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Featured researches published by James B. Brewer.


The Journal of Neuroscience | 2009

One year brain atrophy evident in healthy aging

Anders M. Fjell; Kristine B. Walhovd; Christine Fennema-Notestine; Linda K. McEvoy; Donald J. Hagler; Dominic Holland; James B. Brewer; Anders M. Dale

An accurate description of changes in the brain in healthy aging is needed to understand the basis of age-related changes in cognitive function. Cross-sectional magnetic resonance imaging (MRI) studies suggest thinning of the cerebral cortex, volumetric reductions of most subcortical structures, and ventricular expansion. However, there is a paucity of detailed longitudinal studies to support the cross-sectional findings. In the present study, 142 healthy elderly participants (60–91 years of age) were followed with repeated MRI, and were compared with 122 patients with mild to moderate Alzheimers disease (AD). Volume changes were measured across the entire cortex and in 48 regions of interest. Cortical reductions in the healthy elderly were extensive after only 1 year, especially evident in temporal and prefrontal cortices, where annual decline was ∼0.5%. All subcortical and ventricular regions except caudate nucleus and the fourth ventricle changed significantly over 1 year. Some of the atrophy occurred in areas vulnerable to AD, while other changes were observed in areas less characteristic of the disease in early stages. This suggests that the changes are not primarily driven by degenerative processes associated with AD, although it is likely that preclinical changes associated with AD are superposed on changes due to normal aging in some subjects, especially in the temporal lobes. Finally, atrophy was found to accelerate with increasing age, and this was especially prominent in areas vulnerable to AD. Thus, it is possible that the accelerating atrophy with increasing age is due to preclinical AD.


Radiology | 2009

Alzheimer Disease: Quantitative Structural Neuroimaging for Detection and Prediction of Clinical and Structural Changes in Mild Cognitive Impairment

Linda K. McEvoy; Christine Fennema-Notestine; J. Cooper Roddey; Donald J. Hagler; Dominic Holland; David S. Karow; Christopher J. Pung; James B. Brewer; Anders M. Dale

PURPOSE To use structural magnetic resonance (MR) images to identify a pattern of regional atrophy characteristic of mild Alzheimer disease (AD) and to investigate whether presence of this pattern prospectively can aid prediction of 1-year clinical decline and increased structural loss in mild cognitive impairment (MCI). MATERIALS AND METHODS The study was conducted with institutional review board approval and compliance with HIPAA regulations. Written informed consent was obtained from each participant. High-throughput volumetric segmentation and cortical surface reconstruction methods were applied to MR images from 84 subjects with mild AD, 175 with MCI, and 139 healthy control (HC) subjects. Stepwise linear discriminant analysis was used to identify regions that best can aid discrimination of HC subjects from subjects with AD. A classifier trained on data from HC subjects and those with AD was applied to data from subjects with MCI to determine whether presence of phenotypic AD atrophy at baseline was predictive of clinical decline and structural loss. RESULTS Atrophy in mesial and lateral temporal, isthmus cingulate, and orbitofrontal areas aided discrimination of HC subjects from subjects with AD, with fully cross-validated sensitivity of 83% and specificity of 93%. Subjects with MCI who had phenotypic AD atrophy showed significantly greater 1-year clinical decline and structural loss than those who did not and were more likely to have progression to probable AD (annual progression rate of 29% for subjects with MCI who had AD atrophy vs 8% for those who did not). CONCLUSION Semiautomated, individually specific quantitative MR imaging methods can be used to identify a pattern of regional atrophy in MCI that is predictive of clinical decline. Such information may aid in prediction of patient prognosis and increase the efficiency of clinical trials.


American Journal of Neuroradiology | 2010

Combining MR Imaging, Positron-Emission Tomography, and CSF Biomarkers in the Diagnosis and Prognosis of Alzheimer Disease

Kristine B. Walhovd; Anders M. Fjell; James B. Brewer; Linda K. McEvoy; C. Fennema-Notestine; Donald J. Hagler; R.G. Jennings; D. Karow; Anders M. Dale

