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A blood microRNA classifier for the prediction of ICU mortality in COVID-19 patients: a multicenter validation study
David de Gonzalo-Calvo1,2, Marta Molinero1,2, Iván D Benítez1,2
1Translational Research in Respiratory Medicine, University Hospital Arnau de Vilanova and Santa Maria, IRBLleida, Lleida, Spain.
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.
Insights
Identifying high-risk COVID-19 patients is crucial. A novel blood microRNA (miRNA) classifier accurately predicts fatal outcomes in critically ill patients, improving early risk assessment.
Area of Science:
- Biomarkers
- Critical Care Medicine
- Molecular Diagnostics
Background:
- Accurate identification of critically ill COVID-19 patients at risk of fatal outcomes remains a significant clinical challenge.
- MicroRNAs (miRNAs) are explored as potential biomarkers for predicting patient prognosis.
- This study aimed to validate candidate miRNAs and develop a predictive classifier for intensive care unit (ICU) mortality.
Purpose of the Study:
- To validate specific microRNAs (miRNAs) as biomarkers for clinical decision-making in critically ill patients.
- To construct and validate a blood-based miRNA classifier for the early prediction of adverse outcomes in the ICU.
Main Methods:
- A multicenter, observational study included 503 critically ill patients admitted to the ICU.
- Quantitative PCR (qPCR) assays were performed on plasma samples collected within 48 hours of admission.
- A 16-miRNA panel was used, and a 4-miRNA signature was developed using LASSO regression.
Main Results:
- Nine miRNAs were validated as biomarkers for all-cause in-ICU mortality.
- A 4-miRNA signature (miR-16-5p, miR-192-5p, miR-323a-3p, miR-451a) predicted the risk of all-cause in-ICU mortality (HR 2.5).
- The miRNA signature significantly improved the prognostic capacity of conventional scores (APACHE-II, SOFA) and clinical risk models.
Conclusions:
- A blood miRNA classifier demonstrates improved early prediction of fatal outcomes in critically ill COVID-19 patients.
- This classifier enhances the prognostic value of existing clinical scoring systems.
- Functional analysis suggests involvement of inflammatory and fibrotic pathways in mortality.
