Increased levels of platelet function-related miR-16-5p predicts increased severity of ischemic stroke: in silico validation analysis

Abstract Background Ischemic stroke (IS) is one of the most frequent causes of death. Since miRNAs have been illustrated to play an important role in various processes through regulation of multiple genes, and platelet function, their utility as novel biomarkers should be determined. We aimed to identify and validate circulating miRNAs, modulated in acute ischemic stroke (IS) patients in order to distinguish the most specific as biomarkers to facilitate diagnosis and prognosis. Method Sixty patients with acute IS (24-h and 7-days after IS) and 30 age- and gender-matched individuals free of stroke with multiple risk factors for cardiovascular disease. Studied miRNAs were selected based on bioinformatic analysis that was previously published by our team (1-2-3). PlasmaRNA was extracted; quality RNA was assessed: fluorometric assay; RT-PCR for miRNAs expression measurement p<0.05. Results Let-7e expression 7-day of IS was significantly lower than both controls and first day of IS (p=0.007, p=0.001, res). miR-125a-3p was lower both at day-1 and day-7 of IS compared to controls (p=0.008, p=0.020, res). miR-125a-5p on the other hand, had significantly higher expression at day-1 compared to controls (p=0.002). Both miR-125a-3p and -5p showed diagnostic value in ROC curve analysis (AUC= 0.705, AUC= 0.709, res). Patients with moderate stroke (based on NIHSS) had significantly higher miR-16-5p expression levels compared to patients with minor stroke at the first day of IS (AUC: 0.718, (95% CI, 0.59-0.85) p = 0.004). High baseline expression of miR-16-5p and diabetes mellitus are independent predictors of increased severity of stroke to a multivariate analysis (OR: 4.341; 95% CI, 1.15–16.42; p = 0.031 and OR: 4.653; 95% CI, 1.07–20.19; p = 0.040, res). Conclusion In this study we validated miRNAs based on our previous bioinformatic analysis which could serve as novel, platelet-related predictive biomarkers of the IS severity, and can be used for early stratification of patients and prediction of severity of disease development in an individual.