Age and neurodegeneration imaging biomarkers in persons with Alzheimer disease dementia

Abstract

Objective: To examine neurodegenerative imaging biomarkers in Alzheimer disease (AD) dementia from middle to old age.Methods: Persons with AD dementia and elevated brain b-amyloid with Pittsburgh compound B (PiB)-PET imaging underwent [18 F]-fluorodeoxyglucose (FDG)-PET and structural MRI. We evaluated 3 AD-related neurodegeneration biomarkers: hippocampal volume adjusted for total intracranial volume (HVa), FDG standardized uptake value ratio (SUVR) in regions of interest linked to AD, and cortical thickness in AD-related regions of interest. We examined associations of each biomarker with age and evaluated age effects on cutpoints defined by the 90th percentile in AD dementia. We assembled an age-, sex-, and intracranial volume-matched group of 194 similarly imaged clinically normal (CN) persons. Results:The 97 participants with AD dementia (aged 49-93 years) had PiB SUVR $1.8. A nonlinear (inverted-U) relationship between FDG SUVR and age was seen in the AD group but an inverse linear relationship with age was seen in the CN group. Cortical thickness had an inverse linear relationship with age in AD but a nonlinear (flat, then inverse linear) relationship in the CN group. HVa showed an inverse linear relationship with age in both AD and CN groups. Age effects on 90th percentile cutpoints were small for FDG SUVR and cortical thickness, but larger for HVa. Conclusions:In persons with AD dementia with elevated PiB SUVR, values of each neurodegeneration biomarker were associated with age. Cortical thickness had the smallest differences in 90th percentile cutpoints from middle to old age, and HVa the largest differences. Neurodegeneration imaging biomarkers allow us to monitor directly the pathophysiology of Alzheimer disease (AD). To explore the entire natural history of AD including its preclinical and earliest overt manifestations, it is necessary to understand the distribution of the imaging biomarkers in persons at the most impaired end of the spectrum-those with AD dementia. While much work in imaging biomarkers in AD dementia has gone into investigations for clinical diagnostic purposes, the definition of a minimum threshold for abnormal neurodegeneration is critical for studying early stages of AD. We therefore conducted analyses of MRI and PET in persons with clinically diagnosed AD dementia who had elevated b-amyloid by Pittsburgh compound B (PiB)-PET imaging. To help us distinguish between disease-related and agerelated changes, we also examined a group of clinically normal (CN) individuals who were well matched to the patients with AD dementia. Our goal was to develop definitions of neurodegeneration imaging biomarkers that were as free as possible of age interactions. Our a priori From the Departments of Neurology

Patterns of progressive atrophy vary with age in Alzheimer's disease patients

“…However, unlike Cho et al., we did not find the caudate, thalamus, or basal ganglia to be involved in patients at younger ages ( Cho et al., 2013b ). In addition, our results do not fit with a recent study by Knopman et al., who found early-onset patients showed greater deficits in glucose metabolism compared to late-onset patients but no differences in cerebral atrophy ( Knopman et al., 2016 ). Knopman was an observational community-based study, whereas the present study is a mock clinical trial.…”

Alzheimer Disease

“…98 More recent recommendations from Knopman, Jack, and colleagues are that cortical/gray matter thickness may be a more consistent, age-independent AD biomarker in contrast to hippocampal volumes that must account for age-specific norms and head size. 99 Many other MRI-based techniques are used including ventricular volume, white matter tract integrity (diffusion tensor imaging), resting state functional MRI (fMRI) as well as activation paradigm-based fMRI among others that all share the general principle of progressive decline in cerebral anatomy and functional integrity reflecting AD progression.…”

Weighting and standardization of frequencies to determine prevalence of AD imaging biomarkers

“…6 Despite the cross-sectional design, the low prevalence of positive biomarkers in 50-to 69-year-olds is consistent with the strong age dependence of declines in cortical thickness and elevations in brain amyloid levels. 30 The high prevalence of A1N1 among persons 70 and older is consistent with increasing incidence of MCI and AD dementia with increasing age. The higher prevalence of A1N2 in women than in men (1.8-fold higher in 50-to 69year-olds and 1.4-fold higher in 70-to 89-year-olds) raises questions about potential differences in the mechanisms that underlie the development of A1 in women vs men.…”