Daniel Skovronsky

Imaging of amyloid β in Alzheimer's disease with 18F-BAY94-9172, a novel PET tracer: proof of mechanism

BACKGROUND Amyloid-beta (Abeta) plaque formation is a hallmark of Alzheimers disease (AD) and precedes the onset of dementia. Abeta imaging should allow earlier diagnosis, but clinical application is hindered by the short decay half-life of current Abeta-specific ligands. (18)F-BAY94-9172 is an Abeta ligand that, due to the half-life of (18)F, is suitable for clinical use. We thus studied the effectiveness of this ligand in identifying patients with AD. METHODS 15 patients with mild AD, 15 healthy elderly controls, and five individuals with frontotemporal lobar degeneration (FTLD) were studied. (18)F-BAY94-9172 binding was quantified by use of the standardised uptake value ratio (SUVR), which was calculated for the neocortex by use of the cerebellum as reference region. SUVR images were visually rated as normal or AD. FINDINGS (18)F-BAY94-9172 binding matched the reported post-mortem distribution of Abeta plaques. All AD patients showed widespread neocortical binding, which was greater in the precuneus/posterior cingulate and frontal cortex than in the lateral temporal and parietal cortex. There was relative sparing of sensorimotor, occipital, and medial temporal cortex. Healthy controls and FTLD patients showed only white-matter binding, although three controls and one FTLD patient had mild uptake in frontal and precuneus cortex. At 90-120 min after injection, higher neocortical SUVR was observed in AD patients (2.0 [SD 0.3]) than in healthy controls (1.3 [SD 0.2]; p<0.0001) or FTLD patients (1.2 [SD 0.2]; p=0.009). Visual interpretation was 100% sensitive and 90% specific for detection of AD. INTERPRETATION (18)F-BAY94-9172 PET discriminates between AD and FTLD or healthy controls and might facilitate integration of Abeta imaging into clinical practice.

In Vivo Imaging of Amyloid Deposition in Alzheimer Disease Using the Radioligand 18F-AV-45 (Flobetapir F 18)

An 18F-labeled PET amyloid-β (Aβ) imaging agent could facilitate the clinical evaluation of late-life cognitive impairment by providing an objective measure for Alzheimer disease (AD) pathology. Here we present the results of a clinical trial with (E)-4-(2-(6-(2-(2-(2-18F-fluoroethoxy)ethoxy)ethoxy)pyridin-3-yl)vinyl)-N-methyl benzenamine (18F-AV-45 or flobetapir F 18). Methods: An open-label, multicenter brain imaging, metabolism, and safety study of 18F-AV-45 was performed on 16 patients with AD (Mini-Mental State Examination score, 19.3 ± 3.1; mean age ± SD, 75.8 ± 9.2 y) and 16 cognitively healthy controls (HCs) (Mini-Mental State Examination score, 29.8 ± 0.45; mean age ± SD, 72.5 ± 11.6 y). Dynamic PET was performed over a period of approximately 90 min after injection of the tracer (370 MBq [10 mCi]). Standardized uptake values and cortical-to-cerebellum standardized uptake value ratios (SUVRs) were calculated. A simplified reference tissue method was used to generate distribution volume ratio (DVR) parametric maps for a subset of subjects. Results: Valid PET data were available for 11 AD patients and 15 HCs. 18F-AV-45 accumulated in cortical regions expected to be high in Aβ deposition (e.g., precuneus and frontal and temporal cortices) in AD patients; minimal accumulation of the tracer was seen in cortical regions of HCs. The cortical-to-cerebellar SUVRs in AD patients showed continual substantial increases through 30 min after administration, reaching a plateau within 50 min. The 10-min period from 50 to 60 min after administration was taken as a representative sample for further analysis. The cortical average SUVR for this period was 1.67 ± 0.175 for patients with AD versus 1.25 ± 0.177 for HCs. Spatially normalized DVRs generated from PET dynamic scans were highly correlated with SUVR (r = 0.58–0.88, P < 0.005) and were significantly greater for AD patients than for HCs in cortical regions but not in subcortical white matter or cerebellar regions. No clinically significant changes in vital signs, electrocardiogram, or laboratory values were observed. Conclusion: 18F-AV-45 was well tolerated, and PET showed significant discrimination between AD patients and HCs, using either a parametric reference region method (DVR) or a simplified SUVR calculated from 10 min of scanning 50–60 min after 18F-AV-45 administration.

