Alzheimer's disease‐like brain atrophy patterns after mild traumatic brain injury can be predicted based on acute cognitive deficit. (31st December 2021)

• Record Type: Journal Article
• Authors: Rostowsky, Kenneth A.; Amgalan, Anar; Irimia, Andrei
• Is Part Of: Alzheimer's & dementia. Volume 17(2021)Supplement 5
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-31
• Subjects: Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1002/alz.054779
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: The neurological events that follow traumatic brain injury (TBI) can include cognitive decline, personality changes, and long‐term structural and functional effects. At the microscale, the neuropathological changes following TBI overlap partially with those seen in Alzheimer's disease (AD). Nevertheless, our understanding of how mild TBI (mTBI) can lead to AD remains inadequate. The predictive potential of acute mTBI degeneration patterns in prognosticating the risk of AD‐like structural changes is also largely unexplored. Method: In 66 AD patients, 33 mTBI patients and 72 healthy controls (HCs), diffusion‐weighted imaging (DWI) was used to calculate the fractional anisotropy (FA) of white matter (WM) connections and T1 ‐weighted magnetic resonance imaging (MRI) was used to estimate gray matter (GM) thickness. Support vector machines (SVMs) then leveraged acute mTBI data to predict the severity of AD‐like neurodegeneration measured six months after mTBI. Result: In both AD and mTBI, WM degeneration patterns and their extent are indistinguishable, in a statistical sense, within the fornix, corpus callosum, and corona radiata. In these structures, 78%, 35%, and 56% of their respective voxels have mean FAs which differ significantly from those of HCs for both mTBI and AD cohorts ( p < 0.05). The mean FAs of these same sets of voxels are statistically equivalent across the mTBI and AD groups ( p < 0.05, two one‐sided tests of statistical equivalence). mTBI and AD participants exhibit statistically significant similarities in their GM degeneration patterns, particularly within temporal poles (memory) and orbitofrontal cortices (executive function). 47% and 75% of voxels in these structures, respectively, exhibit statistical equivalence of mean FA across mTBI and AD ( p < 0.05); these sets of voxels' mean FAs are also statistically significantly different from those of HCs. SVM predictions suggest that acute post‐traumatic cognitive assessments contain information that accurately predicts AD‐like neurodegeneration patterns and severity observed chronically after mTBI (sensitivity: 0.87±0.09, specificity: 0.93±0.09; precision: 0.88±0.2). Conclusion: Our findings suggest that mTBI‐induced atrophy can relegate the brain onto AD‐like neurodegeneration trajectories and that post‐mTBI cognitive assessments may provide early indications of AD risk after TBI.