Brain aerobic glycolysis and resilience in Alzheimer disease.

The distribution of brain aerobic glycolysis (AG) in normal young adults correlates spatially with amyloid-beta (Aß) deposition in individuals with symptomatic and preclinical Alzheimer disease (AD). Brain AG decreases with age, but the functional significance of this decrease with regard to the development of AD symptomatology is poorly understood. Using PET measurements of regional blood flow, oxygen consumption, and glucose utilization-from which we derive AG-we find that cognitive impairment is strongly associated with loss of the typical youthful pattern of AG. In contrast, amyloid positivity without cognitive impairment was associated with preservation of youthful brain AG, which was even higher than that seen in cognitively unimpaired, amyloid negative adults. Similar findings were not seen for blood flow nor oxygen consumption. Finally, in cognitively unimpaired adults, white matter hyperintensity burden was found to be specifically associated with decreased youthful brain AG. Our results suggest that AG may have a role in the resilience and/or response to early stages of amyloid pathology and that age-related white matter disease may impair this process.

Persistent metabolic youth in the aging female brain.

Sex differences influence brain morphology and physiology during both development and aging. Here we apply a machine learning algorithm to a multiparametric brain PET imaging dataset acquired in a cohort of 20- to 82-year-old, cognitively normal adults (n = 205) to define their metabolic brain age. We find that throughout the adult life span the female brain has a persistently lower metabolic brain age-relative to their chronological age-compared with the male brain. The persistence of relatively younger metabolic brain age in females throughout adulthood suggests that development might in part influence sex differences in brain aging. Our results also demonstrate that trajectories of natural brain aging vary significantly among individuals and provide a method to measure this.

Advanced structural brain aging in preclinical autosomal dominant Alzheimer disease.

BACKGROUND: "Brain-predicted age" estimates biological age from complex, nonlinear features in neuroimaging scans. The brain age gap (BAG) between predicted and chronological age is elevated in sporadic Alzheimer disease (AD), but is underexplored in autosomal dominant AD (ADAD), in which AD progression is highly predictable with minimal confounding age-related co-pathology. METHODS: We modeled BAG in 257 deeply-phenotyped ADAD mutation-carriers and 179 non-carriers from the Dominantly Inherited Alzheimer Network using minimally-processed structural MRI scans. We then tested whether BAG differed as a function of mutation and cognitive status, or estimated years until symptom onset, and whether it was associated with established markers of amyloid (PiB PET, CSF amyloid-ß-42/40), phosphorylated tau (CSF and plasma pTau-181), neurodegeneration (CSF and plasma neurofilament-light-chain [NfL]), and cognition (global neuropsychological composite and CDR-sum of boxes). We compared BAG to other MRI measures, and examined heterogeneity in BAG as a function of ADAD mutation variants, APOE Îµ4 carrier status, sex, and education. RESULTS: Advanced brain aging was observed in mutation-carriers approximately 7 years before expected symptom onset, in line with other established structural indicators of atrophy. BAG was moderately associated with amyloid PET and strongly associated with pTau-181, NfL, and cognition in mutation-carriers. Mutation variants, sex, and years of education contributed to variability in BAG. CONCLUSIONS: We extend prior work using BAG from sporadic AD to ADAD, noting consistent results. BAG associates well with markers of pTau, neurodegeneration, and cognition, but to a lesser extent, amyloid, in ADAD. BAG may capture similar signal to established MRI measures. However, BAG offers unique benefits in simplicity of data processing and interpretation. Thus, results in this unique ADAD cohort with few age-related confounds suggest that brain aging attributable to AD neuropathology can be accurately quantified from minimally-processed MRI.

Falls: a marker of preclinical Alzheimer disease: a cohort study protocol.

INTRODUCTION: Progression to symptomatic Alzheimer disease (AD) occurs slowly over a series of preclinical stages. Declining functional mobility may be an early indicator of loss of brain network integration and may lead to an increased risk of experiencing falls. It is unknown whether measures of functional mobility and falls are preclinical markers of AD. The purpose of this study is to examine (1) the relationship between falls and functional mobility with AD biomarkers to determine when falls occur within the temporal progression to symptomatic Alzheimer disease, and (2) the attentional compared with perceptual/motor systems that underlie falls and functional mobility changes seen with AD. METHODS AND ANALYSIS: This longitudinal cohort study will be conducted at the Knight Alzheimer Disease Research Center. Approximately 350 cognitively normal participants (with and without preclinical AD) will complete an in-home visit every year for 4 years. During each yearly assessment, functional mobility will be assessed using the Performance Oriented Mobility Assessment, Timed Up and Go, and Timed Up and Go dual task. Data regarding falls (including number and severity) will be collected monthly by self-report and confirmed through interviews. This study will leverage ongoing neuropsychological assessments and neuroimaging (including molecular imaging using positron emission tomography and MRI) performed by the Knight Alzheimer Disease Research Center. Relationships between falls and biomarkers of amyloid, tau and neurodegeneration will be evaluated. ETHICS AND DISSEMINATION: This study was approved by the Washington University in St. Louis Institutional Review Board (reference number 201807135). Written informed consent will be obtained in the home prior to the collection of any study data. Results will be published in peer-reviewed publications and presented at national and international conferences. TRIAL REGISTRATION NUMBER: NCT04949529; Pre-results.

