Selective worsening of brain injury biomarker abnormalities in cognitively normal elderly persons with β-amyloidosis

Elevated cerebral blood flow proxy with increased beta-amyloid burden in Alzheimer's disease preclinical phase evaluated by dual-phase 18F-florbetaben positron emission tomography

This study investigated the earliest change of cerebral blood flow (CBF) and its relationship with β-amyloid (Aβ) burden in preclinical Alzheimer's disease (AD) employing dual-phase 18F-florbetaben (FBB) PET. Seventy-one cognitively normal (NC) individuals were classified as Aβ negative (Aβ-NC) or positive (Aβ+NC) based on two different cutoff values: an SUVR of > 1.08 and a Centiloid scale of > 20. The PET scans were acquired in two phases: an early phase (0-10 min, eFBB) and a delayed phase (90-110 min, dFBB), which were averaged to generate single-frame images for each phase. Furthermore, an R1 parametric map was generated from the early phase data using a simplified reference tissue model. We conducted regional and voxel-based analyses to compare the eFBB, dFBB, and R1 images between the Aβ positive and negative groups. In addition, the correlations between the CBF proxy R1 and the dFBB SUVR were analyzed. The Aβ+NC group showed significantly higher dFBB SUVR in both the global cerebral cortex and target regions compared to the Aβ-NC group, while no significant differences were observed in eFBB SUVR between the two groups. Furthermore, the Aβ+NC group exhibited significantly higher R1 values, a proxy for cerebral perfusion, in both the global cerebral cortex and target regions compared to the Aβ-NC group. Significant positive correlations were observed between R1 and dFBB SUVR in both the global cerebral cortex and target regions, which remained significant after controlling for demographics and cognitive profiles, except for the medial temporal and occipital cortices. The findings reveal increased CBF in preclinical AD and a positive correlation between CBF and amyloid pathology. The positive correlation between R1 and amyloid burden may indicate a compensatory mechanism in the preclinical stage of Alzheimer's disease, but to elucidate this hypothesis, further longitudinal observational studies are necessary.

Biomarkers of Aging and Relevant Evaluation Techniques: A Comprehensive Review

The risk of developing chronic illnesses and disabilities is increasing with age. To predict and prevent aging, biomarkers relevant to the aging process must be identified. This paper reviews the known molecular, cellular, and physiological biomarkers of aging. Moreover, we discuss the currently available technologies for identifying these biomarkers, and their applications and potential in aging research. We hope that this review will stimulate further research and innovation in this emerging and fast-growing field.

Can hippocampal subfield measures supply information that could be used to improve the diagnosis of Alzheimer's disease?

The diagnosis of Alzheimer's disease (AD) needs to be improved. We investigated if hippocampal subfield volume measured by structural imaging, could supply information, so that the diagnosis of AD could be improved. In this study, subjects were classified based on clinical, neuropsychological, and amyloid positivity or negativity using PET scans. Data from 478 elderly Korean subjects grouped as cognitively unimpaired β-amyloid-negative (NC), cognitively unimpaired β-amyloid-positive (aAD), mild cognitively impaired β-amyloid-positive (pAD), mild cognitively impaired-specific variations not due to dementia β-amyloid-negative (CIND), severe cognitive impairment β-amyloid-positive (ADD+) and severe cognitive impairment β-amyloid-negative (ADD-) were used. NC and aAD groups did not show significant volume differences in any subfields. The CIND did not show significant volume differences when compared with either the NC or the aAD (except L-HATA). However, pAD showed significant volume differences in Sub, PrS, ML, Tail, GCMLDG, CA1, CA4, HATA, and CA3 when compared with the NC and aAD. The pAD group also showed significant differences in the hippocampal tail, CA1, CA4, molecular layer, granule cells/molecular layer/dentate gyrus, and CA3 when compared with the CIND group. The ADD- group had significantly larger volumes than the ADD+ group in the bilateral tail, SUB, PrS, and left ML. The results suggest that early amyloid depositions in cognitive normal stages are not accompanied by significant bilateral subfield volume atrophy. There might be intense and accelerated subfield volume atrophy in the later stages associated with the cognitive impairment in the pAD stage, which subsequently could drive the progression to AD dementia. Early subfield volume atrophy associated with the β-amyloid burden may be characterized by more symmetrical atrophy in CA regions than in other subfields. We conclude that the hippocampal subfield volumetric differences from structural imaging show promise for improving the diagnosis of Alzheimer's disease.

PET Imaging of Dementia: Update 2022

ABSTRACT

PET imaging plays an essential role in achieving earlier and more specific diagnoses of dementia syndromes, important for clinical prognostication and optimal medical management. This has become especially vital with the recent development of pathology-specific disease-modifying therapy for Alzheimer disease, which will continue to evolve and require methods to select appropriate treatment candidates. Techniques that began as research tools such as amyloid and tau PET have now entered clinical use, making nuclear medicine physicians and radiologists essential members of the care team. This review discusses recent changes in the understanding of dementia and examines the roles of nuclear medicine imaging in clinical practice. Within this framework, multiple cases will be shown to illustrate a systematic approach of FDG PET interpretation and integration of PET imaging of specific molecular pathology including dopamine transporters, amyloid, and tau. The approach presented here incorporates contemporary understanding of both common and uncommon dementia syndromes, intended as an updated practical guide to assist with the sophisticated interpretation of nuclear medicine examinations in the context of this rapidly and continually developing area of imaging.

Engineering extracellular vesicles for Alzheimer's disease: An emerging cell-free approach for earlier diagnosis and treatment

Alzheimer's disease (AD) is a debilitating neurodegenerative disorder affecting over five million people globally and has no established cure. Current AD-related treatments only alleviate cognitive and behavioral symptoms and do not address disease onset or progression, underlining the unmet need to create an effective, innovative AD therapeutic. Extracellular vesicles (EVs) have emerged as a new class of nanotherapeutics. These secreted, lipid-bound cellular signaling carriers show promise for potential clinical applications for neurodegenerative diseases like AD. Additionally, analyzing contents and characteristics of patient-derived EVs may address the unmet need for earlier AD diagnostic techniques, informing physicians of altered genetic expression or cellular communications specific to healthy and diseased physiological states. There are numerous recent advances in regenerative medicine using EVs and include bioengineering perspectives to modify EVs, target glial cells in neurodegenerative diseases like AD, and potentially use EVs to diagnose and treat AD earlier. This article is categorized under: Neurological Diseases > Biomedical Engineering Neurological Diseases > Molecular and Cellular Physiology Neurological Diseases > Stem Cells and Development.

Deep learning identifies brain structures that predict cognition and explain heterogeneity in cognitive aging

Specific brain structures (gray matter regions and white matter tracts) play a dominant role in determining cognitive decline and explain the heterogeneity in cognitive aging. Identification of these structures is crucial for screening of older adults at risk of cognitive decline. Using deep learning models augmented with a model-interpretation technique on data from 1432 Mayo Clinic Study of Aging participants, we identified a subset of brain structures that were most predictive of individualized cognitive trajectories and indicative of cognitively resilient vs. vulnerable individuals. Specifically, these structures explained why some participants were resilient to the deleterious effects of elevated brain amyloid and poor vascular health. Of these, medial temporal lobe and fornix, reflective of age and pathology-related degeneration, and corpus callosum, reflective of inter-hemispheric disconnection, accounted for 60% of the heterogeneity explained by the most predictive structures. Our results are valuable for identifying cognitively vulnerable individuals and for developing interventions for cognitive decline.

Regional age-related atrophy after screening for preclinical alzheimer disease

Brain atrophy occurs in aging even in the absence of dementia, but it is unclear to what extent this is due to undetected preclinical Alzheimer disease. Here we examine a cross-sectional cohort (ages 18-88) free from confounding influence of preclinical Alzheimer disease, as determined by amyloid PET scans and three years of clinical evaluation post-imaging. We determine the regional strength of age-related atrophy using linear modeling of brain volumes and cortical thicknesses with age. Age-related atrophy was seen in nearly all regions, with greatest effects in the temporal lobe and subcortical regions. When modeling age with the estimated derivative of smoothed aging curves, we found that the temporal lobe declined linearly with age, subcortical regions declined faster at later ages, and frontal regions declined slower at later ages than during midlife. This age-derivative pattern was distinct from the linear measure of age-related atrophy and significantly associated with a measure of myelin. Atrophy did not detectably differ from a preclinical Alzheimer disease cohort when age ranges were matched.

Exploring brain glucose metabolic patterns in cognitively normal adults at risk of Alzheimer's disease: A cross-validation study with Chinese and ADNI cohorts

OBJECTIVE

Disease-related metabolic brain patterns have been verified for a variety of neurodegenerative diseases including Alzheimer's disease (AD). This study aimed to explore and validate the pattern derived from cognitively normal controls (NCs) in the Alzheimer's continuum.

METHODS

This study was based on two cohorts; one from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the other from the Sino Longitudinal Study on Cognitive Decline (SILCODE). Each subject underwent [18F]fluoro-2-deoxyglucose positron emission tomography (PET) and [18F]florbetapir-PET imaging. Participants were binary-grouped based on β-amyloid (Aβ) status, and the positivity was defined as Aβ+. Voxel-based scaled subprofile model/principal component analysis (SSM/PCA) was used to generate the "at-risk AD-related metabolic pattern (ARADRP)" for NCs. The pattern expression score was obtained and compared between the groups, and receiver operating characteristic curves were drawn. Notably, we conducted cross-validation to verify the robustness and correlation analyses to explore the relationships between the score and AD-related pathological biomarkers.