BACKGROUND AND PURPOSE: Different biomarkers for AD may potentially be complementary in diagnosis and prognosis of AD. Our aim was to combine MR imaging, FDG-PET, and CSF biomarkers in the diagnostic classification and 2-year prognosis of MCI and AD, by examining the following: 1) which measures are most sensitive to diagnostic status, 2) to what extent the methods provide unique information in diagnostic classification, and 3) which measures are most predictive of clinical decline. MATERIALS AND METHODS: ADNI baseline MR imaging, FDG-PET, and CSF data from 42 controls, 73 patients with MCI, and 38 patients with AD; and 2-year clinical follow-up data for 36 controls, 51 patients with MCI, and 25 patients with AD were analyzed. The hippocampus and entorhinal, parahippocampal, retrosplenial, precuneus, inferior parietal, supramarginal, middle temporal, lateral, and medial orbitofrontal cortices were used as regions of interest. CSF variables included Aβ42, t-tau, p-tau, and ratios of t-tau/Aβ42 and p-tau/Aβ42. Regression analyses were performed to determine the sensitivity of measures to diagnostic status as well as 2-year change in CDR-SB, MMSE, and delayed logical memory in MCI. RESULTS: Hippocampal volume, retrosplenial thickness, and t-tau/Aβ42 uniquely predicted diagnostic group. Change in CDR-SB was best predicted by retrosplenial thickness; MMSE, by retrosplenial metabolism and thickness; and delayed logical memory, by hippocampal volume. CONCLUSIONS: All biomarkers were sensitive to the diagnostic group. Combining MR imaging morphometry and CSF biomarkers improved diagnostic classification (controls versus AD). MR imaging morphometry and PET were largely overlapping in value for discrimination. Baseline MR imaging and PET measures were more predictive of clinical change in MCI than were CSF measures.


Neurology | 2009

Regional rates of neocortical atrophy from normal aging to early Alzheimer disease

Carrie R. McDonald; Linda K. McEvoy; Lusineh Gharapetian; Christine Fennema-Notestine; Donald J. Hagler; Dominic Holland; Alain K. Koyama; James B. Brewer; A.M. Dale

Objective: To evaluate the spatial pattern and regional rates of neocortical atrophy from normal aging to early Alzheimer disease (AD). Methods: Longitudinal MRI data were analyzed using high-throughput image analysis procedures for 472 individuals diagnosed as normal, mild cognitive impairment (MCI), or AD. Participants were divided into 4 groups based on Clinical Dementia Rating Sum of Boxes score (CDR-SB). Annual atrophy rates were derived by calculating percent cortical volume loss between baseline and 12-month scans. Repeated-measures analyses of covariance were used to evaluate group differences in atrophy rates across regions as a function of impairment. Planned comparisons were used to evaluate the change in atrophy rates across levels of disease severity. Results: In patients with MCI–CDR-SB 0.5–1, annual atrophy rates were greatest in medial temporal, middle and inferior lateral temporal, inferior parietal, and posterior cingulate. With increased impairment (MCI–CDR-SB 1.5–2.5), atrophy spread to parietal, frontal, and lateral occipital cortex, followed by anterior cingulate cortex. Analysis of regional trajectories revealed increasing rates of atrophy across all neocortical regions with clinical impairment. However, increases in atrophy rates were greater in early disease within medial temporal cortex, whereas increases in atrophy rates were greater at later stages in prefrontal, parietal, posterior temporal, parietal, and cingulate cortex. Conclusions: Atrophy is not uniform across regions, nor does it follow a linear trajectory. Knowledge of the spatial pattern and rate of decline across the spectrum from normal aging to Alzheimer disease can provide valuable information for detecting early disease and monitoring treatment effects at different stages of disease progression.


The Journal of Neuroscience | 2010

CSF Biomarkers in Prediction of Cerebral and Clinical Change in Mild Cognitive Impairment and Alzheimer's Disease

Anders M. Fjell; Kristine B. Walhovd; Christine Fennema-Notestine; Linda K. McEvoy; Donald J. Hagler; Dominic Holland; James B. Brewer; Anders M. Dale