Cerebral PET with florbetapir compared with neuropathology at autopsy for detection of neuritic amyloid-β plaques: a prospective cohort study

BACKGROUND Results of previous studies have shown associations between PET imaging of amyloid plaques and amyloid-β pathology measured at autopsy. However, these studies were small and not designed to prospectively measure sensitivity or specificity of amyloid PET imaging against a reference standard. We therefore prospectively compared the sensitivity and specificity of amyloid PET imaging with neuropathology at autopsy. METHODS This study was an extension of our previous imaging-to-autopsy study of participants recruited at 22 centres in the USA who had a life expectancy of less than 6 months at enrolment. Participants had autopsy within 2 years of PET imaging with florbetapir ((18)F). For one of the primary analyses, the interpretation of the florbetapir scans (majority interpretation of five nuclear medicine physicians, who classified each scan as amyloid positive or amyloid negative) was compared with amyloid pathology (assessed according to the Consortium to Establish a Registry for Alzheimers Disease standards, and classed as amyloid positive for moderate or frequent plaques or amyloid negative for no or sparse plaques); correlation of the image analysis results with amyloid burden was tested as a coprimary endpoint. Correlation, sensitivity, and specificity analyses were also done in the subset of participants who had autopsy within 1 year of imaging as secondary endpoints. The study is registered with ClinicalTrials.gov, number NCT 01447719 (original study NCT 00857415). FINDINGS We included 59 participants (aged 47-103 years; cognitive status ranging from normal to advanced dementia). The sensitivity and specificity of florbetapir PET imaging for detection of moderate to frequent plaques were 92% (36 of 39; 95% CI 78-98) and 100% (20 of 20; 80-100%), respectively, in people who had autopsy within 2 years of PET imaging, and 96% (27 of 28; 80-100%) and 100% (18 of 18; 78-100%), respectively, for those who had autopsy within 1 year. Amyloid assessed semiquantitatively with florbetapir PET was correlated with the post-mortem amyloid burden in the participants who had an autopsy within 2 years (Spearman ρ=0·76; p<0·0001) and within 12 months between imaging and autopsy (0·79; p<0·0001). INTERPRETATION The results of this study validate the binary visual reading method approved in the USA for clinical use with florbetapir and suggest that florbetapir could be used to distinguish individuals with no or sparse amyloid plaques from those with moderate to frequent plaques. Additional research is needed to understand the prognostic implications of moderate to frequent plaque density. FUNDING Avid Radiopharmaceuticals.

Preclinical Properties of 18F-AV-45: A PET Agent for Aβ Plaques in the Brain

β-amyloid plaques (Aβ plaques) in the brain, containing predominantly fibrillary Aβ peptide aggregates, represent a defining pathologic feature of Alzheimer disease (AD). Imaging agents targeting the Aβ plaques in the living human brain are potentially valuable as biomarkers of pathogenesis processes in AD. (E)-4-(2-(6-(2-(2-(2-18F-fluoroethoxy)ethoxy)ethoxy)pyridin-3-yl)vinyl)-N-methyl benzenamine (18F-AV-45) is such as an agent currently in phase III clinical studies for PET of Aβ plaques in the brain. Methods: In vitro binding of 18F-AV-45 to Aβ plaques in the postmortem AD brain tissue was evaluated by in vitro binding assay and autoradiography. In vivo biodistribution of 18F-AV-45 in mice and ex vivo autoradiography of AD transgenic mice (APPswe/PSEN1) with Aβ aggregates in the brain were performed. Small-animal PET of a monkey brain after an intravenous injection of 18F-AV-45 was evaluated. Results: 18F-AV-45 displayed a high binding affinity and specificity to Aβ plaques (Kd, 3.72 ± 0.30 nM). In vitro autoradiography of postmortem human brain sections showed substantial plaque labeling in AD brains and not in the control brains. Initial high brain uptake and rapid washout from the brain of healthy mice and monkey were observed. Metabolites produced in the blood of healthy mice after an intravenous injection were identified. 18F-AV-45 displayed excellent binding affinity to Aβ plaques in the AD brain by ex vivo autoradiography in transgenic AD model mice. The results lend support that 18F-AV-45 may be a useful PET agent for detecting Aβ plaques in the living human brain.

