Diagnosis of traumatic brain injury using miRNA signatures in nanomagnetically isolated brain-derived extracellular vesicles

Abstract

The accurate diagnosis and clinical management of traumatic brain injury (TBI) is currently limited by the lack of accessible molecular biomarkers that reflect the pathophysiology of this heterogeneous disease. To address this challenge, we developed a microchip diagnostic that can characterize TBI more comprehensively using the RNA found in brain-derived extracellular vesicles (EVs). Our approach measures a panel of EV miRNAs, processed with machine learning algorithms to capture the state of the injured and recovering brain. Our diagnostic combines surface marker-specific nanomagnetic isolation of brain-derived EVs, biomarker discovery using RNA sequencing, and machine learning processing of the EV miRNA cargo to minimally invasively measure the state of TBI. We achieved an accuracy of 99% identifying the signature of injured vs. sham control mice using an independent blinded test set (N = 77), where the injured group consists of heterogeneous populations (injury intensity, elapsed time since injury) to model the variability present in clinical samples. Moreover, we successfully predicted the intensity of the injury, the elapsed time since injury, and the presence of a prior injury using independent blinded test sets (N = 82). We demonstrated the translatability in a blinded test set by identifying TBI patients from healthy controls (AUC = 0.9, N = 60). This approach, which can detect signatures of injury that persist across a variety of injury types and individual responses to injury, more accurately reflects the heterogeneity of human TBI injury and recovery than conventional diagnostics, opening new opportunities to improve treatment of traumatic brain injuries.

Using Serum Amino Acids to Predict Traumatic Brain Injury: A Systematic Approach to Utilize Multiple Biomarkers

“…Studies show that supervised classifier algorithms perform better than unsupervised methods when development of predictive models of injury and future outcome is the goal rather than identification of hidden patterns within the dataset [33]. Some supervised algorithms that have been used previously to construct classification models between different injury and non-injury classes in biomarker studies include linear discriminant analysis (LDA) [14], logistic regression analysis (Logit) [22], and k-nearest-neighbors (KNN) [34]. LDA and logit algorithms are more common and advantageous than KNN algorithms because they are easier to be implemented and interpreted.…”

“…These biochemical and metabolomic alterations first appear in the brain tissue and then, by crossing a number of barriers, manifest in biofluids such as cerebrospinal fluid (CSF), blood, saliva and urine [1][2][3][4][5][6][7][8][9][10][11][12]. Therefore, biofluids contain valuable information about the occurrence and progression of TBI and thus recently have been explored as a source for potential biomarkers to diagnose TBI, as well as to assess its severity, monitor its progression, predict patient outcomes, and determine the effectiveness of therapeutic interventions [1,4,5,[9][10][11][13][14][15][16][17][18][19]. The use of serum biomarkers has greatly contributed to improved diagnostic and therapeutic methods in fields such as hematology, cardiology, oncology, and infectious disease [10].…”

Extracellular Vesicle Proteins and MicroRNAs as Biomarkers for Traumatic Brain Injury

“…In a 2018 study, Ko et al (176) identified a miRNA based panel biomarker to diagnose TBI, both in a mouse model and human TBI. MiRNAs associated with EVs positive for GluR2 (an AMPA receptor subunit) were isolated from plasma of mice exposed to blast overpressure injury.…”

Extracellular Vesicles miRNA Cargo for Microglia Polarization in Traumatic Brain Injury

“…They also found that the expression of miR-21 in the brain was primarily localized in neurons adjacent the lesion site and microglia present near these miR-21-expressing neurons were activated [ 139 ]. Interestingly, Han et al found that miR-21-5p was elevated in neurons after TBI [ 140 ]. Recently the same group demonstrated that Exos derived from neurons of TBI with highly expressed miR-21-5p, injected into the mouse induced the polarization of M1 microglia.…”