Neuroimaging Predictors of Cognitive Decline and Impairment

National Institute On Aging

Investigators

Linked publications & trials

Abstract

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 preclinical predictors of cognitive change and impairment, including Alzheimer's disease (AD). We continue longitudinal testing of older participants and evaluation of new participants, including MRI and neuropsychological assessments of participants younger than 55 years old. For a subsample aged 55 and older, we performed PET measurements of cerebral blood flow, followed by a PET scan using 11-C-Pittsburgh Compound B (PiB) to measure in vivo amyloid deposition. Over the last year we expanded our amyloid imaging studies from 50 scans per year to 70 scans per year through AD funding initiatives. In addition, we initiated Tau PET (AV-1451) studies of BLSA participants receiving PET amyloid scans (separate annual report). Our progress includes continued acquisition of new neuroimaging assessments and continued analysis of existing data and methods development. We use 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 during the preclinical or asymptomatic stage of disease will be critical in identifying individuals likely to benefit from interventions if a successful treatment for prevention or delaying onset of disease is available. We have published a number of papers describing results from the BLSA neuroimaging study: Decision Making and Brain Activation in Older Adults. Frontal, striatal, and medial temporal functions implicated in value-based decision processing of rewards and costs undergo substantial age-related changes. However, age effects on brain function and cognition differ across individuals. How this normative variation relates to older-adult value-based decision making is unclear. We performed a functional magnetic resonance imaging study in 173 human older adults during a lottery choice task in which costly to more desirable stakes were depicted using low to high expected values (EVs) of points (Goh et al., 2016). Across trials that varied in EVs, participants decided to accept or decline the offered stakes to maximize total accumulated points. We found that greater age was associated with less optimal decisions, accepting stakes when losses were likely and declining stakes when gains were likely, and was associated with increased frontal activity for costlier stakes. Risk preferences varied substantially across older adults and neural sensitivity to EVs in the frontal, striatal, and medial temporal areas dissociated risk-aversive from risk-taking individuals. Risk-averters increased neural responses to increasing EVs as stakes became more desirable, whereas risk-takers increased neural responses with decreasing EV as stakes became more costly. Risk preference also modulated striatal responses during feedback with risk-takers showing more positive responses to gains compared with risk-averters. Our findings highlight the frontal, striatal, and medial temporal areas as key neural loci in which individual differences differentially affect value-based decision-making ability in older adults. Through longitudinal follow-ups we will determine whether changes in decision making and their neural correlates predict subsequent cognitive impairment. Brain network changes and memory decline. It has been suggested that age-related changes within the default mode network (DMN) of the brain impact the ability to successfully perform cognitive operations. We investigated this this theory by examining functional covariance within brain networks using regional cerebral blood flow data, measured by 15O-water PET. We assessed data from 99 BLSA participants (mean baseline age 68.6 7.5) over a 7.4 year period (Beason-Held et al., 2017). The sample was divided in tertiles based on longitudinal performance on a verbal recognition memory task administered during scanning, and functional covariance was compared between the upper (improvers) and lower (decliners) tertile groups. The DMN and verbal memory networks (VMN) were then examined during the verbal memory scan condition. For each network, group differences in node-to-network coherence and individual node-to-node covariance relationships were assessed at baseline and in change over time. Compared with improvers, decliners showed differences in node-to-network coherence and in node-to-node relationships in the DMN but not the VMN during verbal memory. These DMN differences reflected greater covariance with better task performance at baseline and both increasing and declining covariance with declining task performance over time for decliners. When examined during the resting state alone, the direction of change in DMN covariance was similar to that seen during task performance, but node-to-node relationships differed from those observed during the task condition. These results suggest that disengagement of DMN components during task performance is not essential for successful cognitive performance as previously proposed. Instead, a proper balance in network processes may be needed to support optimal task performance. Motor Function and Amyloid Burden. With Drs. Stephanie Studenski, Luigi Ferrucci and Teresa Tian, we examined the relation between amyloid burden and longitudinal change in motor function (Tian et al., 2017). We studied 59 cognitively normal participants in the neuroimaging substudy of the BLSA. Participants had baseline PET-PiB scans and repeated measures of lower (usual gait speed, 400-m time, Health ABC Physical Performance Battery (HABCPPB) score, total standing balance time) and upper (mean tapping time) extremity performance during a mean follow-up of 4.7 years. After adjusting for covariates, linear mixed effect models revealed that higher mean cortical A burden was associated with greater declines in gait speed and HABCPPB score and a greater increase in 400-m time. These findings suggest that amyloid burden predicts subsequent decline in lower extremity motor function. Methodological Developments. We have continued to optimize our approach for MRI volumetric analysis. We have used the MUSE analysis pipeline to harmonize MRI volumetric data over more than 20 years, allowing analysis of predictors of neurodegeneration. In addition to these selected highlights, we are completing a manuscript investigating the independent effects of amyloid burden and neurodegeneration on cognitive change in cognitively normal older adults.