Micro Ribonucleic Acid Profiles of Traumatic Brain Injury Isolated From Plasma Extracellular Vesicles
Abstract INTRODUCTION Extracellular vesicles (EVs) are membrane-bound particles released by the majority of human cells, including cells within the central nervous system. They may represent a diagnostic or prognostic target obtainable in peripheral blood of neurotrauma patients. We have isolated micro RNA sequences contained within EVs of 15 patients with traumatic brain injury (TBI) and compared them to miRNA sequences from 5 healthy controls. METHODS Extracellular vesicles were isolated from 15 TBI subjects, including 6 mild TBI (Glasgow Coma Scale (GCS) 13-15), 3 moderate TBI (GCS 9-12), and 6 severe TBI (GCS 3-8), as well as 5 healthy control. EVs were analyzed using nanoparticle tracking analysis. Samples underwent RNA isolation and extraction, followed by miRNA sequencing and analysis. RESULTS TBI patients presenting with an altered level of consciousness (GCS = 14) had a significantly higher mean extracellular vesicle size compared to subjects with normal GCS (mean + /− sem = 108.3 nm + /− 7.7 nm vs 89.2 nm + /− 6.7 nm; P < .04). GFAP ELISA of the samples demonstrated significantly higher GFAP concentration in subjects with altered level of consciousness (GCS = 14) as compared to those with normal GCS (mean + /− sem GFAP concentration 2204.2 pg/mL + /− 1067.2 pg/mL vs. 207.8 pg/mL + /− 270.8 pg/mL, P = .05). We identified 9 miRNA sequences that were found in a significantly higher proportion in patients with altered consciousness compared to controls, as well as 2 miRNA sequences that were significantly downregulated in subjects with altered consciousness as compared to controls. CONCLUSION EVs may contain brain specific biomarkers that are released in greater quantities after TBI. These molecules can be isolated from plasma and sequenced. Further analysis will better elucidate the final pathways affected by these up and downregulated miRNA sequences. Analysis of EVs in subjects with TBI may allow for the identification of novel diagnostic and potentially prognostic biomarkers.