A. Márquez-Salinas, C. A. Fermín-Martínez, N. Antonio-Villa, A. Vargas-Vázquez, E. C. Guerra, A. Campos-Muñoz, L. Zavala-Romero, R. Mehta, J. Bahena-López, E. Ortiz-Brizuela, M. Gonzalez-Lara, C. M. Román-Montes, B. Martínez-Guerra, A. Ponce de León, J. Sifuentes-Osornio, L. Gutiérrez-Robledo, C. Aguilar-Salinas, Omar Yaxmehen Bello-Chavolla
The journals of gerontology. Series A, Biological sciences and medical sciences, 2021
Abstract Background Chronological age (CA) is a predictor of adverse COVID-19 outcomes; however, CA alone does not capture individual responses to SARS-CoV-2 infection. Here, we evaluated the influence of aging metrics PhenoAge and PhenoAgeAccel to predict adverse COVID-19 outcomes. Furthermore, we sought to model adaptive metabolic and inflammatory responses to severe SARS-CoV-2 infection using individual PhenoAge components. Methods In this retrospective cohort study, we assessed cases admitted to a COVID-19 reference center in Mexico City. PhenoAge and PhenoAgeAccel were estimated using laboratory values at admission. Cox proportional hazards models were fitted to estimate risk for COVID-19 lethality and adverse outcomes (ICU admission, intubation, or death). To explore reproducible patterns which model adaptive responses to SARS-CoV-2 infection, we used k-means clustering using PhenoAge components. Results We included 1068 subjects of whom 222 presented critical illness and 218 died. PhenoAge was a better predictor of adverse outcomes and lethality compared to CA and SpO2 and its predictive capacity was sustained for all age groups. Patients with responses associated to PhenoAgeAccel>0 had higher risk of death and critical illness compared to those with lower values (log-rank p<0.001). Using unsupervised clustering we identified four adaptive responses to SARS-CoV-2 infection: 1) Inflammaging associated with CA, 2) metabolic dysfunction associated with cardio-metabolic comorbidities, 3) unfavorable hematological response, and 4) response associated with favorable outcomes. Conclusions Adaptive responses related to accelerated aging metrics are linked to adverse COVID-19 outcomes and have unique and distinguishable features. PhenoAge is a better predictor of adverse outcomes compared to CA.
Cited by 3 publications.
Field of study: Medicine