Relationships between big-five personality factors and Alzheimer's disease pathology in autosomal dominant Alzheimer's disease.

INTRODUCTION: Changes in personality characteristics are associated with the onset of symptoms in Alzheimer's disease (AD) and may even precede clinical diagnosis. However, personality changes caused by disease progression can be difficult to separate from changes that occur with normal aging. The Dominantly Inherited Alzheimer Network (DIAN) provides a unique cohort in which to relate measures of personality traits to in vivo markers of disease in a much younger sample than in typical late onset AD. METHODS: Personality traits measured with the International Personality Item Pool at baseline from DIAN participants were analyzed as a function of estimated years to onset of clinical symptoms and well-established AD biomarkers. RESULTS: Both neuroticism and conscientiousness were correlated with years to symptom onset and markers of tau pathology in the cerebrospinal fluid. Self-reported conscientiousness and both neuroticism and conscientiousness ratings from a collateral source were correlated with longitudinal rates of cognitive decline such that participants who were rated as higher on neuroticism and lower on conscientiousness exhibited accelerated rates of cognitive decline. DISCUSSION: Personality traits are correlated with the accumulation of AD pathology and time to symptom onset, suggesting that AD progression can influence an individual's personality characteristics. Together these findings suggest that measuring neuroticism and conscientiousness may hold utility in tracking disease progression in AD.

Aerobic glycolysis and tau deposition in preclinical Alzheimer's disease.

Research of the human brain metabolism in vivo has largely focused on total glucose use (via fluorodeoxyglucose positron emission tomography) and, until recently, did not examine the use of glucose outside oxidative phosphorylation, which is known as aerobic glycolysis (AG). AG supports important functions including biosynthesis and neuroprotection but decreases dramatically with aging. This multitracer positron emission tomography study evaluated the relationship between AG, total glucose use (CMRGlc), oxygen metabolism (CMRO2), tau, and amyloid deposition in 42 individuals, including those at preclinical and symptomatic stages of Alzheimer's disease. Our findings demonstrate that in individuals with amyloid burden, lower AG is associated with higher tau deposition. No such correlation was observed for CMRGlc or CMRO2. We suggest that aging-related loss of AG leading to decreased synaptic plasticity and neuroprotection may accelerate tauopathy in individuals with amyloid burden. Longitudinal AG and Alzheimer's disease pathology studies are needed to verify causality.

Quantitative hemodynamic PET imaging using image-derived arterial input function and a PET/MR hybrid scanner.

Positron emission tomography (PET) with 15O-tracers is commonly used to measure brain hemodynamic parameters such as cerebral blood flow, cerebral blood volume, and cerebral metabolic rate of oxygen. Conventionally, the absolute quantification of these parameters requires an arterial input function that is obtained invasively by sampling blood from an artery. In this work, we developed and validated an image-derived arterial input function technique that avoids the unreliable and burdensome arterial sampling procedure for full quantitative 15O-PET imaging. We then compared hemodynamic PET imaging performed on a PET/MR hybrid scanner against a conventional PET only scanner. We demonstrated the proposed imaging-based technique was able to generate brain hemodynamic parameter measurements in strong agreement with the traditional arterial sampling based approach. We also demonstrated that quantitative 15O-PET imaging can be successfully implemented on a PET/MR hybrid scanner.

Loss of Brain Aerobic Glycolysis in Normal Human Aging.

The normal aging human brain experiences global decreases in metabolism, but whether this affects the topography of brain metabolism is unknown. Here we describe PET-based measurements of brain glucose uptake, oxygen utilization, and blood flow in cognitively normal adults from 20 to 82 years of age. Age-related decreases in brain glucose uptake exceed that of oxygen use, resulting in loss of brain aerobic glycolysis (AG). Whereas the topographies of total brain glucose uptake, oxygen utilization, and blood flow remain largely stable with age, brain AG topography changes significantly. Brain regions with high AG in young adults show the greatest change, as do regions with prolonged developmental transcriptional features (i.e., neoteny). The normal aging human brain thus undergoes characteristic metabolic changes, largely driven by global loss and topographic changes in brain AG.

Diffusion tensor MRI as a biomarker in axonal and myelin damage.

Diffusion tensor imaging has been used extensively as a research tool to understand the structural changes associated with white matter pathology. Using water diffusion as the basis to construct anatomic details, diffusion tensor imaging offers the potential to identify structural and functional adaptations before gross anatomical changes, such as lesions and tumors, become apparent on conventional MRI. Over the past 10 years, further parameters, such as axial and radial diffusivity, have been developed to characterize white matter changes specific to axons and myelin. In this paper, the potential application and outstanding issues on the use of diffusion tensor imaging directional diffusivity as a biomarker in axonal and myelin damage in neurological disorders will be reviewed.