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Background and Purpose— Evidence suggests that atrial fibrillation (AF) is associated with increased risk of cognitive decline and dementia, even in the absence of stroke. White matter disease (WMD) is a potential mechanism linking AF to cognitive impairment. In this study, we explored the association between prevalent AF and WMD. Methods— We performed a cross-sectional analysis of participants attending the ARIC-NCS (Atherosclerosis Risk in Communities–Neurocognitive Study) in 2011 to 2013 who underwent brain magnetic resonance imaging. AF was ascertained from study visit electrocardiograms or prior hospitalization codes. Extent of WMD was defined by measures of white matter (WM) microstructural integrity and WM hyperintensity volume. Multivariable linear regression models were used to assess the association between AF and WMD. Results— Among 1899 participants (mean age, 76 years; 28% black; 60% women), 133 (7%) had prevalent AF. After multivariable adjustment, differences between participants with and without AF were −0.001 (95% CI, −0.006 to 0.004) for global WM fractional anisotropy, 0.031×10 −4 mm 2 /s (95% CI, −0.075 to 0.137) for global WM mean diffusivity, and 0.08 mm 3 (95% CI, −0.14 to 0.30) for WM hyperintensity volume. Conclusions— The results suggest that there is no association between prevalent AF and WMD.

AbstractIntroductionLittle is known about the role of age on neurodegeneration and protein deposition in atypical variants of Alzheimer's disease (AD).MethodsRegional tau and β‐amyloid positron emission tomography standard uptake value ratios and gray matter volumes were calculated in a cohort of 42 participants with atypical AD. The relationship between regional metrics and age was modeled using a Bayesian hierarchical linear model.ResultsAge was strongly associated with tau uptake across all cortical regions, particularly parietal, with greater uptake in younger participants. Younger age was associated with smaller parietal and lateral temporal volumes. Regional β‐amyloid differed little by age. Age showed a stronger association with tau than volume and β‐amyloid in all cortical regions. Age was not associated with cognitive performance.DiscussionAge is an important determinant of severity of cortical tau uptake in atypical AD, with young participants more likely to show widespread and severe cortical tau uptake.

AbstractObjectiveTo investigate the associations of Pittsburgh compound‐B (PiB) uptake in white matter hyperintensities (WMH) and normal appearing white matter (NAWM) with white matter (WM) integrity measured with DTI and cognitive function in cognitively unimpaired older adults.MethodsCognitively unimpaired older adults from the population‐based Mayo Clinic Study of Aging (n = 537, age 65–95) who underwent both PiB PET and DTI were included. The associations of WM PiB standard uptake value ratio (SUVr) with fractional anisotropy (FA) and mean diffusivity (MD) in the WMH and NAWM were tested after adjusting for age. The associations of PiB SUVr with cognitive function z‐scores were tested after adjusting for age and global cortical PiB SUVr.ResultsThe WMH PiB SUVr was lower than NAWM PiB SUVr (P < 0.001). In the WMH, lower PiB SUVr correlated with lower FA (r = 0.21, P < 0.001), and higher MD (r = −0.31, P < 0.001). In the NAWM, lower PiB SUVr only correlated with higher MD (r = −0.10, P = 0.02). Both in the WMH and NAWM, lower PiB SUVr was associated with lower memory, language, and global cognitive function z‐scores after adjusting for age and global cortical PiB SUVr.InterpretationReduced PiB uptake in the WMH is associated with a loss of WM integrity and cognitive function after accounting for the global cortical PiB uptake, suggesting that WM PiB uptake may be an early biomarker of WM integrity that precedes cognitive impairment in older adults. When using WM as a reference region in cross‐sectional analysis of PiB SUVr, individual variability in WMH volume as well as age should be considered.

Abstract Introduction Quantitative in vivo measurement of brain amyloid burden is important for both research and clinical purposes. However, the existence of multiple imaging tracers presents challenges to the interpretation of such measurements. This study presents a direct comparison of Pittsburgh compound B–based and florbetapir‐based amyloid imaging in the same participants from two independent cohorts using a crossover design. Methods Pittsburgh compound B and florbetapir amyloid PET imaging data from three different cohorts were analyzed using previously established pipelines to obtain global amyloid burden measurements. These measurements were converted to the Centiloid scale to allow fair comparison between the two tracers. The mean and inter‐individual variability of the two tracers were compared using multivariate linear models both cross‐sectionally and longitudinally. Results Global amyloid burden measured using the two tracers were strongly correlated in both cohorts. However, higher variability was observed when florbetapir was used as the imaging tracer. The variability may be partially caused by white matter signal as partial volume correction reduces the variability and improves the correlations between the two tracers. Amyloid burden measured using both tracers was found to be in association with clinical and psychometric measurements. Longitudinal comparison of the two tracers was also performed in similar but separate cohorts whose baseline amyloid load was considered elevated (i.e., amyloid positive). No significant difference was detected in the average annualized rate of change measurements made with these two tracers. Discussion Although the amyloid burden measurements were quite similar using these two tracers as expected, difference was observable even after conversion into the Centiloid scale. Further investigation is warranted to identify optimal strategies to harmonize amyloid imaging data acquired using different tracers.

