Browsing by Subject "Alzheimer’s disease"
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Item Open Access APOE4-mediated amyloid-β pathology depends on its neuronal receptor LRP1.(The Journal of clinical investigation, 2019-02-11) Tachibana, Masaya; Holm, Marie-Louise; Liu, Chia-Chen; Shinohara, Mitsuru; Aikawa, Tomonori; Oue, Hiroshi; Yamazaki, Yu; Martens, Yuka A; Murray, Melissa E; Sullivan, Patrick M; Weyer, Kathrin; Glerup, Simon; Dickson, Dennis W; Bu, Guojun; Kanekiyo, TakahisaCarrying the ε4 allele of the APOE gene encoding apolipoprotein E (APOE4) markedly increases the risk for late-onset Alzheimer's disease (AD), in which APOE4 exacerbates the brain accumulation and subsequent deposition of amyloid-β (Aβ) peptides. While the LDL receptor-related protein 1 (LRP1) is a major apoE receptor in the brain, we found that its levels are associated with those of insoluble Aβ depending on APOE genotype status in postmortem AD brains. Thus, to determine the functional interaction of apoE4 and LRP1 in brain Aβ metabolism, we crossed neuronal LRP1-knockout mice with amyloid model APP/PS1 mice and APOE3-targeted replacement (APO3-TR) or APOE4-TR mice. Consistent with previous findings, mice expressing apoE4 had increased Aβ deposition and insoluble amounts of Aβ40 and Aβ42 in the hippocampus of APP/PS1 mice compared with those expressing apoE3. Intriguingly, such effects were reversed in the absence of neuronal LRP1. Neuronal LRP1 deficiency also increased detergent-soluble apoE4 levels, which may contribute to the inhibition of Aβ deposition. Together, our results suggest that apoE4 exacerbates Aβ pathology through a mechanism that depends on neuronal LRP1. A better understanding of apoE isoform-specific interaction with their metabolic receptor LRP1 on Aβ metabolism is crucial for defining APOE4-related risk for AD.Item Open Access Bayesian Functional Joint Models for Multivariate Longitudinal and Time-to-Event Data.(Computational statistics & data analysis, 2019-01) Li, Kan; Luo, ShengA multivariate functional joint model framework is proposed which enables the repeatedly measured functional outcomes, scalar outcomes, and survival process to be modeled simultaneously while accounting for association among the multiple (functional and scalar) longitudinal and survival processes. This data structure is increasingly common across medical studies of neurodegenerative diseases and is exemplified by the motivating Alzheimer's Disease Neuroimaging Initiative (ADNI) study, in which serial brain imaging, clinical and neuropsychological assessments are collected to measure the progression of Alzheimer's disease (AD). The proposed functional joint model consists of a longitudinal function-on-scalar submodel, a regular longitudinal submodel, and a survival submodel which allows time-dependent functional and scalar covariates. A Bayesian approach is adopted for parameter estimation and a dynamic prediction framework is introduced for predicting the subjects' future health outcomes and risk of AD conversion. The proposed model is evaluated by a simulation study and is applied to the motivating ADNI study.Item Open Access PET Imaging of Tau Pathology in Alzheimer's Disease and Tauopathies.(Frontiers in neurology, 2015-01) James, Olga G; Doraiswamy, P Murali; Borges-Neto, Salvador