A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study

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...

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Autores: de Gonzalo Calvo, David, Molinero, Marta, Benítez, Iván, Perez-Pons, Manel, García Mateo, Nadia, Ortega, Alicia, Postigo, Tamara, García Hidalgo, María Coronada, Belmonte, Thalía, Rodríguez Muñoz, Carlos, González, Jessica, Torres, Gerard, Gort Paniello, Clara, Moncusí Moix, Anna, Estella, Ángel, Tamayo Lomas, Luis, Martínez de la Gándara, Amalia, Socias, Lorenzo, Peñasco, Yhivian, de la Torre, Maria del Carmen, Bustamante Munguira, Elena, Gallego, Elena, Martínez Varela, Ignacio, Martin Delgado, María Cruz, Vidal Cortés, Pablo, López Messa, Juan, Pérez García, Felipe, Caballero, Jesús, Añón, José M., Loza Vázquez, Ana, Carbonell, Nieves, Marin Corral, Judith, Jorge García, Ruth Noemí, Barberà, Carme, Ceccato, Adrián, Fernández Barat, Laia, Ferrer, Ricard, García Gasulla, Darío, Lorente-Balanza, Jose Ángel, Menéndez, Rosario, Motos, Anna, Peñuelas, Oscar, Riera, Jordi, Bermejo Martin, Jesús F., Torres, Antoni, Barbé Illa, Ferran
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2023
País:España
Institución:Universitat de Lleida (UdL)
Repositorio:Repositori Obert UdL
OAI Identifier:oai:repositori.udl.cat:10459.1/464293
Acceso en línea:https://doi.org/10.1186/s12931-023-02462-x
https://hdl.handle.net/10459.1/464293
Access Level:acceso abierto
Palabra clave:Biomarker
COVID-19
ICU
microRNA
Prognosis
SARS-CoV-2
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spelling A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation studyde Gonzalo Calvo, DavidMolinero, MartaBenítez, IvánPerez-Pons, ManelGarcía Mateo, NadiaOrtega, AliciaPostigo, TamaraGarcía Hidalgo, María CoronadaBelmonte, ThalíaRodríguez Muñoz, CarlosGonzález, JessicaTorres, GerardGort Paniello, ClaraMoncusí Moix, AnnaEstella, ÁngelTamayo Lomas, LuisMartínez de la Gándara, AmaliaSocias, LorenzoPeñasco, Yhiviande la Torre, Maria del CarmenBustamante Munguira, ElenaGallego, ElenaMartínez Varela, IgnacioMartin Delgado, María CruzVidal Cortés, PabloLópez Messa, JuanPérez García, FelipeCaballero, JesúsAñón, José M.Loza Vázquez, AnaCarbonell, NievesMarin Corral, JudithJorge García, Ruth NoemíBarberà, CarmeCeccato, AdriánFernández Barat, LaiaFerrer, RicardGarcía Gasulla, DaríoLorente-Balanza, Jose ÁngelMenéndez, RosarioMotos, AnnaPeñuelas, OscarRiera, JordiBermejo Martin, Jesús F.Torres, AntoniBarbé Illa, FerranBiomarkerCOVID-19ICUmicroRNAPrognosisSARS-CoV-2Background: 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.BMJ2023info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttps://doi.org/10.1186/s12931-023-02462-xhttps://hdl.handle.net/10459.1/464293reponame:Repositori Obert UdL instname:Universitat de Lleida (UdL)InglésReproducció del document publicat a: https://doi.org/10.1186/s12931-023-02462-xRespiratory Research, 2023, vol. 24, núm. 159cc-by (c)The authors, 2023Attribution 4.0 Internationalinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/oai:repositori.udl.cat:10459.1/4642932026-06-24T12:42:17Z
dc.title.none.fl_str_mv A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
title A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
spellingShingle A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
de Gonzalo Calvo, David
Biomarker
COVID-19
ICU
microRNA
Prognosis
SARS-CoV-2
title_short A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
title_full A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
title_fullStr A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
title_full_unstemmed A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
title_sort A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
dc.creator.none.fl_str_mv de Gonzalo Calvo, David
Molinero, Marta
Benítez, Iván
Perez-Pons, Manel
García Mateo, Nadia
Ortega, Alicia
Postigo, Tamara
García Hidalgo, María Coronada
Belmonte, Thalía
Rodríguez Muñoz, Carlos
González, Jessica
Torres, Gerard
Gort Paniello, Clara
Moncusí Moix, Anna
Estella, Ángel
Tamayo Lomas, Luis
Martínez de la Gándara, Amalia
Socias, Lorenzo
Peñasco, Yhivian
de la Torre, Maria del Carmen
Bustamante Munguira, Elena
Gallego, Elena
Martínez Varela, Ignacio
Martin Delgado, María Cruz
Vidal Cortés, Pablo
López Messa, Juan
Pérez García, Felipe
Caballero, Jesús
Añón, José M.
