Quantifying the impact of immune history and variant on SARS-CoV-2 viral kinetics and infection rebound: a retrospective cohort study

  1. James A Hay
  2. Stephen M Kissler
  3. Joseph R Fauver
  4. Christina Mack
  5. Caroline G Tai
  6. Radhika M Samant
  7. Sarah Connolly
  8. Deverick J Anderson
  9. Gaurav Khullar
  10. Matthew MacKay
  11. Miral Patel
  12. Shannan Kelly
  13. April Manhertz
  14. Isaac Eiter
  15. Daisy Salgado
  16. Tim Baker
  17. Ben Howard
  18. Joel T Dudley
  19. Christopher E Mason
  20. Manoj Nair
  21. Yaoxing Huang
  22. John DiFiori
  23. David D Ho
  24. Nathan Grubaugh  Is a corresponding author
  25. Yonatan H Grad  Is a corresponding author
  1. Harvard TH Chan School of Public Health, United States
  2. Yale School of Public Health, United States
  3. IQVIA, United States
  4. Duke Center for Antimicrobial Stewardship and Infection Prevention, United States
  5. Tempus Labs, United States
  6. Columbia University, United States
  7. Hospital for Special Surgery, United States

Abstract

Background: The combined impact of immunity and SARS-CoV-2 variants on viral kinetics during infections has been unclear.

Methods: We characterized 1,280 infections from the National Basketball Association occupational health cohort identified between June 2020 and January 2022 using serial RT-qPCR testing. Logistic regression and semi-mechanistic viral RNA kinetics models were used to quantify the effect of age, variant, symptom status, infection history, vaccination status and antibody titer to the founder SARS-CoV-2 strain on the duration of potential infectiousness and overall viral kinetics. The frequency of viral rebounds was quantified under multiple cycle threshold (Ct) value-based definitions.

Results: Among individuals detected partway through their infection, 51.0% (95% credible interval [CrI]: 48.3-53.6%) remained potentially infectious (Ct<30) five days post detection, with small differences across variants and vaccination status. Only seven viral rebounds (0.7%; N=999) were observed, with rebound defined as 3+ days with Ct<30 following an initial clearance of 3+ days with Ct≥30. High antibody titers against the founder SARS-CoV-2 strain predicted lower peak viral loads and shorter durations of infection. Among Omicron BA.1 infections, boosted individuals had lower pre-booster antibody titers and longer clearance times than non-boosted individuals.

Conclusions: SARS-CoV-2 viral kinetics are partly determined by immunity and variant but dominated by individual-level variation. Since booster vaccination protects against infection, longer clearance times for BA.1-infected, boosted individuals may reflect a less effective immune response, more common in older individuals, that increases infection risk and reduces viral RNA clearance rate. The shifting landscape of viral kinetics underscores the need for continued monitoring to optimize isolation policies and to contextualize the health impacts of therapeutics and vaccines.

Funding: Supported in part by CDC contract #200-2016-91779, a sponsored research agreement to Yale University from the National Basketball Association contract #21-003529, and the National Basketball Players Association.

Data availability

All code and data required to reproduce the analyses are available at https://github.com/gradlab/SC2-kinetics-immune-history.

Article and author information

Author details

  1. James A Hay

    Harvard TH Chan School of Public Health, Boston, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-1998-1844
  2. Stephen M Kissler

    Harvard TH Chan School of Public Health, Boston, United States
    Competing interests
    Stephen M Kissler, SMK has a consulting agreement with the NBA.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-3062-7800
  3. Joseph R Fauver

    Yale School of Public Health, New Haven, United States
    Competing interests
    Joseph R Fauver, has a consulting agreement for Tempus and receives financial support from Tempus to develop SARS-CoV-2 diagnostic tests.
  4. Christina Mack

    IQVIA, Durham, United States
    Competing interests
    Christina Mack, is an employee of IQVIA, Real World Solutions.
  5. Caroline G Tai

    IQVIA, Durham, United States
    Competing interests
    Caroline G Tai, is an employee of IQVIA, Real World Solutions.
  6. Radhika M Samant

    IQVIA, Durham, United States
    Competing interests
    Radhika M Samant, is an employee of IQVIA, Real World Solutions.
  7. Sarah Connolly

    IQVIA, Durham, United States
    Competing interests
    Sarah Connolly, is an employee of IQVIA, Real World Solutions.
  8. Deverick J Anderson

    Duke Center for Antimicrobial Stewardship and Infection Prevention, Durham, United States
    Competing interests
    Deverick J Anderson, is co-owner of Infection Control Education for Major Sports.
  9. Gaurav Khullar

    Tempus Labs, Chicago, United States
    Competing interests
    Gaurav Khullar, is an employee of Tempus Labs.
  10. Matthew MacKay

    Tempus Labs, Chicago, United States
    Competing interests
    Matthew MacKay, is an employee of Tempus Labs.
  11. Miral Patel

    Tempus Labs, Chicago, United States
    Competing interests
    Miral Patel, is an employee of Tempus Labs.
  12. Shannan Kelly

    Tempus Labs, Chicago, United States
    Competing interests
    Shannan Kelly, is an employee of Tempus Labs.
  13. April Manhertz

    Tempus Labs, Chicago, United States
    Competing interests
    April Manhertz, is an employee of Tempus Labs.
  14. Isaac Eiter

    Tempus Labs, Chicago, United States
    Competing interests
    Isaac Eiter, is an employee of Tempus Labs.
  15. Daisy Salgado

