In Pre-Clinical AD Small Vessel Disease is Associated With Altered Hippocampal Connectivity and Atrophy.

OBJECTIVE: Small Vessel Disease (SVD) is known to be associated with higher AD risk, but its relationship to amyloidosis in the progression of AD is unclear. In this cross-sectional study of cognitively normal older adults, we explored the interactive effects of SVD and amyloid-beta (Aß) pathology on hippocampal functional connectivity during an associative encoding task and on hippocampal volume. METHODS: This study included 61 cognitively normal older adults (age range: 65-93 years, age mean ± standard deviation: 75.8 ± 6.4, 41 [67.2%] female). PiB PET, T2-weighted FLAIR, T1-weighted and face-name fMRI images were acquired on each participant to evaluate brain Aß, white matter hyperintensities (WMH+/- status), gray matter density, and hippocampal functional connectivity. RESULTS: We found that, in WMH (+) older adults greater Aß burden was associated with greater hippocampal local connectivity (i.e., hippocampal-parahippocampal connectivity) and lower gray matter density in medial temporal lobe (MTL), whereas in WMH (-) older adults greater Aß burden was associated with greater hippocampal distal connectivity (i.e., hippocampal-prefrontal connectivity) and no changes in MTL gray matter density. Moreover, greater hippocampal local connectivity was associated with MTL atrophy. CONCLUSION: These observations support a hippocampal excitotoxicity model linking SVD to neurodegeneration in preclinical AD. This may explain how SVD may accelerate the progression from Aß positivity to neurodegeneration, and subsequent AD.

Prevalence Estimates of Amyloid Abnormality Across the Alzheimer Disease Clinical Spectrum.

IMPORTANCE: One characteristic histopathological event in Alzheimer disease (AD) is cerebral amyloid aggregation, which can be detected by biomarkers in cerebrospinal fluid (CSF) and on positron emission tomography (PET) scans. Prevalence estimates of amyloid pathology are important for health care planning and clinical trial design. OBJECTIVE: To estimate the prevalence of amyloid abnormality in persons with normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia and to examine the potential implications of cutoff methods, biomarker modality (CSF or PET), age, sex, APOE genotype, educational level, geographical region, and dementia severity for these estimates. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional, individual-participant pooled study included participants from 85 Amyloid Biomarker Study cohorts. Data collection was performed from January 1, 2013, to December 31, 2020. Participants had normal cognition, subjective cognitive decline, mild cognitive impairment, or clinical AD dementia. Normal cognition and subjective cognitive decline were defined by normal scores on cognitive tests, with the presence of cognitive complaints defining subjective cognitive decline. Mild cognitive impairment and clinical AD dementia were diagnosed according to published criteria. EXPOSURES: Alzheimer disease biomarkers detected on PET or in CSF. MAIN OUTCOMES AND MEASURES: Amyloid measurements were dichotomized as normal or abnormal using cohort-provided cutoffs for CSF or PET or by visual reading for PET. Adjusted data-driven cutoffs for abnormal amyloid were calculated using gaussian mixture modeling. Prevalence of amyloid abnormality was estimated according to age, sex, cognitive status, biomarker modality, APOE carrier status, educational level, geographical location, and dementia severity using generalized estimating equations. RESULTS: Among the 19 097 participants (mean [SD] age, 69.1 [9.8] years; 10 148 women [53.1%]) included, 10 139 (53.1%) underwent an amyloid PET scan and 8958 (46.9%) had an amyloid CSF measurement. Using cohort-provided cutoffs, amyloid abnormality prevalences were similar to 2015 estimates for individuals without dementia and were similar across PET- and CSF-based estimates (24%; 95% CI, 21%-28%) in participants with normal cognition, 27% (95% CI, 21%-33%) in participants with subjective cognitive decline, and 51% (95% CI, 46%-56%) in participants with mild cognitive impairment, whereas for clinical AD dementia the estimates were higher for PET than CSF (87% vs 79%; mean difference, 8%; 95% CI, 0%-16%; P = .04). Gaussian mixture modeling-based cutoffs for amyloid measures on PET scans were similar to cohort-provided cutoffs and were not adjusted. Adjusted CSF cutoffs resulted in a 10% higher amyloid abnormality prevalence than PET-based estimates in persons with normal cognition (mean difference, 9%; 95% CI, 3%-15%; P = .004), subjective cognitive decline (9%; 95% CI, 3%-15%; P = .005), and mild cognitive impairment (10%; 95% CI, 3%-17%; P = .004), whereas the estimates were comparable in persons with clinical AD dementia (mean difference, 4%; 95% CI, -2% to 9%; P = .18). CONCLUSIONS AND RELEVANCE: This study found that CSF-based estimates using adjusted data-driven cutoffs were up to 10% higher than PET-based estimates in people without dementia, whereas the results were similar among people with dementia. This finding suggests that preclinical and prodromal AD may be more prevalent than previously estimated, which has important implications for clinical trial recruitment strategies and health care planning policies.