RESULTS

Forty-eight Aβ+ NCs and 48 Aβ- NCs were included in the ADNI cohort, and 25 Aβ+ NCs and 30 Aβ- NCs were included in the SILCODE cohort. The ARADRPs were identified from the combined cohorts and the two separate cohorts, characterized by relatively lower regional loadings in the posterior parts of the precuneus, posterior cingulate, and regions of the temporal gyrus, as well as relatively higher values in the superior/middle frontal gyrus and other areas. Patterns identified from the two separate cohorts showed some regional differences, including the temporal gyrus, basal ganglia regions, anterior parts of the precuneus, and middle cingulate. Cross-validation suggested that the pattern expression score was significantly higher in the Aβ+ group of both cohorts (p < 0.01), and contributed to the diagnosis of Aβ+ NCs (with area under the curve values of 0.696-0.815). The correlation analysis revealed that the score was related to tau pathology measured in cerebrospinal fluid (p-tau: p < 0.02; t-tau: p < 0.03), but not Aβ pathology assessed with [18F]florbetapir-PET (p > 0.23).

CONCLUSIONS

ARADRP exists for NCs, and the acquired pattern expression score shows a certain ability to discriminate Aβ+ NCs from Aβ- NCs. The SSM/PCA method is expected to be helpful in the ultra-early diagnosis of AD in clinical practice.

Convolutional Neural Net Learning Can Achieve Production-Level Brain Segmentation in Structural Magnetic Resonance Imaging

Deep learning implementations using convolutional neural nets have recently demonstrated promise in many areas of medical imaging. In this article we lay out the methods by which we have achieved consistently high quality, high throughput computation of intra-cranial segmentation from whole head magnetic resonance images, an essential but typically time-consuming bottleneck for brain image analysis. We refer to this output as “production-level” because it is suitable for routine use in processing pipelines. Training and testing with an extremely large archive of structural images, our segmentation algorithm performs uniformly well over a wide variety of separate national imaging cohorts, giving Dice metric scores exceeding those of other recent deep learning brain extractions. We describe the components involved to achieve this performance, including size, variety and quality of ground truth, and appropriate neural net architecture. We demonstrate the crucial role of appropriately large and varied datasets, suggesting a less prominent role for algorithm development beyond a threshold of capability.

PET imaging of neural activity, β-amyloid, and tau in normal brain aging

Normal brain aging is commonly associated with neural activity alteration, β-amyloid (Aβ) deposition, and tau aggregation, driving a progressive cognitive decline in normal elderly individuals. Positron emission tomography (PET) with radiotracers targeting these age-related changes has been increasingly employed to clarify the sequence of their occurrence and the evolution of clinically cognitive deficits. Herein, we reviewed recent literature on PET-based imaging of normal human brain aging in terms of neural activity, Aβ, and tau. Neural hypoactivity reflected by decreased glucose utilization with PET imaging has been predominately reported in the frontal, cingulate, and temporal lobes of the normal aging brain. Aβ PET imaging uncovers the pathophysiological association of Aβ deposition with cognitive aging, as well as the potential mechanisms. Tau-associated cognitive changes in normal aging are likely independent of but facilitated by Aβ as indicated by tau and Aβ PET imaging. Future longitudinal studies using multi-radiotracer PET imaging combined with other neuroimaging modalities, such as magnetic resonance imaging (MRI) morphometry, functional MRI, and magnetoencephalography, are essential to elucidate the neuropathological underpinnings and interactions in normal brain aging.

Reduced Dynamic Complexity of BOLD Signals Differentiates Mild Cognitive Impairment From Normal Aging

Mild cognitive impairment (MCI) is characterized as a transitional phase between cognitive decline associated with normal aging and Alzheimer’s disease (AD). Resting-state functional magnetic resonance imaging (fMRI) measuring blood oxygenation level-dependent (BOLD) signals provides complementary information considered essential for understanding disease progression. Previous studies suggested that multi-scale entropy (MSE) analysis quantifying the complexity of BOLD signals is a novel and promising method for investigating neurodegeneration associated with cognitive decline in different stages of MCI. Therefore, the current study used MSE to explore the changes in the complexity of resting-state brain BOLD signals in patients with early MCI (EMCI) and late MCI (LMCI). We recruited 345 participants’ data from the Alzheimer’s Disease Neuroimaging Initiative database, including 176 normal control (NC) subjects, 87 patients with EMCI and 82 patients with LMCI. We observed a significant reduction of brain signal complexity toward regularity in the left fusiform gyrus region in the EMCI group and in the rostral anterior cingulate cortex in the LMCI group. Our results extend prior work by revealing that significant reductions of brain BOLD signal complexity can be detected in different stages of MCI independent of age, sex and regional atrophy. Notably, the reduction of BOLD signal complexity in the rostral anterior cingulate cortex was significantly associated with greater risk of progression to AD. The present study thus identified MSE as a potential imaging biomarker for the early diagnosis of pre-clinical Alzheimer’s disease and provides further insights into the neuropathology of cognitive decline in prodromal AD.

Relationships Between Executive Control Circuit Activity, Amyloid Burden, and Education in Cognitively Healthy Older Adults

INTRODUCTION

In cognitively healthy older adults, amyloid-beta (Aβ) burden is associated with greater activity on task-based functional magnetic resonance imaging. Higher levels of functional activation are associated with other factors along with amyloid and the authors investigated these relationships as well as how they relate to Aβ in cognitively healthy older adults.

METHODS

The authors recruited cognitive healthy older adults (N = 50) from the Pittsburgh community that underwent extensive cognitive batteries, activation during a working memory (digit symbol substitution task, DSST), positron emission tomography scan for Pittsburgh Compound B (PiB, measuring amyloid), and other demographic measures. The authors tested the association between DSST activation and global PiB, neurocognitive batteries, and education.

RESULTS

The authors found that the DSST robustly activated expected structures involved in working memory. The authors found that greater global Aβ deposition was associated with greater DSST activation in the right calcarine, precuneus, middle temporal as well as the left insula and inferior frontal gyrus. The authors also found that greater education was associated with lower DSST activation - however this was not significant after adjusting for Aβ.

DISCUSSION

Greater amyloid was associated with greater activation, which may represent compensatory activation. Greater education was associated with lower activation, which may represent more efficient activation (i.e., less activation for the same task). After adjusting for amyloid, education was not significantly associated with activation suggesting that during the preclinical stage amyloid is the primary determinant of activation. Further, activation was not associated with cognitive function. Compensatory activation in the preclinical stage may help maintain cognitive function.

Abnormal Structural Brain Connectome in Individuals with Preclinical Alzheimer's Disease

Alzheimer's disease has a long preclinical phase during which amyloid pathology and neurodegeneration accumulate in the brain without producing overt cognitive deficits. It is currently unclear whether these early disease stages are associated with a progressive disruption in the communication between brain regions that subsequently leads to cognitive decline and dementia. In this study we assessed the organization of structural networks in cognitively normal (CN) individuals harboring amyloid pathology (A+N-), neurodegeneration (A-N+), or both (A+N+) from the prospective and longitudinal Swedish BioFINDER study. We combined graph theory with diffusion tensor imaging to investigate integration, segregation, and centrality measures in the brain connectome in the previous groups. At baseline, our findings revealed a disrupted network topology characterized by longer paths, lower efficiency, increased clustering and modularity in CN A-N+ and CN A+N+, but not in CN A+N-. After 2 years, CN A+N+ showed significant abnormalities in all global network measures, whereas CN A-N+ only showed abnormalities in the global efficiency. Network connectivity and organization were associated with memory in CN A+N+ individuals. Altogether, our findings suggest that amyloid pathology is not sufficient to disrupt structural network topology, whereas neurodegeneration is.

Biomarker-Based Signature of Alzheimer's Disease in Pre-MCI Individuals

Alzheimer’s disease (AD) pathology begins decades before the onset of clinical symptoms. It is recognized as a clinicobiological entity, being detectable in vivo independently of the clinical stage by means of pathophysiological biomarkers. Accordingly, neuropathological studies that were carried out on healthy elderly subjects, with or without subjective experience of cognitive decline, reported evidence of AD pathology in a high proportion of cases. At present, mild cognitive impairment (MCI) represents the only clinically diagnosed pre-dementia stage. Several attempts have been carried out to detect AD as early as possible, when subtle cognitive alterations, still not fulfilling MCI criteria, appear. Importantly, pre-MCI individuals showing the positivity of pathophysiological AD biomarkers show a risk of progression similar to MCI patients. In view of successful treatment with disease modifying agents, in a clinical setting, a timely diagnosis is mandatory. In clinical routine, biomarkers assessment should be taken into consideration whenever a subject with subtle cognitive deficits (pre-MCI), who is aware of his/her decline, requests to know the cause of such disturbances. In this review, we report the available neuropsychological and biomarkers data that characterize the pre-MCI patients, thus proposing pre-MCI as the first clinical manifestation of AD.

AD molecular: PET amyloid imaging across the Alzheimer's disease spectrum: From disease mechanisms to prevention

The advent of amyloid-beta (Aβ) positron emission tomography (PET) imaging has transformed the field of Alzheimer's disease (AD) by enabling the quantification of cortical Aβ accumulation and propagation in vivo. This revolutionary tool has made it possible to measure direct associations between Aβ and other AD biomarkers, to identify factors that influence Aβ accumulation and to redefine entry criteria into clinical trials as well as measure drug target engagement. This chapter summarizes the main findings on the associations of Aβ with other biomarkers of disease progression across the AD spectrum. It discusses investigations of the timing at which Aβ pathology starts to accumulate, demonstrates the clinical utility of Aβ PET imaging and discusses some ethical implications. Finally, it presents genetic and potentially modifiable lifestyle factors that might influence Aβ accumulation and therefore be targets for AD prevention.

NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease

In 2011, the National Institute on Aging and Alzheimer’s Association created separate diagnostic recommendations for the preclinical, mild cognitive impairment, and dementia stages of Alzheimer’s disease. Scientific progress in the interim led to an initiative by the National Institute on Aging and Alzheimer’s Association to update and unify the 2011 guidelines. This unifying update is labeled a “research framework” because its intended use is for observational and interventional research, not routine clinical care. In the National Institute on Aging and Alzheimer’s Association Research Framework, Alzheimer’s disease (AD) is defined by its underlying pathologic processes that can be documented by postmortem examination or in vivo by biomarkers. The diagnosis is not based on the clinical consequences of the disease (i.e., symptoms/signs) in this research framework, which shifts the definition of AD in living people from a syndromal to a biological construct. The research framework focuses on the diagnosis of AD with biomarkers in living persons. Biomarkers are grouped into those of β amyloid deposition, pathologic tau, and neurodegeneration [AT(N)]. This ATN classification system groups different biomarkers (imaging and biofluids) by the pathologic process each measures. The AT(N) system is flexible in that new biomarkers can be added to the three existing AT(N) groups, and new biomarker groups beyond AT(N) can be added when they become available. We focus on AD as a continuum, and cognitive staging may be accomplished using continuous measures. However, we also outline two different categorical cognitive schemes for staging the severity of cognitive impairment: a scheme using three traditional syndromal categories and a six-stage numeric scheme. It is important to stress that this framework seeks to create a common language with which investigators can generate and test hypotheses about the interactions among different pathologic processes (denoted by biomarkers) and cognitive symptoms. We appreciate the concern that this biomarker-based research framework has the potential to be misused. Therefore, we emphasize, first, it is premature and inappropriate to use this research framework in general medical practice. Second, this research framework should not be used to restrict alternative approaches to hypothesis testing that do not use biomarkers. There will be situations where biomarkers are not available or requiring them would be counterproductive to the specific research goals (discussed in more detail later in the document). Thus, biomarker-based research should not be considered a template for all research into age-related cognitive impairment and dementia; rather, it should be applied when it is fit for the purpose of the specific research goals of a study. Importantly, this framework should be examined in diverse populations. Although it is possible that β-amyloid plaques and neurofibrillary tau deposits are not causal in AD pathogenesis, it is these abnormal protein deposits that define AD as a unique neurodegenerative disease among different disorders that can lead to dementia. We envision that defining AD as a biological construct will enable a more accurate characterization and understanding of the sequence of events that lead to cognitive impairment that is associated with AD, as well as the multifactorial etiology of dementia. This approach also will enable a more precise approach to interventional trials where specific pathways can be targeted in the disease process and in the appropriate people.

Increased cerebral blood flow with increased amyloid burden in the preclinical phase of alzheimer's disease

BACKGROUND

Arterial spin labeling (ASL) is an emerging MRI technique for noninvasive measurement of cerebral blood flow (CBF) that has been used to show hemodynamic changes in the brains of people with Alzheimer's disease (AD). CBF changes have been measured using positron emission tomography (PET) across the AD spectrum, but ASL showed limited success in measuring CBF variations in the preclinical phase of AD, where amyloid β (Aβ) plaques accumulate in the decades prior to symptom onset.

PURPOSE

To investigate the relationship between CBF measured by multiphase-pseudocontinuous-ASL (MP-PCASL) and Aβ burden as measured by ¹¹ C-PiB PET imaging in a study of cognitively normal (CN) subjects age over 65.

STUDY TYPE

Cross-sectional.

POPULATION

Forty-six CN subjects including 33 with low levels of Aβ burden and 13 with high levels of Aβ.

FIELD STRENGTH/SEQUENCE

3T/3D MP-PCASL.

ASSESSMENT

The MP-PCASL method was chosen because it has a high signal-to-noise ratio. Furthermore, the data were analyzed using an efficient processing pipeline consisting of motion correction, ASL motion correction imprecision removal, temporal and spatial filtering, and partial volume effect correction.

STATISTICAL TESTS

General Linear Model.

RESULTS

In CN subjects positive for Aβ burden (n = 13), we observed a positive correlation between CBF and Aβ burden in the hippocampus, amygdala, caudate (P < 0.01), frontal, temporal, and insula (P < 0.05).

DATA CONCLUSION

To the best of our knowledge, this is the first study using MP-PCASL in the study of AD, and the results suggest a potential compensatory hemodynamic mechanism that protects against pathology in the early stages of AD.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:505-513.

Low Cerebrospinal Fluid Aβ42 and Aβ40 are Related to White Matter Lesions in Cognitively Normal Elderly

Background:

Low cerebrospinal fluid (CSF) levels of Aβ₄₂ may be the earliest manifestation of Alzheimer’s disease (AD). Knowledge on how CSF Aβ interacts with different brain pathologies early in the disease process is limited. We examined how CSF Aβ markers relate to brain atrophy and white matter lesions (WMLs) in octogenarians with and without dementia to explore the earliest pathogenetic pathways of AD in the oldest old.

Objective:

To study CSF amyloid biomarkers in relation to brain atrophy and WMLs in 85-year-olds with and without dementia.

Methods:

53 octogenarians took part in neuropsychiatric examinations and underwent both a lumbar puncture and a brain CT scan. CSF levels of Aβ₄₂ and Aβ₄₀ were examined in relation to cerebral atrophy and WMLs. Dementia was diagnosed.

Results:

In 85-year-olds without dementia, lower levels of both CSF Aβ₄₂ and CSF Aβ₄₀ were associated with WMLs. CSF Aβ₄₂ also correlated with measures of central atrophy, but not with cortical atrophy. In participants with dementia, lower CSF levels of Aβ₄₂ were related to frontal, temporal, and parietal cortical atrophy but not to WMLs.

Conclusions:

Our findings may suggest that there is an interrelationship between Aβ and subcortical WMLs in older persons without dementia. After onset of dementia, low CSF Aβ₄₂, probably representing amyloid deposition in plaques, is associated with cortical atrophy. WMLs may be an earlier manifestation of Aβ deposition than cortical degeneration.

Entorhinal cortex tau, amyloid-β, cortical thickness and memory performance in non-demented subjects

As more biomarkers for Alzheimer's disease and age-related brain conditions become available, more sophisticated analytic approaches are needed to take full advantage of the information they convey. Most work has been done using categorical approaches but the joint relationships of tau PET, amyloid PET and cortical thickness in their continuous distributions to cognition have been under-explored. We evaluated non-demented subjects over age 50 years in the Mayo Clinic Study of Aging, 2037 of whom had undergone 3 T MRI scan, 985 amyloid PET scan with 11C-Pittsburgh compound B (PIB) and MRI, and 577 PIB-PET, 18F-AV1451 flortaucipir PET and MRI. Participants received a nine-test cognitive battery. Three test scores (logical memory delayed recall, visual reproduction delayed recall and auditory verbal learning test delayed recall) were used to generate a memory composite z-score. We used Gradient Boosting Machine models to analyse the relationship between regional cortical thickness, flortaucipir PET signal, PIB-PET signal and memory z-scores. Age, education, sex and number of test exposures were included in the model as covariates. In this population-based study of non-demented subjects, most of the associations between biomarkers and memory z-scores accrued after 70 years of age. Entorhinal cortex exhibited the strongest associations between biomarkers and memory z-scores. Other temporal regions showed similar but attenuated associations, and non-temporal regions had negligible associations between memory z-scores and biomarkers. Entorhinal flortaucipir PET signal, PIB-PET signal and entorhinal cortical thickness were independently and additively associated with declining memory z-scores. In contrast to global PIB-PET signal where only very high amyloid-β levels were associated low memory z-scores, entorhinal flortaucipir PET signal just above background levels was associated with low memory z-scores. The lowest memory z-scores occurred with the confluence of elevated entorhinal flortaucipir PET signal and lower entorhinal cortical thickness.

Amyloid β deposition and glucose metabolism on the long-term progression of preclinical Alzheimer's disease

Aim:

Longitudinal changes in beta amyloid (Aβ) deposition and glucose metabolism over a long-term progression of preclinical Alzheimer's disease (AD) were evaluated.

Methods:

22 preclinical AD subjects with amyloid-positive scans underwent [¹¹C]-labeled Pittsburgh Compound-B (PIB) positron emission tomography (PET) and [¹⁸F]-fluorodeoxyglucose (FDG) PET imaging over 6.0 ± 1.8 years. A quantitative analysis of [¹¹C]-PIB and [¹⁸F]-FDG was used with a standardized uptake value ratio (SUVR) in the same regions.

Results:

In preclinical AD subjects, the cortical PIB SUVR was higher at baseline and increased at follow-up. 12 of the preclinical AD subjects progressed to mild cognitive impairment, six of whom had reduced glucose metabolism. The annual change in PIB SUVR was not related to that in FDG SUVR.

Conclusion:

Increases in Aβ deposition lead to the progression to mild cognitive impairment, but decreases in glucose metabolism do not contribute to progression.

Longitudinal changes in Aβ deposition and glucose metabolism were clarified over a long-term progression of preclinical AD using [¹¹C]-PIB PET and [¹⁸F]-FDG PET imaging. 73% of the preclinical AD subjects progressed to mild cognitive impairment during 6 years of a long follow-up period. The increases in Aβ deposition lead to the progression to mild cognitive impairment but decreases in glucose metabolism do not contribute to progression.

