Lesnick, Timothy

Background and Purpose: Cerebral microbleeds (CMBs) are represented by small areas of hemosiderin deposition, detected on brain magnetic resonance imaging (MRI), and found in ≈23% of the cognitively normal population over age of 60 years. CMBs predict risk of hemorrhagic and ischemic stroke. They correlate with increased cardiovascular mortality. In this article, we sought to determine in a population-based study whether antithrombotic medications correlate with CMBs and, if present, whether the association was direct or mediated by another variable. Methods: The study consisted of 1253 participants from the population-based Mayo Clinic Study of Aging who underwent T2* gradient-recalled echo magnetic resonance imaging. We tested the relationship between antithrombotic medications and CMB presence and location, using multivariable logistic-regression models. Ordinal logistic models tested the relationship between antithrombotics and CMB frequency. Using structural equation models, we assessed the effect of antithrombotic medications on presence/absence of CMBs and count of CMBs in the CMB-positive group, after considering the effects of age, sex, vascular risk factors, amyloid load by positron emission tomography, and apoE. Results: Two hundred ninety-five participants (26.3%) had CMBs. Among 678 participants taking only antiplatelet medications, 185 (27.3%) had CMBs. Among 95 participants taking only an anticoagulant, 43 (45.3%) had CMBs. Among 44 participants taking an anticoagulant and antiplatelet therapy, 21 (48.8%) had CMBs. Anticoagulants correlated with the presence and frequency of CMBs, whereas antiplatelet agents were not. Structural equation models showed that predictors for presence/absence of CMBs included older age at magnetic resonance imaging, male sex, and anticoagulant use. Predictors of CMB count in the CMB-positive group were male sex and amyloid load. Conclusions: Anticoagulant use correlated with presence of CMBs in the general population. Amyloid positron emission tomography correlated with the count of CMBs in the CMB-positive group.

Abstract Objective: Little is known about how menopausal hormone treatment (HT) may influence the development of white matter hyperintensities (WMHs) in the brain. This study evaluated the associations of changes in levels of pituitary-ovarian hormones during HT and changes in WMH. Methods: Women (n = 78 adherent to treatment) enrolled in the Kronos Early Estrogen Prevention Study underwent brain magnetic resonance imaging, and blood collection before and after 48 months of randomization to 0.45 mg/d oral conjugated equine estrogen (oCEE) daily, 50 μg/d transdermal 17β estradiol (tE2), or placebo pills and patches. Women in the active treatment groups also received oral 200 mg/d micronized progesterone the first 12 days of the month. Estradiol (E2), estrone (E1), follicle-stimulating hormone (FSH), and luteinizing hormone (LH) were measured in serum by high sensitivity liquid chromatography/mass spectrometry at baseline and following 48 months of HT. Longitudinal change in WMH volume was determined from fluid-attenuated inversion recovery magnetic resonance imaging using a semiautomated image segmentation algorithm. Results: Serum levels of FSH, LH, E1, or E2 did not associate with WMH volume at baseline. After 48 months of treatment, smaller increases in WMH associated with decreases in FSH from baseline in the tE2 group and increases in E1 in both tE2 and oCEE groups. Changes in LH did not associate with changes in WMH in any group. Conclusions: Circulating levels of pituitary-ovarian hormones associate with changes in WMH volume in recently menopausal women using HT. Whether these relationships would be influenced by different doses of tE2 or oCEE remains to be determined. Video Summary: http://links.lww.com/MENO/A590.

ABSTRACT BACKGROUND AND PURPOSE The objective of this study was to longitudinally investigate the trajectory of change in 1 H MRS measurements in asymptomatic MAPT mutation carriers who became symptomatic during follow‐up, and to determine the time at which the neurochemical alterations accelerated during disease progression. METHODS We identified eight MAPT mutations carriers who transitioned from asymptomatic to symptomatic disease during follow‐up. All participants were longitudinally followed with an average of 7.75 years (range 4‐11 years) and underwent two or more single voxel 1 H MRS examinations from the posterior cingulate voxel, with a total of 60 examinations. The rate of longitudinal change for each metabolite was estimated using linear mixed models. A flex point model was used to estimate the flex time point of the change in slope. RESULTS The decrease in the NAA/mI ratio accelerated 2.09 years prior to symptom onset, and continued to decline. A similar trajectory was observed in the presumed glial marker mI/Cr ratio accelerating 1.86 years prior to symptom onset. CONCLUSIONS Our findings support the potential use of longitudinal 1 H MRS for monitoring the neurodegenerative progression in MAPT mutation carriers starting from the asymptomatic stage.

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.