Jack, Clifford R

ABSTRACT Background and Purpose Neurodegeneration of the substantia nigra in Lewy body disease is associated with iron deposition, which increases the magnetic susceptibility of the substantia nigra on MRI. Our objective was to measure iron deposition in the substantia nigra in patients with probable dementia with Lewy bodies (pDLB) and patients who are at risk for pDLB by quantitative susceptibility mapping (QSM). Methods Participants included pDLB ( n = 36), mild cognitive impairment with at least one core feature of DLB (MCI‐LB; n = 15), idiopathic rapid eye movement sleep behavior disorder (iRBD; n = 11), and an age‐and gender‐matched clinically unimpaired control group ( n = 102). QSM was derived from multi‐echo 3D gradient recalled echo MRI at 3T, and groups were compared on mean susceptibility values of the substantia nigra and its relation to parkinsonism severity. Results Patients with pDLB had higher susceptibility in the substantia nigra compared to controls ( p < 0.001) and MCI‐LB ( p = 0.043). The susceptibility of substantia nigra showed an increasing trend from controls to iRBD and MCI‐LB, and to pDLB ( p < 0.001). Parkinsonism severity was not associated with the mean susceptibility in the substantia nigra in the patient groups. Conclusions Our data suggested that QSM is sensitive to the increased magnetic susceptibility due to higher iron content in the substantia nigra in pDLB. The trend of increasing susceptibility from controls to iRBD and MCI‐LB, and to pDLB suggests that iron deposition in the substantia nigra starts to increase as early as the prodromal stage in DLB and continues to increase as the disease progresses, independent of parkinsonism severity.

AbstractPatients with early‐onset Alzheimer's disease (EOAD) are commonly excluded from large‐scale observational and therapeutic studies due to their young age, atypical presentation, or absence of pathogenic mutations. The goals of the Longitudinal EOAD Study (LEADS) are to (1) define the clinical, imaging, and fluid biomarker characteristics of EOAD; (2) develop sensitive cognitive and biomarker measures for future clinical and research use; and (3) establish a trial‐ready network. LEADS will follow 400 amyloid beta (Aβ)‐positive EOAD, 200 Aβ‐negative EOnonAD that meet National Institute on Aging–Alzheimer's Association (NIA‐AA) criteria for mild cognitive impairment (MCI) or AD dementia, and 100 age‐matched controls. Participants will undergo clinical and cognitive assessments, magnetic resonance imaging (MRI), [18F]Florbetaben and [18F]Flortaucipir positron emission tomography (PET), lumbar puncture, and blood draw for DNA, RNA, plasma, serum and peripheral blood mononuclear cells, and post‐mortem assessment. To develop more effective AD treatments, scientists need to understand the genetic, biological, and clinical processes involved in EOAD. LEADS will develop a public resource that will enable future planning and implementation of EOAD clinical trials.

Abstract White matter microstructure undergoes progressive changes during the lifespan, but the neurobiological underpinnings related to ageing and disease remains unclear. We used an advanced diffusion MRI, Neurite Orientation Dispersion and Density Imaging, to investigate the microstructural alterations due to demographics, common age-related pathological processes (amyloid, tau and white matter hyperintensities) and cognition. We also compared Neurite Orientation Dispersion and Density Imaging findings to the older Diffusion Tensor Imaging model-based findings. Three hundred and twenty-eight participants (264 cognitively unimpaired, 57 mild cognitive impairment and 7 dementia with a mean age of 68.3 ± 13.1 years) from the Mayo Clinic Study of Aging with multi-shell diffusion imaging, fluid attenuated inversion recovery MRI as well as amyloid and tau PET scans were included in this study. White matter tract level diffusion measures were calculated from Diffusion Tensor Imaging and Neurite Orientation Dispersion and Density Imaging. Pearson correlation and multiple linear regression analyses were performed with diffusion measures as the outcome and age, sex, education/occupation, white matter hyperintensities, amyloid and tau as predictors. Analyses were also performed with each diffusion MRI measure as a predictor of cognitive outcomes. Age and white matter hyperintensities were the strongest predictors of all white matter diffusion measures with low associations with amyloid and tau. However, neurite density decrease from Neurite Orientation Dispersion and Density Imaging was observed with amyloidosis specifically in the temporal lobes. White matter integrity (mean diffusivity and free water) in the corpus callosum showed the greatest associations with cognitive measures. All diffusion measures provided information about white matter ageing and white matter changes due to age-related pathological processes and were associated with cognition. Neurite orientation dispersion and density imaging and diffusion tensor imaging are two different diffusion models that provide distinct information about variation in white matter microstructural integrity. Neurite Orientation Dispersion and Density Imaging provides additional information about synaptic density, organization and free water content which may aid in providing mechanistic insights into disease progression.

