Although several previous studies have demonstrated navigational deficits in early-stage symptomatic Alzheimer's disease (AD), navigational abilities in preclinical AD have not been examined. The present investigation examined the effects of preclinical AD and early-stage symptomatic AD on spatial navigation performance. Performance on tasks of wayfinding and route learning in a virtual reality environment were examined. Comparisons were made across the following three groups: Clinically normal without preclinical AD (n = 42), clinically normal with preclinical AD (n = 13), and early-stage symptomatic AD (n = 16) groups. Preclinical AD was defined based on cerebrospinal fluid Aβ42 levels below 500 pg/ml. Preclinical AD was associated with deficits in the use of a wayfinding strategy, but not a route learning strategy. Moreover, post-hoc analyses indicated that wayfinding performance had moderate sensitivity and specificity. Results also confirmed early-stage symptomatic AD-related deficits in the use of both wayfinding and route learning strategies. The results of this study suggest that aspects of spatial navigation may be particularly sensitive at detecting the earliest cognitive deficits of AD.

This study investigated differences in retrospective cognitive trajectories between amyloid and tau PET biomarker stratified groups in initially cognitively unimpaired participants sampled from the Wisconsin Registry for Alzheimer’s Prevention. One hundred and sixty-seven initially unimpaired individuals (baseline age 59 ± 6 years; 115 females) were stratified by elevated amyloid-β and tau status based on 11C-Pittsburgh compound B (PiB) and 18F-MK-6240 PET imaging. Mixed effects models were used to determine if longitudinal cognitive trajectories based on a composite of cognitive tests including memory and executive function differed between biomarker groups. Secondary analyses investigated group differences for a variety of cross-sectional health and cognitive tests, and associations between 18F-MK-6240, 11C-PiB, and age. A significant group × age interaction was observed with post hoc comparisons indicating that the group with both elevated amyloid and tau pathophysiology were declining approximately three times faster in retrospective cognition compared to those with just one or no elevated biomarkers. This result was robust against various thresholds and medial temporal lobe regions defining elevated tau. Participants were relatively healthy and mostly did not differ between biomarker groups in health factors at the beginning or end of study, or most cognitive measures at study entry. Analyses investigating association between age, MK-6240 and PiB indicated weak associations between age and 18F-MK-6240 in tangle-associated regions, which were negligible after adjusting for 11C-PiB. Strong associations, particularly in entorhinal cortex, hippocampus and amygdala, were observed between 18F-MK-6240 and global 11C-PiB in regions associated with Braak neurofibrillary tangle stages I–VI. These results suggest that the combination of pathological amyloid and tau is detrimental to cognitive decline in preclinical Alzheimer’s disease during late middle-age. Within the Alzheimer’s disease continuum, middle-age health factors likely do not greatly influence preclinical cognitive decline. Future studies in a larger preclinical sample are needed to determine if and to what extent individual contributions of amyloid and tau affect cognitive decline. 18F-MK-6240 shows promise as a sensitive biomarker for detecting neurofibrillary tangles in preclinical Alzheimer’s disease.

Introduction This study applies a novel algorithm to longitudinal amyloid positron emission tomography (PET) imaging to identify age‐heterogeneous amyloid trajectory groups, estimate the age and duration (chronicity) of amyloid positivity, and investigate chronicity in relation to cognitive decline and tau burden. Methods Cognitively unimpaired participants (n = 257) underwent one to four amyloid PET scans (Pittsburgh Compound B, PiB). Group‐based trajectory modeling was applied to participants with longitudinal scans (n = 171) to identify and model amyloid trajectory groups, which were combined with Bayes theorem to estimate age and chronicity of amyloid positivity. Relationships between chronicity, cognition, clinical progression, and tau PET (MK‐6240) were investigated using regression models. Results Chronicity explained more heterogeneity in amyloid burden than age and binary amyloid status. Chronicity was associated with faster cognitive decline, increased risk of abnormal cognition, and higher entorhinal tau. Discussion Amyloid chronicity provides unique information about cognitive decline and neurofibrillary tangle development and may be useful to investigate preclinical Alzheimer's disease.