Association of the APOE#6034 Allele with Progression of Alzheimer?s Disease

 


   Note: An Official Proposal has not been Submitted to NACC.


   Lead Investigator:    Xi Chen
   Institution      :    University of Rochester School of Medicine  Denti
   E-Mail           :    xi_chen@urmc.rochester.edu
   Proposal ID      :    1734



   Proposal Description:
   Aim 1. To analyze the effects of e4 and e2 alleles on the rate of AD progression (measured by neurocognitive batteries and MRI brain volumes) across ethnically diversified populations. All cross-sectional and longitudinal data will be analyzed across the #6033/ #6033, #6033/#6034, #6034/#6034 genotypes. One-way        analysis of variance (ANOVA) followed by Least Significant Difference (LSD) tests will be used to test between-group differences of clinical and demographic data. Both linear and non-linear multilevel modeling approaches will be used to compare rates of change in cognitive scores and brain volumes.  This analysis will be separated into the MCI stages and AD stages as determined by clinical diagnosis. A significant main effect of time would indicate that a given cognitive or volumetric measure changed significantly over time in all participants. A significant main effect of the #4004 allele would indicate that a baseline data set for a given measure varied significantly across #603 /#4003, #4003/#4004, and #4004/#4004 genotypes. A significant interaction between time and the #4004 allele would indicate that the rate of cognitive decline or brain atrophy   varied as a function of the #4004 allele. This interaction would determine not only the magnitude of an #4004 effect but also the allele-dose dependency pattern by directly comparing #4003/#4004 and #4004/#4004 genotypes. Repeat analysis will be    conducted with #4002 allele carriers, to assess potential attenuating effects on the trajectory of AD. Additionally, stratified analyses will be conducted on data collected after AD transition by stratifying the participants by median age of the transition, sex, race, and median education level.               Aim 2. To identify genetic covariates (e.g., Klotho-VS) modulating the effect of APOE e4 allele on the rate of AD progression. GWAS data will be analyzed using the software PLINK, creating a genetic profile for each participant that can be used as co