Longitudinal Characterization of Early Alzheimer's Disease Cognitive Subtypes

 
   Lead Investigator:    Graham Eglit
   Institution      :    San Diego Veterans Healthcare System
   E-Mail           :    geglit@ucsd.edu
   Proposal ID      :    1191



   Proposal Description:
   Alzheimer?s disease dementia is a heterogeneous clinical syndrome.  Previous research has identified distinct cognitive profiles in Alzheimer?s disease, especially in early, pre-dementia stages.  Furthermore, a recently published  study using NACC data (Barnes et al., 2015) reported heterogeneity in initial symptom presentation among AD patients, with initial non-memory symptoms more common among younger as opposed to older individuals.  However, to date, relatively little research has explored the longitudinal progression of these cognitive subgroups and whether transitions among these subgroups can be predicted by non-cognitive variables (demographics, vascular risk, psychiatric functioning).   To improve our understanding of early Alzheimer?s disease heterogeneity, the proposed project will use latent transition analysis to characterize early AD subgroups, identify which subgroups are at greatest risk for further cognitive decline, and identify risk/resiliency factors.              The goals of the project are the following:                                       (1) To determine the number, prevalence, and characteristics of cognitive subtypes among non-demented individuals who exhibit post-mortem AD neuropathological change.                                                         (2) To identify rates of stability and transition between cognitive subgroups and identify cognitive subgroups at greatest risk for further cognitive decline   (3) To identify non-cognitive risk/resiliency factors that predict transition between cognitive subgroups.                                                      This research will add to a growing literature base identifying heterogeneity in clinical presentation in early stages of Alzheimer?s disease.  In addition, this research will help to identify cognitive profiles that increase risk of further cognitive decline.