Prevalence and risk of progression of preclinical Alzheimer's disease stages: a systematic review and meta-analysis

Background

Alzheimer’s disease (AD) pathology begins several years before the clinical onset. The long preclinical phase is composed of three stages according to the 2011National Institute on Aging and Alzheimer’s Association (NIA-AA) criteria, followed by mild cognitive impairment (MCI), a featured clinical entity defined as “due to AD”, or “prodromal AD”, when pathophysiological biomarkers (i.e., cerebrospinal fluid or positron emission tomography with amyloid tracer) are positive. In the clinical setting, there is a clear need to detect the earliest symptoms not yet fulfilling MCI criteria, in order to proceed to biomarker assessment for diagnostic definition, thus offering treatment with disease-modifying drugs to patients as early as possible. According to the available evidence, we thus estimated the prevalence and risk of progression at each preclinical AD stage, with special interest in Stage 3.

Methods

Cross-sectional and longitudinal studies published from April 2008 to May 2018 were obtained through MEDLINE-PubMed, screened, and systematically reviewed by four independent reviewers. Data from included studies were meta-analyzed using random-effects models. Heterogeneity was assessed by I² statistics.

Results

Estimated overall prevalence of preclinical AD was 22% (95% CI = 18–26%). Rate of biomarker positivity overlapped in cognitively normal individuals and people with subjective cognitive decline. The risk of progression increases across preclinical AD stages, with individuals classified as NIA-AA Stage 3 showing the highest risk (73%, 95% CI = 40–92%) compared to those in Stage 2 (38%, 95% CI = 21–59%) and Stage 1 (20%, 95% CI = 10–34%).

Conclusion

Available data consistently show that risk of progression increases across the preclinical AD stages, where Stage 3 shows a risk of progression comparable to MCI due to AD. Accordingly, an effort should be made to also operationalize the diagnostic work-up in subjects with subtle cognitive deficits not yet fulfilling MCI criteria. The possibility to define, in the clinical routine, a patient as “pre-MCI due to AD” could offer these subjects the opportunity to use disease-modifying drugs at best.

Electronic supplementary material

The online version of this article (10.1186/s13195-018-0459-7) contains supplementary material, which is available to authorized users.

Neuropsychology of aging

All people want to age "successfully," maintaining functional capacity and quality of life as they reach advanced age. Achieving this goal depends on preserving optimal cognitive and brain functioning. Yet, significant individual differences exist in this regard. Some older adults continue to retain most cognitive abilities throughout their lifetime. Others experience declines in cognitive and functional capacity that range from mild decrements in certain cognitive functions over time to severe dementia among those with neurodegenerative diseases. Even among relatively healthy "successful agers," certain cognitive functions are reduced from earlier levels. This is particularly true for cognitive functions that are dependent on cognitive processing speed and efficiency. Working memory and executive and attentional functions tend to be most vulnerable. Learning and memory functions are also usually reduced, although in the absence of neurodegenerative disease learning and retrieval efficiency rather than memory storage are affected. Other functions, such as visual perception, language, semantics, and knowledge, are often well preserved. Structural, functional, and physiologic/metabolic brain changes correspond with age-associated cognitive decline. Physiologic and metabolic mechanisms, such as oxidative stress and neuroinflammation, may contribute to these changes, along with the contribution of comorbidities that secondarily affect the brain of older adults. Cognitive frailty often corresponds with physical frailty, both affected by multiple exogenous and endogenous factors. Neuropsychologic assessment provides a way of measuring the cognitive and functional status of older adults, which is useful for monitoring changes that may be occurring. Neuroimaging is also useful for characterizing age-associated structural, functional, physiologic, and metabolic brain changes, including alterations in cerebral blood flow and metabolite concentrations. Some interventions that may enhance cognitive function, such as cognitive training, neuromodulation, and pharmacologic approaches, exist or are being developed. Yet, preventing, slowing, and reversing the adverse effects of cognitive aging remains a challenge.

"Exceptional brain aging" without Alzheimer's disease: triggers, accelerators, and the net sum game

Background

As human longevity increases and Alzheimer’s disease (AD) increasingly becomes a significant societal burden, finding pathways or protective factors that facilitate exceptional brain aging without AD pathophysiologies (ADP) will be critical. The goal of this viewpoint is two-fold: 1) to present evidence for “exceptional brain aging” without ADP; and 2) to bring together ideas and observations from the literature and present them as testable hypotheses for biomarker studies to discover protective factors for “exceptional brain aging” without ADP and AD dementia.

Discovering pathways to exceptional aging

There are three testable hypotheses. First, discovering and quantifying links between risk factor(s) and early ADP changes in midlife using longitudinal biomarker studies will be fundamental to understanding why the majority of individuals deviate from normal aging to the AD pathway. Second, a risk factor may have quantifiably greater impact as a trigger and/or accelerator on a specific component of the biomarker cascade (amyloid, tau, neurodegeneration). Finally, and most importantly, while each risk factor may have a different mechanism of action on AD biomarkers, “exceptional aging” and protection against AD dementia will come from “net sum” protection against all components of the biomarker cascade. The knowledge of the mechanism of action of risk factor(s) from hypotheses 1 and 2 will aid in better characterization of their effect on outcomes, identification of subpopulations that would benefit, and the timing at which the risk factor(s) would have the maximal impact. Additionally, hypothesis 3 highlights the importance of multifactorial or multi-domain approaches to “exceptional aging” as well as prevention of AD dementia.

Conclusion

While important strides have been made in identifying risk factors for AD dementia incidence, further efforts are needed to translate these into effective preventive strategies. Using biomarker studies for understanding the mechanism of action, effect size estimation, selection of appropriate end-points, and better subject recruitment based on subpopulation effects are fundamental for better design and success of prevention trials.

A Systematic Review of Longitudinal Studies Which Measure Alzheimer's Disease Biomarkers

Alzheimer’s disease (AD) is a progressive and fatal neurodegenerative disease, with no effective treatment or cure. A gold standard therapy would be treatment to slow or halt disease progression; however, knowledge of causation in the early stages of AD is very limited. In order to determine effective endpoints for possible therapies, a number of quantitative surrogate markers of disease progression have been suggested, including biochemical and imaging biomarkers. The dynamics of these various surrogate markers over time, particularly in relation to disease development, are, however, not well characterized. We reviewed the literature for studies that measured cerebrospinal fluid or plasma amyloid-β and tau, or took magnetic resonance image or fluorodeoxyglucose/Pittsburgh compound B-positron electron tomography scans, in longitudinal cohort studies. We summarized the properties of the major cohort studies in various countries, commonly used diagnosis methods and study designs. We have concluded that additional studies with repeat measures over time in a representative population cohort are needed to address the gap in knowledge of AD progression. Based on our analysis, we suggest directions in which research could move in order to advance our understanding of this complex disease, including repeat biomarker measurements, standardization and increased sample sizes.

Use of multimodality imaging and artificial intelligence for diagnosis and prognosis of early stages of Alzheimer's disease

Alzheimer's disease (AD) is a major neurodegenerative disease and the most common cause of dementia. Currently, no treatment exists to slow down or stop the progression of AD. There is converging belief that disease-modifying treatments should focus on early stages of the disease, that is, the mild cognitive impairment (MCI) and preclinical stages. Making a diagnosis of AD and offering a prognosis (likelihood of converting to AD) at these early stages are challenging tasks but possible with the help of multimodality imaging, such as magnetic resonance imaging (MRI), fluorodeoxyglucose (FDG)-positron emission topography (PET), amyloid-PET, and recently introduced tau-PET, which provides different but complementary information. This article is a focused review of existing research in the recent decade that used statistical machine learning and artificial intelligence methods to perform quantitative analysis of multimodality image data for diagnosis and prognosis of AD at the MCI or preclinical stages. We review the existing work in 3 subareas: diagnosis, prognosis, and methods for handling modality-wise missing data-a commonly encountered problem when using multimodality imaging for prediction or classification. Factors contributing to missing data include lack of imaging equipment, cost, difficulty of obtaining patient consent, and patient drop-off (in longitudinal studies). Finally, we summarize our major findings and provide some recommendations for potential future research directions.

Progressive medial temporal lobe atrophy during preclinical Alzheimer's disease

This study examined whether longitudinal MRI trajectories in medial temporal lobe (MTL) brain regions differed among groups of cognitively normal individuals defined by their cerebrospinal fluid (CSF) levels when they were first enrolled (N = 207; mean clinical follow-up = 13.3 years (max = 20 years), mean MRI follow-up = 2.4 years (max = 8 years)). We first compared atrophy rates among groups defined by CSF amyloid and phosphorylated-tau (p-tau) vs. CSF amyloid and total tau (t-tau). We also examined whether, in the presence of amyloid or tau/p-tau, the atrophy rates differed based on whether the subjects ultimately progressed to a diagnosis of mild cognitive impairment (MCI), as well as whether apolipoprotein ε4 (Apoε4) status had an impact on the longitudinal MRI trajectories. The primary finding was that when the groups were defined using CSF amyloid and p-tau, individuals with low levels of CSF amyloid and high levels of CSF p-tau (referred to as Stage 2) showed a significantly greater rate of atrophy in a composite measure of MTL volumes compared to groups defined by evidence of abnormal CSF levels in only one of the brain proteins (but not both), or no evidence of CSF abnormality. In contrast, there were no differences in rate of MTL atrophy when the groups were defined by levels of CSF amyloid and t-tau (instead of p-tau). Additionally, the rate of MTL atrophy did not differ between subjects who progressed to MCI at follow-up vs. those who remained cognitively normal when CSF levels of amyloid, t-tau, or p-tau were covaried. Lastly, the presence of an APOE ε4 genotype did not modulate the degree of MTL atrophy once baseline levels of CSF amyloid, p-tau or t-tau were accounted for. These results suggest that abnormal levels of CSF amyloid and CSF p-tau (but not t-tau) maximize the likelihood of observing significant MTL atrophy over time among individuals with normal cognition at baseline, and emphasize the importance of differentiating biomarkers that primarily reflect neurofibrillary tangle pathology (CSF p-tau) compared with biomarkers of neuronal injury (CSF t-tau).