Neurofibrillary tau depositions emerge with subthreshold cerebral beta-amyloidosis in down syndrome.

INTRODUCTION: Adults with Down syndrome are genetically predisposed to develop Alzheimer's disease and accumulate beta-amyloid plaques (Aß) early in life. While Aß has been heavily studied in Down syndrome, its relationship with neurofibrillary tau is less understood. The aim of this study was to evaluate neurofibrillary tau deposition in individuals with Down syndrome with varying levels of Aß burden. METHODS: A total of 161 adults with Down syndrome (mean age = 39.2 (8.50) years) and 40 healthy, non-Down syndrome sibling controls (43.2 (12.6) years) underwent T1w-MRI, [C-11]PiB and [F-18]AV-1451 PET scans. PET images were converted to units of standardized uptake value ratios (SUVrs). Aß burden was calculated using the amyloid load metric (AßL); a measure of global Aß burden that improves quantification from SUVrs by suppressing the nonspecific binding signal component and computing the specific Aß signal from all Aß-carrying voxels from the image. Regional tau was assessed using control-standardized AV-1451 SUVr. Control-standardized SUVrs were compared across Down syndrome groups of Aß-negative (A-) (AßL < 13.3), subthreshold A+ (13.3 ≤ AßL < 20) and conventionally A+ (AßL ≥ 20) individuals. The subthreshold A + group was identified as having significantly higher Aß burden compared to the A- group, but not high enough to satisfy a conventional A + classification. RESULTS: A large-sized association that survived adjustment for chronological age, mental age (assessed using the Peabody Picture Vocabulary Test), and imaging site was observed between AßL and AV-1451 within each Braak region (p < .05). The A + group showed significantly higher AV-1451 retention across all Braak regions compared to the A- and subthreshold A + groups (p < .05). The subthreshold A + group showed significantly higher AV-1451 retention in Braak regions I-III compared to an age-matched sample from the A- group (p < .05). DISCUSSION: These results show that even the earliest detectable Aß accumulation in Down syndrome is accompanied by elevated tau in the early Braak stage regions. This early detection of tau can help characterize the tau accumulation phase during preclinical Alzheimer's disease progression in Down syndrome and suggests that there may be a relatively narrow window after Aß accumulation begins to prevent the downstream cascade of events that leads to Alzheimer's disease.

Predicting resistance to amyloid-beta deposition and cognitive resilience in the oldest-old.

OBJECTIVE: To explore long-term predictors of avoiding ß-amyloid (Aß) deposition and maintaining unimpaired cognition as outcomes in the oldest old. METHODS: In a longitudinal observational cohort study, 100 former participants of the Ginkgo Evaluation of Memory Study (GEMS; 2000-2008) completed biannual Pittsburgh compound B-PET imaging and annual clinical-cognitive evaluations beginning in 2010. Most recent Aß status and cognitive status were selected for each participant. Longitudinal outcomes included change in serial Aß and cognitive tests. Baseline predictors from GEMS included neuropsychological tests, daily functioning, APOE genotype, lifestyle variables, occupational measures, health history, sleep, subjective memory, physical and cognitive activities, depressive symptoms, and physical performance and health indices, among others. RESULTS: Mean age at the last cognitive evaluation was 92.0 (range 86-100) years. Mean follow-up time from baseline to last measured Aß status was 12.3 (SD 1.9) years and to last cognitive evaluation was 14.1 (SD 1.9) years. The APOE*2 allele predicted last Aß status (n = 34 Aß negative vs n = 66 Aß positive). Baseline cognition predicted cognitive status (n = 30 unimpaired vs n = 70 impaired). Predictors of cognitive status among Aß-positive participants only (n = 14 normal cognition vs n = 52 impaired) were baseline cognitive test scores and smoking history. Baseline pulse pressure predicted longitudinal Aß increase; paid work engagement and life satisfaction predicted less cognitive decline. CONCLUSIONS: The APOE*2 allele and lower pulse pressure predict resistance to Aß deposition in advanced aging. Cognitive test scores 14 years prior, likely reflecting premorbid abilities, predict cognitive status and maintenance of unimpaired cognition in the presence of Aß. Several lifestyle factors appear protective.

