Dataset Information

Applying Proteomics and Computational Approaches to Identify Novel Targets in Blast Associated Post-Traumatic Epilepsy

ABSTRACT: Traumatic brain injury (TBI) remains a leading cause of post traumatic epilepsy (PTE). Blast TBI (bTBI) found in Veterans presents cognitive and behavioral disturbance such as PTE, however, the underlying mechanisms that drive the long-term sequelae are not well understood. Using an unbiased proteomics approach in a murine model of repeated bTBI (rbTBI), this study addresses this gap in knowledge. Following rbTBI, mice underwent 24/7 EEG recording for four months before collecting the cortex and hippocampus of PTE+, PTE- and sham mice. Hundreds of differentially expressed proteins were identified in the cortex and hippocampus of PTE+ and PTE- relative to sham. Focusing on protein pathways unique to PTE+ animals revealed mitochondrial function, post translational modifications, and protein transport proteins were disrupted. Computational metabolic modeling using dysregulated protein expression predicted mitochondrial proton pump dysregulation, suggesting electron transport chain dysregulation in epileptic tissue relative to PTE- and sham. Finally, data mining enabled the identification of several novel and previously validated TBI and epilepsy biomarkers in our data set, many of which were found to already be targeted by drugs in various phases of clinical testing. These findings highlight novel proteins and protein pathways that may drive the chronic PTE sequala following rbTBI.

INSTRUMENT(S): Orbitrap Fusion Lumos

ORGANISM(S): Mus Musculus (mouse)

TISSUE(S): Brain

DISEASE(S): Traumatic Brain Injury

SUBMITTER: Keith Ray

LAB HEAD: Michelle L. Olsen

PROVIDER: PXD048228 | Pride | 2024-06-22

REPOSITORIES: pride

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Dataset's files

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			Action	DRS
	230613_OlsenDoD_18C_01.msf	Msf
	230613_OlsenDoD_18C_01.msfView	Msf
	230613_OlsenDoD_18C_01.mzML	Mzml
	230613_OlsenDoD_18C_01.mzid.gz	Mzid
	230613_OlsenDoD_18C_01.pdResult	Other

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Publications

Applying Proteomics and Computational Approaches to Identify Novel Targets in Blast-Associated Post-Traumatic Epilepsy.

Browning Jack L JL Wilson Kelsey A KA Shandra Oleksii O Wei Xiaoran X Mahmutovic Dzenis D Maharathi Biswajit B Robel Stefanie S VandeVord Pamela J PJ Olsen Michelle L ML

International journal of molecular sciences 20240301 5

Traumatic brain injury (TBI) can lead to post-traumatic epilepsy (PTE). Blast TBI (bTBI) found in Veterans presents with several complications, including cognitive and behavioral disturbances and PTE; however, the underlying mechanisms that drive the long-term sequelae are not well understood. Using an unbiased proteomics approach in a mouse model of repeated bTBI (rbTBI), this study addresses this gap in the knowledge. After rbTBI, mice were monitored using continuous, uninterrupted video-EEG f ...[more]

PMID: 38474127

Similar Datasets

Project description:Purpose: Post-traumatic epilepsy (PTE) is an epilepsy that develops after traumatic brain injury (TBI), and it comprises 10-20% of structural epilepsies and 5% of all epilepsies. The lack of prognostic biomarkers for PTE hinders the development of anti-epileptogenic treatments. In this preclinical multicenter study, plasma samples collected from a rat model of PTE were analyzed by small RNA sequencing to reveal the post-TBI expression profile of circulating microRNAs and to identify potential miRNA biomarkers for PTE development. Methods: The animal experiments were conducted at 3 different study sites: University of Eastern Finland (Finland), Monash University (Australia), and University of California, Los Angeles (USA). Severe TBI was induced in adult male Sprague-Dawley rats by the lateral fluid-percussion injury (LFPI) method. Rats that developed PTE were identified by video-EEG monitoring during the 7th post-injury month (TBI rats with epilepsy, TBIE; TBI rats without epilepsy, TBIN). Small RNA sequencing was conducted with plasma samples collected 48 hours after TBI or sham operation (craniotomy). Following the primary quantification, DESeq2 (v. 1.42.0) was used to identify differentially expressed miRNAs between the experiment groups. Results were further validated in a larger sample cohort by droplet digital PCR (ddPCR). Results: Small RNA sequencing detected a total of 754 miRNAs that were expressed in at least one sample. DESeq2 detected 23 differentially expressed (DE) miRNAs between the TBI and sham groups, 12 between the TBIE and sham groups, and 5 between the TBIN and sham groups. In contrast, no DE miRNAs were detected between the TBIE and TBIN groups. From the list of 23 DE miRNAs between the TBI and sham groups, 3 upregulated miRNAs (rno-miR-183-5p, rno-miR-323-3p, and miR-434-3p) were selected for further ddPCR validation. The list of miRNAs for validation was further complemented by 4 miRNAs (rno-miR-9a-3p, rno-miR-124-3p, rno-miR-132-3p, and rno-miR-212-3p), which were not differentially expressed in the DESeq2 analysis, but which we have previously detected to be acutely upregulated in TBI rat plasma. The validation was conducted with samples from the entire EpiBioS4Rx cohort [26 baseline samples, 45 sham, 164 TBI (32 TBIE, 132 TBIN)]. DdPCR analysis revealed that all 7 investigated miRNAs were upregulated in the TBI rats compared with the sham controls. No differences were detected between the rats with (TBIE) or without epilepsy (TBIN). In contrast, TBIE rats that had seizure clusters (severe PTE) had lower levels of plasma miR-212-3p compared with other TBI rats. Furthermore, elastic net regularized logistic regression (glmnet) analysis identified miR-212-3p and miR-132-3p as the optimal set to differentiate TBIE rats with seizure clusters from other TBI rats. Conclusions: The profile of circulating plasma microRNAs differed between TBI rats and sham controls. MiR-212-3p alone or in combination with miR-132-3p showed potential as prognostic biomarkers for development of severe PTE.