of work: As part of our program of research on early markers of Alzheimers disease (EMAD), we are performing serial magnetic resonance imaging (MRI), including measures of vascular changes, positron emission tomography (PET), and neuropsychological assessments in participants from the Baltimore Longitudinal Study of Aging (BLSA) to investigate the neurobiological basis of memory change and cognitive impairment. These evaluations allow us to examine changes in brain structure and function which may be early predictors of cognitive change and impairment, including Alzheimer's disease (AD). We are continuing longitudinal testing of older participants and evaluating new participants, including MRI and concurrent neuropsychological assessments of participants less than 55 years old. For a subsample of individuals aged 55 and older, we also perform a single PET measurement of CBF, followed by a PET scan using 11-C-Pittsburgh Compound B (PiB) to measure in vivo amyloid distribution. Our progress over the last year includes continued acquisition of new neuroimaging assessments as well as continued analysis of existing data and methods development. Approximately half of the neuroimaging study participants are enrolled in the BLSA autopsy program, and we continue to use the 3-dimensional imaging findings to guide more detailed neuropathological investigations. In addition, we are using neuroimaging tools to investigate modulators of cognitive and brain changes, including sex differences in brain aging, genetic, metabolic, and inflammatory risk factors, and the effects of sex steroid and other hormones. An understanding of these brain-behavior associations and early detection of accelerated brain changes that predict cognitive decline and impairment will be critical in identifying individuals likely to benefit from interventions if a successful treatment for prevention or delaying onset of disease is identified. Over the last year, we have published a number of papers from this study. In a prior study, we found both concordance and discordance between in vivo amyloid imaging patterns and pathological ratings of amyloid plaques according to the CERAD classification for pathological diagnosis of AD (Sojkova et al, 2010). Our imaging-neuropathology analyses highlighted difficulties in using standard neuropathological diagnosis for autopsy validation of PiB due to differences in regions examined under the standard CERAD assessment and the brain regions showing the earliest amyloid deposition on PiB imaging. In a follow-up study (Driscoll et al, 2012), we examined the correspondence among regional (11)C-PiB load, region-matched quantitative immunohistological assessments of amyloid-beta and neurofibrillary tangles (NFT), and brain atrophy (MRI) in the same six older Baltimore Longitudinal Study of Aging participants who came to autopsy. We used unbiased stereological principles to quantify amyloid-beta plaques and NFTs in hippocampus, orbito-frontal cortex, anterior and posterior cingulate gyrus, precuneus and cerebellum. We found a general agreement between the regional measures of amyloid obtained via stereological assessment and imaging, with significant relationships evident for the anterior and posterior cingulate gyri, and the precuneus. No associations were observed between (11)C-PiB load and NFT count for any of the regions examined, or between regional Aβor NFT counts and corresponding brain volumes. These findings support the validity of the PiB imaging for quantification of amyloid plaque burden in vivo. In a follow-up to our earlier work investigating plasma clusterin, we found that higher plasma clusterin was associated with a slower rate of brain atrophy in whole brain, ventricular CSF, temporal gray matter as well as parahippocampal, superior temporal and cingulate gyri. However, this relationship was not observed in individuals who remained cognitively normal (Thambisetty et al, 2012). In a second study, we examined the risk variant rs11136000 single nucleotide polymorphism in the clusterin gene (CLU) in relation to longitudinal changes in resting state regional cerebral blood flow (rCBF) during normal aging, as well as its influence on cognitive decline in presymptomatic stages of disease progression. We examined the effect of the novel Alzheimer's disease (AD) risk variant rs11136000 single nucleotide polymorphism in the clusterin gene (CLU) on longitudinal changes in resting state regional cerebral blood flow (rCBF) during normal aging and investigated its influence on cognitive decline in presymptomatic stages of disease progression. A subset of 88 cognitively normal older