Exploring the Proteomic Landscape of Traumatic Brain Injury Models
Date
2025-03
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Publisher
Stellenbosch University
Abstract
Background: Traumatic brain injury (TBI) is a multifaceted condition characterized by primary and secondary injury mechanisms, leading to significant molecular and cellular disruptions. Understanding these processes at the proteomic level is critical for developing targeted therapeutic strategies. Systematic reviews and meta-analyses can provide insights into the broader landscape of TBI research, while experimental comparisons of TBI models can refine our understanding of their relevance to human pathology. Research Gap: Current models fail to capture the full complexity of human TBI, particularly the interplay between biochemical and biomechanical mechanisms. Comparative analyses of TBI models and integrative proteomic studies remain limited. Objective: This study aimed to integrate findings from a systematic review, conduct a meta-analysis of publicly available proteomic datasets, and evaluate two chemical TBI models, sodium dithionite (SDT) and 2-deoxy-D-glucose (2DG), to better understand TBI-associated proteomic changes. Method: A systematic review and meta-analysis identified key proteins and pathways altered in TBI. Proteomic analyses of SDT and 2DG models were conducted to assess their ability to replicate TBI pathologies, including oxidative stress, apoptosis, autophagy, and metabolic dysfunction. Comparative analyses explored shared and distinct molecular responses. Key Findings: The systematic review and meta-analysis identified critical proteins and pathways linked to oxidative stress, mitochondrial dysfunction, and cell death. SDT induced oxidative stress and excitotoxicity, while 2DG disrupted metabolic pathways and caused energy depletion. Both models showed overlapping responses, such as inflammation and mitochondrial dysfunction, and distinct pathway activations. Limitations included the inability of chemical models to replicate biomechanical injury, the static nature of proteomic analyses, and incomplete metadata affecting reproducibility. Implications: By combining systematic review, meta-analysis, and experimental model comparison, this study offers a comprehensive framework for understanding TBI at the proteomic level. These findings highlight the strengths and limitations of current models and inform future research directions, including integrating mechanical and chemical models, employing longitudinal and multi-omics approaches, and improving metadata reporting and experimental validation. This approach will enhance the translational relevance of findings and support the development of targeted therapies and biomarkers to improve TBI management and outcomes.