EEG Functional Connectivity Differences Predict Future Conversion to Dementia in Mild Cognitive Impairment With Lewy Body or Alzheimer Disease

IF 3.6 3区医学 Q2 GERIATRICS & GERONTOLOGY

International Journal of Geriatric Psychiatry Pub Date : 2024-09-11 DOI:10.1002/gps.6138

Jahfer Hasoon, Calum A. Hamilton, Julia Schumacher, Sean Colloby, Paul C. Donaghy, Alan J. Thomas, John-Paul Taylor

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引用次数: 0

Abstract

Background

Predicting which individuals may convert to dementia from mild cognitive impairment (MCI) remains difficult in clinical practice. Electroencephalography (EEG) is a widely available investigation but there is limited research exploring EEG connectivity differences in patients with MCI who convert to dementia.

Methods

Participants with a diagnosis of MCI due to Alzheimer's disease (MCI-AD) or Lewy body disease (MCI-LB) underwent resting state EEG recording. They were followed up annually with a review of the clinical diagnosis (n = 66). Participants with a diagnosis of dementia at year 1 or year 2 follow up were classed as converters (n = 23) and those with a diagnosis of MCI at year 2 were classed as stable (n = 43). We used phase lag index (PLI) to estimate functional connectivity as well as analysing dominant frequency (DF) and relative band power. The Network-based statistic (NBS) toolbox was used to assess differences in network topology.

Results

The converting group had reduced DF (U = 285.5, p = 0.005) and increased relative pre-alpha power (U = 702, p = 0.005) consistent with previous findings. PLI showed reduced average beta band synchrony in the converting group (U = 311, p = 0.014) as well as significant differences in alpha and beta network topology. Logistic regression models using regional beta PLI values revealed that right central to right lateral (Sens = 56.5%, Spec = 86.0%, −2LL = 72.48, p = 0.017) and left central to right lateral (Sens = 47.8%, Spec = 81.4%, −2LL = 71.37, p = 0.012) had the best classification accuracy and fit when adjusted for age and MMSE score.

Conclusion

Patients with MCI who convert to dementia have significant differences in EEG frequency, average connectivity and network topology prior to the onset of dementia. The MCI group is clinically heterogeneous and have underlying physiological differences that may be driving the progression of cognitive symptoms. EEG connectivity could be useful to predict which patients with MCI-AD and MCI-LB convert to dementia, regardless of the neurodegenerative aetiology.

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脑电图功能连接性差异可预测轻度认知障碍伴路易体或阿尔茨海默病患者未来向痴呆症的转化

背景在临床实践中，预测哪些人可能会从轻度认知障碍（MCI）转为痴呆症仍然是个难题。脑电图（EEG）是一种广泛使用的检查方法，但对MCI患者转化为痴呆症的脑电图连接性差异的研究却很有限。方法对诊断为阿尔茨海默病（MCI-AD）或路易体病（MCI-LB）导致的 MCI 患者进行静息状态脑电图记录。每年对他们进行随访，并对临床诊断进行复查（n = 66）。第1年或第2年随访时诊断为痴呆症的参与者被归类为转换者（n = 23），第2年诊断为MCI的参与者被归类为稳定者（n = 43）。我们使用相位滞后指数（PLI）估算功能连接性，并分析主导频率（DF）和相对频带功率。基于网络的统计（NBS）工具箱用于评估网络拓扑结构的差异。结果转换组的主导频率降低（U = 285.5，p = 0.005），相对α前功率增加（U = 702，p = 0.005），这与之前的研究结果一致。PLI 显示，转换组的β波段平均同步性降低（U = 311，p = 0.014），α和β网络拓扑结构也存在显著差异。使用区域贝塔PLI值的逻辑回归模型显示，在对年龄和MMSE评分进行调整后，右中央到右外侧（Sens = 56.5%，Spec = 86.0%，-2LL = 72.48，p = 0.017）和左中央到右外侧（Sens = 47.8%，Spec = 81.4%，-2LL = 71.37，p = 0.012）的分类准确性和拟合度最好。结论 MCI 转为痴呆症的患者在痴呆症发病前的脑电图频率、平均连接性和网络拓扑结构存在显著差异。MCI 组在临床上具有异质性，其潜在的生理差异可能是认知症状进展的驱动因素。无论神经退行性病因如何，脑电图连通性都有助于预测哪些MCI-AD和MCI-LB患者会转变为痴呆症。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Geriatric Psychiatry 医学-精神病学

CiteScore

6.10

自引率

2.50%

发文量

168

审稿时长

4-8 weeks

期刊介绍： The rapidly increasing world population of aged people has led to a growing need to focus attention on the problems of mental disorder in late life. The aim of the Journal is to communicate the results of original research in the causes, treatment and care of all forms of mental disorder which affect the elderly. The Journal is of interest to psychiatrists, psychologists, social scientists, nurses and others engaged in therapeutic professions, together with general neurobiological researchers. The Journal provides an international perspective on the important issue of geriatric psychiatry, and contributions are published from countries throughout the world. Topics covered include epidemiology of mental disorders in old age, clinical aetiological research, post-mortem pathological and neurochemical studies, treatment trials and evaluation of geriatric psychiatry services.