Transcriptional Pathology Evolves over Time in Rat Hippocampus after Lateral Fluid Percussion Traumatic Brain Injury

Autor: Rinaldo Catta-Preta, Iva Zdilar, Bradley Jenner, Emily T. Doisy, Kayleen Tercovich, Alex S. Nord, Gene G. Gurkoff
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Neurotrauma Reports, Vol 2, Iss 1, Pp 512-525 (2021)
Druh dokumentu: article
ISSN: 2689-288X
DOI: 10.1089/NEUR.2021.0021
Popis: Traumatic brain injury (TBI) causes acute and lasting impacts on the brain, driving pathology along anatomical, cellular, and behavioral dimensions. Rodent models offer an opportunity to study the temporal progression of disease from injury to recovery. Transcriptomic and epigenomic analysis were applied to evaluate gene expression in ipsilateral hippocampus at 1 and 14 days after sham (n?=?2 and 4, respectively per time point) and moderate lateral fluid percussion injury (n?=?4 per time point). This enabled the identification of dynamic changes and differential gene expression (differentially expressed genes; DEGs) modules linked to underlying epigenetic response. We observed acute signatures associated with cell death, astrocytosis, and neurotransmission that largely recovered by 2 weeks. Inflammation and immune signatures segregated into upregulated modules with distinct expression trajectories and functions. Whereas most down-regulated genes recovered by 14 days, two modules with delayed and persistent changes were associated with cholesterol metabolism, amyloid beta clearance, and neurodegeneration. Differential expression was paralleled by changes in histone H3 lysine residue 4 trimethylation at the promoters of DEGs at 1 day post-TBI, with the strongest changes observed for inflammation and immune response genes. These results demonstrate how integrated genomics analysis in the pre-clinical setting has the potential to identify stage-specific biomarkers for injury and/or recovery. Though limited in scope here, our general strategy has the potential to capture pathological signatures over time and evaluate treatment efficacy at the systems level.
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