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Examined association between CSF AD biomarkers and medial temporal lobe atrophy

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Abnormal levels of both amyloid and p-tau were associated with greatest atrophy.

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No difference in rate of atrophy based on levels of amyloid and total tau

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Follow-up diagnosis was unrelated to atrophy rate when covarying amyloid and p-tau.

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Levels of CSF amyloid and p-tau were associated with atrophy in preclinical AD.

Neuroimaging biomarkers and impaired olfaction in cognitively normal individuals

OBJECTIVE

There is a need for inexpensive noninvasive tests to identify older healthy persons at risk for Alzheimer disease (AD) for enrollment in AD prevention trials. Our objective was to examine whether abnormalities in neuroimaging measures of amyloid and neurodegeneration are correlated with odor identification (OI) in the population-based Mayo Clinic Study of Aging.

METHODS

Cognitively normal (CN) participants had olfactory function assessed using the Brief Smell Identification Test (B-SIT), underwent magnetic resonance imaging (n = 829) to assess a composite AD signature cortical thickness and hippocampal volume (HVa), and underwent ¹¹ C-Pittsburgh compound B (n = 306) and ¹⁸ fluorodeoxyglucose (n = 305) positron emission tomography scanning to assess amyloid accumulation and brain hypometabolism, respectively. The association of neuroimaging biomarkers with OI was examined using multinomial logistic regression and simple linear regression models adjusted for potential confounders.

RESULTS

Among 829 CN participants (mean age = 79.2 years; 51.5% men), 248 (29.9%) were normosmic and 78 (9.4%) had anosmia (B-SIT score < 6). Abnormal AD signature cortical thickness and reduced HVa were associated with decreased OI as a continuous measure (slope = -0.43, 95% confidence interval [CI] = -0.76 to -0.09, p = 0.01 and slope = -0.72, 95% CI = -1.15 to -0.28, p < 0.01, respectively). Reduced HVa, decreased AD signature cortical thickness, and increased amyloid accumulation were significantly associated with increased odds of anosmia.

INTERPRETATION

Our findings suggest that OI may be a noninvasive, inexpensive marker for risk stratification, for identifying participants at the preclinical stage of AD who may be at risk for cognitive impairment and eligible for inclusion in AD prevention clinical trials. These cross-sectional findings remain to be validated prospectively. Ann Neurol 2017;81:871-882.

Positive affect predicts cerebral glucose metabolism in late middle-aged adults

Positive affect is associated with a number of health benefits; however, few studies have examined the relationship between positive affect and cerebral glucose metabolism, a key energy source for neuronal function and a possible index of brain health. We sought to determine if positive affect was associated with cerebral glucose metabolism in late middle-aged adults (n = 133). Participants completed the positive affect subscale of the Center for Epidemiological Studies Depression Scale at two time points over a two-year period and underwent 18F-fluorodeoxyglucose-positron emission tomography scanning. After controlling for age, sex, perceived health status, depressive symptoms, anti-depressant use, family history of Alzheimer’s disease, APOE ε4 status and interval between visits, positive affect was associated with greater cerebral glucose metabolism across para-/limbic, frontal, temporal and parietal regions. Our findings provide evidence that positive affect in late midlife is associated with greater brain health in regions involved in affective processing and also known to be susceptible to early neuropathological processes. The current findings may have implications for interventions aimed at increasing positive affect to attenuate early neuropathological changes in at-risk individuals.

Longitudinal β-Amyloid Deposition and Hippocampal Volume in Preclinical Alzheimer Disease and Suspected Non-Alzheimer Disease Pathophysiology

Importance

Preclinical Alzheimer disease (AD) can be staged using a 2-factor model denoting the presence or absence of β-amyloid (Aβ+/-) and neurodegeneration (ND+/-). The association of these stages with longitudinal biomarker outcomes is unknown.

Objective

To examine whether longitudinal Aβ accumulation and hippocampal atrophy differ based on initial preclinical staging.

Design, Setting, and Participants

This longitudinal population-based cohort study used data collected at the Knight Alzheimer Disease Research Center, Washington University, St Louis, Missouri, from December 1, 2006, to June 31, 2015. Cognitively normal older adults (n = 174) were recruited from the longitudinal Adult Children Study and Healthy Aging and Senile Dementia Study at the Knight Alzheimer Disease Research Center. At baseline, all participants had magnetic resonance imaging (MRI) scans, positron emission tomography (PET) scans with carbon 11-labeled Pittsburgh Compound B (PiB), and cerebrospinal fluid assays of tau and phosphorylated tau (ptau) acquired within 12 months. Using the baseline biomarkers, individuals were classified into preclinical stage 0 (Aβ-/ND-), 1 (Aβ+/ND-), or 2+ (Aβ+/ND+) or suspected non-AD pathophysiology (SNAP; Aβ-/ND+).

Main Outcomes and Measures

Subsequent longitudinal accumulation of Aβ assessed with PiB PET and loss of hippocampal volume assessed with MRI in each group.

Results

Among the 174 participants (81 men [46.6%]; 93 women [53.4%]; mean [SD] age, 65.7 [8.9] years), a proportion (14%-17%) of individuals with neurodegeneration alone (SNAP) later demonstrated Aβ+. The rates of Aβ accumulation and loss of hippocampal volume in individuals with SNAP were indistinguishable from those without any pathologic features at baseline (for Aβ accumulation: when hippocampal volume was used to define ND, t = 0.00 [P > .99]; when tau and ptau were used to define ND, t = -0.02 [P = .98]; for loss of hippocampal volume: when hippocampal volume was used to define ND, t = -1.34 [P = .18]; when tau and ptau were used to define ND, t = 0.84 [P = .40]). Later preclinical stages (stages 1 and 2+) had elevated Aβ accumulation. Using hippocampal volume to define ND, individuals with stage 1 had accelerated Aβ accumulation relative to stage 0 (t = 11.06; P < .001), stage 2+ (t = 2.10; P = .04), and SNAP (t = 9.32; P < .001), and those with stage 2+ had accelerated Aβ accumulation relative to stage 0 (t = 4.38; P < .001) and SNAP (t = 4.08; P < .001). When ND was defined using tau and ptau, individuals with stage 2+ had accelerated Aβ accumulation relative to stage 0 (t = 4.96) and SNAP (t = 4.06), and those with stage 1 had accelerated Aβ accumulation relative to stage 0 (t = 8.44) and SNAP (t = 6.61) (P < .001 for all comparisons). When ND was defined using cerebrospinal fluid biomarkers, individuals with stage 2+ had accelerated hippocampal atrophy relative to stage 0 (t = -3.41; P < .001), stage 1 (t = -2.48; P = .03), and SNAP (t = -2.26; P = .03).

Conclusions and Relevance

More advanced preclinical stages of AD have greater longitudinal Aβ accumulation. SNAP appears most likely to capture inherent individual variability in brain structure or to represent comorbid pathologic features rather than early emerging AD. Low hippocampal volumes or elevated levels of tau or ptau in isolation may not accurately represent ongoing neurodegenerative processes.

Amyloid-β and hyperphosphorylated tau synergy drives metabolic decline in preclinical Alzheimer's disease

This study was designed to test the interaction between amyloid-β and tau proteins as a determinant of metabolic decline in preclinical Alzheimer's disease (AD). We assessed 120 cognitively normal individuals with [¹⁸F]florbetapir positron emission tomography (PET) and cerebrospinal fluid (CSF) measurements at baseline, as well as [¹⁸F]fluorodeoxyglucose ([¹⁸F]FDG) PET at baseline and at 24 months. A voxel-based interaction model was built to test the associations between continuous measurements of CSF biomarkers, [¹⁸F]florbetapir and [¹⁸F]FDG standardized uptake value ratios (SUVR). We found that the synergistic interaction between [¹⁸F]florbetapir SUVR and CSF phosphorylated tau (p-tau) measurements, rather than the sum of their independent effects, was associated with a 24-month metabolic decline in basal and mesial temporal, orbitofrontal, and anterior and posterior cingulate cortices (P<0.001). In contrast, interactions using CSF amyloid-β_1-42 and total tau biomarkers did not associate with metabolic decline over a time frame of 24 months. The interaction found in this study further support the framework that amyloid-β and hyperphosphorylated tau aggregates synergistically interact to cause downstream AD neurodegeneration. In fact, the regions displaying the metabolic decline reported here were confined to brain networks affected early by amyloid-β plaques and neurofibrillary tangles. Preventive clinical trials may benefit from using a combination of amyloid-β PET and p-tau biomarkers to enrich study populations of cognitively normal subjects with a high probability of disease progression in studies, using [¹⁸F]FDG as a biomarker of efficacy.

Evolution of neurodegeneration-imaging biomarkers from clinically normal to dementia in the Alzheimer disease spectrum

The availability of antemortem biomarkers for Alzheimer's disease (AD) enables monitoring the evolution of neurodegenerative processes in real time. Pittsburgh compound B (PIB) positron emission tomography (PET) was used to select participants in the Mayo Clinic Study of Aging and the Mayo Alzheimer's Disease Research Center with elevated β-amyloid, designated as "A+," and hippocampal volume and (18)fluorodeoxyglucose (FDG) positron emission tomography were used to characterize participants as having evidence of neurodegeneration ("N+") at the baseline evaluation. There were 145 clinically normal (CN) A+ individuals, 62 persons with mild cognitive impairment (MCI) who were A+ and 20 with A+ AD dementia. Over a period of 1-6 years, MCI A+N+ individuals showed declines in medial temporal, lateral temporal, lateral parietal, and to a lesser extent, medial parietal regions for both FDG standardized uptake value ratio and gray matter volume that exceeded declines seen in the CN A+N+ group. The AD dementia group showed declines in the same regions on FDG standardized uptake value ratio and gray matter volume with rates that exceeded that in MCI A+N+. Expansion of regional involvement and faster rate of neurodegeneration characterizes progression in the AD pathway.

