for 10.1101/2021.01.14.21249839: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Cell subsets were identified using FlowJo™ software (Becton, Dickson and Company).
    FlowJo™
    suggested: (FlowJo, RRID:SCR_008520)
    STATISTICAL ANALYSIS AND DATA VISUALIZATION: Data were prepared for analysis with the tidyverse56 package, and visualized using the ggplot257 and ggpubr58 packages, within the R computer software environment
    R computer
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    Results from JetFighter: Please consider improving the rainbow (“jet”) colormap(s) used on page 27. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  10. Version published to 10.1101/2021.01.14.21249839v1 on medRxiv