COVID-19 severity is predicted by earlier evidence of accelerated aging

  1. Chia-Ling Kuo
  2. Luke C. Pilling
  3. Janice L Atkins
  4. Jane AH Masoli
  5. João Delgado
  6. Christopher Tignanelli
  7. George A Kuchel
  8. David Melzer
  9. Kenneth B Beckman
  10. Morgan E. Levine

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

With no known treatments or vaccine, COVID-19 presents a major threat, particularly to older adults, who account for the majority of severe illness and deaths. The age-related susceptibility is partly explained by increased comorbidities including dementia and type II diabetes [1]. While it is unclear why these diseases predispose risk, we hypothesize that increased biological age, rather than chronological age, may be driving disease-related trends in COVID-19 severity with age. To test this hypothesis, we applied our previously validated biological age measure (PhenoAge) [2] composed of chronological age and nine clinical chemistry biomarkers to data of 347,751 participants from a large community cohort in the United Kingdom (UK Biobank), recruited between 2006 and 2010. Other data included disease diagnoses (to 2017), mortality data (to 2020), and the UK national COVID-19 test results (to May 31, 2020) [3]. Accelerated aging 10-14 years prior to the start of the COVID-19 pandemic was associated with test positivity (OR=1.15 per 5-year acceleration, 95% CI: 1.08 to 1.21, p=3.2×10 −6 ) and all-cause mortality with test-confirmed COVID-19 (OR=1.25, per 5-year acceleration, 95% CI: 1.09 to 1.44, p=0.002) after adjustment for demographics including current chronological age and pre-existing diseases or conditions. The corresponding areas under the curves were 0.669 and 0.803, respectively. Biological aging, as captured by PhenoAge, is a better predictor of COVID-19 severity than chronological age, and may inform risk stratification initiatives, while also elucidating possible underlying mechanisms, particularly those related to inflammaging.

Article activity feed

  1. ScreenIT

    SciScore for 10.1101/2020.07.10.20147777: (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

    No key resources detected.

    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: We detected the following sentences addressing limitations in the study:
    There are limitations to this study, which warrant acknowledgement. First, the disease status was determined based on self-reported doctor diagnoses at baseline and hospital admission records to 2017 (3 years before the pandemic), without use of the primary care data (to 2017, for nearly half of the UKB participants). Second, we did not include cancers in the analysis as the status of cancer (e.g., progressing vs. remission) is not available, which is strongly associated with mortality related to COVID-19 [27]. Additionally, some participants are not old enough to develop late-onset diseases. As disease cases may be misclassified as non-disease cases, the disease odds ratio estimates were likely to be biased towards the null [28]. Also, clinical severity data is not available, but we used the mortality data to derive the severity outcome, all-cause mortality with test-confirmed COVID-19. While the mortality data is incomplete (censored at March 31, 2020, with additional mortality data from April, 2020), we excluded those who were tested positive and survived so the impact on the results of all-cause mortality should be minimal. Lastly, the UKB sample is known to be healthier than the general population [29]; however, risk factor associations are usually generalizable [30]. In conclusion, accelerated aging measured by PhenoAge was associated with both COVID-19 severity outcomes, with adjustment for demographics including current chronological age, and disease comorbidities. Ac...

    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: We did not find any issues relating to colormaps.

    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.
    • Thank you for including a protocol registration statement.

    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.

  2. ScreenIT

    SciScore for 10.1101/2020.07.10.20147777: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementUK Biobank received an approval from the UK Biobank Research Ethics Committee (REC;Randomizationnot detected.Blindingnot detected.Power Analysisnot detected.Sex as a biological variableMen were more likely to test positive for COVID-19 and die with test-confirmed COVID-19 than women.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    When considering PhenoAgeAccel, the odds ratio per 5-year increase in PhenoAgeAccel was 1.30 (95% CI: 1.24 to 1.38, p=1.78´10-22) for test positivity and 1.55 (95% CI: 1.36 to 1.76, p=3.04´1011 ) for all-cause mortality in M2.
    PhenoAgeAccel
    suggested: None

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:

    • There are limitations to this study, which warrant acknowledgement.
    • First, the disease status was determined based on self-reported doctor diagnoses at baseline and hospital admission records to 2017 (3 years before the pandemic), without use of the primary care data (to 2017, for nearly half of the UKB participants).
    • Second, we did not include cancers in the analysis as the status of cancer (e.g., progressing vs. remission) is not available, which is strongly associated with mortality related to COVID-19

    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).

    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 is not a substitute for expert review. SciScore checks for the presence and correctness of RRIDs (research resource identifiers) in the manuscript, and detects sentences that appear to be missing RRIDs. SciScore also checks to make sure that rigor criteria are addressed by authors. It does this by detecting sentences that discuss criteria such as blinding or power analysis. SciScore does not guarantee that the rigor criteria that it detects are appropriate for the particular study. Instead it assists authors, editors, and reviewers by drawing attention to sections of the manuscript that contain or should contain various rigor criteria and key resources. For details on the results shown here, including references cited, please follow this link.

  3. Version published to 10.1101/2020.07.10.20147777v1 on medRxiv