PB0138 - COVID-19 induces miRNA changes-ACE-2 related network: in silico, machine learning and validation analysis

Sunday, June 25, 2023

18:30 – 19:30 ET

Room: Exhibition

Co-Author(s)

Zofia Wicik, PhD

Senior Researcher
Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, Center for Preclinical Research and Technology CEPT, 02-091 Warsaw, Poland
Warsaw, Mazowieckie, Poland

Presenting Author(s)

Ceren Eyileten, DVM, PhD, MSc (she/her/hers)

Senior Researcher
Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, Center for Preclinical Research and Technology CEPT, 02-091 Warsaw, Poland
Warsaw, Mazowieckie, Poland

Co-Author(s)

AN

Anna Nowak

PhD Candidate
Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, Center for Preclinical Research and Technology CEPT, 02-091 Warsaw, Poland; Doctoral School, Medical University of Warsaw, 02-091, Warsaw, Poland
Warsaw, Mazowieckie, Poland
DK

Disha Keshwani

Student
1. Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, Center for Preclinical Research and Technology CEPT, 02-091 Warsaw, Poland
Warsaw, Mazowieckie, Poland
MM

Mikołaj Marszałek

Student
Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, Center for Preclinical Research and Technology CEPT, 02-091 Warsaw, Poland
Warsaw, Mazowieckie, Poland
SS

Sérgio N. Simões

Researcher
Federal Institute of Education, Science and Technology of Espírito Santo, Serra-ES, 29056-264, Brazil
Victoria-ES, Espirito Santo, Brazil
DM

David C. Martins, Jr.

Researcher
Centro de Matemática, Computação e Cognição, Universidade Federal do ABC, Santo André-SP, 09606-045, Brazil
Santo Andre - SP, Sao Paulo, Brazil
JS

Jolanta M. Siller-Matula

Professor
Department of Internal Medicine II, Division of Cardiology, Medical University of Vienna,1090 Vienna, Austria
Vienna, Wien, Austria
MP

Marek Potuła

Professor
Department of Experimental and Clinical Pharmacology, Medical University of Warsaw, Center for Preclinical Research and Technology CEPT, 02-091 Warsaw, Poland
Warsaw, Mazowieckie, Poland

Background: COVID-19 is associated with an increased risk of mortality and adverse cardiovascular (CV) occurrences. ACE2 interaction network caused by virus infection can affect the expression levels of miRNAs and influence severity of the disease.

Aims: This study aimed to analyse the diagnostic/predictive utility of ACE2-related miRNAs, which were identified by in silico analysis (miR-10b-5p,miR-124-3p,miR-200b-3p,miR-26b-5p,miR-302c-5p) in patients with COVID-19, and aimed to unravel the functions of miRNAs, by using machine learning-SHAP analysis for clinical data and bioinformatic tools.

Methods: Blood samples and clinical data of 79 patients and 32 healthy were collected at; day of admission, 7days and 21days after admission. Endpoint was hospitalisation length of stay (>21days) and/or death in follow-up.

Results: Delta low miR-200b-3p expression (after 7days of admission) presents predictive utility in assessment of the hospital length of stay and/or death in ROC curve analysis (AUC:0.730,p=0.002)(Fig. 1). Delta low miR-200b-3p expression, diabetes mellitus (DM) are independent predictors of increased hospital length of stay and/or death (OR=5.78;CI=0.57-21.21;p= 0.008,OR= 4.89;CI=1-23.86;p=0.04). MiR-26b-5p and miR-10b-5p in patients were found lower at the baseline, 7 and 21-days after admission compared to the healthy controls (p < 0.0001 for all time points). SHAP analysis indicated miR-200b-3p (day7th), miR-302c-5p (day7th), CRP (day7th), neutrophils (day0), and D-Dimer (day0) as the most promising predictors of long hospitalisation. Pathway-enrichment showed that interleukin-2 signaling pathway, and Pathways in cancer were the top pathways. MiR-200b-3p showed regulation of COVID-19-related targets associated with T cell protein tyrosine phosphatase and HIF-1 transcriptional activity in hypoxia, key pathways in COVID-19. Bioinformatics analysis pointed out the role of those miRNAs in multiple CVDs phenotypes associated with COVID-19(Fig. 2).

Conclusion(s): In this study we validated and characterized miRNAs which could serve as novel, predictive biomarkers of the long term COVID-19 hospitalisation and can be used for early stratification of patients and prediction of severity of infection development in an individual.