Objective: To determine the frequency and characteristics of symptomatic intracerebral hemorrhage in a population-based study Patients and Methods: The population-based Mayo Clinic Study of Aging included 4,994 participants age ≥50 years entered from 11/29/2004 to 3/11/2017. Participants with intracranial hemorrhage were identified using the Rochester Epidemiology Project medical records linkage system. Medical records of these individuals were reviewed. Each hemorrhage was classified as deep, lobar, or cerebellar intracerebral hemorrhage (ICH) or convexity subarachnoid hemorrhage (cSAH). Traumatic, subdural, non-convexal SAH, and epidural hemorrhages were excluded. Patient demographics, presence of hypertension, antithrombotic regimen, APOE genotype, and amyloid PET scan results were collected when available. Individuals with hemorrhages were matched 3:1 on age and gender to controls without symptomatic hemorrhage. Analyses within the cases and between the groups were performed. Results: Symptomatic hemorrhages were identified in 57 individuals for a frequency of 1.14%. Twenty-one were classified as deep, 26 lobar, 5 cerebellar, and 5 cSAH. Mean age at the time of hemorrhage was 80.9 years (SD ±7.9). 54.4% of hemorrhages occurred in men. Hypertension was present in 45.6%. Of those with lobar ICH or cSAH, 87.1% were on an antithrombotic compared to 65.6% of controls (p=0.02) and 32.3% of these were on warfarin compared to 12.9% of controls (p=0.01). APOE genotype was available in 54 of the 57. APOE e2 and/or e4 was found in 46.7% of those with lobar ICH/cSAH compared to 39.1% of controls (p=0.47) and 35.0% of those with deep ICH versus 39.3% of controls (p=0.73). Of the 31 with either lobar ICH or cSAH, 7 underwent amyloid PET scans; of these, 71.4% were abnormal compared to 42.9% of controls with mean SUVR of 1.911 and 1.565, respectively (p=0.08). Conclusions: Symptomatic ICH occurred in approximately 1 in 100 individuals age 50-94 years in this population-based study. In a matched case-control study, antithrombotic use (particularly warfarin) was statistically associated with the development of an ICH. While only a subset underwent amyloid PET, there was a trend towards greater amyloid load in those who developed a lobar or cSAH compared to controls.

Background: Although white matter hyperintensities (WMH) have been viewed as a marker of vascular disease, pathology studies have found an association of WMH with Alzheimer’s disease (AD) pathologies. Our objective was to investigate the topographic patterns of WMH associated with AD biomarkers. Methods: From the population-based Mayo Clinic Study of aging, 434 non-demented participants with FLAIR-MRI, tau-PET and PiB-PET scans were identified. A subset had microbleeds on T2* GRE scans. We ran SPM12 based voxel-wise multiple regression analyses to detect WMH regions associated with AD biomarkers (global amyloid from PiB-PET and meta-ROI tau uptake from tau-PET) adjusting for age, sex, and hypertension. For amyloid associations, we additionally adjusted for tau and vice versa. Results: Topographic patterns of WMH associated with amyloid after both voxel and cluster level corrections primarily included periventricular WMH (frontal and parietal lobes). Masks with lenient threshold (greater detection sensitivity) and strict thresholds (greater detection specificity) are shown in the figure. (A) and (B) show the areas of positive associations between PIB ratio and WMHs adjusted by age, sex, education, hypertension and Tau meta ROI. The sensitive mask (A) was thresholded at FDR p<0.05 at voxel level and FWE p<0.05 at cluster level. The specific mask (B) was thresholded at FDR p<0.001 at voxel level and FDR p<0.05 at cluster level. (C) Shows the frequency of WMHs in the study sample, ranging from infrequent (dark blue) to frequent (green to red). Both the sensitive (p<0.001, Cohen’s D=0.615) and specific WMH maps (p<0.001, Cohen’s D = 0.705) were associated with microbleeds. No WMH regions were associated with tau. Conclusion: Amyloid but not tau load on PET was associated with WMH topographically. The WMH regions associated with amyloid were associated with CMBs suggesting that cerebral amyloid angiopathy may be contributing to the relationship between amyloid and WMH.