Biological Aging Predicts Vulnerability to COVID-19 Severity in UK Biobank Participants

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  • Chia-Ling Kuo
    Connecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health, Farmington, USA
  • Luke C Pilling
    University of Connecticut Center on Aging, School of Medicine, Farmington, USA
  • Janice L Atkins
    College of Medicine and Health, University of Exeter, UK
  • Jane A H Masoli
    College of Medicine and Health, University of Exeter, UK
  • João Delgado
    College of Medicine and Health, University of Exeter, UK
  • Christopher Tignanelli
    Department of Surgery, University of Minnesota, Minneapolis, USA
  • George A Kuchel
    University of Connecticut Center on Aging, School of Medicine, Farmington, USA
  • David Melzer
    University of Connecticut Center on Aging, School of Medicine, Farmington, USA
  • Kenneth B Beckman
    Institute for Health Informatics, University of Minnesota, Minneapolis, USA
  • Morgan E Levine
    Department of Pathology, Yale School of Medicine, New Haven, Connecticut, USA
  • Anne B Newman
    editor

説明

<jats:title>Abstract</jats:title> <jats:sec> <jats:title>Background</jats:title> <jats:p>Age and disease prevalence are the 2 biggest risk factors for Coronavirus disease 2019 (COVID-19) symptom severity and death. We therefore hypothesized that increased biological age, beyond chronological age, may be driving disease-related trends in COVID-19 severity.</jats:p> </jats:sec> <jats:sec> <jats:title>Methods</jats:title> <jats:p>Using the UK Biobank England data, we tested whether a biological age estimate (PhenoAge) measured more than a decade prior to the COVID-19 pandemic was predictive of 2 COVID-19 severity outcomes (inpatient test positivity and COVID-19-related mortality with inpatient test-confirmed COVID-19). Logistic regression models were used with adjustment for age at the pandemic, sex, ethnicity, baseline assessment centers, and preexisting diseases/conditions.</jats:p> </jats:sec> <jats:sec> <jats:title>Results</jats:title> <jats:p>Six hundred and thirteen participants tested positive at inpatient settings between March 16 and April 27, 2020, 154 of whom succumbed to COVID-19. PhenoAge was associated with increased risks of inpatient test positivity and COVID-19-related mortality (ORMortality = 1.63 per 5 years, 95% CI: 1.43–1.86, p = 4.7 × 10−13) adjusting for demographics including age at the pandemic. Further adjustment for preexisting diseases/conditions at baseline (ORM = 1.50, 95% CI: 1.30–1.73 per 5 years, p = 3.1 × 10−8) and at the early pandemic (ORM = 1.21, 95% CI: 1.04–1.40 per 5 years, p = .011) decreased the association.</jats:p> </jats:sec> <jats:sec> <jats:title>Conclusions</jats:title> <jats:p>PhenoAge measured in 2006–2010 was associated with COVID-19 severity outcomes more than 10 years later. These associations were partly accounted for by prevalent chronic diseases proximate to COVID-19 infection. Overall, our results suggest that aging biomarkers, like PhenoAge may capture long-term vulnerability to diseases like COVID-19, even before the accumulation of age-related comorbid conditions.</jats:p> </jats:sec>

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