Key factors of the deranged antiviral response in elderly patients with COVID-19: a machine-learning analysis
Year: 2026
Type: article
Study design: Observational Study
Abstract: Age is a well-known risk factor to develop severe viral respiratory infections, including severe COVID-19. This study aimed to identify the biological alterations linked to severe disease in elderly patients with COVID-19. For this purpose, we employed a derivation cohort with 450 SARS-CoV-2 infected and unvaccinated patients admitted to hospital wards and a validation cohort with 244 SARS-CoV-2 infected and unvaccinated patients admitted to hospital Intensive Care Unit (ICU). Twenty-one biomarkers were measured in plasma samples from patients upon admission, including SARS-CoV-2 RNA, IgG antibodies, and protein biomarkers. Patient cohorts were divided into two groups based on age: adult (≤ 70 years old) and elderly (> 70 years old) patients. In the derivation cohort, 90-day mortality rate observed in the adult group was 6.0% whereas in the elderly group it rises to 31.6%, same trend was noticed regarding the validation cohort, with 11.2% versus 40.3% 90-day mortality rates for adult and elderly groups, respectively. The machine-learning framework XGBoost-SHAP, fed with the plasma biomarkers information, was used to profile an age-related host response to SARS-CoV-2 infection. Based on SHAP plot, elderly patients had a strong thrombo-inflammatory response profile (significantly elevated plasma levels of: lipocalin-2, endothelin-1, D-dimer) combined with deficient adaptive and cytotoxic antiviral responses. Model performance evaluated with the validation cohort confirmed the robustness and generalizability of the model developed (AUC = 0.710). In conclusion, the machine learning approach we built allowed us to identify the presence of a deranged host response in elderly patients with COVID-19 linked to poor viral control and increased mortality.
Source: GeroScience
Authors: Tamara Postigo-Casado, Alicia Ortega, Alejandro Álvaro-Meca, Daniel Vélez-Serrano, Nadia García-Mateo, Ana P. Tedim, Raquel Almansa, Jose María Eiros, David de Gonzalo-Calvo, Anna Moncusí-Moix, Clara Gort-Paniello, Manel Perez-Pons, Marta Molinero, Marta Dominguez-Gil, Amanda de la Fuente, Laura González-González, Tania Luis-García, Fátima Rodríguez-Jara, Noelia Jorge, Jessica González, Gerard Torres, Oliver Norberto Gutiérrez-Pérez, María José Villegas, Sonia Campo, Eva Ayllón, Tomás Ruiz Albi, Julio de Frutos Arribas, Ainhoa Arroyo Domingo, Jessica Abadia-Otero, Julia Gómez Barquero, Wysali Trapiello, Luis Javier García Frade, Luis Inglada, Félix del Campo, Ferrán Barbé, Antoni Torres, Raúl López-Izquierdo, Jesús F. Bermejo-Martin, CIBERES-U. C. I.-COVID group, Luis Jorge Valdivia, Juan López Messa, Pablo Vidal-Cortés, Nieves Carbonell, Elena Bustamante-Munguira, María del Carmen De la Torre, Caridad Martín López, Milagros González Rivera, Ruth Noemí Jorge García, Alejandro Úbeda Iglesias, Elena Gallego Curto, Lorenzo Socias, Jesús Caballero, Ángel Estella, Víctor Sagredo Meneses, María Cruz Martín Delgado, Amalia Martínez de la Gándara, Emilio Maseda, Ignacio Martínez Varela, Sandra Campos-Fernández, Felipe Pérez-García, Luis Tamayo, Ana Loza Vázquez, Salvador Resino, Isidoro Martínez, Anna Motos, Laia Fernández-Barat, Adrián Ceccato
Institutions: Instituto de Investigación Biomédica de Salamanca, Gerencia Regional de Salud de Castilla y León (Sacyl), Instituto de Salud Carlos III, Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Centro de Investigación Biomédica en Red, Universidad Rey Juan Carlos, Centro de Investigación Biomédica en Red Enfermedades Infecciosas, Universidad Complutense de Madrid, Universidad de Valladolid, Hospital Universitario Río Hortega, Hospital Universitari Arnau de Vilanova, Hospital Clínico Universitario de Valladolid, Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine, Institució Catalana de Recerca i Estudis Avançats, Hospital Clínic de Barcelona, Consorci Institut D'Investigacions Biomediques August Pi I Sunyer, Universitat de Barcelona, Universidad de Salamanca
Language: English
Subfield: Infectious Diseases
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
Estimated APC paid: $2,890
OpenAlex ID: W7155219402