| Literature DB >> 30886525 |
Abstract
There is growing public concern surrounding traumatic brain injury (TBI). TBI can cause significant morbidity, and the long-term sequelae are poorly understood. TBI diagnosis and management rely on patient-reported symptoms and subjective clinical assessment. There are no biologic tools to detect mild TBI or to track brain recovery. Emerging evidence suggests that microRNAs (miRNAs) may provide information about the injured brain. These tiny epigenetic molecules are expressed throughout the body. However, they are particularly important in neurons, can cross the blood-brain barrier, and are securely transported from cell to cell, where they regulate gene expression. miRNA levels may identify patients with TBI and predict symptom duration. This review synthesizes miRNA findings from 14 human studies. We distill more than 291 miRNAs to 17 biomarker candidates that overlap across multiple studies and multiple biofluids. The goal of this review is to establish a collective understanding of miRNA biology in TBI and identify clinical priorities for future investigations of this promising biomarker.Entities:
Keywords: Concussion; biomarkers; diagnosis; miRNA; prognosis; traumatic brain injury; treatment
Year: 2019 PMID: 30886525 PMCID: PMC6410383 DOI: 10.1177/1179069519832286
Source DB: PubMed Journal: J Exp Neurosci ISSN: 1179-0695
Figure 1.(a) Acute injury response of miRNAs: across 3 biofluids (cerebrospinal fluid, saliva, and blood) in the acute period (<96 hours post injury); (b) secondary injury response of miRNAs: across 3 biofluids (cerebrospinal fluid, saliva, and blood) in the subacute or chronic period (>5 days post injury).
CSF, cerebrospinal fluid; miRNA, microRNA; TBI, traumatic brain injury.
Arrows denote the general direction of change for each miRNA, along with the study in which it was detected (the superscript number corresponds to the reference). Gray boxes denote the time-points or biofluids without existing miRNA TBI studies.
Putative targets of the 17 miRNAs with the highest TBI biomarker potential.
| MicroRNA Targets | miR-181a-5p ↑ (4) | miR-128-3p ↓ (4) | miR-16-5p ↑ (4) | miR-221-3p ↓ (4) | miR-26b-5p ↑ (3) | miR-27b-3p ↑ (6) | miR-29a/c-3p ↓ (4) | miR-30a-5p ↑ (5) | miR-320c ↑ (4) | miR-532-5p ↑ (3) | miR-1307-3p ↑ (3) | miR-151a-3p ↑ (2) | miR-7-5p ↓ (3) | miR-629-5p ↓ (3) | miR-10a/b-5p ↑ (3) | mRNA targets |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Total no. of transcripts | 49 | 197 | 203 | 20 | 246 | 313 | 168 | 380 | 72 | 7 | 124 | 40 | 105 | 8 | 82 | 2014 |
| ECM-receptor interaction (FDR = 2.3E-39) | 1 | 4 | 0 | 0 | 1 | 4 | 13 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | ITGA8, COL4A5, COL27A1, ITGA5, COL3A1, SV2A, COL2A1, RELN, COL5A1, COL4A4, COL1A2, LAMC1, COL11A1, COL6A3, LAMA2, COL5A3, COL5A2, SPP1, COL4A1, VEGFA |
| Pluripotency of stem cells (FDR = 1.5E-06) | 1 | 5 | 11 | 0 | 6 | 7 | 2 | 3 | 1 | 0 | 0 | 0 | 1 | 0 | 1 | BMI1, JARID2, GSK3B, WNT7A, INHBB, APC, WNT10B, REST, MAPK14, RAF1, INHBA, WNT4, ZFHX3, FZD3, ACVR1, ACVR2B, FZD10, LIFR, PIK3R1, ACVR2A, FGF2, ACVR1C, IGF1, AKT3, BMPR1A, WNT3A, ISL1, GRB2, SMAD1, PIK3R2 |
| Amphetamine addiction (FDR = 2.6E-05) | 0 | 4 | 0 | 0 | 1 | 5 | 1 | 5 | 1 | 0 | 2 | 0 | 1 | 0 | 2 | AFT2, CAMK4, CREB5, PPP1CC, PPP3R1, DRD1, GRIA1, CREB1, PPP3CA, SLC6A3, PRKX, PRKCB, CAMK2B, GRIA4, GRIN2D |
| Cocaine addiction (FDR = 0.020) | 0 | 2 | 1 | 0 | 2 | 2 | 0 | 4 | 1 | 0 | 1 | 0 | 0 | 0 | 2 | ATF2, CREB5, DRD1, GPSM1, GRM3, CDK5R1, BDNF, CREB1, SLC6A3, PRKX, GRIN2D |
| Neurotrophin signaling (FDR = 0.021) | 0 | 6 | 4 | 0 | 3 | 6 | 3 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | GSK3B, SH2B3, CAMK4, MAP2K7, RAP1A, MAPK14, RAF1, BCL2, PRKCD, BDNF, KIDINS220, RPS6KA6, PIK3R1, SOS1, IRS1, GAB1, AKT3, CAMK2B, PRDM4, GRB2, RAP1B, NGFR, PIK3R2 |
| Glioma (FDR = 0.0022) | 0 | 1 | 3 | 0 | 2 | 2 | 3 | 1 | 1 | 0 | 3 | 0 | 1 | 0 | 1 | REF1, EGFR, CDK6, E2F3, PIK3R1, SOS1, PRKCB, IGF1, AKT3, CAMK2B, PTEN, GRB2, PIK3R2 |
| ErbB signaling (FDR = 0.0056) | 0 | 4 | 1 | 1 | 2 | 7 | 1 | 3 | 0 | 0 | 1 | 0 | 3 | 0 | 1 | GSK3B, HBEGF, MAP2K7, RAF1, CDKN1B, EGFR, CBLB, NRG3, PIK3R1, SOS1, PRKCB, GAB1, AKT3, CAMK2B, MAP2K4, ABL2, GRB2, PIK3R2 |
| Long-term potentiation (FDR = 0.016) | 0 | 4 | 3 | 0 | 3 | 7 | 0 | 7 | 1 | 0 | 0 | 0 | 2 | 0 | 1 | CAMK4, PPP1CC, RAP1A, GRM5, PPP3R1, RAF1, GRIA1, PPP3CA, PLCB1, RPS6KA6, PRKX, PRKCB, CAMK2B, GRIN2D, RAP1B |
ECM, extracellular matrix; FDR, false discovery rate; KEGG, Kyoto Encyclopedia of Genes and Genomes; TBI, traumatic brain injury.
The 17 miRNAs identified in ⩾2 human TBI studies, across 3 biofluids (cerebrospinal fluid, saliva, and blood), were interrogated for putative mRNA targets. Together, they targeted 2014 coding transcripts with high confidence (microT-CDS > 0.975) which demonstrated enrichment (FDR < 0.05) for 22 KEGG signaling pathways. Of the 22 pathways, 8 implicated in brain-related processes are shown here (FDR P-values in parentheses). The number of mRNAs targeted by each miRNA in the respective pathway is displayed. Arrows denote the general direction of change for each miRNA, along with the number of studies in which it was detected (in parentheses).