Principal component analysis of synaptic density measured with [11C] UCB-J PET in early Alzheimer's disease

被引:2
|
作者
O'Dell, Ryan S. [1 ,2 ]
Higgins-Chen, Albert [1 ,2 ,3 ]
Gupta, Dhruva [1 ]
Chen, Ming -Kai [4 ]
Naganawa, Mika [4 ]
Toyonaga, Takuya [4 ]
Lu, Yihuan [4 ]
Ni, Gessica [1 ,2 ]
Chupak, Anna [1 ,2 ]
Zhao, Wenzhen [1 ,2 ]
Salardini, Elaheh [1 ,2 ]
Nabulsi, Nabeel B. [4 ]
Huang, Yiyun [4 ]
Arnsten, Amy F. T. [5 ]
Carson, Richard E. [4 ]
van Dyck, Christopher H. [1 ,2 ,5 ,6 ]
Mecca, Adam P. [1 ,2 ]
机构
[1] Yale Univ, Alzheimers Dis Res Unit, Sch Med, One Church St,8th Floor, New Haven, CT 06510 USA
[2] Yale Univ, Sch Med, Dept Psychiat, 300 George St, New Haven, CT 06510 USA
[3] VA Connecticut Healthcare Syst, Pain Res Informat Multimorbid & Educ Ctr Innovat, West Haven, CT USA
[4] Yale Univ, Sch Med, Dept Radiol & Biomed Imaging, POB 208048, New Haven, CT 06520 USA
[5] Yale Univ, Sch Med, Dept Neurosci, POB 208001, New Haven, CT 06520 USA
[6] Yale Univ, Sch Med, Dept Neurol, POB 208018, New Haven, CT 06520 USA
基金
美国国家卫生研究院;
关键词
Alzheimer's disease; Synaptic density; SV2A; 11C]UCB-J; Positron emission tomography; Principal component analysis; PARTIAL VOLUME CORRECTION; ASSOCIATION WORKGROUPS; DIAGNOSTIC GUIDELINES; NATIONAL INSTITUTE; MILD; DEMENTIA; RECOMMENDATIONS; MULTIVARIATE; PROGRESSION; IMPAIRMENT;
D O I
10.1016/j.nicl.2023.103457
中图分类号
R445 [影像诊断学];
学科分类号
100207 ;
摘要
Background: Synaptic loss is considered an early pathological event and major structural correlate of cognitive impairment in Alzheimer's disease (AD). We used principal component analysis (PCA) to identify regional patterns of covariance in synaptic density using [11C]UCB-J PET and assessed the association between principal components (PC) subject scores with cognitive performance. Methods: [11C]UCB-J binding was measured in 45 amyloid + participants with AD and 19 amyloid- cognitively normal participants aged 55-85. A validated neuropsychological battery assessed performance across five cognitive domains. PCA was applied to the pooled sample using distribution volume ratios (DVR) standardized (z-scored) by region from 42 bilateral regions of interest (ROI). Results: Parallel analysis determined three significant PCs explaining 70.2% of the total variance. PC1 was characterized by positive loadings with similar contributions across the majority of ROIs. PC2 was characterized by positive and negative loadings with strongest contributions from subcortical and parietooccipital cortical regions, respectively, while PC3 was characterized by positive and negative loadings with strongest contributions from rostral and caudal cortical regions, respectively. Within the AD group, PC1 subject scores were positively correlated with performance across all cognitive domains (Pearson r = 0.24-0.40, P = 0.06-0.006), PC2 subject scores were inversely correlated with age (Pearson r = -0.45, P = 0.002) and PC3 subject scores were significantly correlated with CDR-sb (Pearson r = 0.46, P = 0.04). No significant correlations were observed between cognitive performance and PC subject scores in CN participants. Conclusions: This data-driven approach defined specific spatial patterns of synaptic density correlated with unique participant characteristics within the AD group. Our findings reinforce synaptic density as a robust biomarker of disease presence and severity in the early stages of AD.
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页数:11
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