The Alzheimer's Disease Neuroimaging Initiative positron emission tomography core

This is a progress report of the Alzheimers Disease Neuroimaging Initiative (ADNI) positron emission tomography (PET) Core.

Protein kinase C-dependent alpha-secretase competes with beta-secretase for cleavage of amyloid-beta precursor protein in the trans-golgi network.

The release of amyloidogenic amyloid-β peptide (Aβ) from amyloid-β precursor protein (APP) requires cleavage by β- and γ-secretases. In contrast, α-secretase cleaves APP within the Aβ sequence and precludes amyloidogenesis. Regulated and unregulated α-secretase activities have been reported, and the fraction of cellular α-secretase activity regulated by protein kinase C (PKC) has been attributed to the ADAM (a disintegrin and metalloprotease) family members TACE and ADAM-10. Although unregulated α-secretase cleavage of APP has been shown to occur at the cell surface, we sought to identify the intracellular site of PKC-regulated α-secretase APP cleavage. To accomplish this, we measured levels of secreted ectodomains and C-terminal fragments of APP generated by α-secretase (sAPPα) (C83) versus β-secretase (sAPPβ) (C99) and secreted Aβ in cultured cells treated with PKC and inhibitors of TACE/ADAM-10. We found that PKC stimulation increased sAPPα but decreased sAPPβ levels by altering the competition between α- versus β-secretase for APP within the same organelle rather than by perturbing APP trafficking. Moreover, data implicating the trans-Golgi network (TGN) as a major site for β-secretase activity prompted us to hypothesize that PKC-regulated α-secretase(s) also reside in this organelle. To test this hypothesis, we performed studies demonstrating proteolytically mature TACE intracellularly, and we also showed that regulated α-secretase APP cleavage occurs in the TGN using an APP mutant construct targeted specifically to the TGN. By detecting regulated α-secretase APP cleavage in the TGN by TACE/ADAM-10, we reveal ADAM activity in a novel location. Finally, the competition between TACE/ADAM-10 and β-secretase for intracellular APP cleavage may represent a novel target for the discovery of new therapeutic agents to treat Alzheimers disease.

Using Positron Emission Tomography and Florbetapir F 18 to Image Cortical Amyloid in Patients With Mild Cognitive Impairment or Dementia Due to Alzheimer Disease

OBJECTIVES To characterize quantitative florbetapir F 18 (hereafter referred to as simply florbetapir) positron emission tomographic (PET) measurements of fibrillar β-amyloid (Aβ) burden in a large clinical cohort of participants with probable Alzheimer disease (AD) or mild cognitive impairment (MCI) and older healthy controls (OHCs). DESIGN Cerebral-to-whole-cerebellar florbetapir standard uptake value ratios (SUVRs) were computed. Mean cortical SUVRs were compared. A threshold of SUVRs greater than or equal to 1.17 was used to reflect pathological levels of amyloid associated with AD based on separate antemortem PET and postmortem neuropathology data from 19 end-of-life patients. Similarly, a threshold of SUVRs greater than 1.08 was used to signify the presence of any identifiable Aβ because this was the upper limit from a separate set of 46 individuals 18 to 40 years of age who did not carry apolipoprotein E (APOE) ε4. SETTING Multiple research imaging centers. PARTICIPANTS A total of 68 participants with probable AD, 60 participants with MCI, and 82 OHCs who were 55 years of age or older. Main Outcome Measure Florbetapir-PET activity. RESULTS All of the participants (ie, those with probable AD or MCI and those who were OHCs) differed significantly in mean (SD) cortical florbetapir SUVRs (1.39 [0.24], 1.17 [0.27], and 1.05 [0.16], respectively; P < 1.0 × 10⁻⁷), in percentage meeting levels of amyloid associated with AD by SUVR criteria (80.9%, 40.0%, and 20.7%, respectively; P < 1.0 × 10⁻⁷), and in percentage meeting SUVR criteria for the presence of any identifiable Aβ (85.3%, 46.6%, and 28.1%, respectively; P < 1.0 × 10⁻⁷). Among OHCs, the percentage of florbetapir positivity increased linearly by age decile (P = .05). For the 54 OHCs with available APOE genotypes, APOE ε4 carriers had a higher mean (SD) cortical SUVR than did noncarriers (1.14 [0.2] vs 1.03 [0.16]; P = .048). CONCLUSIONS The findings of our analysis confirm the ability of florbetapir-PET SUVRs to characterize amyloid levels in clinically probable AD, MCI, and OHC groups using continuous and binary measures of fibrillar Aβ burden. It introduces criteria to determine whether an image is associated with an intermediate-to-high likelihood of pathologic AD or with having any identifiable cortical amyloid level above that seen in low-risk young controls.

