Adaptive responses to SARS-CoV-2 infection linked to accelerated aging measures predict adverse outcomes in patients with severe COVID-19

INTRODUCTION: Chronological age (CA) is a predictor of adverse COVID-19 outcomes; however, CA alone has not shown to be the better predictor of adverse outcomes in COVID-19 as it does not capture individual responses to SARS-CoV-2 infection. Here, we evaluated the influence of aging metrics PhenoAge and PhenoAccelAge on the adaptive responses to SARS-CoV-2 infection in hospitalized patients. METHODS: We assessed cases admitted to a COVID-19 reference center in Mexico City. PhenoAge and PhenoAccelAge 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), and k-means clustering was performed to explore reproducible patterns of adaptive response to SARS-CoV-2 infection using PhenoAge components. RESULTS: We included 1069 subjects of whom 401 presented critical illness and 204 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 PhenoAccelAge >0 had higher risk of death and critical illness compared to those who had values according to CA (log-rank p<0.001). Using unsupervised clustering we identified four adaptive responses to SARS-CoV-2 infection: 1) Inflammaging associated with CA, 2) adaptive metabolic dysfunction associated with cardio-metabolic comorbidities, 3) adaptive 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.