Nair Sajitha Somasundaran, Govindankutty Mini Maniyelil, Balakrishnan Minimol, Prasad Krishna, Sathyaprabha Talakad N, Udupa Kaviraja
Model Engineering College, Cochin University of Science and Technology, Kochi 682022, India.
Department of Neurophysiology, National Institute of Mental Health and Neurosciences, Bengaluru 560029, India.
Brain Sci. 2023 Sep 14;13(9):1322. doi: 10.3390/brainsci13091322.
(1) Background and Objective: Alzheimer's disease (AD) is commonly accompanied by autonomic dysfunction. Investigating autonomic dysfunction's occurrence patterns and severity may aid in making a distinction between different dementia subtypes, as cardiac autonomic dysfunction and AD severity are correlated. Heart rate variability (HRV) allows for a non-invasive assessment of the autonomic nervous system (ANS). AD is characterized by cholinergic depletion. A computational model of ANS based on the kinetics of acetylcholine and norepinephrine is used to simulate HRV for various autonomic states. The model has the flexibility to suitably modulate the concentration of acetylcholine corresponding to different autonomic states. (2) Methods: Twenty clinically plausible AD patients are compared to 20 age- and gender-matched healthy controls using HRV measures. Statistical analysis is performed to identify the HRV parameters that vary significantly in AD. By modulating the acetylcholine concentration in a controlled manner, different autonomic states of Alzheimer's disease are simulated using the ANS model. (3) Results: In patients with AD, there is a significant decrease in vagal activity, sympathovagal imbalance with a dominant sympathetic activity, and change in the time domain, frequency domain, and nonlinear HRV characteristics. Simulated HRV features corresponding to 10 progressive states of AD are presented. (4) Conclusions: There is a significant difference in the HRV features during AD. As cholinergic depletion and autonomic dysfunction have a common neurological basis, autonomic function assessment can help in diagnosis and assessment of AD. Quantitative models may help in better comprehending the pathophysiology of the disease and assessment of its progress.
（1）背景与目的：阿尔茨海默病（AD）常伴有自主神经功能障碍。研究自主神经功能障碍的发生模式和严重程度可能有助于区分不同的痴呆亚型，因为心脏自主神经功能障碍与AD严重程度相关。心率变异性（HRV）可用于无创评估自主神经系统（ANS）。AD的特征是胆碱能耗竭。基于乙酰胆碱和去甲肾上腺素动力学的ANS计算模型用于模拟各种自主神经状态下的HRV。该模型具有灵活调节对应于不同自主神经状态的乙酰胆碱浓度的能力。（2）方法：使用HRV测量方法，将20例临床诊断合理的AD患者与20例年龄和性别匹配的健康对照进行比较。进行统计分析以确定AD中显著变化的HRV参数。通过以可控方式调节乙酰胆碱浓度，使用ANS模型模拟阿尔茨海默病的不同自主神经状态。（3）结果：在AD患者中，迷走神经活动显著降低，交感迷走神经失衡且交感神经活动占主导，时域、频域和非线性HRV特征均发生变化。展示了对应于AD 10个进展状态的模拟HRV特征。（4）结论：AD期间HRV特征存在显著差异。由于胆碱能耗竭和自主神经功能障碍有共同的神经学基础，自主神经功能评估有助于AD的诊断和评估。定量模型可能有助于更好地理解该疾病的病理生理学及其进展评估。
