Neuroimaging Predictors of Alzheimer's Disease and Cognitive Decline

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As part of our program of research on early markers of Alzheimers disease, we continue to perform 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 individual differences in memory change over time, as well as predictors of cognitive impairment and resilience. These evaluations allow us to examine changes in brain structure and function which may be early preclinical predictors of cognitive change, impairment, including Alzheimer's disease (AD), and resilience or maintenance of cognitive health. Longitudinal neuroimaging evaluations of BLSA participants began in 1994 with approximately 160 individuals aged 55-85 at enrollment. In 2009, we expanded MRI assessments to more than 1000 individuals (with greater than 60% receiving 2 or more scans) and cognitive assessments. At present, MRI scans are conducted in conjunction with BLSA visits which vary by age: annually for individuals 80 and older, every two years for individuals 60-79, and every four years for those less than 60. For a subsample aged 55 and older, we performed PET scans using 11-C-Pittsburgh Compound B (PiB) to measure in vivo amyloid deposition in approximately 230 individuals to date, with close to 70% receiving two or more PiB scans. PET measurements of cerebral blood flow were also done in a subset of participants through 2015. In 2016, we initiated Tau PET (AV-1451) studies of BLSA participants receiving PET amyloid scans (separate annual report), with more than 100 individuals receiving Tau PET to date. Our progress includes continued acquisition of neuroimaging assessments, 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. Early detection of accelerated brain changes during the preclinical or asymptomatic stages of disease will be critical in identifying individuals likely to benefit from interventions if a successful treatment for prevention or delaying onset of AD is available. Key publications over the last year are highlighted in the following sections. We continued investigation of the associations between hearing loss and brain volumes, investigating the relation between midlife hearing impairment and late-life temporal lobe volume loss (Armstrong et al, in press). Hearing loss is a highly prevalent condition in older adults and is a risk factor for Alzheimers disease and related dementias (ADRD). However, the mechanisms underlying this relationship and the temporal association between sensory decline and cognitive decline have been unclear. In a previous study, we found that hearing loss was associated with longitudinal volumetric declines in whole brain and regional volumes in the right temporal lobe in older adults (Lin et al., 2014). We extended these findings by examining the relationship between mid-life hearing assessment and late-life MRI scans in 194 BLSA participants. We found that poorer mid-life hearing was associated with steeper late-life volumetric declines in right temporal gray matter, right hippocampus, and left entorhinal cortex, generally in line with our earlier report. These studies are consistent with the hypothesis that change in brain structure/function may mediate the association between hearing loss and ADRD. In a recent publication, we investigated hippocampal activation and connectivity in the aging brain (Beason-Held et al. 2020). Functional MRI studies were acquired in 210 older BLSA participants during performance of an associative face-scene (Face-Place) encoding task designed to target the hippocampus and underlying cortices. Brain activation patterns were examined during encoding of novel Face-Place pairs, and functional connectivity of the hippocampus was also examined during encoding, with seed regions placed in the hippocampal head, body, and tail. Validating our objective, task activation patterns included the hippocampus and underlying ventral temporal cortices. Functional connectivity analyses during encoding showed that the hippocampal head was connected to frontal and anterior/middle temporal brain regions, the body with frontal, widespread temporal and occipital regions, and the tail with posterior temporal and occipital cortex. Longitudinal assessments are ongoing and will identify changes in hippocampal activation and connectivity that predict development of cognitive decline. In Han et al (2020), we implemented a new method for cerebellar parcellation using convolutional neural networks to investigate cross-sectional and longitudinal age effects on 28 cerebellar subregions. We analyzed 2023 MRI scans from 822 cognitively normal BLSA participants ranging in age from 50-95 years. Using linear mixed effects models, we found spatially varying atrophy patterns across the cerebellum with respect to age and sex in both cross-sectional and longitudinal analyses. Future work will investigate the associations with cognitive and motor outcomes and whether trajectories of cerebellar atrophy vary with cognitive status. BLSA PiB data have been used in two recent collaborative studies. Through an MRC UK - NIH collaborative fellowship program, Dr. Ivan Koychev investigated trajectories of rapid amyloid accumulation using PiB data in BLSA and CSF amyloid and phosphorylated-Tau accumulation in BIOCARD participants (Koychev et al., 2020). In another collaborative study, an association was demonstrated between common variants in RBFOX1, an RNA-binding protein, and brain amyloidosis in early and preclinical Alzheimer Disease (Raghavan et al., 2020). Our methodological paper on surrogate measures of regional cerebral blood flow was published over the last period (Bilgel et al., JCBFM 2020). We investigated whether surrogates of neuronal activity, measured by regional cerebral blood flow (rCBF), can be estimated from dynamic amyloid PET imaging. Using data for 149 BLSA participants (345 visits), we assessed whether the average of early amyloid frames (EA) and R1 computed from dynamic PiB PET can serve as surrogates of rCBF computed from 15O-H2O-PET. We found that regional PiB-based measures, in particular R1, can be suitable surrogates of rCBF, perhaps obviating the need for a separate scan to measure neuronal activity and reducing patient burden, radioactivity exposure, and cost. Data generated by this project are also used by many intramural and extramural collaborators for methods development and in studies of the neural underpinnings of motor function, energetics, sleep and a variety of sensorimotor functions. They are also used actively in the Preclinical AD Consortium, led by Marilyn Albert of Johns Hopkins, and the iSTAGING consortium, led by Christos Davatzikos of the University of Pennsylvania.