Citations

Abstract Although white matter hyperintensities have traditionally been viewed as a marker of vascular disease, recent pathology studies have found an association between white matter hyperintensities and Alzheimer’s disease pathologies. The objectives of this study were to investigate the topographic patterns of white matter hyperintensities associated with Alzheimer’s disease biomarkers measured using PET. From the population-based Mayo Clinic Study of Aging, 434 participants without dementia (55% male) with FLAIR and gradient recall echo MRI, tau-PET (AV-1451) and amyloid-PET scans were identified. A subset had cerebral microbleeds detected on T2* gradient recall echo scans. White matter hyperintensities were semi-automatically segmented using FLAIR MRI in participant space and normalized to a custom template. We used statistical parametric mapping 12-based, voxel-wise, multiple-regression analyses to detect white matter hyperintense regions associated with Alzheimer’s biomarkers (global amyloid from amyloid-PET and meta-regions of interest tau uptake from tau-PET) after adjusting for age, sex and hypertension. For amyloid associations, we additionally adjusted for tau and vice versa. Topographic patterns of amyloid-associated white matter hyperintensities included periventricular white matter hyperintensities (frontal and parietal lobes). White matter hyperintense volumes in the detected topographic pattern correlated strongly with lobar cerebral microbleeds (P < 0.001, age and sex adjusted Cohen’s d = 0.703). In contrast, there were no white matter hyperintense regions significantly associated with increased tau burden using voxel-based analysis or region-specific analysis. Among non-demented elderly, amyloid load correlated with a topographic pattern of white matter hyperintensities. Further, the amyloid-associated, white matter hyperintense regions strongly correlated with lobar cerebral microbleeds suggesting that cerebral amyloid angiopathy contributes to the relationship between amyloid and white matter hyperintensities. The study did not support an association between increased tau burden and white matter hyperintense burden.

Abstract White matter hyperintensities (WMHs) are frequently seen on brain magnetic resonance imaging scans of older people. Usually interpreted clinically as a surrogate for cerebral small vessel disease, WMHs are associated with increased likelihood of cognitive impairment and dementia (including Alzheimer's disease [AD]). WMHs are also seen in cognitively healthy people. In this collaboration of academic, clinical, and pharmaceutical industry perspectives, we identify outstanding questions about WMHs and their relation to cognition, dementia, and AD. What molecular and cellular changes underlie WMHs? What are the neuropathological correlates of WMHs? To what extent are demyelination and inflammation present? Is it helpful to subdivide into periventricular and subcortical WMHs? What do WMHs signify in people diagnosed with AD? What are the risk factors for developing WMHs? What preventive and therapeutic strategies target WMHs? Answering these questions will improve prevention and treatment of WMHs and dementia.

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.

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.

AbstractAs more biomarkers for Alzheimer’s disease and age-related brain conditions become available, more sophisticated analytic approaches are needed to take full advantage of the information they convey. Most work has been done using categorical approaches but the joint relationships of tau PET, amyloid PET and cortical thickness in their continuous distributions to cognition have been under-explored. We evaluated non-demented subjects over age 50 years in the Mayo Clinic Study of Aging, 2037 of whom had undergone 3 T MRI scan, 985 amyloid PET scan with 11C-Pittsburgh compound B (PIB) and MRI, and 577 PIB-PET, 18F-AV1451 flortaucipir PET and MRI. Participants received a nine-test cognitive battery. Three test scores (logical memory delayed recall, visual reproduction delayed recall and auditory verbal learning test delayed recall) were used to generate a memory composite z-score. We used Gradient Boosting Machine models to analyse the relationship between regional cortical thickness, flortaucipir PET signal, PIB-PET signal and memory z-scores. Age, education, sex and number of test exposures were included in the model as covariates. In this population-based study of non-demented subjects, most of the associations between biomarkers and memory z-scores accrued after 70 years of age. Entorhinal cortex exhibited the strongest associations between biomarkers and memory z-scores. Other temporal regions showed similar but attenuated associations, and non-temporal regions had negligible associations between memory z-scores and biomarkers. Entorhinal flortaucipir PET signal, PIB-PET signal and entorhinal cortical thickness were independently and additively associated with declining memory z-scores. In contrast to global PIB-PET signal where only very high amyloid-β levels were associated low memory z-scores, entorhinal flortaucipir PET signal just above background levels was associated with low memory z-scores. The lowest memory z-scores occurred with the confluence of elevated entorhinal flortaucipir PET signal and lower entorhinal cortical thickness.