ReviewNeurobiology of disease2026
Chronic traumatic encephalopathy: A devastating legacy of repetitive concussion.
Review in Neurobiology of disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 authors.
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Abstract
Repetitive concussive and subconcussive traumatic brain injury (TBI) is increasingly linked to chronic traumatic encephalopathy (CTE), yet a central challenge remains in connecting exposure to long-term neurodegeneration through a coherent mechanistic framework. Here, we synthesize evidence across epidemiology, neuropathology, and clinical studies to define the continuum from repetitive injury to disease. Primary injury initiates secondary cascades, including mitochondrial dysfunction, metabolic stress, neuroinflammation, and axonal injury across neuronal, glial, and vascular compartments, which, over time, promote protein misfolding and progressive pathology involving tau, amyloid precursor protein (APP), and TDP-43. CTE is defined by a distinct pattern of perivascular hyperphosphorylated tau accumulation at the depths of cortical sulci, linking injury-associated biomechanical strain and vascular vulnerability to spatially localized disease progression. These pathological processes give rise to heterogeneous clinical features that are only partially captured by current diagnostic frameworks and emerging imaging and fluid biomarkers, which remain limited in specificity. Experimental models, including in vivo systems and human 3D in vitro platforms, provide complementary insight into specific aspects of CTE pathobiology, but no single model fully recapitulates the disease trajectory. Together, this synthesis reframes CTE as a mechanistically linked continuum from exposure to neurodegeneration, highlights key gaps in diagnosis and modeling, and identifies priorities for advancing in-life detection and therapeutic development.
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