Brain atrophy and altered CSF levels of amyloid β (Aβ42) and the microtubule-associated protein tau are potent biomarkers of Alzheimers disease (AD)-related pathology. However, the relationship between CSF biomarkers and brain morphometry is poorly understood. Thus, we addressed the following questions. (1) Can CSF biomarker levels explain the morphometric differences between normal controls (NC) and patients with mild cognitive impairment (MCI) or AD? (2) How are CSF biomarkers related to atrophy across the brain? (3) How closely are CSF biomarkers and morphometry related to clinical change [clinical dementia rating sum of boxes (CDR-sb)]? Three hundred seventy participants (105 NC, 175 MCI, 90 AD) from the Alzheimers Disease Neuroimaging Initiative were studied, of whom 309 were followed for 1 year and 176 for 2 years. Analyses were performed across the entire cortical surface, as well as for 30 cortical and subcortical regions of interest. Results showed that CSF biomarker levels could not account for group differences in brain morphometry at baseline but that CSF biomarker levels showed moderate relationships to longitudinal atrophy rates in numerous brain areas, not restricted to medial temporal structures. Baseline morphometry was at least as predictive of atrophy as were CSF biomarkers. Even MCI patients with levels of Aβ42 comparable with controls and of p-tau lower than controls showed more atrophy than the controls. Morphometry predicted change in CDR-sb better than did CSF biomarkers. These results indicate that morphometric changes in MCI and AD are not secondary to CSF biomarker changes and that the two types of biomarkers yield complementary information.


Neurology | 2015

A randomized, double-blind, placebo-controlled trial of resveratrol for Alzheimer disease.

R. Scott Turner; Ronald G. Thomas; Suzanne Craft; Christopher H. van Dyck; Jacobo Mintzer; Brigid Reynolds; James B. Brewer; Robert A. Rissman; Rema Raman; Paul S. Aisen

Objective: A randomized, placebo-controlled, double-blind, multicenter 52-week phase 2 trial of resveratrol in individuals with mild to moderate Alzheimer disease (AD) examined its safety and tolerability and effects on biomarker (plasma Aβ40 and Aβ42, CSF Aβ40, Aβ42, tau, and phospho-tau 181) and volumetric MRI outcomes (primary outcomes) and clinical outcomes (secondary outcomes). Methods: Participants (n = 119) were randomized to placebo or resveratrol 500 mg orally once daily (with dose escalation by 500-mg increments every 13 weeks, ending with 1,000 mg twice daily). Brain MRI and CSF collection were performed at baseline and after completion of treatment. Detailed pharmacokinetics were performed on a subset (n = 15) at baseline and weeks 13, 26, 39, and 52. Results: Resveratrol and its major metabolites were measurable in plasma and CSF. The most common adverse events were nausea, diarrhea, and weight loss. CSF Aβ40 and plasma Aβ40 levels declined more in the placebo group than the resveratrol-treated group, resulting in a significant difference at week 52. Brain volume loss was increased by resveratrol treatment compared to placebo. Conclusions: Resveratrol was safe and well-tolerated. Resveratrol and its major metabolites penetrated the blood–brain barrier to have CNS effects. Further studies are required to interpret the biomarker changes associated with resveratrol treatment. Classification of evidence: This study provides Class II evidence that for patients with AD resveratrol is safe, well-tolerated, and alters some AD biomarker trajectories. The study is rated Class II because more than 2 primary outcomes were designated.


Neurology | 2011

Predicting MCI outcome with clinically available MRI and CSF biomarkers

D. Heister; James B. Brewer; S. Magda; Kaj Blennow; Linda K. McEvoy

Objective: To determine the ability of clinically available volumetric MRI (vMRI) and CSF biomarkers, alone or in combination with a quantitative learning measure, to predict conversion to Alzheimer disease (AD) in patients with mild cognitive impairment (MCI). Methods: We stratified 192 MCI participants into positive and negative risk groups on the basis of 1) degree of learning impairment on the Rey Auditory Verbal Learning Test; 2) medial temporal atrophy, quantified from Food and Drug Administration–approved software for automated vMRI analysis; and 3) CSF biomarker levels. We also stratified participants based on combinations of risk factors. We computed Cox proportional hazards models, controlling for age, to assess 3-year risk of converting to AD as a function of risk group and used Kaplan-Meier analyses to determine median survival times. Results: When risk factors were examined separately, individuals testing positive showed significantly higher risk of converting to AD than individuals testing negative (hazard ratios [HR] 1.8–4.1). The joint presence of any 2 risk factors substantially increased risk, with the combination of greater learning impairment and increased atrophy associated with highest risk (HR 29.0): 85% of patients with both risk factors converted to AD within 3 years, vs 5% of those with neither. The presence of medial temporal atrophy was associated with shortest median dementia-free survival (15 months). Conclusions: Incorporating quantitative assessment of learning ability along with vMRI or CSF biomarkers in the clinical workup of MCI can provide critical information on risk of imminent conversion to AD.


