Amyloid PET in European and North American cohorts; and exploring age as a limit to clinical use of amyloid imaging

APOE genotype and sex modulate Alzheimer's disease pathology in aged EFAD transgenic mice

Increasing evidence supports that age, APOE and sex interact to modulate Alzheimer's disease (AD) risk, however the underlying pathways are unclear. One way that AD risk factors may modulate cognition is by impacting amyloid beta (Aβ) accumulation as plaques, and/or neuroinflammation Therefore, the goal of the present study was to evaluate the extent to which age, APOE and sex modulate Aβ pathology, neuroinflammation and behavior in vivo. To achieve this goal, we utilized the EFAD mice, which express human APOE3 or APOE4 and have five familial AD mutations (FAD) that result in Aβ42 overproduction. We assessed Aβ levels, reactive glia and Morris water maze performance in 6-, 10-, 14-, and 18-month-old EFAD mice. Female APOE4 mice had the highest Aβ deposition, fibrillar amyloid deposits and neuroinflammation as well as earlier behavior deficits. Interestingly, we found that female APOE3 mice and male APOE4 mice had similar levels of pathology. Collectively our data support that the combination of APOE4 and female sex is the most detrimental combination for AD, and that at older ages, female sex may be equivalent to APOE4 genotype.

Evaluation of in vivo staging of amyloid deposition in cognitively unimpaired elderly aged 78-94

Amyloid-beta (Aβ) deposition is common in cognitively unimpaired (CU) elderly >85 years. This study investigated amyloid distribution and evaluated three published in vivo amyloid-PET staging schemes from a cognitively unimpaired (CU) cohort aged 84.9 ± 4.3 years (n = 75). SUV-based principal component analysis (PCA) was applied to 18F-flutemetamol PET data to determine an unbiased regional covariance pattern of tracer uptake across grey matter regions. PET staging schemes were applied to the data and compared to the PCA output. Concentration of p-tau181 was measured in blood plasma. The PCA revealed three distinct components accounting for 91.2% of total SUV variance. PC1 driven by the large common variance of uptake in neocortical and striatal regions was significantly positively correlated with global SUVRs, APOE4 status and p-tau181 concentration. PC2 represented mainly non-specific uptake in typical amyloid-PET reference regions, and PC3 the occipital lobe. Application of the staging schemes demonstrated that the majority of the CU cohort (up to 93%) were classified as having pathological amount and distribution of Aβ. Good correspondence existed between binary (+/-) classification and later amyloid stages, however, substantial differences existed between schemes for low stages with 8-17% of individuals being unstageable, i.e., not following the sequential progression of Aβ deposition. In spite of the difference in staging outcomes there was broad spatial overlap between earlier stages and PC1, most prominently in default mode network regions. This study critically evaluated the utility of in vivo amyloid staging from a single PET scan in CU elderly and found that early amyloid stages could not be consistently classified. The majority of the cohort had pathological Aβ, thus, it remains an open topic what constitutes abnormal brain Aβ in the oldest-old and what is the best method to determine that.

Relationship between F-18 florbetapir uptake in occipital lobe and neurocognitive performance in Alzheimer's disease

PURPOSE

To determine the association between occipital amyloid-PET uptake and neurocognitive performance in Alzheimer's disease (AD).

MATERIALS AND METHODS

Fifty-eight participants with normal aged, mild cognitive impairment (MCI) due to AD and AD subjects who underwent F-18 florbetapir brain PET/CT scans were divided into four groups (A, normal; B, MCI; C, mild AD; and D, moderate/severe AD). Semiquantitative analyses of SUVR images were performed. The differences between groups and the correlations between florbetapir uptake and Thai Mental State Examination (TMSE) scores were determined. Significant differences were defined using a P < 0.001, uncorrected, or a P < 0.05, FWE for the voxel-based analyses with Statistical Parametric Mapping (SPM).

RESULTS

There was a slightly higher florbetapir uptake in the precuneus, parietal, and occipital association cortices in Group B > A. The occipital florbetapir uptake in Groups C and D was significantly higher than in Group A, in addition to the precuneus, anterior cingulate, posterior cingulate, temporoparietal, and frontal cortices. There was a strong negative correlation between TMSE scores and florbetapir uptake in the occipital lobe.

CONCLUSIONS

Occipital amyloid uptake is associated with clinically advanced AD, and is inversely correlated with neurocognitive performance and may be useful for evaluating AD severity.

Low-dose CT for the spatial normalization of PET images: A validation procedure for amyloid-PET semi-quantification

The reference standard for spatial normalization of brain positron emission tomography (PET) images involves structural Magnetic Resonance Imaging (MRI) data. However, the lack of such structural information is fairly common in clinical settings. This might lead to lack of proper image quantification and to evaluation based only on visual ratings, which does not allow research studies or clinical trials based on quantification.

