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

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 [(11)C]UCB-J PET and assessed the a...

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Autores principales: O'Dell, Ryan S., Higgins-Chen, Albert, Gupta, Dhruva, Chen, Ming-Kai, Naganawa, Mika, Toyonaga, Takuya, Lu, Yihuan, Ni, Gessica, Chupak, Anna, Zhao, Wenzhen, Salardini, Elaheh, Nabulsi, Nabeel B., Huang, Yiyun, Arnsten, Amy F.T., Carson, Richard E., van Dyck, Christopher H., Mecca, Adam P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338149/
https://www.ncbi.nlm.nih.gov/pubmed/37422964
http://dx.doi.org/10.1016/j.nicl.2023.103457
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author O'Dell, Ryan S.
Higgins-Chen, Albert
Gupta, Dhruva
Chen, Ming-Kai
Naganawa, Mika
Toyonaga, Takuya
Lu, Yihuan
Ni, Gessica
Chupak, Anna
Zhao, Wenzhen
Salardini, Elaheh
Nabulsi, Nabeel B.
Huang, Yiyun
Arnsten, Amy F.T.
Carson, Richard E.
van Dyck, Christopher H.
Mecca, Adam P.
author_facet O'Dell, Ryan S.
Higgins-Chen, Albert
Gupta, Dhruva
Chen, Ming-Kai
Naganawa, Mika
Toyonaga, Takuya
Lu, Yihuan
Ni, Gessica
Chupak, Anna
Zhao, Wenzhen
Salardini, Elaheh
Nabulsi, Nabeel B.
Huang, Yiyun
Arnsten, Amy F.T.
Carson, Richard E.
van Dyck, Christopher H.
Mecca, Adam P.
author_sort O'Dell, Ryan S.
collection PubMed
description 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 [(11)C]UCB-J PET and assessed the association between principal components (PC) subject scores with cognitive performance. METHODS: [(11)C]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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spelling pubmed-103381492023-07-13 Principal component analysis of synaptic density measured with [(11)C]UCB-J PET in early Alzheimer’s disease O'Dell, Ryan S. Higgins-Chen, Albert Gupta, Dhruva Chen, Ming-Kai Naganawa, Mika Toyonaga, Takuya Lu, Yihuan Ni, Gessica Chupak, Anna Zhao, Wenzhen Salardini, Elaheh Nabulsi, Nabeel B. Huang, Yiyun Arnsten, Amy F.T. Carson, Richard E. van Dyck, Christopher H. Mecca, Adam P. Neuroimage Clin Regular Article 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 [(11)C]UCB-J PET and assessed the association between principal components (PC) subject scores with cognitive performance. METHODS: [(11)C]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. Elsevier 2023-06-22 /pmc/articles/PMC10338149/ /pubmed/37422964 http://dx.doi.org/10.1016/j.nicl.2023.103457 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
O'Dell, Ryan S.
Higgins-Chen, Albert
Gupta, Dhruva
Chen, Ming-Kai
Naganawa, Mika
Toyonaga, Takuya
Lu, Yihuan
Ni, Gessica
Chupak, Anna
Zhao, Wenzhen
Salardini, Elaheh
Nabulsi, Nabeel B.
Huang, Yiyun
Arnsten, Amy F.T.
Carson, Richard E.
van Dyck, Christopher H.
Mecca, Adam P.
Principal component analysis of synaptic density measured with [(11)C]UCB-J PET in early Alzheimer’s disease
title Principal component analysis of synaptic density measured with [(11)C]UCB-J PET in early Alzheimer’s disease
title_full Principal component analysis of synaptic density measured with [(11)C]UCB-J PET in early Alzheimer’s disease
title_fullStr Principal component analysis of synaptic density measured with [(11)C]UCB-J PET in early Alzheimer’s disease
title_full_unstemmed Principal component analysis of synaptic density measured with [(11)C]UCB-J PET in early Alzheimer’s disease
title_short Principal component analysis of synaptic density measured with [(11)C]UCB-J PET in early Alzheimer’s disease
title_sort principal component analysis of synaptic density measured with [(11)c]ucb-j pet in early alzheimer’s disease
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10338149/
https://www.ncbi.nlm.nih.gov/pubmed/37422964
http://dx.doi.org/10.1016/j.nicl.2023.103457
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