Fluid and PET biomarkers for amyloid pathology in Alzheimer's disease.

Alzheimer's disease (AD) is characterized by amyloid plaques and tau pathology (neurofibrillary tangles and neuropil threads). Amyloid plaques are primarily composed of aggregated and oligomeric ß-amyloid (Aß) peptides ending at position 42 (Aß42). The development of fluid and PET biomarkers for Alzheimer's disease (AD), has allowed for detection of Aß pathology in vivo and marks a major advancement in understanding the role of Aß in Alzheimer's disease (AD). In the recent National Institute on Aging and Alzheimer's Association (NIA-AA) Research Framework, AD is defined by the underlying pathology as measured in patients during life by biomarkers (Jack et al., 2018), while clinical symptoms are used for staging of the disease. Therefore, sensitive, specific and robust biomarkers to identify brain amyloidosis are central in AD research. Here, we discuss fluid and PET biomarkers for Aß and their application.

Early striatal amyloid deposition distinguishes Down syndrome and autosomal dominant Alzheimer's disease from late-onset amyloid deposition.

INTRODUCTION: The objective of this study was to evaluate amyloid ß (Aß) deposition patterns in different groups of cerebral ß amyloidosis: (1) nondemented with amyloid precursor protein overproduction (Down syndrome); (2) nondemented with abnormal processing of amyloid precursor protein (preclinical autosomal dominant Alzheimer disease); (3) presumed alteration in Aß clearance with clinical symptoms (late-onset AD); and (4) presumed alterations in Aß clearance (preclinical AD). METHODS: We performed whole-brain voxelwise comparison of cerebral Aß between 23 Down syndrome, 10 preclinical autosomal dominant Alzheimer disease, 17 late-onset AD, and 16 preclinical AD subjects, using Pittsburgh Compound B-positron emission tomography. RESULTS: We found both Down syndrome and preclinical autosomal dominant Alzheimer disease shared a distinct pattern of increased bilateral striatal and thalamic Aß deposition compared to late-onset AD and preclinical AD. CONCLUSION: Disorders associated with early-life alterations in amyloid precursor protein production or processing are associated with a distinct pattern of early striatal fibrillary Aß deposition before significant cognitive impairment. A better understanding of this unique pattern could identify important mechanisms of Aß deposition and possibly important targets for early intervention.

Classification of amyloid-positivity in controls: comparison of visual read and quantitative approaches.

UNLABELLED: An important research application of amyloid imaging with positron emission tomography (PET) is detection of the earliest evidence of fibrillar amyloid-beta (Aß) deposition. Use of amyloid PET for this purpose, requires a reproducible method for defining a cutoff that separates individuals with no significant Aß deposition from those in which Aß deposition has begun. We previously reported the iterative outlier approach (IO) for the analysis of Pittsburgh Compound-B (PiB) PET data. Developments in amyloid imaging since the initial report of IO have led us to re-examine the generalizability of this method. IO was developed using full-dynamic atrophy-corrected PiB PET data obtained from a group of control subjects with a fairly distinct separation between PiB-positive [PiB(+)] and PiB-negative [PiB(-)] subjects. METHODS: We tested the performance of IO using late-summed tissue ratio data with atrophy correction or with an automated template method without atrophy correction and tested the robustness of the method when applied to a cohort of older subjects in which separation between PiB(+) and PiB(-) subjects was not so distinct. RESULTS: The IO method did not perform consistently across analyses and performed particularly poorly when separation was less clear. We found that a sparse k-means (SKM) cluster analysis approach performed significantly better; performing more consistently across methods and subject cohorts. We also compared SKM to a consensus visual read approach and found very good correspondence. CONCLUSION: The visual read and SKM methods, applied together, may optimize the identification of early Aß deposition. These methods have the potential to provide a standard approach to the detection of PiB-positivity that is generalizable across centers.