Loza Vázquez, Ana
Carbonell, Nieves
Marin Corral, Judith
Jorge García, Ruth Noemí
Barberà, Carme
Ceccato, Adrián
Fernández Barat, Laia
Ferrer, Ricard
García Gasulla, Darío
Lorente-Balanza, Jose Ángel
Menéndez, Rosario
Motos, Anna
Peñuelas, Oscar
Riera, Jordi
Bermejo Martin, Jesús F.
Torres, Antoni
Barbé Illa, Ferran
author de Gonzalo Calvo, David
author_facet de Gonzalo Calvo, David
Molinero, Marta
Benítez, Iván
Perez-Pons, Manel
García Mateo, Nadia
Ortega, Alicia
Postigo, Tamara
García Hidalgo, María Coronada
Belmonte, Thalía
Rodríguez Muñoz, Carlos
González, Jessica
Torres, Gerard
Gort Paniello, Clara
Moncusí Moix, Anna
Estella, Ángel
Tamayo Lomas, Luis
Martínez de la Gándara, Amalia
Socias, Lorenzo
Peñasco, Yhivian
de la Torre, Maria del Carmen
Bustamante Munguira, Elena
Gallego, Elena
Martínez Varela, Ignacio
Martin Delgado, María Cruz
Vidal Cortés, Pablo
López Messa, Juan
Pérez García, Felipe
Caballero, Jesús
Añón, José M.
Loza Vázquez, Ana
Carbonell, Nieves
Marin Corral, Judith
Jorge García, Ruth Noemí
Barberà, Carme
Ceccato, Adrián
Fernández Barat, Laia
Ferrer, Ricard
García Gasulla, Darío
Lorente-Balanza, Jose Ángel
Menéndez, Rosario
Motos, Anna
Peñuelas, Oscar
Riera, Jordi
Bermejo Martin, Jesús F.
Torres, Antoni
Barbé Illa, Ferran
author_role author
author2 Molinero, Marta
Benítez, Iván
Perez-Pons, Manel
García Mateo, Nadia
Ortega, Alicia
Postigo, Tamara
García Hidalgo, María Coronada
Belmonte, Thalía
Rodríguez Muñoz, Carlos
González, Jessica
Torres, Gerard
Gort Paniello, Clara
Moncusí Moix, Anna
Estella, Ángel
Tamayo Lomas, Luis
Martínez de la Gándara, Amalia
Socias, Lorenzo
Peñasco, Yhivian
de la Torre, Maria del Carmen
Bustamante Munguira, Elena
Gallego, Elena
Martínez Varela, Ignacio
Martin Delgado, María Cruz
Vidal Cortés, Pablo
López Messa, Juan
Pérez García, Felipe
Caballero, Jesús
Añón, José M.
Loza Vázquez, Ana
Carbonell, Nieves
Marin Corral, Judith
Jorge García, Ruth Noemí
Barberà, Carme
Ceccato, Adrián
Fernández Barat, Laia
Ferrer, Ricard
García Gasulla, Darío
Lorente-Balanza, Jose Ángel
Menéndez, Rosario
Motos, Anna
Peñuelas, Oscar
Riera, Jordi
Bermejo Martin, Jesús F.
Torres, Antoni
Barbé Illa, Ferran
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
author
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author
author
author
author
author
author
author
author
dc.subject.none.fl_str_mv Biomarker
COVID-19
ICU
microRNA
Prognosis
SARS-CoV-2
topic Biomarker
COVID-19
ICU
microRNA
Prognosis
SARS-CoV-2
description 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.
publishDate 2023
dc.date.none.fl_str_mv 2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv https://doi.org/10.1186/s12931-023-02462-x
https://hdl.handle.net/10459.1/464293
url https://doi.org/10.1186/s12931-023-02462-x
https://hdl.handle.net/10459.1/464293
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Reproducció del document publicat a: https://doi.org/10.1186/s12931-023-02462-x
Respiratory Research, 2023, vol. 24, núm. 159
dc.rights.none.fl_str_mv cc-by (c)The authors, 2023
Attribution 4.0 International
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/
rights_invalid_str_mv cc-by (c)The authors, 2023
Attribution 4.0 International
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv BMJ
publisher.none.fl_str_mv BMJ
dc.source.none.fl_str_mv reponame:Repositori Obert UdL
instname:Universitat de Lleida (UdL)
instname_str Universitat de Lleida (UdL)
reponame_str Repositori Obert UdL
collection Repositori Obert UdL
repository.name.fl_str_mv
repository.mail.fl_str_mv
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