遗忘型轻度认知障碍个体的结构网络改变及其与阿尔茨海默病发病的预测研究

Structural network changes in individuals with amnestic mild cognitive impairment and their association with the onset of Alzheimer's disease

目的探究遗忘型轻度认知障碍(aMCI)个体的结构网络改变及其与阿尔茨海默病(AD)发病的相关性。方法前瞻性收集100例aMCI个体以及25名与之年龄、性别相匹配的健康对照者作为研究对象。所有受试者入组后均接受系统的MRI扫描和相关临床量表评估,随后进行长达3年的纵向随访(每6个月1次)。根据随访期内是否发生AD,所有aMCI受试者被分为稳定型aMCI组以及进展型aMCI组。采用中文版简易精神状态检查量表(MMSE)、蒙特利尔认知评估量表(MoCA)、临床痴呆评定量表(CDR)以及听觉词语学习测试(AVLT)评估受试者的整体精神及认知状况。基于Pearson相关分析探究受试者的脑结构网络属性与认知改变的相关性。构建Logistic回归模型探究aMCI个体脑结构网络属性对于AD的预测效能。结果与稳定型aMCI组相比,进展型aMCI组表现出全局效率(P=0.002)、局部效率(P=0.007)、feeder连接(P=0.003)、local连接(P=0.008)以及右侧楔前叶节点效率(P=0.010)的降低。相关分析显示基线时全局效率(r=0.604,P=0.002)、feeder连接(r=0.513,P=0.012)和楔前叶节点效率(r=0.504,P=0.014)与进展型aMCI组的AVLT延迟评分相关。Logistic回归模型显示全局效率、feeder连接和右侧楔前叶节点效率可以预测未来AD的发生,并且具有良好的预测效能(均P<0.05,AUC联合=0.797,95%CI:0.684~0.884,敏感度=73.91,95%CI:51.6~89.8,特异度=76.60,95%CI:62.0~87.7)。结论在已经出现aMCI的个体中,存在全局效率、feeder连接或者右侧楔前叶节点效率改变的个体在未来更容易发展为AD,这些指标有望成为新的临床干预靶点。

ObjectiveTo examine the structural network changes in participants with amnestic mild cognitive impairment(aMCI)and investigate the correlation between these changes and the onset of Alzheimer's disease(AD).MethodsIn this prospective study,a total of 100 individuals with amnestic mild cognitive impairment(aMCI)were enrolled as the research group.Additionally,25 healthy individuals who were matched in terms of age and sex were enrolled as healthy controls.Upon enrollment,all participants underwent MRI scans,neuropsychological assessments,and clinical evaluations.The participants were then followed every 6 months for a period of 36 months or until they withdrew from the study.Based on the outcome of the follow-up(whether Alzheimer's disease occurred),the aMCI participants were divided into two groups:stable aMCI group and progressive aMCI group.The Chinese version of the Brief Mental State Examination(MMSE),the Montreal Cognitive Assessment(MoCA),the Clinical Dementia Rating Scale(CDR),and the Auditory Word Learning Test(AVLT)were utilized to evaluate the overall mental and cognitive status of the subjects.Pearson correlation analysis was employed to investigate the relationship between structural network changes and cognitive decline.Logistic regression was performed to analyze the predictive ability of structural network changes in determining the onset of AD.ResultsCompared to the stable aMCI group,the progressive aMCI group exhibited lower levels of global efficiency(P=0.002),local efficiency(P=0.007),feeder connections(P=0.003),local connections(P=0.008),and right precuneus nodal efficiency(P=0.010).Correlation analysis revealed that global efficiency(r=0.604,P=0.002),feeder connections(r=0.513,P=0.012),and right precuneus nodal efficiency(r=0.504,P=0.014)were correlated with AVLT-delay scores(baseline)in the progressive aMCI group.A logistic regression model demonstrated that global efficiency,feeder connections,and right precuneus nodal efficiency could significantly predict the onset of AD(all P<0.05,AUCunited=0.797,95%CI:0.684-0.884,sensitivity=73.91,95%CI:51.6-89.8,specificity=76.60,95%CI:62.0-87.7).ConclusionsAmong participants with aMCI,individuals who exhibit lower global efficiency,feeder connections,or right precuneus nodal efficiency are at a higher risk of developing AD.These indicators are anticipated to serve as new targets for clinical intervention.