학술논문
A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
intensive care units
intensive care units
Document Type
Report
Author
de Gonzalo-Calvo, David; Molinero, Marta; Benítez, Iván D.; Perez-Pons, Manel; García-Mateo, Nadia; Ortega, Alicia; Postigo, Tamara; García-Hidalgo, María C.; Belmonte, Thalia; Rodríguez-Muéoz, Carlos; González, Jessica; Torres, Gerard; Gort-Paniello, Clara; Moncusí-Moix, Anna; Estella, Ãngel; Tamayo Lomas, Luis; Martínez de la Gándara, Amalia; Socias, Lorenzo; Peéasco, Yhivian; de la Torre, Maria Del Carmen; Bustamante-Munguira, Elena; Gallego Curto, Elena; Martínez Varela, Ignacio; Martin Delgado, María Cruz; Vidal-Cortés, Pablo; López Messa, Juan; Pérez-García, Felipe; Caballero, Jesús; Aéón, José M.; Loza-Vázquez, Ana; Carbonell, Nieves; Marin-Corral, Judith; Jorge García, Ruth Noemí; Barberà, Carmen; Ceccato, Adrián; Fernández-Barat, Laia; Ferrer, Ricard; Garcia-Gasulla, Dario; Lorente-Balanza, Jose Ãngel; Menéndez, Rosario; Motos, Ana; Peéuelas, Oscar; Riera, Jordi; Bermejo-Martin, Jesús F.; Torres, Antoni; Barbé, Ferran
Source
Respiratory Research. June 17, 2023, Vol. 24 Issue 1
Subject
Language
English
ISSN
1465-9921
Abstract
Author(s): David de Gonzalo-Calvo[sup.1,2] , Marta Molinero[sup.1,2] , Iván D. Benítez[sup.1,2] , Manel Perez-Pons[sup.1,2] , Nadia García-Mateo[sup.3] , Alicia Ortega[sup.2,3] , Tamara Postigo[sup.2,3] , María C. García-Hidalgo[sup.1,2] , Thalia Belmonte[sup.1,2] [...]
Background The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. Methods This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. Results Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan-Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. Conclusions A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients. Keywords: Biomarker, COVID-19, ICU, microRNA, Prognosis, SARS-CoV-2
Background The identification of critically ill COVID-19 patients at risk of fatal outcomes remains a challenge. Here, we first validated candidate microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients. Second, we constructed a blood miRNA classifier for the early prediction of adverse outcomes in the ICU. Methods This was a multicenter, observational and retrospective/prospective study including 503 critically ill patients admitted to the ICU from 19 hospitals. qPCR assays were performed in plasma samples collected within the first 48 h upon admission. A 16-miRNA panel was designed based on recently published data from our group. Results Nine miRNAs were validated as biomarkers of all-cause in-ICU mortality in the independent cohort of critically ill patients (FDR < 0.05). Cox regression analysis revealed that low expression levels of eight miRNAs were associated with a higher risk of death (HR from 1.56 to 2.61). LASSO regression for variable selection was used to construct a miRNA classifier. A 4-blood miRNA signature composed of miR-16-5p, miR-192-5p, miR-323a-3p and miR-451a predicts the risk of all-cause in-ICU mortality (HR 2.5). Kaplan-Meier analysis confirmed these findings. The miRNA signature provides a significant increase in the prognostic capacity of conventional scores, APACHE-II (C-index 0.71, DeLong test p-value 0.055) and SOFA (C-index 0.67, DeLong test p-value 0.001), and a risk model based on clinical predictors (C-index 0.74, DeLong test-p-value 0.035). For 28-day and 90-day mortality, the classifier also improved the prognostic value of APACHE-II, SOFA and the clinical model. The association between the classifier and mortality persisted even after multivariable adjustment. The functional analysis reported biological pathways involved in SARS-CoV infection and inflammatory, fibrotic and transcriptional pathways. Conclusions A blood miRNA classifier improves the early prediction of fatal outcomes in critically ill COVID-19 patients. Keywords: Biomarker, COVID-19, ICU, microRNA, Prognosis, SARS-CoV-2