PET/CT systems are widely available and CT normalization procedures need to be explored. Here we describe and validate a procedure for the spatial normalization of PET images based on the low-dose Computed Tomography (CT) images contextually acquired for attenuation correction in PET/CT systems. We included N = 34 subjects, spanning from cognitively normal to mild cognitive impairment and dementia, who underwent amyloid-PET/CT (¹⁸F-Florbetaben) and structural MRI scans. The proposed pipeline is based on the SPM12 unified segmentation algorithm applied to low-dose CT images. The validation of the normalization pipeline focused on 1) statistical comparisons between regional and global ¹⁸F-Florbetaben-PET/CT standardized uptake value ratios (SUVrs) estimated from both CT-based and MRI-based normalized PET images (SUVr_CT, SUVr_MRI) and 2) estimation of the degrees of overlap between warped gray matter (GM) segmented maps derived from CT- and MRI-based spatial transformations.

We found negligible deviations between regional and global SUVrs in the two CT and MRI-based methods. SUVr_CT and SUVr_MRI global uptake scores showed negligible differences (mean ± sd 0.01 ± 0.03). Notably, the CT- and MRI-based warped GM maps showed excellent overlap (90% within 1 mm).

The proposed analysis pipeline, based on low-dose CT images, allows accurate spatial normalization and subsequent PET image quantification. A CT-based analytical pipeline could benefit both research and clinical practice, allowing the recruitment of larger samples and favoring clinical routine analysis.

Impact of amyloid-beta changes on cognitive outcomes in Alzheimer's disease: analysis of clinical trials using a quantitative systems pharmacology model

BACKGROUND

Despite a tremendous amount of information on the role of amyloid in Alzheimer's disease (AD), almost all clinical trials testing this hypothesis have failed to generate clinically relevant cognitive effects.

METHODS

We present an advanced mechanism-based and biophysically realistic quantitative systems pharmacology computer model of an Alzheimer-type neuronal cortical network that has been calibrated with Alzheimer Disease Assessment Scale, cognitive subscale (ADAS-Cog) readouts from historical clinical trials and simulated the differential impact of amyloid-beta (Aβ40 and Aβ42) oligomers on glutamate and nicotinic neurotransmission.

RESULTS

Preclinical data suggest a beneficial effect of shorter Aβ forms within a limited dose range. Such a beneficial effect of Aβ40 on glutamate neurotransmission in human patients is absolutely necessary to reproduce clinical data on the ADAS-Cog in minimal cognitive impairment (MCI) patients with and without amyloid load, the effect of APOE genotype effect on the slope of the cognitive trajectory over time in placebo AD patients and higher sensitivity to cholinergic manipulation with scopolamine associated with higher Aβ in MCI subjects. We further derive a relationship between units of Aβ load in our model and the standard uptake value ratio from amyloid imaging. When introducing the documented clinical pharmacodynamic effects on Aβ levels for various amyloid-related clinical interventions in patients with low Aβ baseline, the platform predicts an overall significant worsening for passive vaccination with solanezumab, beta-secretase inhibitor verubecestat and gamma-secretase inhibitor semagacestat. In contrast, all three interventions improved cognition in subjects with moderate to high baseline Aβ levels, with verubecestat anticipated to have the greatest effect (around ADAS-Cog value 1.5 points), solanezumab the lowest (0.8 ADAS-Cog value points) and semagacestat in between. This could explain the success of many amyloid interventions in transgene animals with an artificial high level of Aβ, but not in AD patients with a large variability of amyloid loads.

CONCLUSIONS

If these predictions are confirmed in post-hoc analyses of failed clinical amyloid-modulating trials, one should question the rationale behind testing these interventions in early and prodromal subjects with low or zero amyloid load.

PET Imaging for Early Detection of Alzheimer's Disease: From Pathologic to Physiologic Biomarkers

This article describes the application of various PET imaging agents in the investigation and diagnosis of Alzheimer's disease (AD), including radiotracers for pathologic biomarkers of AD such as β-amyloid deposits and tau protein aggregates, and the neuroinflammation biomarker 18 kDa translocator protein, as well as physiologic biomarkers, such as cholinergic receptors, glucose metabolism, and the synaptic density biomarker synaptic vesicle glycoprotein 2A. Potential of these biomarkers for early AD diagnosis is also assessed.

Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials

INTRODUCTION

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015.

METHODS

We used standard searches to find publications using ADNI data.

RESULTS

(1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers.

DISCUSSION

Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.