Background: Periodontal disease (PD) is associated positively with neurocognitive outcomes. Few studies have investigated the relationship between PD and indicators of brain aging and vascular changes. Hypothesis: PD is associated with greater cerebral small vessel disease, lower total and regional brain volumes and elevated β-amyloid (Aβ) deposition. Methods: We included 6,793 participants who received full-mouth periodontal examinations and tooth counts at Visit 4 (1996-1998) of the Atherosclerosis Risk in Communities Study. We used a modified 3-level version of the Periodontal Profile Class to categorize PD based on severity and extent of gingival inflammation and tissue loss. Among participants who attended Visit 5 (2011-2013), n=1,306 received a brain MRI and n=248 received a PET scan. Total brain volume, Alzheimer’s disease signature volume, and presence of microhemorrhages and cerebral infarctions were ascertained via 3T MRI; Aβ deposition was assessed from PET. We regressed brain volumes on baseline PD status using weighted multivariable linear regression. Presence of cerebrovascular microhemorrhages, infarctions, or elevated Aβ (standardized uptake value ratio>1.2) were regressed on PD category using logistic models. We examined the interaction between Apolipoprotein E ε4 ( APOE ) allele possession and PD categories on the Aβ outcome. Results: Prevalence of baseline periodontal disease was 73% (959/1306) and 87% (206/248) among the MRI and PET subgroups, respectively. PD was not associated with volumetric brain measures nor microhemorrhages. PD was inversely associated with the odds of subcortical and lacunar infarctions. PD and Aβ were not associated in main effect or interaction analyses, although there was a notably stronger association among carriers of APOE . Conclusion: PD was not associated with altered brain structure, cerebral microhemorrhages or elevated Aβ deposition. Counter to the hypothesis, PD and complete tooth loss were inversely associated with cerebral infarctions.

Introduction: Studies have found that smaller brain volumes, cerebral infarcts, and white matter abnormalities are associated with dementia and mild cognitive impairment. However, these studies have been limited by short follow-up precluding a strong establishment of temporality. Therefore, it is unknown whether brain imaging findings are preceded by long-term changes in cognition. We sought to address this gap by examining brain imaging and two decades of cognitive changes in and a large, representative population-based cohort of older adults of black and white race. Hypothesis: We hypothesized that 22-year declines in global cognitive factor scores (GCFS) would be associated with a pattern of smaller total brain and temporal lobe meta region of interest (likely to be affected by Alzheimer’s disease) volumes, larger white matter hyperintensity volumes, and greater odds of ≥1 lacunar infarct and elevated brain β-amyloid deposition. Methods: ARIC participants with brain imaging data, complete cognitive factor score, and not missing key covariates were included. GCFS were collected at three visits across 22 years (1990-2013), and brain MRI and florbetapir PET imaging were collected in 2011-13; PET in subset of n=327. Mixed effects models with random intercepts and slopes predicted individual change in GCFS. Outcomes of interest were total brain volume (cc), temporal lobe meta region volume, log 2 (white matter hyperintensity volume), ≥1 lacunar infarct, and elevated brain β-amyloid deposition (SUVR >1.2). Multivariable linear and logistic regression was used to relate outcomes to GCFS slopes after adjusting for confounders, including vascular risk factors. As appropriate, models were also adjusted for total intracranial volume. Results: Among 1957 with complete brain MRI imaging, 1830 were included in the study, 60% (n=1096) women and 26% (n=480) black. At the first visit, the mean (SD) baseline age was 55 (5.2) yrs. The mean (SD) observed GCFS at the three visits were 0.16 (0.79), 0.05 (0.75), and -0.78 (0.86). After adjustment, a 1-SD larger decline in GCFS was significantly associated with a smaller brain volume by 1.6% [95%CI: 1.3, 1.8] relative to mean brain volume, a smaller temporal lobe meta region volume by 2.4% [2.1, 2.8] relative to the mean volume, a 15% [11, 19] larger volume of white matter hyperintensities, 1.3-fold [1.2, 1.4] higher odds of having ≥1 lacune, and 1.8-fold [1.4, 2.4] higher odds of elevated brain β-amyloid deposition. Associations remained significant after further adjustment for first or last GCFS. Conclusions: Greater declines in long-term cognitive functioning were significantly associated with smaller brain volumes and dementia-related brain characteristics and were independent of last visit GCFS. This suggests long-term changes in cognition may precede late-life brain morphology and outperform cross-sectional cognitive measures.