Amyloid-β deposition and regional grey matter atrophy rates in dementia with Lewy bodies

Alzheimer's disease pathology frequently coexists with Lewy body disease at autopsy in patients with probable dementia with Lewy bodies. More than half of patients with probable dementia with Lewy bodies have high amyloid-β deposition as measured with 11C-Pittsburgh compound B binding on positron emission tomography. Biomarkers of amyloid-β deposition precede neurodegeneration on magnetic resonance imaging during the progression of Alzheimer's disease, but little is known about how amyloid-β deposition relates to longitudinal progression of atrophy in patients with probable dementia with Lewy bodies. We investigated the associations between baseline 11C-Pittsburgh compound B binding on positron emission tomography and the longitudinal rates of grey matter atrophy in a cohort of clinically diagnosed patients with dementia with Lewy bodies (n = 20), who were consecutively recruited to the Mayo Clinic Alzheimer's Disease Research Centre. All patients underwent 11C-Pittsburgh compound B positron emission tomography and magnetic resonance imaging examinations at baseline. Follow-up magnetic resonance imaging was performed after a mean (standard deviation) interval of 2.5 (1.1) years. Regional grey matter loss was determined on three-dimensional T1-weighted magnetic resonance imaging with the tensor-based morphometry-symmetric normalization technique. Linear regression was performed between baseline 11C-Pittsburgh compound B standard unit value ratio and longitudinal change in regional grey matter volumes from an in-house modified atlas. We identified significant associations between greater baseline 11C-Pittsburgh compound B standard unit value ratio and greater grey matter loss over time in the posterior cingulate gyrus, lateral and medial temporal lobe, and occipital lobe as well as caudate and putamen nuclei, after adjusting for age (P < 0.05). Greater baseline 11C-Pittsburgh compound B standard unit value ratio was also associated with greater ventricular expansion rates (P < 0.01) and greater worsening over time in Clinical Dementia Rating Scale, sum of boxes (P = 0.02). In conclusion, in patients with probable dementia with Lewy bodies, higher amyloid-β deposition at baseline is predictive of faster neurodegeneration in the cortex and also in the striatum. This distribution is suggestive of possible interactions among amyloid-β, tau and α-synuclein aggregates, which needs further investigation. Furthermore, higher amyloid-β deposition at baseline predicts a faster clinical decline over time in patients with probable dementia with Lewy bodies.

Accelerated decline in white matter integrity in clinically normal individuals at risk for Alzheimer's disease

Prior studies have identified white matter abnormalities in Alzheimer's disease (AD). Yet, cross-sectional studies in normal older individuals show little evidence for an association between markers of AD risk (APOE4 genotype and amyloid deposition), and white matter integrity. Here, 108 normal older adults (age, 66-87) with assessments of apolipoprotein e4 (APOE4) genotype and assessment of amyloid burden by positron emission tomography underwent diffusion tensor imaging scans for measuring white matter integrity at 2 time points, on average 2.6 years apart. Linear mixed-effects models showed that amyloid burden at baseline was associated with steeper decline in fractional anisotropy in the parahippocampal cingulum (p < 0.05). This association was not significant between baseline measures suggesting that longitudinal analyses can provide novel insights that are not detectable in cross-sectional designs. Amyloid-related changes in hippocampus volume did not explain the association between amyloid burden and change in fractional anisotropy. The results suggest that accumulation of cortical amyloid and white matter changes in parahippocampal cingulum are not independent processes in individuals at increased risk for AD.

Role of β-Amyloidosis and Neurodegeneration in Subsequent Imaging Changes in Mild Cognitive Impairment

IMPORTANCE

To understand how a model of Alzheimer disease pathophysiology based on β-amyloidosis and neurodegeneration predicts the regional anatomic expansion of hypometabolism and atrophy in persons with mild cognitive impairment (MCI).

OBJECTIVE

To define the role of β-amyloidosis and neurodegeneration in the subsequent progression of topographic cortical structural and metabolic changes in MCI.

DESIGN, SETTING, AND PARTICIPANTS

Longitudinal, observational study with serial brain imaging conducted from March 28, 2006, to January 6, 2015, using a population-based cohort. A total of 96 participants with MCI (all aged >70 years) with serial imaging biomarkers from the Mayo Clinic Study of Aging or Mayo Alzheimer's Disease Research Center were included. Participants were characterized initially as having elevated or not elevated brain β-amyloidosis (A+ or A-) based on 11C-Pittsburgh compound B positron emission tomography. They were further characterized initially by the presence or absence of neurodegeneration (N+ or N-), where the presence of neurodegeneration was defined by abnormally low hippocampal volume or hypometabolism in an Alzheimer disease-like pattern on 18fluorodeoxyglucose (FDG)-positron emission tomography.

MAIN OUTCOMES AND MEASURES

Regional FDG standardized uptake value ratio (SUVR) and gray matter volumes in medial temporal, lateral temporal, lateral parietal, and medial parietal regions.

RESULTS

In the primary regions of interest (ROI), the A+N+ group (n = 45) had lower FDG SUVR at baseline compared with the A+N- group (n = 17) (all 4 ROIs; P < .001). The A+N+ group also had lower FDG SUVR at baseline (all 4 ROIs; P < .01) compared with the A-N- group (n = 12). The A+N+ group had lower medial temporal gray matter volume at baseline (P < .001) compared with either the A+N- group or A-N- group. The A+N+ group showed large longitudinal declines in FDG SUVR (P < .05 for medial temporal, lateral temporal, and medial parietal regions) and gray matter volumes (P < .05 for medial temporal and lateral temporal regions) compared with the A-N+ group (n = 22). The A+N+ group also showed large longitudinal declines compared with the A-N- group on FDG SUVR (P < .05 for medial temporal and lateral parietal regions) and gray matter volumes (all 4 ROIs; P < .05) compared with the A+N- group. The A-N+ group did not show declines in FDG SUVR or gray matter volume compared with the A+N- or A-N- groups.

CONCLUSIONS AND RELEVANCE

Persons with MCI who were A+N+ demonstrated volumetric and metabolic worsening in temporal and parietal association areas, consistent with the expectation that the MCI stage in the Alzheimer pathway heralds incipient isocortical involvement. The A-N+ group, those with suspected non-Alzheimer pathophysiology, lacked a distinctive longitudinal volumetric or metabolic profile.

Suspected non-Alzheimer disease pathophysiology--concept and controversy

Suspected non-Alzheimer disease pathophysiology (SNAP) is a biomarker-based concept that applies to individuals with normal levels of amyloid-β biomarkers in the brain, but in whom biomarkers of neurodegeneration are abnormal. The term SNAP has been applied to clinically normal individuals (who do not meet criteria for either mild cognitive impairment or dementia) and to individuals with mild cognitive impairment, but is applicable to any amyloid-negative, neurodegeneration-positive individual regardless of clinical status, except when the pathology underlying neurodegeneration can be reliably inferred from the clinical presentation. SNAP is present in ∼23% of clinically normal individuals aged >65 years and in ∼25% of mildly cognitively impaired individuals. APOE*ε4 is underrepresented in individuals with SNAP compared with amyloid-positive individuals. Clinically normal and mildly impaired individuals with SNAP have worse clinical and/or cognitive outcomes than individuals with normal levels of neurodegeneration and amyloid-β biomarkers. In this Perspectives article, we describe the available data on SNAP and address topical controversies in the field.

Genetic and degenerative disorders primarily causing dementia

Neuroimaging comprises a powerful set of instruments to diagnose the different causes of dementia, clarify their neurobiology, and monitor their treatment. Magnetic resonance imaging (MRI) depicts volume changes with neurodegeneration and inflammation, as well as abnormalities in functional and structural connectivity. MRI arterial spin labeling allows for the quantification of regional cerebral blood flow, characteristically altered in Alzheimer's disease, diffuse Lewy-body disease, and the frontotemporal dementias. Positron emission tomography allows for the determination of regional metabolism, with similar abnormalities as flow, and for the measurement of β-amyloid and abnormal tau deposition in the brain, as well as regional inflammation. These instruments allow for the quantification in vivo of most of the pathologic features observed in disorders causing dementia. Importantly, they allow for the longitudinal study of these abnormalities, having revealed, for instance, that the deposition of β-amyloid in the brain can antecede by decades the onset of dementia. Thus, a therapeutic window has been opened and the efficacy of immunotherapies directed at removing β-amyloid from the brain of asymptomatic individuals is currently being tested. Tau and inflammation imaging, still in their infancy, combined with genomics, should provide powerful insights into these disorders and facilitate their treatment.

Is amyloid-β harmful to the brain? Insights from human imaging studies

Although the amyloid-β protein associated with the Alzheimer's disease plaque has been detectable in living people for over a decade, its importance in the pathogenesis of Alzheimer's disease is still debated. The frequent presence of amyloid-β in the brains of cognitively healthy older people has been interpreted as evidence against a causative role. If amyloid-β is crucial to the development of Alzheimer's disease, it should be associated with other Alzheimer's disease-like neurological changes. This review examines whether amyloid-β is associated with other biomarkers indicative of early Alzheimer's disease in normal older people. The preponderance of evidence links amyloid-β to functional change, progressive brain atrophy, and cognitive decline. Individuals at greatest risk of decline seem to be those with evidence of both amyloid-β and findings suggestive of neurodegeneration. The crucial question is thus how amyloid-β is related to brain degeneration and how these two processes interact to cause cognitive decline and dementia.

