Toward personalized cognitive diagnostics of at-genetic-risk Alzheimer's disease.

ABSTRACT: Spatial navigation is emerging as a critical factor in identifying preclinical Alzheimer's disease (AD). However, the impact of interindividual navigation ability and demographic risk factors (e.g., APOE, age, and sex) on spatial navigation make it difficult to identify persons "at high risk" of AD in the preclinical stages. In the current study, we use spatial navigation big data (n = 27,108) from the Sea Hero Quest (SHQ) game to overcome these challenges by investigating whether big data can be used to benchmark a highly phenotyped healthy aging laboratory cohort into high- vs. low-risk persons based on their genetic (APOE) and demographic (sex, age, and educational attainment) risk factors. Our results replicate previous findings in APOE ε4 carriers, indicative of grid cell codin

SUBMITTER: Coughlan G 

PROVIDER: S-EPMC6511014 | biostudies-literature | 2019 May

REPOSITORIES: biostudies-literature