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

Ryan S. O'Dell; Albert Higgins-Chen; Dhruva Gupta; Ming-Kai Chen; Mika Naganawa; Takuya Toyonaga; Yihuan Lu; Gessica Ni; Anna Chupak; Wenzhen Zhao; Elaheh Salardini; Nabeel B. Nabulsi; Yiyun Huang; Amy F.T. Arnsten; Richard E. Carson; Christopher H. van Dyck; Adam P. Mecca

NeuroImage: Clinical (Jan 2023)

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

Ryan S. O'Dell,
Albert Higgins-Chen,
Dhruva Gupta,
Ming-Kai Chen,
Mika Naganawa,
Takuya Toyonaga,
Yihuan Lu,
Gessica Ni,
Anna Chupak,
Wenzhen Zhao,
Elaheh Salardini,
Nabeel B. Nabulsi,
Yiyun Huang,
Amy F.T. Arnsten,
Richard E. Carson,
Christopher H. van Dyck,
Adam P. Mecca

Affiliations

Ryan S. O'Dell: Alzheimer’s Disease Research Unit, Yale University School of Medicine, One Church Street, 8th Floor, New Haven, CT 06510, USA; Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT 06510, USA
Albert Higgins-Chen: Alzheimer’s Disease Research Unit, Yale University School of Medicine, One Church Street, 8th Floor, New Haven, CT 06510, USA; Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT 06510, USA; Pain Research, Informatics, Multi-morbidities, and Education Center, VA Connecticut Healthcare System, West Haven, CT, USA
Dhruva Gupta: Alzheimer’s Disease Research Unit, Yale University School of Medicine, One Church Street, 8th Floor, New Haven, CT 06510, USA
Ming-Kai Chen: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, P.O. Box 208048, New Haven, CT 06520, USA
Mika Naganawa: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, P.O. Box 208048, New Haven, CT 06520, USA
Takuya Toyonaga: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, P.O. Box 208048, New Haven, CT 06520, USA
Yihuan Lu: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, P.O. Box 208048, New Haven, CT 06520, USA
Gessica Ni: Alzheimer’s Disease Research Unit, Yale University School of Medicine, One Church Street, 8th Floor, New Haven, CT 06510, USA; Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT 06510, USA
Anna Chupak: Alzheimer’s Disease Research Unit, Yale University School of Medicine, One Church Street, 8th Floor, New Haven, CT 06510, USA; Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT 06510, USA
Wenzhen Zhao: Alzheimer’s Disease Research Unit, Yale University School of Medicine, One Church Street, 8th Floor, New Haven, CT 06510, USA; Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT 06510, USA
Elaheh Salardini: Alzheimer’s Disease Research Unit, Yale University School of Medicine, One Church Street, 8th Floor, New Haven, CT 06510, USA; Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT 06510, USA
Nabeel B. Nabulsi: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, P.O. Box 208048, New Haven, CT 06520, USA
Yiyun Huang: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, P.O. Box 208048, New Haven, CT 06520, USA
Amy F.T. Arnsten: Department of Neuroscience, Yale University School of Medicine, P.O. Box 208001, New Haven, CT 06520, USA
Richard E. Carson: Department of Radiology and Biomedical Imaging, Yale University School of Medicine, P.O. Box 208048, New Haven, CT 06520, USA
Christopher H. van Dyck: Alzheimer’s Disease Research Unit, Yale University School of Medicine, One Church Street, 8th Floor, New Haven, CT 06510, USA; Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT 06510, USA; Department of Neuroscience, Yale University School of Medicine, P.O. Box 208001, New Haven, CT 06520, USA; Department of Neurology, Yale University School of Medicine, P.O. Box 208018, New Haven, CT 06520, USA
Adam P. Mecca: Alzheimer’s Disease Research Unit, Yale University School of Medicine, One Church Street, 8th Floor, New Haven, CT 06510, USA; Department of Psychiatry, Yale University School of Medicine, 300 George Street, New Haven, CT 06510, USA; Corresponding author at: Alzheimer’s Disease Research Unit, Yale University School of Medicine, One Church Street, 8th Floor, New Haven, CT 06510, USA.

Journal volume & issue: Vol. 39
p. 103457

Abstract

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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.

Published in NeuroImage: Clinical

ISSN: 2213-1582 (Online)
Publisher: Elsevier
Country of publisher: Netherlands
LCC subjects: Medicine: Medicine (General): Computer applications to medicine. Medical informatics; Medicine: Internal medicine: Neurosciences. Biological psychiatry. Neuropsychiatry: Neurology. Diseases of the nervous system
Website: http://www.journals.elsevier.com/neuroimage-clinical/

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