Transition rates between amyloid and neurodegeneration biomarker states and to dementia: a population-based, longitudinal cohort study

Background

We previously observed in a cross-sectional analysis that frequencies of amyloid and neurodegeneration biomarker states varied greatly by age among cognitively non-impaired participants, suggesting dynamic within-person processes. Our objective in this longitudinal study was to estimate rates of transitioning from a less- to a more-abnormal biomarker state by age among non-demented individuals, as well as rates of transitioning to dementia by biomarker state.

Methods

All participants (n=4049) were non-demented at baseline. A subset of 1541 underwent multi-modality imaging. Amyloid PET was used to classify individuals as amyloid positive (A+) or negative (A−). FDG PET and MRI were used to classify individuals as neurodegeneration positive (N+) or negative (N−). All observations from the 4049 individuals were used in a multi-state model to estimate four different age-specific biomarker state transition rates among non-demented individuals: A−N− to A+N−; A−N− to A−N+ (suspected non-Alzheimer pathology, SNAP); A+N− to A+N+; A−N+ (SNAP) to A+N+. We also estimated two age-specific rates to dementia: A+N+ to dementia; and A−N+ (SNAP) to dementia. Using these state-to-state transition rates, we estimated biomarker state frequencies by age.

Findings

All transition rates were low at age 50 and (with one exception) were well-characterized by an exponential increase with age. The rates per 100-person years at ages 65 versus 85 were 1.6 versus 17.2 for A−N− to A−N+, 6.1 versus 20.8 for A+N− to A+N+, 2.6 versus 13.2 for A−N+ to A+N+, 0.8 versus 7.0 for A+N+ to dementia, and 0.6 versus 1.7 for A−N+ to dementia. The one exception to an exponential increase with age was the transition rate from A−N− to A+N− which increased from 4.0 transitions per 100 person-years at age 65 to approximately 7 transitions per 100 person-years in the 70s and then plateaued beyond that age. Estimated biomarker frequencies by age from the multistate model were similar to cross-sectional biomarker frequencies.

Interpretation

Dynamic state-to-state transition rates illustrate important measurable aspects of the changing biology underlying brain aging. The biomarker states we describe relate to both AD and non-AD processes. Our transition rates suggest that brain aging can be conceptualized as a nearly inevitable acceleration toward worse biomarker and clinical states. The one exception was that transition to amyloidosis without neurodegeneration was most dynamic from age 60 to 70 and then plateaued beyond that age. We found that simple transition rates can explain complex, highly interdependent biomarker state frequencies in our sample.

Mapping 3-year changes in gray matter and metabolism in Aβ-positive nondemented subjects

Gray matter (GM) atrophy and brain glucose hypometabolism are already detected in the predementia stages of Alzheimer's disease (AD), but the regional and longitudinal associations between the two are not well understood. Here, we analyzed the patterns of longitudinal atrophy (magnetic resonance imaging [MRI]) and (18)F-Fluorodeoxyglucose-positron emission tomography ([18F]FDG-PET) metabolism decline in 40 cognitively healthy control (HC) and 52 mildly impaired (mild cognitive impairment [MCI]) subjects during 3 years. Based on cerebrospinal fluid and brain amyloid-PET, the subjects were divided into amyloid-beta (Aβ)- and Aβ+ subgroups. In voxel-based and region of interest analyses, we compared the 3-year rates of change in GM and glucose metabolism between Aβ-subgroups, within each diagnostic group. In joint-independent component analyses, we assessed the patterns of covariation between longitudinal change in GM volume and glucose metabolism. MCI-Aβ+ showed faster atrophy than MCI-Aβ- within the temporal, medial temporal, and medial parietal lobes. HC-Aβ+ showed faster atrophy within the precuneus than HC-Aβ-. For FDG-PET metabolism, MCI-Aβ+ exhibited faster decline than MCI-Aβ- in temporoparietal regions, whereas no differences between HC subgroups were observed. Joint-independent component analysis showed that accelerated atrophy and metabolism decline correlated across distant brain regions for MCI-Aβ+. In conclusion, abnormally increased levels of Aβ in nondemented subjects were associated with accelerated decline in both GM and glucose metabolism, where both types of neurodegeneration progress in spatially divergent patterns.

BACE1 activity impairs neuronal glucose oxidation: rescue by beta-hydroxybutyrate and lipoic acid

Glucose hypometabolism and impaired mitochondrial function in neurons have been suggested to play early and perhaps causative roles in Alzheimer's disease (AD) pathogenesis. Activity of the aspartic acid protease, beta-site amyloid precursor protein (APP) cleaving enzyme 1 (BACE1), responsible for beta amyloid peptide generation, has recently been demonstrated to modify glucose metabolism. We therefore examined, using a human neuroblastoma (SH-SY5Y) cell line, whether increased BACE1 activity is responsible for a reduction in cellular glucose metabolism. Overexpression of active BACE1, but not a protease-dead mutant BACE1, protein in SH-SY5Y cells reduced glucose oxidation and the basal oxygen consumption rate, which was associated with a compensatory increase in glycolysis. Increased BACE1 activity had no effect on the mitochondrial electron transfer process but was found to diminish substrate delivery to the mitochondria by inhibition of key mitochondrial decarboxylation reaction enzymes. This BACE1 activity-dependent deficit in glucose oxidation was alleviated by the presence of beta hydroxybutyrate or α-lipoic acid. Consequently our data indicate that raised cellular BACE1 activity drives reduced glucose oxidation in a human neuronal cell line through impairments in the activity of specific tricarboxylic acid cycle enzymes. Because this bioenergetic deficit is recoverable by neutraceutical compounds we suggest that such agents, perhaps in conjunction with BACE1 inhibitors, may be an effective therapeutic strategy in the early-stage management or treatment of AD.

Mapping the Relationship of Contributing Factors for Preclinical Alzheimer's Disease

While detecting and validating correlations among the contributing factors to the preclinical phase of Alzheimer’s disease (pAD) has been a focus, a potent meta-analysis method to integrate current findings is essential. The entity-relationship diagram with nodes as entities and edges as relationships is a graphical representation that summarizes the relationships among multiple factors in an intuitive manner. Based on this concept, a new meta-analysis approach with this type of diagram is proposed to summarize research about contributing factors of pAD and their interactions. To utilize the information for enriched visualization, width and color of the edges are encoded with reporting times, number of pAD subjects, correlation coefficient, and study design (cross-sectional or longitudinal). The proposed Probabilistic Entity-Relationship Diagram (PERD) demonstrated its effectiveness in this research for studying pAD. Another kind of diagram with occurrence order for some factors was also proposed to provide sequential information of the factors. In addition, PERD could potentially develop into an online application named PERD-online, which would help researchers to pool findings on the same relationships and guide further tests to validate uncertain relationships in PERD. PERD as a generic graphical meta-analysis tool can also be applied in studying other multifactorial diseases.

Spatially distinct atrophy is linked to β-amyloid and tau in preclinical Alzheimer disease

OBJECTIVES

To determine whether an MRI-based Alzheimer disease (AD) signature biomarker can detect tau-related neurodegeneration in preclinical AD, and to assess whether AD signature cortical thinning is associated with cognitive changes in cognitively normal (CN) older individuals.

METHODS

In a large cohort of CN individuals (n = 188), we measured the hippocampal volume and cortical thickness within independently defined AD signature regions. We cross-sectionally assessed the associations between AD signature cortical thinning or hippocampal atrophy with CSF biomarkers of tau (increased tau) and β-amyloid (Aβ) (decreased Aβ42). We also examined the impact of AD signature cortical thinning or other biomarker changes (i.e., hippocampal atrophy, reduced CSF Aβ42, or increased CSF tau) on cognitive performance in CN individuals.

RESULTS

Elevated CSF tau was associated with AD signature cortical thinning but not hippocampal atrophy. In contrast, decreased CSF Aβ42 was associated with hippocampal loss but not AD signature cortical thinning. In addition, AD signature cortical thinning was associated with lower visuospatial performance. Reduced CSF Aβ42 was related to poorer performance on episodic memory.

CONCLUSIONS

Spatially distinct neurodegeneration is associated with Aβ and tau pathology in preclinical AD. Aβ deposition and AD signature cortical atrophy independently affect cognition in CN older individuals.

The evolution of preclinical Alzheimer's disease: implications for prevention trials

As the field begins to test the concept of a "preclinical" stage of neurodegenerative disease, when the pathophysiological process has begun in the brain, but clinical symptoms are not yet manifest, a number of intriguing questions have already arisen. In particular, in preclinical Alzheimer's disease (AD), the temporal relationship of amyloid markers to markers of neurodegeneration and their relative utility in the prediction of cognitive decline among clinically normal older individuals remains to be fully elucidated. Secondary prevention trials in AD have already begun in both genetic at-risk and amyloid at-risk cohorts, with several more trials in the planning stages, and should provide critical answers about whether intervention at this very early stage of disease can truly bend the curve of clinical progression. This review will highlight recent progress in cognitive, imaging, and biomarker outcomes in the field of preclinical AD, and the remaining gaps in knowledge.

Synergistic effect of β-amyloid and neurodegeneration on cognitive decline in clinically normal individuals

IMPORTANCE

Assessing the ability of Alzheimer disease neuroimaging markers to predict short-term cognitive decline among clinically normal (CN) individuals is critical for upcoming secondary prevention trials using cognitive outcomes.

OBJECTIVE

To determine whether neuroimaging markers of β-amyloid (Aβ) and neurodegeneration (ND) are independently or synergistically associated with longitudinal cognitive decline in CN individuals.

DESIGN, SETTING, AND PARTICIPANTS

Academic medical center longitudinal natural history study among 166 CN individuals (median age, 74 years; 92 women).