Amyloid-β assessed by florbetapir F 18 PET and 18-month cognitive decline: a multicenter study.

Objectives: Florbetapir F 18 PET can image amyloid-β (Aβ) aggregates in the brains of living subjects. We prospectively evaluated the prognostic utility of detecting Aβ pathology using florbetapir PET in subjects at risk for progressive cognitive decline. Methods: A total of 151 subjects who previously participated in a multicenter florbetapir PET imaging study were recruited for longitudinal assessment. Subjects included 51 with recently diagnosed mild cognitive impairment (MCI), 69 cognitively normal controls (CN), and 31 with clinically diagnosed Alzheimer disease dementia (AD). PET images were visually scored as positive (Aβ+) or negative (Aβ−) for pathologic levels of β-amyloid aggregation, blind to diagnostic classification. Cerebral to cerebellar standardized uptake value ratios (SUVr) were determined from the baseline PET images. Subjects were followed for 18 months to evaluate changes in cognition and diagnostic status. Analysis of covariance and correlation analyses were conducted to evaluate the association between baseline PET amyloid status and subsequent cognitive decline. Results: In both MCI and CN, baseline Aβ+ scans were associated with greater clinical worsening on the Alzheimers Disease Assessment Scale–Cognitive subscale (ADAS-Cog (p < 0.01) and Clinical Dementia Rating–sum of boxes (CDR-SB) (p < 0.02). In MCI Aβ+ scans were also associated with greater decline in memory, Digit Symbol Substitution (DSS), and Mini-Mental State Examination (MMSE) (p < 0.05). In MCI, higher baseline SUVr similarly correlated with greater subsequent decline on the ADAS-Cog (p < 0.01), CDR-SB (p < 0.03), a memory measure, DSS, and MMSE (p < 0.05). Aβ+ MCI tended to convert to AD dementia at a higher rate than Aβ− subjects (p < 0.10). Conclusions: Florbetapir PET may help identify individuals at increased risk for progressive cognitive decline.

Performance Characteristics of Amyloid PET with Florbetapir F 18 in Patients with Alzheimer's Disease and Cognitively Normal Subjects

