Associations of Amyloid Burden, White Matter Hyperintensities, and Hippocampal Volume With Cognitive Trajectories in
Jingxuan Wang1, Sarah Ackley1, Davis C Woodworth1
1From the Department of Epidemiology and Biostatistics (J.W.), University of California, San Francisco; Department of Epidemiology (J.W., S.A., M.M.G.), Boston University, MA; Department of Neurology (D.C.W., S.A.S., C.K., M.M.C.), University of California, Irvine; Imaging of Dementia and Aging Laboratory (C.S.D., E.F.F.), Department of Neurology, University of California, Davis; and Department of Epidemiology and Biostatistics (L.J., M.M.C.), and Department of Neurobiology and Behavior (C.K.), University of California, Irvine.
Background And Objectives:
Amyloid pathology, vascular disease pathology, and pathologies affecting the medial temporal lobe are associated with cognitive trajectories in older adults. However, only limited evidence exists on how these pathologies influence cognition in the oldest old. We evaluated whether amyloid burden, white matter hyperintensity (WMH) volume, and hippocampal volume (HV) are associated with cognitive level and decline in the oldest old.
Methods:
This was a longitudinal, observational community-based cohort study. We included participants with 18F-florbetapir PET and MRI data from the 90+ Study. Amyloid load was measured using the standardized uptake value ratio in the precuneus/posterior cingulate with eroded white matter mask as reference. WMH volume was log-transformed. All imaging measures were standardized using sample means and SDs. HV and log-WMH volume were normalized by total intracranial volume using the residual approach. Global cognitive performance was measured by the Mini-Mental State Examination (MMSE) and modified MMSE (3MS) tests, repeated every 6 months. We used linear mixed-effects models with random intercepts; random slopes; and interaction between time, time squared, and imaging variables to estimate the associations of imaging variables with cognitive level and cognitive decline. Models were adjusted for demographics, APOE genotype, and health behaviors.
Results:
The sample included 192 participants. The mean age was 92.9 years, 125 (65.1%) were female, 71 (37.0%) achieved a degree beyond college, and the median follow-up time was 3.0 years. A higher amyloid load was associated with a lower cognitive level (βMMSE = -0.82, 95% CI -1.17 to -0.46; β3MS = -2.77, 95% CI -3.69 to -1.84). A 1-SD decrease in HV was associated with a 0.70-point decrease in the MMSE score (95% CI -1.14 to -0.27) and a 2.27-point decrease in the 3MS score (95% CI -3.40 to -1.14). Clear nonlinear cognitive trajectories were detected. A higher amyloid burden and smaller HV were associated with faster cognitive decline. WMH volume was not significantly associated with cognitive level or decline.
Discussion:
Amyloid burden and hippocampal atrophy are associated with both cognitive level and cognitive decline in the oldest old. Our findings shed light on how different pathologies contributed to driving cognitive function in the oldest old.
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