MAIN OUTCOMES AND MEASURES

The Aβ status was determined with Pittsburgh Compound B-positron emission tomography, while ND was assessed using 2 a priori measures, hippocampus volume (magnetic resonance imaging) and glucose metabolism (positron emission tomography with fludeoxyglucose F 18), extracted from Alzheimer disease-vulnerable regions. Based on imaging markers, CN individuals were categorized into the following preclinical Alzheimer disease stages: stage 0 (Aβ-/ND-), stage 1 (Aβ(+)/ND-), stage 2 (Aβ(+)/ND(+)), and suspected non-Alzheimer disease pathology (Aβ-/ND(+)). Cognition was assessed with a composite of neuropsychological tests administered annually.

RESULTS

The Aβ(+) CN individuals were more likely to be classified as ND+: 59.6% of Aβ(+) CN individuals were ND(+), whereas 31.9% of Aβ- CN individuals were ND(+) (odds ratio, 3.14; 95% CI, 1.44-7.02; P = .004). In assessing longitudinal cognitive performance, practice effects were evident in CN individuals negative for both Aβ and ND, whereas diminished practice effects were observed in CN individuals positive for either Aβ or ND. Decline over time was observed only in CN individuals positive for both Aβ and ND, and decline in this group was significantly greater than that in all other groups (P < .001 for all). A significant interaction term between Aβ and ND confirmed that this decline was greater than the additive contributions of Aβ and ND (P = .04).

CONCLUSIONS AND RELEVANCE

The co-occurrence of Aβ and ND accelerates cognitive decline in CN individuals. Therefore, both factors are important to consider in upcoming secondary prevention trials targeting CN individuals at high risk for progression to the symptomatic stages of Alzheimer disease.

Emerging β-amyloid pathology and accelerated cortical atrophy

IMPORTANCE

The effect of β-amyloid (Aβ) accumulation on regional structural brain changes in early stages of Alzheimer disease (AD) is not well understood.

OBJECTIVE

To test the hypothesis that the development of Aβ pathology is related to increased regional atrophy in the brains of cognitively normal (CN) persons.

DESIGN, SETTING, AND PARTICIPANTS

Longitudinal clinicobiomarker cohort study involving 47 CN control subjects and 15 patients with AD dementia. All participants underwent repeated cerebrospinal fluid Aβ42 and structural magnetic resonance imaging measurements for up to 4 years. Cognitively normal controls were classified using the longitudinal cerebrospinal fluid Aβ42 data and included 13 stable Aβ negative (normal baseline Aβ42 levels, with less than the median reduction over time), 13 declining Aβ negative (normal baseline Aβ42 levels, with greater than the median reduction over time), and 21 Aβ positive (pathologic baseline Aβ42 levels). All 15 patients with AD dementia were Aβ positive.

MAIN OUTCOMES AND MEASURES

Group effects on regional gray matter volumes at baseline and over time, tested by linear mixed-effects models.

RESULTS

Baseline gray matter volumes were similar among the CN Aβ groups, but atrophy rates were increased in frontoparietal regions in the declining Aβ-negative and Aβ-positive groups and in amygdala and temporal regions in the Aβ-positive group. Aβ-positive patients with AD dementia had further increased atrophy rates in hippocampus and temporal and cingulate regions.

CONCLUSIONS AND RELEVANCE

Emerging Aβ pathology is coupled to increased frontoparietal (but not temporal) atrophy rates. Atrophy rates peak early in frontoparietal regions but accelerate in hippocampus, temporal, and cingulate regions as the disease progresses to dementia. Early-stage Aβ pathology may have mild effects on local frontoparietal cortical integrity while effects in temporal regions appear later and accelerate, leading to the atrophy pattern typically seen in AD.

The relevance of beta-amyloid on markers of Alzheimer's disease in clinically normal individuals and factors that influence these associations

Aberrant accumulation of beta-amyloid (Aβ) is thought to be an early event in a biological cascade that eventually leads to Alzheimer's disease (AD). Along these lines, many clinically normal (CN) older individuals have evidence of beta-amyloid (Aβ) accumulation, which may be indicative of preclinical AD. However, relationships between Aβ and "downstream" AD markers are often inconsistent across studies. These inconsistencies may be due to the presence of other age-related processes that also influence AD markers, as well as additional risk factors that interact with Aβ to influence downstream changes. For instance, it is possible that the effect of Aβ is modified by neurodegeneration, genetics, sex-differences and cognitive reserve. Thus, a multivariate approach to determining risk of AD within CN participants may be more appropriate than reliance on Aβ status alone. An understanding of how additional risk factors interact with Aβ to influence an individual's trajectory towards AD is essential for characterizing preclinical AD and has implications for prevention trials.

Amyloid deposition is linked to aberrant entorhinal activity among cognitively normal older adults

Normal aging is often difficult to distinguish from the earliest stages of Alzheimer's disease. Years before clinical memory deficits manifest, amyloid-β deposits in the cortex in many older individuals. Neuroimaging studies indicate that a set of densely connected neocortical regions, referred to as the default network, is especially vulnerable to amyloid-β deposition. Yet, the impact of amyloid-β on age-related changes within the medial temporal lobe (MTL) memory system is less clear. Here we demonstrate that cognitively normal older humans, compared with young adults, show reduced ability to modulate hippocampal activations and entorhinal deactivations during an episodic memory task. Among older adults, amyloid-β deposition was associated with failure to modulate activity in entorhinal cortex, but not hippocampus. Furthermore, we show that entorhinal regions demonstrating amyloid-β-related dysfunction are directly connected to the neocortical regions of the default network. Together these findings link neocortical amyloid-β deposition to neuronal dysfunction specifically in entorhinal cortex, while aging is associated with more widespread functional changes across the MTL.

Role of HIV in amyloid metabolism

HIV infection has changed from an acute devastating disease to a more chronic illness due to combination anti-retroviral treatment (cART). In the cART era, the life expectancy of HIV-infected (HIV+) individuals has increased. More HIV + individuals are aging with current projections suggesting that 50% of HIV + individuals will be over 50 years old by 2015. With advancing age, HIV + individuals may be at increased risk of developing other potential neurodegenerative disorders [especially Alzheimer's disease (AD)]. Pathology studies have shown that HIV increases intra and possibly extracellular amyloid beta (Aβ42), a hallmark of AD. We review the synthesis and clearance of Aβ42; the effects of HIV on the amyloid pathway; and contrast the impact of AD and HIV on Aβ42 metabolism. Biomarker studies (cerebrospinal fluid AB and amyloid imaging) in HIV + participants have shown mixed results. CSF Aβ42 has been shown to be either normal or diminished in with HIV associated neurocognitive disorders (HAND). Amyloid imaging using [(11)C] PiB has also not demonstrated increased extracellular amyloid fibrillar deposits in HAND. We further demonstrate that Aβ42 deposition is not increased in older HIV + participants using [(11)C] PiB amyloid imaging. Together, these results suggest that HIV and aging each independently affect Aβ42 deposition with no significant interaction present. Older HIV + individuals are probably not at increased risk for developing AD. However, future longitudinal studies of older HIV + individuals using multiple modalities (including the combination of CSF markers and amyloid imaging) are necessary for investigating the effects of HIV on Aβ42 metabolism.

Early detection of Alzheimer's disease using PiB and FDG PET

Use of biomarkers in the detection of early and preclinical Alzheimer's disease (AD) has become of central importance following publication of the NIA-Alzheimer's Association revised criteria for the diagnosis of AD, mild cognitive impairment (MCI) and preclinical AD. The use of in vivo amyloid imaging agents, such a Pittsburgh Compound-B and markers of neurodegeneration, such as fluoro-2-deoxy-D-glucose (FDG) is able to detect early AD pathological processes and subsequent neurodegeneration. Imaging with PiB and FDG thus has many potential clinical benefits: early or perhaps preclinical detection of disease and accurately distinguishing AD from dementias of other etiologies in patients presenting with mild or atypical symptoms or confounding comorbidities in which the diagnostic distinction is difficult to make clinically. From a research perspective, this allows us to study relationships between amyloid pathology and changes in cognition, brain structure, and function across the continuum from normal aging to MCI to AD. The present review focuses on use of PiB and FDG-PET and their relationship to one another.

Association of hypometabolism and amyloid levels in aging, normal subjects

OBJECTIVE

We evaluated the relationship of amyloid, seen on Pittsburgh compound B (PiB)-PET, and metabolism, seen on [(18)F]-fluorodeoxyglucose (FDG)-PET, in normal subjects to better understand pathogenesis and biomarker selection in presymptomatic subjects.

METHODS

Normal participants (aged 70-95 years; 600 with PiB-PET, FDG-PET, and MRI) were included. We performed a cross-sectional evaluation and subcategorized participants into amyloid-negative (<1.4), high-normal (1.4-1.5), positive (1.5-2.0), and markedly positive (>2.0) PiB standardized uptake value ratio groups representing different levels of amyloid brain load. Associations with metabolism were assessed in each group. Relationships with APOE ε4 carriage were evaluated.

RESULTS

Hypometabolism in "Alzheimer disease (AD)-signature" regions was strongly associated with PiB load. Hypometabolism was greater with more positive PiB levels. Additional, more-diffuse cortical hypometabolism was also found to be associated with PiB, although less so. No hypermetabolism was seen in any subset. No significant incremental hypometabolism was seen in APOE-positive vs -negative subjects.

CONCLUSIONS

Hypometabolism in PiB-positive, cognitively normal subjects in a population-based cohort occurs in AD-signature cortical regions and to a lesser extent in other cortical regions. It is more pronounced with higher amyloid load and supports a dose-dependent association. The effect of APOE ε4 carriage in this group of subjects does not appear to modify their hypometabolic "AD-like" neurodegeneration. Consideration of hypometabolism associated with amyloid load may aid trials of AD drug therapy.