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COVID-19 severity is predicted by earlier evidence of accelerated aging
[Unspecified Source]; 2020.
Non-conventional in English | [Unspecified Source] | ID: grc-750517
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. 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) 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). 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=3.2x10-6) 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.

Full text: Available Collection: Databases of international organizations Database: [Unspecified Source] Type of study: Cohort study / Observational study / Prognostic study Topics: Vaccines Language: English Year: 2020 Document Type: Non-conventional

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Full text: Available Collection: Databases of international organizations Database: [Unspecified Source] Type of study: Cohort study / Observational study / Prognostic study Topics: Vaccines Language: English Year: 2020 Document Type: Non-conventional