{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,29]],"date-time":"2026-03-29T01:21:16Z","timestamp":1774747276381,"version":"3.50.1"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"2","license":[{"start":{"date-parts":[[2024,3,26]],"date-time":"2024-03-26T00:00:00Z","timestamp":1711411200000},"content-version":"vor","delay-in-days":85,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000049","name":"National Institute on Aging","doi-asserted-by":"publisher","award":["P30AG066508, P50AG047270, K23AG057784, R01AG052560, R01AG062276, RF1AG057553 and P30AG021342"],"award-info":[{"award-number":["P30AG066508, P50AG047270, K23AG057784, R01AG052560, R01AG062276, RF1AG057553 and P30AG021342"]}],"id":[{"id":"10.13039\/100000049","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100005331","name":"American Brain Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100005331","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100001068","name":"Dana Foundation","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100001068","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Clinical and Translational Science","award":["UL1TR000142"],"award-info":[{"award-number":["UL1TR000142"]}]},{"DOI":"10.13039\/100006108","name":"National Center for Advancing Translational Science","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100006108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institute of Health","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Synaptic loss is a primary pathology in Alzheimer\u2019s disease and correlates best with cognitive impairment as found in post-mortem studies. Previously, we observed in vivo reductions of synaptic density with [11C]UCB-J PET (radiotracer for synaptic vesicle protein 2A) throughout the neocortex and medial temporal brain regions in early Alzheimer\u2019s disease. In this study, we applied independent component analysis to synaptic vesicle protein 2A-PET data to identify brain networks associated with cognitive deficits in Alzheimer\u2019s disease in a blinded data-driven manner. [11C]UCB-J binding to synaptic vesicle protein 2A was measured in 38 Alzheimer\u2019s disease (24 mild Alzheimer\u2019s disease dementia and 14 mild cognitive impairment) and 19 cognitively normal participants. [11C]UCB-J distribution volume ratio values were calculated with a whole cerebellum reference region. Principal components analysis was first used to extract 18 independent components to which independent component analysis was then applied. Subject loading weights per pattern were compared between groups using Kruskal\u2013Wallis tests. Spearman\u2019s rank correlations were used to assess relationships between loading weights and measures of cognitive and functional performance: Logical Memory II, Rey Auditory Verbal Learning Test\u2014long delay, Clinical Dementia Rating sum of boxes and Mini-Mental State Examination. We observed significant differences in loading weights among cognitively normal, mild cognitive impairment and mild Alzheimer\u2019s disease dementia groups in 5 of the 18 independent components, as determined by Kruskal\u2013Wallis tests. Only Patterns 1 and 2 demonstrated significant differences in group loading weights after correction for multiple comparisons. Excluding the cognitively normal group, we observed significant correlations between the loading weights for Pattern 1 (left temporal cortex and the cingulate gyrus) and Clinical Dementia Rating sum of boxes (r = \u22120.54, P = 0.0019), Mini-Mental State Examination (r = 0.48, P = 0.0055) and Logical Memory II score (r = 0.44, P = 0.013). For Pattern 2 (temporal cortices), significant associations were demonstrated between its loading weights and Logical Memory II score (r = 0.34, P = 0.0384). Following false discovery rate correction, only the relationship between the Pattern 1 loading weights with Clinical Dementia Rating sum of boxes (r = \u22120.54, P = 0.0019) and Mini-Mental State Examination (r = 0.48, P = 0.0055) remained statistically significant. We demonstrated that independent component analysis could define coherent spatial patterns of synaptic density. Furthermore, commonly used measures of cognitive performance correlated significantly with loading weights for two patterns within only the mild cognitive impairment\/mild Alzheimer\u2019s disease dementia group. This study leverages data-centric approaches to augment the conventional region-of-interest\u2013based methods, revealing distinct patterns that differentiate between mild cognitive impairment and mild Alzheimer\u2019s disease dementia, marking a significant advancement in the field.<\/jats:p>","DOI":"10.1093\/braincomms\/fcae107","type":"journal-article","created":{"date-parts":[[2024,3,25]],"date-time":"2024-03-25T23:10:49Z","timestamp":1711408249000},"source":"Crossref","is-referenced-by-count":7,"title":["Synaptic density patterns in early Alzheimer\u2019s disease assessed by independent component analysis"],"prefix":"10.1093","volume":"6","author":[{"given":"Xiaotian T","family":"Fang","sequence":"first","affiliation":[{"name":"Yale PET Center, Yale University School of Medicine , New Haven, CT 06520 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5637-7219","authenticated-orcid":false,"given":"Nakul 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USA"},{"name":"Department of Radiology and Biomedical Imaging, Yale University School of Medicine , New Haven, CT 06520 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Adam P","family":"Mecca","sequence":"additional","affiliation":[{"name":"Alzheimer\u2019s Disease Research Unit, Yale University School of Medicine , New Haven, CT 06520 , USA"},{"name":"Department of Psychiatry, Yale University School of Medicine , New Haven, CT 06520 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ming-Kai","family":"Chen","sequence":"additional","affiliation":[{"name":"Yale PET Center, Yale University School of Medicine , New Haven, CT 06520 , USA"},{"name":"Department of Radiology and Biomedical Imaging, Yale University School of Medicine , New Haven, CT 06520 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher H","family":"van Dyck","sequence":"additional","affiliation":[{"name":"Alzheimer\u2019s Disease Research Unit, Yale University School of Medicine , New Haven, CT 06520 , USA"},{"name":"Department of Psychiatry, Yale University School of Medicine , New Haven, CT 06520 , USA"},{"name":"Department of Neurology, Yale University School of Medicine , New Haven, CT 06520 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Richard E","family":"Carson","sequence":"additional","affiliation":[{"name":"Yale PET Center, Yale University School of Medicine , New Haven, CT 06520 , USA"},{"name":"Department of Radiology and Biomedical Imaging, Yale University School of Medicine , New Haven, CT 06520 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2024,3,26]]},"reference":[{"issue":"2","key":"2024043010254708300_fcae107-B1","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1016\/0022-510X(87)90057-8","article-title":"A quantitative morphometric analysis of the neuronal and synaptic content of the frontal and temporal cortex in 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