Examining Complex Relationships among Cerebrovascular, β‐Amyloid, Tau and Cognitive Measures in a Cognitively Unimpaired Late‐Middle Aged Sample

Abstract

AbstractBackgroundRecent research linking vascular risk with promotion of tau pathology in the inferior temporal cortex (ITC) suggests a potential mechanism connecting cerebrovascular risk to AD pathology and cognitive decline among cognitively unimpaired (CU) individuals (Yau et al, 2022).We used MRI White Matter Hyperintensity (WMH), a neuroimaging marker of chronic cerebral small‐vessel disease/cerebrovascular disease, to further elucidate longitudinal relationships between cerebrovascular risk, PET AD pathological burden, and cognition.MethodWe examined baseline CU late middle‐aged adults from the University of Wisconsin’s Alzheimer’s disease research cohorts. β‐Amyloid burden was measured with 11C‐Pittsburgh compound B (“PiB”; DVR derived from a 0‐70 min dynamic PET scan; PET A+ threshold∼1.16 DVR/∼CL 17). Cerebrovascular risk was quantified using WMH volumes (T2‐FLAIR images; SPM Lesion Segmentation Tool). Tau burden was measured with florquinitau PET (MK6240 SUVR from 70‐90 min post‐injection). Tau outcomes included bilateral volume‐weighted averages for ITC, Medial temporal lobe (MTL) and Meta‐temporal (MTC) composites. Biomarker values were z‐transformed relative to CU/PET A‐ values. Random intercept models examined interactive effects of baseline WMH and Aβ levels on longitudinal tau (covarying baseline tau age, sex, APOE ε4 count). We modeled time two ways: years since baseline PiB (TimePiB1; replicating Yau, et al models); and, in parallel models, amyloid duration (years) at tau scans was substituted for years since PiB1 in the A+ subset (TimePiB1/PiB+). We also used LME to examine Aβ, WMH, and time interactions in longitudinal cognition (PACC3 and Digit Symbol Substitution).ResultThe mean(SD) tau baseline age was 67.9(6.8) years (sample details in Table1). The most parsimonious models using TimePiB1 included WMH*Aβ*Time for ITC and MTC and WMH*Aβ for MTL. Patterns showed a synergistic effect of WMH and Aβ on tau accumulation that was attenuated using TimePiB1/PiB+ where the most parsimonious models included Aβ_status*TimePiB1/PiB+ (ITC, MTC) or WMH*Aβ_status*TimePiB1/PiB+ (MTL; Figure1). AICc model fits were substantially better using TimePiB1/PiB+. Both Aβ and WMH contributed to cognitive trajectories (Figure2).ConclusionAlthough cerebrovascular risk’s apparent contribution to tau accumulation varied depending on how time was modeled, results suggest that cerebrovascular risk may complement imaging biomarkers in assessing risk of tau accumulation and cognitive decline in preclinical Alzheimer disease.