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Acute cognitive deficits after traumatic brain injury predict Alzheimer's disease-like degradation of the human default mode network.
GeroScience ( IF 5.6 ) Pub Date : 2020-08-02 , DOI: 10.1007/s11357-020-00245-6
Andrei Irimia 1, 2 , Alexander S Maher 1 , Nikhil N Chaudhari 1 , Nahian F Chowdhury 1 , Elliot B Jacobs 1 ,
Affiliation  

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.



中文翻译:

脑外伤后的急性认知功能障碍预示着人类默认模式网络的老年痴呆症样退化。

颅脑外伤(TBI)和阿尔茨海默氏病(AD)是重要的神经系统疾病,人们对其神经和认知共性了解甚少。假设与TBI相关的神经生理异常的程度反映了AD样神经变性,因为TBI可以增加对AD的易感性。然而,部分地预测AD风险仍然具有挑战性,因为急性创伤后后遗症和慢性AD样退化之间的功能关系仍然难以捉摸。在这里,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TBI(mTBI)在默认模式网络中可导致AD样的静止状态活动改变的程度(DMN)。发现该网络包含的模块类似于AD,可以根据患有脑微出血的老年mTBI患者的急性认知功能障碍来准确预测创伤后退化。除了在老年性mTBI,认知障碍和AD样功能退化之间建立预测的生理联系外,这些发现还促进了急性预测mTBI患者沿着AD样功能轨迹正常偏离慢性的目标。老年人mTBI与伤害后最早约6个月的AD样功能性大脑连接改变有关,这对公共卫生具有重大影响,因为TBI在老年人中的患病率较高。除了在老年性mTBI,认知障碍和AD样功能退化之间建立预测的生理联系外,这些发现还促进了急性预测mTBI患者沿着AD样功能轨迹正常偏离慢性的目标。老年人mTBI与伤害后最早约6个月的AD样功能性大脑连接改变有关,这对公共卫生具有重大影响,因为TBI在老年人中的患病率较高。除了在老年性mTBI,认知障碍和AD样功能退化之间建立预测的生理联系外,这些发现还促进了急性预测mTBI患者沿着AD样功能轨迹正常偏离慢性的目标。老年人mTBI与伤害后最早约6个月的AD样功能性大脑连接改变有关,这对公共卫生具有重大影响,因为TBI在老年人中的患病率较高。

更新日期:2020-08-02
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