Background: Elevated carotid intima-media thickness (cIMT) and presence of carotid plaque are markers of atherosclerosis, which may be linked to structural brain injury. Using data from the ARIC-NCS cohort, we tested the hypotheses that greater cIMT and presence of carotid plaque at late midlife were each associated with presence of infarcts (lacunar and cortical) and cerebral microbleeds (lobar and subcortical), greater white matter hyperintensity (WMH) volume, and smaller regional brain volumes in late life. Methods: We included 1,795 ARIC participants who had carotid ultrasounds in 1990-92 and brain MRI scans in 2011-13. Weighted linear regression was used for continuous (brain volume) outcomes, and weighted logistic regression for dichotomous outcomes (infarcts and cerebral microbleeds). Results: Participants were aged 57±6 years at baseline, 57% were female, and 23% were Black. Mean ± SD follow-up was 21±1 years. After multivariable adjustments, the highest quintile of cIMT in late midlife was associated with smaller deep grey matter volume (β [95% CI]: -0.11 [-0.22, -0.01]) and cortical volume in a temporal-parietal meta region of interest (ROI) (β [95% CI]: -0.10 [-0.20, -0.01]) in late life (Table). At baseline, 473 (26%) participants had carotid plaque present on their carotid ultrasound. Similar to cIMT, those with carotid plaque had smaller regional brain volumes than those without carotid plaque present (βs [95% CIs]: -0.05 [-0.12, 0.03] and -0.06 [-0.13, 0.01] for deep grey matter and temporal-parietal meta ROI volumes, respectively). No significant relations were observed with WMH volume, or the presence of any infarcts or cerebral microbleeds. Conclusion: Greater midlife cIMT and presence of carotid plaque were associated with smaller deep grey matter volume and cortical volume in a temporal-parietal meta ROI in later life. Contrary to our hypothesis, associations between midlife subclinical atherosclerosis and markers of vascular brain injury in later life were null.

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 While cerebrovascular disease can be observed in vivo using MRI, the multiplicity and heterogeneity in the mechanisms of cerebrovascular damage impede accounting for these measures in ageing and dementia studies. Our primary goal was to investigate the key sources of variability across MRI markers of cerebrovascular disease and evaluate their impact in comparison to amyloidosis on cognitive decline in a population-based sample. Our secondary goal was to evaluate the prognostic utility of a cerebrovascular summary measure from all markers. We included both visible lesions seen on MRI (white matter hyperintensities, cortical and subcortical infarctions, lobar and deep microbleeds) and early white matter damage due to systemic vascular health using diffusion changes in the genu of the corpus callosum. We identified 1089 individuals aged ≥60 years with concurrent amyloid-PET and MRI scans from the population-based Mayo Clinic Study of Aging. We divided these into discovery and validation datasets. Using the discovery dataset, we conducted principal component analyses and ascertained the main sources of variability in cerebrovascular disease markers. Using linear regression and mixed effect models, we evaluated the utility of these principal components and combinations of these components for the prediction of cognitive performance along with amyloidosis. Our main findings were (i) there were three primary sources of variability among the CVD measures—white matter changes are driven by white matter hyperintensities and diffusion changes; number of microbleeds (lobar and deep); and number of infarctions (cortical and subcortical); (ii) Components of white matter changes and microbleeds but not infarctions significantly predicted cognition trajectories in all domains with greater contributions from white matter; and (iii) The summary vascular score explained 3–5% of variability in baseline global cognition in comparison to 3–6% variability explained by amyloidosis. Across all cognitive domains, the vascular summary score had the least impact on memory performance (∼1%). Though there is mechanistic heterogeneity in the cerebrovascular disease markers measured on MRI, these changes can be grouped into three components and together explain variability in cognitive performance equivalent to the impact of amyloidosis on cognition. White matter changes represent dynamic ongoing damage, predicts future cognitive decline across all domains and diffusion measurements help capture white matter damage due to systemic vascular changes. Therefore, measuring and accounting for white matter changes using diffusion MRI and white matter hyperintensities along with microbleeds will allow us to capture vascular contributions to cognitive impairment and dementia.

Background Antiplatelets, anticoagulants, and statins are commonly prescribed for various indications. The associations between these medications and the risk of intracerebral hemorrhage (ICH) and cerebral microbleeds (CMBs) are unclear. Methods and Results We performed a retrospective study of the ARIC (Atherosclerosis Risk in Communities) study cohort, recruited from 4 US communities in 1987 to 1989 with follow‐up. In 2011 to 2013, a subset (N=1942) underwent brain magnetic resonance imaging with CMB evaluation. Time‐varying and any antiplatelet, anticoagulant, or statin use was evaluated at subsequent study visits in participants not on each medication at baseline. To determine the hazard of ICH and odds of CMB by medication use, logistic and Cox proportional hazard models were built, respectively, adjusting for the propensity to take the medication, concomitant use of other medications, and cognitive, genetic, and radiographic data. Of 15 719 individuals during up to 20 years of follow‐up, 130 participants experienced an ICH. The adjusted hazard of ICH was significantly lower among participants taking an antiplatelet at the most recent study visit before ICH versus nonusers (hazard ratio [HR], 0.53; 95% CI, 0.30–0.92). Statin users had a significantly lower hazard of an ICH compared with nonusers (adjusted HR, 0.13; 95% CI, 0.05–0.34). There was no association of CMB and antiplatelet, anticoagulant, or statin use in adjusted models. Conclusions In this US community‐based study, antiplatelet and statin use were associated with lower ICH hazard, whereas no association was noted between CMBs and antiplatelets, anticoagulants, and statins. Further study is needed to understand the differential roles of these medications in cerebral microhemorrhages and macrohemorrhages.