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Principal Investigator  
Principal Investigator's Name: Alexandra Weigand
Institution: University of California San Diego
Department: Psychiatry
Country:
Proposed Analysis: Rationale: Research in Alzheimer’s disease (AD) has shifted toward identifying individuals at increased biological risk for the disease prior to the development of clinically manifest symptoms. Although amyloid-beta (Ab)-centric frameworks of AD pathogenesis still predominate, recent advances in tau biomarkers provide an opportunity to better characterize the polypathologic nature of preclinical AD. Design: This proposal contains the following 3 aims, plus an additional 4th aim: (1) empirically assess the proportion studies using thresholding methods for tau positron emission tomography (PET) positivity that are contingent on Ab, as well as differences in resultant mean threshold values and tau positivity rates, based on a systematic literature review; (2) identify the prevalence of Ab and tau (A/T) PET positivity groups and their cognitive profiles; (3) examine the longitudinal cognitive trajectories of A/T groups from Aim 2; and (4) explore apolipoprotein E e4 genetic risk as a moderator on the independent associations of Ab and tau PET with cognition. Participants will be selected from the Alzheimer’s Disease Neuroimaging Initiative based on available data for each aim. Sample size will vary for each aim, but currently at least 523 individuals have concurrent Ab and tau PET data. For Aim 1, relevant studies will be identified using several keywords such as “tau PET positivity.” Outcomes between methods that are or are not conditional on amyloid will be compared with t-tests (threshold value) and Chi-squared tests (tau positivity). For Aims 2–4, cognition will be assessed using composites of memory, language, and attention/executive function, and regional PET variables will be examined. Aim 2 will use conditional inference decision trees to derive PET thresholds and analysis of covariance to assess group differences in cognition; Aim 3 will use multiple linear regression or linear mixed effects models, depending on available data; and Aim 4 will use polynomial multiple linear regression. Models will include relevant covariates (e.g., age, sex) as appropriate, and statistical significance will be set at alpha = .05 with multiple comparison correction applied. Relevance: Findings will elucidate the role of tau independently of Ab in AD pathogenesis, which will improve our conceptualization of AD progression and promote novel treatment targets for early intervention.
Additional Investigators