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O1‐10‐04: The impact of amyloid dynamics on cognition in a humanized quantitative systems pharmacology model
Author(s) -
Geerts Hugo,
Spiros Athan
Publication year - 2015
Publication title -
alzheimer's and dementia
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 6.713
H-Index - 118
eISSN - 1552-5279
pISSN - 1552-5260
DOI - 10.1016/j.jalz.2015.07.084
Subject(s) - amyloid (mycology) , neuroscience , cognition , psychology , medicine , pathology
might affect the estimates.Methods:We selected cognitively normal individuals aged 60-75, consistent with trial entry criteria, from the Framingham Heart Study (FHS: N1⁄49,369, 139 APOE44), Sacramento Area Latino Study on Aging (SALSA: N1⁄41,294, 11 E44), and National Alzheimer’s Coordinating Center (NACC: N1⁄44,103, 128 E44). We developed stratified cumulative incidence curves by age (60-64, 65-69, 70-75) and APOE4 dose. We also developed model-based estimates (using cause-specific hazard regression, a competing risks analogue of Cox proportional hazards model) to estimate risk of MCI/dementia by genotype and baseline age, with or without adjustment for gender, race, education, family history, vascular risk score, and baseline cognitive function. Results: Compared with typically reported figures, E44 genotype and E4 allele frequencies were higher in NACC (0.031, 0.17) and lower in SALSA (0.009, 0.075). Cumulative incidence of MCI/dementia within 5 years (5-year CI) was low in the two population-based cohorts, even for age 70-75: Framingham: 4.1%; SALSA: 8.6%, but higher in NACC: 18.4%. When stratifying on APOE4 dose (0, 1, 2 E4s), 5-year CI was also lower in Framingham (1.3%, 3.1%, 9.4%) and SALSA (4.9%, 11.7%, 19.2%) than NACC (12.3%, 19.0%, 32.8%). Despite small numbers, the same pattern emerged when stratifying on both gene dose and age, e.g., 70-75 and E44 20.2% in Framingham vs. 36.4% in NACC. In the modeled analysis, adding family history, less education, and worse baseline memory increased risk; differences in these features may partially account for observed differences in the unadjusted analyses. Conclusions:Variation across studies complicates the development of clear messages for prospective subjects in an APOE44 high-risk trial, and accurate power estimates. Stratified and modeled estimates and comprehensive vs. sparse models have advantages and disadvantages in providing the information needed to understand personal risk and to plan studies.