Circulating microRNA profiles predict the severity of COVID-19 in hospitalized patients

We aimed to examine the circulating microRNA (miRNA) profile of hospitalized COVID-19 patients and evaluate its potential as a source of biomarkers for the management of the disease. This was an observational and multicenter study that included 84 patients with a positive nasopharyngeal swab Polymerase chain reaction (PCR) test for SARS-CoV-2 recruited during the first pandemic wave in Spain (March-June 2020). Patients were stratified according to disease severity: hospitalized patients admitted to the clinical wards without requiring critical care and patients admitted to the intensive care unit (ICU). An additional study was completed including ICU nonsurvivors and survivors. Plasma miRNA profiling was performed using reverse transcription polymerase quantitative chain reaction (RT-qPCR). Predictive models were constructed using least absolute shrinkage and selection operator (LASSO) regression. Ten circulating miRNAs were dysregulated in ICU patients compared to ward patients. LASSO analysis identified a signature of three miRNAs (miR-148a-3p, miR-451a and miR-486-5p) that distinguishes between ICU and ward patients [AUC (95% CI) = 0.89 (0.81-0.97)]. Among critically ill patients, six miRNAs were downregulated between nonsurvivors and survivors. A signature based on two miRNAs (miR-192-5p and miR-323a-3p) differentiated ICU nonsurvivors from survivors [AUC (95% CI) = 0.80 (0.64–0.96)]. The discriminatory potential of the signature was higher than that observed for laboratory parameters such as leukocyte counts, C-reactive protein (CRP) or D-dimer [maximum AUC (95% CI) for these variables = 0.73 (0.55–0.92)]. miRNA levels were correlated with the duration of ICU stay. Specific circulating miRNA profiles are associated with the severity of COVID-19. Plasma miRNA signatures emerge as a novel tool to assist in the early prediction of vital status deterioration among ICU patients. Supported by ISCIII (CIBERESUCICOVID, COV20/00110), co-funded by ERDF, “Una manera de hacer Europa”. DdGC acknowledges receiving financial support from Instituto de Salud Carlos III (ISCIII), Miguel Servet 2020 (CP20/00041), co-funded by the European Social Fund (ESF), “Investing in your future”. LP is the recipient of a predoctoral fellowship from the Ministry of Universities of Spain (FPU19/03526). This work partially supported by IRBLleida Biobank (B.0000682) and “Plataforma Biobancos PT17/0015/0027/”. Peer Reviewed "Article signat per 33 autors/es: David de Gonzalo-Calvo, Iván D. Benítez, Lucía Pinilla, Amara Carratalá, Anna Moncusí-Moix, Clara Gort-Paniello, Marta Molinero, Jessica González, Gerard Torres, María Bernal, Silvia Pico, Raquel Almansa, Noelia Jorge, Alicia Ortega, Elena Bustamante-Munguira, José Manuel Gómez, Milagros González-Rivera, Dariela Micheloud, Pablo Ryan, Amalia Martinez, Luis Tamayo, César Aldecoa, Ricard Ferrer, Adrián Ceccato, Laia Fernández-Barat, Ana Motos, Jordi Riera, Rosario Menéndez, Dario Garcia-Gasulla, Oscar Peñuelas, Antoni Torres, Jesús F. Bermejo-Martin, Ferran Barbé on behalf of the Ciberesucicovid Project (Cov20/00110, Isciii)"