Respiratory Research (Jun 2023)

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

  • David de Gonzalo-Calvo,
  • Marta Molinero,
  • Iván D. Benítez,
  • Manel Perez-Pons,
  • Nadia García-Mateo,
  • Alicia Ortega,
  • Tamara Postigo,
  • María C. García-Hidalgo,
  • Thalia Belmonte,
  • Carlos Rodríguez-Muñoz,
  • Jessica González,
  • Gerard Torres,
  • Clara Gort-Paniello,
  • Anna Moncusí-Moix,
  • Ángel Estella,
  • Luis Tamayo Lomas,
  • Amalia Martínez de la Gándara,
  • Lorenzo Socias,
  • Yhivian Peñasco,
  • Maria Del Carmen de la Torre,
  • Elena Bustamante-Munguira,
  • Elena Gallego Curto,
  • Ignacio Martínez Varela,
  • María Cruz Martin Delgado,
  • Pablo Vidal-Cortés,
  • Juan López Messa,
  • Felipe Pérez-García,
  • Jesús Caballero,
  • José M. Añón,
  • Ana Loza-Vázquez,
  • Nieves Carbonell,
  • Judith Marin-Corral,
  • Ruth Noemí Jorge García,
  • Carmen Barberà,
  • Adrián Ceccato,
  • Laia Fernández-Barat,
  • Ricard Ferrer,
  • Dario Garcia-Gasulla,
  • Jose Ángel Lorente-Balanza,
  • Rosario Menéndez,
  • Ana Motos,
  • Oscar Peñuelas,
  • Jordi Riera,
  • Jesús F. Bermejo-Martin,
  • Antoni Torres,
  • Ferran Barbé

DOI
https://doi.org/10.1186/s12931-023-02462-x
Journal volume & issue
Vol. 24, no. 1
pp. 1 – 11

Abstract

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Abstract 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.

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