    Tempus Labs, Chicago, United States
    Competing interests
    Daisy Salgado, is an employee of Tempus Labs.
  16. Tim Baker

    Tempus Labs, Chicago, United States
    Competing interests
    Tim Baker, is an employee of Tempus Labs.
  17. Ben Howard

    Tempus Labs, Chicago, United States
    Competing interests
    Ben Howard, is an employee of Tempus Labs.
  18. Joel T Dudley

    Tempus Labs, Chicago, United States
    Competing interests
    Joel T Dudley, is an employee of Tempus Labs.
  19. Christopher E Mason

    Tempus Labs, Chicago, United States
    Competing interests
    Christopher E Mason, is an employee of Tempus Labs.
  20. Manoj Nair

    Vagelos College of Physicians and Surgeons, Columbia University, New York, United States
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5994-3957
  21. Yaoxing Huang

    Vagelos College of Physicians and Surgeons, Columbia University, New York, United States
    Competing interests
    No competing interests declared.
  22. John DiFiori

    Hospital for Special Surgery, New York, United States
    Competing interests
    John DiFiori, is an employee of the NBA.
  23. David D Ho

    Vagelos College of Physicians and Surgeons, Columbia University, New York, United States
    Competing interests
    No competing interests declared.
  24. Nathan Grubaugh

    Yale School of Public Health, New Haven, United States
    For correspondence
    grubaughlab@gmail.com
    Competing interests
    Nathan Grubaugh, has a consulting agreement for Tempus and receives financial support from Tempus to develop SARS-CoV-2 diagnostic tests.
  25. Yonatan H Grad

    Harvard TH Chan School of Public Health, Boston, United States
    For correspondence
    ygrad@hsph.harvard.edu
    Competing interests
    Yonatan H Grad, has a consulting agreement with the NBA.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5646-1314

Funding

Centers for Disease Control and Prevention (200-2016-91779)

  • Yonatan H Grad

National Basketball Association (21-003529)

  • Nathan Grubaugh

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Isabel Rodriguez-Barraquer, University of California, San Francisco, United States

Publication history

  1. Received: July 13, 2022
  2. Accepted: November 15, 2022
  3. Accepted Manuscript published: November 16, 2022 (version 1)

Copyright

© 2022, Hay et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. James A Hay
  2. Stephen M Kissler
  3. Joseph R Fauver
  4. Christina Mack
  5. Caroline G Tai
  6. Radhika M Samant
  7. Sarah Connolly
  8. Deverick J Anderson
  9. Gaurav Khullar
  10. Matthew MacKay
  11. Miral Patel
  12. Shannan Kelly
  13. April Manhertz
  14. Isaac Eiter
  15. Daisy Salgado
  16. Tim Baker
  17. Ben Howard
  18. Joel T Dudley
  19. Christopher E Mason
  20. Manoj Nair
  21. Yaoxing Huang
  22. John DiFiori
  23. David D Ho
  24. Nathan Grubaugh
  25. Yonatan H Grad
(2022)
Quantifying the impact of immune history and variant on SARS-CoV-2 viral kinetics and infection rebound: a retrospective cohort study
eLife 11:e81849.
https://doi.org/10.7554/eLife.81849
  1. Further reading

Further reading

    1. Epidemiology and Global Health
    2. Genetics and Genomics
    Amy L Roberts, Alessandro Morea ... Kerrin S Small
    Research Article

    Background:

    Ageing is a heterogenous process characterised by cellular and molecular hallmarks, including changes to haematopoietic stem cells and is a primary risk factor for chronic diseases. X chromosome inactivation (XCI) randomly transcriptionally silences either the maternal or paternal X in each cell of 46, XX females to balance the gene expression with 46, XY males. Age acquired XCI-skew describes the preferential selection of cells across a tissue resulting in an imbalance of XCI, which is particularly prevalent in blood tissues of ageing females, and yet its clinical consequences are unknown.

    Methods:

    We assayed XCI in 1575 females from the TwinsUK population cohort using DNA extracted from whole blood. We employed prospective, cross-sectional, and intra-twin study designs to characterise the relationship of XCI-skew with molecular and cellular measures of ageing, cardiovascular disease risk, and cancer diagnosis.

    Results:

    We demonstrate that XCI-skew is independent of traditional markers of biological ageing and is associated with a haematopoietic bias towards the myeloid lineage. Using an atherosclerotic cardiovascular disease risk score, which captures traditional risk factors, XCI-skew is associated with an increased cardiovascular disease risk both cross-sectionally and within XCI-skew discordant twin pairs. In a prospective 10 year follow-up study, XCI-skew is predictive of future cancer incidence.

    Conclusions:

    Our study demonstrates that age acquired XCI-skew captures changes to the haematopoietic stem cell population and has clinical potential as a unique biomarker of chronic disease risk.

    Funding:

    KSS acknowledges funding from the Medical Research Council [MR/M004422/1 and MR/R023131/1]. JTB acknowledges funding from the ESRC [ES/N000404/1]. MM acknowledges funding from the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. TwinsUK is funded by the Wellcome Trust, Medical Research Council, European Union, Chronic Disease Research Foundation (CDRF), Zoe Global Ltd and the National Institute for Health Research (NIHR)-funded BioResource, Clinical Research Facility and Biomedical Research Centre based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London.

    1. Epidemiology and Global Health
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