2012
DOI: 10.1016/j.neurobiolaging.2011.05.028
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Modeling regional vulnerability to Alzheimer pathology

Abstract: Latent growth curve (LGC) models estimate change over time in a cohort's serially obtained measurements. We have applied LGC techniques to a spatial distribution of Alzheimer's disease (AD) pathology using autopsy data from 435 participants in the Honolulu-Asia Aging Study. Neurofibrillary tangle (NFT) and neuritic plaques (NP) were distributed across differently ordered sets of anatomical regions. The gradient of spatial change in NP (dNP), was significantly associated with that of NFT (dNFT), but weakly and … Show more

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Cited by 12 publications

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“…We have previously shown in HAAS data that NP are arranged corticofugally in space [2] and that neocortical NFT develop contemporaneously with neocortical NP over the course of CASI surveillance [11]. This supports our conclusion that NP-related NFT formation is corticofugal, and suggests that the process has clinical consequences.…”
Section: Discussion
supporting
confidence: 88%
“…Mean lesion counts by anatomical region have been reported elsewhere [2]. Model fit was excellent (χ 2 :df = 108.0:32, p <0.001; RMSEA = 0.027; CFI= 0.976; BCC = 315.05).…”
Section: Results
mentioning
confidence: 77%
“…NFT in hippocampal regions (CA1 |r| = 0.58; subiculum In general, these factor loadings reveal that regional NP-related NFT counts share most variance with NP counts in the same structures. This does not seem surprising until one realizes that the observable corticofugal temporal spread of amyloid-␤ is incompatible with the hypothesized corticotropic temporal spread of NFT hypothesized by Braak, and confirmed in crosssectional autopsy data [2].…”
Section: Sample Characteristics Are Presented In Table
mentioning
confidence: 82%
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