Vemuri, Prashanthi

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.

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.

Objectives To examine the cross‐sectional association between functional performance and Alzheimer's disease (AD) neuroimaging biomarkers in individuals without dementia (cognitively unimpaired (CU), and those with mild cognitive impairment (MCI)). Design Cross‐sectional. Setting Olmsted County, Minnesota. Participants Population‐based Mayo Clinic Study of Aging (MCSA) participants (aged ≥ 50, mean age 71.3 ± 10.2; 53.4% male; 28.3% apolipoprotein (APO)E ε4 allele carriers, 1,578 CU, 204 MCI) who underwent 11 C‐Pittsburgh compound B ( 11 C‐PiB) positron emission tomography (PET) (N=1,782). Measurements We defined an abnormal (high) 11 C‐PiB‐PET retention ratio as a standardized uptake value ratio greater than 1.42 (high amyloid; A+), abnormal (reduced) AD signature cortical thickness (neurodegeneration; N+) as less than 2.67 mm (MRI measurement), and biomarker groups according to the combination of abnormality (or not) for amyloid accumulation (A+/A–) and neurodegeneration (N+/N–). Functional performance was assessed using the Clinical Dementia Rating (CDR) Sum of Boxes (SOB) for functional domains and the Functional Activities Questionnaire (FAQ). Results Participants with a CDR‐SOB (functional) score greater than 0 were almost 4 times as likely to have N + (odds ratio (OR)=3.92, 95% confidence interval (CI)=1.77–8.67, adjusting for age, sex, education, global cognitive z‐score, and APOE ε4 allele status; p<.001) and those with a FAQ score greater than 0 were 1.5 times as likely to have A + (OR=1.48, 95% CI=1.04–2.11, p=.03). Higher FAQ scores were associated with greater odds of A+N + and A–N + in CU participants. Conclusion The findings of this cross‐sectional study supplement limited available information that supports an association between functional performance and AD neuroimaging biomarkers very early in the dementia pathophysiology. The associations should be validated in longitudinal studies. J Am Geriatr Soc 66:2274–2281, 2018 .

Abstract Introduction We sought to establish the relationships between standard postmortem measures of AD neuropathology and antemortem [ 11 C]PIB–positron emission tomography ([ 11 C]PIB‐PET) analyzed with the Centiloid (CL) method, a standardized scale for Aβ‐PET quantification. Methods Four centers contributed 179 participants encompassing a broad range of clinical diagnoses, PET data, and autopsy findings. Results CL values increased with each CERAD neuritic plaque score increment (median −3 CL for no plaques and 92 CL for frequent plaques) and nonlinearly with Thal Aβ phases (increases were detected starting at phase 2) with overlap between scores/phases. PET‐pathology associations were comparable across sites and unchanged when restricting the analyses to the 56 patients who died within 2 years of PET. A threshold of 12.2 CL detected CERAD moderate‐to‐frequent neuritic plaques (area under the curve = 0.910, sensitivity = 89.2%, specificity = 86.4%), whereas 24.4 CL identified intermediate‐to‐high AD neuropathological changes (area under the curve = 0.894, sensitivity = 84.1%, specificity = 87.9%). Discussion Our study demonstrated the robustness of a multisite Centiloid [ 11 C]PIB‐PET study and established a range of pathology‐based CL thresholds.