Ethel Percy Andrus Gerontology Center, Leonard Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA.
Denney Research Center, Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA.
Geroscience. 2020 Oct;42(5):1411-1429. doi: 10.1007/s11357-020-00245-6. Epub 2020 Aug 2.
Traumatic brain injury (TBI) and Alzheimer's disease (AD) are prominent neurological conditions whose neural and cognitive commonalities are poorly understood. The extent of TBI-related neurophysiological abnormalities has been hypothesized to reflect AD-like neurodegeneration because TBI can increase vulnerability to AD. However, it remains challenging to prognosticate AD risk partly because the functional relationship between acute posttraumatic sequelae and chronic AD-like degradation remains elusive. Here, functional magnetic resonance imaging (fMRI), network theory, and machine learning (ML) are leveraged to study the extent to which geriatric mild TBI (mTBI) can lead to AD-like alteration of resting-state activity in the default mode network (DMN). This network is found to contain modules whose extent of AD-like, posttraumatic degradation can be accurately prognosticated based on the acute cognitive deficits of geriatric mTBI patients with cerebral microbleeds. Aside from establishing a predictive physiological association between geriatric mTBI, cognitive impairment, and AD-like functional degradation, these findings advance the goal of acutely forecasting mTBI patients' chronic deviations from normality along AD-like functional trajectories. The association of geriatric mTBI with AD-like changes in functional brain connectivity as early as ~6 months post-injury carries substantial implications for public health because TBI has relatively high prevalence in the elderly.
创伤性脑损伤（TBI）和阿尔茨海默病（AD）是两种突出的神经疾病，其神经和认知方面的共同之处尚未被充分理解。据推测，TBI 相关的神经生理异常的程度反映了类似 AD 的神经退行性变，因为 TBI 会增加患 AD 的易感性。然而，由于急性创伤后后遗症与慢性类似 AD 的退化之间的功能关系仍难以捉摸，因此预测 AD 风险仍然具有挑战性。在这里，我们利用功能磁共振成像（fMRI）、网络理论和机器学习（ML）来研究老年轻度创伤性脑损伤（mTBI）在多大程度上导致静息状态活动默认模式网络（DMN）中出现类似 AD 的改变。研究发现，该网络包含模块，这些模块的类似 AD 的、创伤后退化的程度可以根据伴有脑微出血的老年 mTBI 患者的急性认知缺陷来准确预测。这些发现除了在老年 mTBI、认知障碍和类似 AD 的功能退化之间建立了一种预测性的生理关联之外，还推进了急性预测 mTBI 患者沿着类似 AD 的功能轨迹偏离正常的慢性偏差的目标。TBI 在老年人中的发病率相对较高，因此创伤后 6 个月左右功能性脑连接就出现类似 AD 的变化，这对公共卫生具有重要意义。
