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Biological Aging Predicts Vulnerability to COVID-19 Severity in UK Biobank Participants
Chia Ling Kuo
, Luke C. Pilling
, Janice L. Atkins
, Jane A.H. Masoli
, João Delgado
,
Christopher Tignanelli
, George A. Kuchel
, David Melzer
,
Kenneth B. Beckman
, Morgan E. Levine
Surgery
Genomics Center
Genetics Mechanisms of Cancer
Research output
:
Contribution to journal
›
Article
›
peer-review
40
Scopus citations
Overview
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Keyphrases
Age Estimation
9%
Age-related
9%
Aging Biomarkers
9%
Assessment Center
9%
Biobank Participants
100%
Biological Age
18%
Biological Aging
100%
Chronic Disease
9%
Chronological Age
9%
Comorbid Conditions
9%
COVID-19
100%
COVID-19 Pandemic
9%
Disease Conditions
18%
Disease Prevalence
9%
Disease-related
9%
Inpatient Setting
9%
Logistic Regression Model
9%
PhenoAge
36%
Pre-existing Conditions
18%
Risk Factors
9%
Symptom Severity
9%
Test Positivity
18%
UK Biobank
100%
Vulnerability
100%
Vulnerability to Disease
9%
Psychology
Chronic Disorder
8%
COVID-19
100%
Pandemic
8%
Regression Model
8%
UK Biobank
100%