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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...
Autores principales: | , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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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. |
format | Online Article Text |
id | pubmed-10338149 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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