Neuroimaging Predictors of Cognitive Decline and Impairment

National Institute On Aging

Investigators

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Abstract

Explanation Summary of work: As part of our program of research on early markers of Alzheimers disease, 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. The MRI research protocol has been expanded to all BLSA participants eligible for MRI scanning and now includes a resting state functional MR (rsfMR) and task activated fMR using a decision making task. 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 neuropathological investigations. In addition, we are using neuroimaging tools to investigate modulators of cognitive and brain changes, including sex differences in cognitive and 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 describing a variety of results from the BLSA neuroimaging study. Using voxel-wise analysis of gray matter images from structural MRI scans, we found accelerated volume declines in whole brain and regional volumes in the right temporal lobe (superior, middle, and inferior temporal gyri, parahippocampus) in individuals with hearing impairment compared with normal hearing (Lin et al, 2014). We also used these serial MRI scans to analyze spatio-temporal patterns by Hidden Markov Models (Wang et al, 2014). This approach quantifies the individual progression of brain changes to identify specific patterns of progression, e.g. AD like patterns of brain changes in cognitively normal BLSA participants. Regional features are used in conjunction with Hidden Markov Models, to measure the dynamic association between brain structure changes and progressive stages of preclinical disease over time. The goal is to use these paths to identify stages of preclinical disease. We also used high dimensional pattern regression methods, applied to MRI and PET scans, to detect imaging biomarkers of change in performance on tests of memory and executive function (Wang et al., 2013). Regression models obtained using combined gray matter, white matter, and PET blood flow imaging modalities outperformed models based on single modalities. Imaging biomarkers related to memory performance included the orbito-frontal and medial temporal cortical regions with long-term memory showing stronger correlation with the temporal lobe than short-term memory. Brain regions predicting executive performance included orbito-frontal, and occipito-temporal areas. One highlight of our publications last year was the identification of changes in brain function that occurred years before the onset of cognitive impairment (Beason-Held et al, 203). We examined changes in resting-state brain function in BLSA participants, comparing longitudinal changes in regional cerebral blood flow (rCBF), assessed by (15)O-water PET, over a mean 7 year period between participants who eventually developed cognitive impairment (n = 22) and those who remained cognitively normal (n = 99). Voxel-based mixed model analysis showed that participants with subsequent impairment showed significantly greater longitudinal rCBF increases in orbitofrontal, medial frontal, and anterior cingulate regions, and greater longitudinal decreases in parietal, temporal, and thalamic regions compared with those who maintained cognitive health. These changes were linear in nature and were not influenced by longitudinal changes in regional tissue volume. Although all participants were cognitively normal during the scanning interval, most of the accelerated rCBF changes seen in the subsequently impaired group occurred within regions thought to be critical for the maintenance of cognitive function. These changes also occurred within regions that show early accumulation of pathology in Alzheimer's disease, suggesting that there may be a connection between early pathologic change and early changes in brain function. We also have continued to investigate progression and modifiers of amyloid burden through the neuroimaging follow-ups of BLSA participants. In one study (Yotter et la, 2013), we showed greater associations between memory decline and estimated spatial patterns of amyloid deposition progression than total amyloid burden. Our results indicated that the spatial pattern of PiB retention could be a useful biomarker of cognitive decline in the early stages of amyloid deposition. In another study, we found associations between self-reported sleep and ABeta deposition on PET amyloid imaging(Spira et al., 2014). Analyzing PET-PiB images in 70 BLSA neuroimaging study participants, we found that lower sleep duration and poorer sleep quality were associated with greater amyloid burden. While it is not clear whether higher ABeta burden results in poorer sleep or poorer sleep causes increased ABeta, these findings are motivating prospective studies with objective sleep measures to determine whether sleep disturbance may cause or accelerate AD.