Neurobiology of Aging | 2010

Multi-modal imaging predicts memory performance in normal aging and cognitive decline

Kristine B. Walhovd; Anders M. Fjell; Anders M. Dale; Linda K. McEvoy; James B. Brewer; David S. Karow; David P. Salmon; Christine Fennema-Notestine

This study (n=161) related morphometric MR imaging, FDG-PET and APOE genotype to memory scores in normal controls (NC), mild cognitive impairment (MCI) and Alzheimers disease (AD). Stepwise regression analyses focused on morphometric and metabolic characteristics of the episodic memory network: hippocampus, entorhinal, parahippocampal, retrosplenial, posterior cingulate, precuneus, inferior parietal, and lateral orbitofrontal cortices. In NC, hippocampal metabolism predicted learning; entorhinal metabolism predicted recognition; and hippocampal metabolism predicted recall. In MCI, thickness of the entorhinal and precuneus cortices predicted learning, while parahippocampal metabolism predicted recognition. In AD, posterior cingulate cortical thickness predicted learning, while APOE genotype predicted recognition. In the total sample, hippocampal volume and metabolism, cortical thickness of the precuneus, and inferior parietal metabolism predicted learning; hippocampal volume and metabolism, parahippocampal thickness and APOE genotype predicted recognition. Imaging methods appear complementary and differentially sensitive to memory in health and disease. Medial temporal and parietal metabolism and morphometry best explained memory variance. Medial temporal characteristics were related to learning, recall and recognition, while parietal structures only predicted learning.


American Journal of Neuroradiology | 2009

Fully-Automated Quantification of Regional Brain Volumes for Improved Detection of Focal Atrophy in Alzheimer Disease

James B. Brewer; S. Magda; C. Airriess; M.E. Smith

SUMMARY: Volumetric analysis of structural MR images of the brain may provide quantitative evidence of neurodegeneration and help identify patients at risk for rapid clinical deterioration. This note describes tests of a fully automated MR imaging postprocessing system for volumetric analysis of structures (such as the hippocampus) known to be affected in early Alzheimer disease (AD). The system yielded results that correlated highly with independent computer-aided manual segmentation and were sensitive to the anatomic atrophy characteristic of mild AD.


Hippocampus | 1999

Level of sustained entorhinal activity at study correlates with subsequent cued-recall performance: a functional magnetic resonance imaging study with high acquisition rate.

Guillén Fernández; James B. Brewer; Zuo Zhao; Gary H. Glover; John D. E. Gabrieli

Functional magnetic resonance imaging (fMRI) with high acquisition rate was performed during the intentional memorizing of words to specify which medial temporal lobe structure is important in determining what words are subsequently remembered in a cued‐recall test and to characterize the time course of activation in that structure. Functional images of six healthy young subjects were analyzed by two subject‐ and voxel‐wise statistics: First, to identify brain areas transiently engaged in encoding of words, brain activity during memorizing visually presented words and watching a fixation cross was compared by a Kolmogorov‐Smirnov statistic (KS‐test). Second, to identify brain areas whose activity correlates with memory encoding success, a Kendalls correlation was calculated between signal intensity at study and performance in a subsequent cued‐recall test. Averaged signal intensities were plotted as a function of time to depict the time course of brain activity detected by both statistical tests. The level of slowly modulated, sustained activity in Brodmann area 28 (entorhinal cortex) did not respond transiently as study words appeared, but did correlate positively with subsequent test performance. More left than right activity in Brodmann area 45 (dorso‐lateral prefrontal cortex) and bilateral activity in Brodmann area 44 (premotor cortex) exhibited transient hemodynamic responses that did not show any relation to subsequent memory performance. Thus, the study identified a novel pattern of slowly modulated brain activity in human entorhinal cortex that may represent a declarative memory encoding state whose level predicts whether experiences will be remembered or forgotten. Hippocampus 1999;9:35–44.

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Anders M. Dale

University of California

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Paul S. Aisen

University of Southern California

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