individuals had longitudinal (15)O-water positron emission tomography measurements of rCBF at baseline and up to eight annual follow-up visits. We also analyzed trajectories of cognitive decline among CLU risk carriers and noncarriers in individuals who remained cognitively normal (n = 599), as well as in those who subsequently converted to mild cognitive impairment or AD (n = 95). Cognitively normal carriers of the CLU risk allele showed significant and dose-dependent longitudinal increases in resting state rCBF in brain regions intrinsic to memory processes. There were no differences in trajectories of memory performance between CLU risk carriers and noncarriers who remained cognitively normal. However, in cognitively normal individuals who eventually converted to mild cognitive impairment or AD, CLU risk carriers showed faster rates of decline in memory performance relative to noncarriers in the presymptomatic stages of disease progression. Thus, the CLU influences longitudinal changes in brain function in asymptomatic individuals and is associated with faster cognitive decline in presymptomatic stages of disease progression. In addition to the association between CLU and patterns of regional cerebral blood flow change, we found associations between baseline cardiovascular risk, measures with the Framingham Cardiovascular Risk Profile (FCRP), and subsequent change in resting rCBF. Images quantifying voxel-wise longitudinal rates of CBF change were calculated and used to examine the relationship between baseline FCRP score and changes over time in regional CBF in 97 individuals. Higher baseline FCRP scores were associated with accelerated longitudinal decline in CBF in orbitofrontal, medial frontal/anterior cingulate, insular, precuneus, and brain stem regions. Of the components that comprise the FCRP score, higher diastolic blood pressure and diabetes were associated independently with greater decline in the medial frontal/anterior cingulate and insular regions, respectively. The association between baseline risk profile and later rCBF decline emphasizes the importance of treating potentially modifiable risk factors for cognitive and brain changes. The data from this project also continue to be used for important methodological developments to enhance analysis of longitudinal neuroimaging data, including papers which aim to determine the temporal relationships among brain changes and cognitive or affective changes (Chen et al, 2012;Dotson et al, 2012;Clark et al, epub).

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National Institute on Aging (NIA)
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Gross, Alden L; Hassenstab, Jason J; Johnson, Sterling C et al. (2017) A classification algorithm for predicting progression from normal cognition to mild cognitive impairment across five cohorts: The preclinical AD consortium. Alzheimers Dement (Amst) 8:147-155
Tian, Qu; Resnick, Susan M; Bilgel, Murat et al. (2017) ?-Amyloid Burden Predicts Lower Extremity Performance Decline in Cognitively Unimpaired Older Adults. J Gerontol A Biol Sci Med Sci 72:716-723
Beason-Held, Lori L; Hohman, Timothy J; Venkatraman, Vijay et al. (2017) Brain network changes and memory decline in aging. Brain Imaging Behav 11:859-873
Tian, Qu; Chastan, Nathalie; Bair, Woei-Nan et al. (2017) The brain map of gait variability in aging, cognitive impairment and dementia-A systematic review. Neurosci Biobehav Rev 74:149-162
Bilgel, Murat; Koscik, Rebecca L; An, Yang et al. (2017) Temporal Order of Alzheimer's Disease-Related Cognitive Marker Changes in BLSA and WRAP Longitudinal Studies. J Alzheimers Dis 59:1335-1347
Habes, M; Toledo, J B; Resnick, S M et al. (2016) Relationship between APOE Genotype and Structural MRI Measures throughout Adulthood in the Study of Health in Pomerania Population-Based Cohort. AJNR Am J Neuroradiol 37:1636-42
Bilgel, Murat; An, Yang; Zhou, Yun et al. (2016) Individual estimates of age at detectable amyloid onset for risk factor assessment. Alzheimers Dement 12:373-9
Korthauer, Laura E; Nowak, Nicole T; Moffat, Scott D et al. (2016) Correlates of virtual navigation performance in older adults. Neurobiol Aging 39:118-27
Chuang, Y-F; An, Y; Bilgel, M et al. (2016) Midlife adiposity predicts earlier onset of Alzheimer's dementia, neuropathology and presymptomatic cerebral amyloid accumulation. Mol Psychiatry 21:910-5
Tian, Qu; Ferrucci, Luigi; Resnick, Susan M et al. (2016) The effect of age and microstructural white matter integrity on lap time variation and fast-paced walking speed. Brain Imaging Behav 10:697-706

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