The objectives of this study were to examine the effective dose range and the test–retest reliability of florbetapir F 18 using, first, visual assessment by independent raters masked to clinical information and, second, semiautomated quantitative measures of cortical target area to cerebellum standardized uptake value ratios (SUVr) as primary outcome measures. Visual ratings of PET image quality and tracer retention or β-amyloid (Aβ) binding expressed as SUVrs were compared after intravenous administration of either 111 MBq (3 mCi) or 370 MBq (10 mCi) of florbetapir F 18 in patients with Alzheimers disease (AD) (n = 9) and younger healthy controls (YHCs) (n = 11). In a separate set of subjects (AD, n = 10; YHCs, n = 10), test–retest reliability was evaluated by comparing intrasubject visual read ratings and SUVrs for 2 PET images acquired within 4 wk of each other. Results: There were no meaningful differences between the 111-MBq (3-mCi) and 370-MBq (10-mCi) dose in the visual rating or SUVr. The difference in the visual quality across 111 and 370 MBq showed a trend toward lower image quality, but no statistical significance was achieved (t test; t1 = −1.617, P = 0.12) in this relatively small sample of subjects. At both dose levels, visual ratings of amyloid burden identified 100% of AD subjects as Aβ-positive and 100% of YHCs as Aβ-negative. Mean intrasubject test–retest variability for cortical average SUVrs with the cerebellum as a reference over the 50- to 70-min period was 2.4% ± 1.41% for AD subjects and 1.5% ± 0.84% for controls. The overall SUVr test–retest correlation coefficient was 0.99. The overall κ-statistic for test–retest agreement for Aβ classification of the masked reads was 0.89 (95% confidence interval, 0.69–1.0). Conclusion: Florbetapir F 18 appears to have a wide effective dose range and a high test–retest reliability for both quantitative (SUVr) values and visual assessment of the ligand. These imaging performance properties provide important technical information on the use of florbetapir F 18 and PET to detect cerebral amyloid aggregates.

18F Stilbenes and Styrylpyridines for PET Imaging of Aβ Plaques in Alzheimer’s Disease: A Miniperspective

Alzheimer’s disease (AD) is a neurodegenerative disease of the brain, characterized by a slowly progressive dementia. This insidious disease is growing in importance because it affects millions of older patients. Clinical symptoms of AD include cognitive decline, irreversible memory loss, disorientation and language impairment. Major neuropathology observations of postmortem AD brain include the presence of senile plaques containing β-amyloid (Aβ) aggregates and neurofibrillary tangles containing highly phosphorylated tau proteins (Figure 1A).1,2 Several genomic factors have been linked to AD. Familial AD (or early onset AD) has been reported to have mutations in genes encoding β-amyloid precursor protein (APP), presenilin 1, presenilin 2 and Apolipoprotein E (APOE).3 The exact mechanisms of these mutations, which lead to the development of AD, are not fully understood; however, formation of plaques comprised of Aβ peptide in the brain is a pivotal event in the pathology of Alzheimer’s disease. Significant evidence suggests that accumulation and aggregation of Aβ peptides may play a major causative role in AD pathogenesis.2,4 The excessive burden of Aβ, produced by various mechanisms, may represent the starting point of neurodegenerative events, and may initiate a cascade of events (β-amyloid cascade, Figure 1B) that includes gliosis, inflammatory changes, neuritic/synaptic change, tangles and transmitter loss.2 Currently, there is no definitive method to diagnose AD, except by postmortem evaluation and staining of the brain tissue, which demonstrates the existence of Aβ plaques. Figure 1 A. Processes (β-amyloid cascade) participating in AD pathogenesis. Aβ peptides produced by neurons aggregate into a variety of assemblies, some of which may impair synapses and neuronal dendrites. Build-up of pathogenic Aβ aggregates ... Recent reports have suggested that β-amyloid aggregates in the brain play a key role in a cascade of events leading to AD.2,5 Thus, the development of diagnostic imaging agents targeting Aβ aggregates is very important in the diagnosis and treatment of AD. Novel PET imaging agents specifically targeting the Aβ plaques may lead to early detection of AD pathology, differential diagnosis of patients with dementia, and for monitoring patients who are undergoing drug treatment designed to reverse the Aβ buildup in the brain. Indeed, diagnosis and treatment of AD have been hampered by the absence of reliable non-invasive markers for the underlying pathology. Diagnosis based on consensus criteria is approximately 81% sensitive and 70% specific by comparison to the gold standard of pathology at autopsy.6 In addition to errors of misdiagnosis in patients with AD, there is significant under diagnosis; approximately 10% of community dwelling elderly still have undiagnosed dementia, and community physicians may fail to diagnose up to 33% of mild dementia cases.7 Thus, there is a need for a biomarker that can be applied in the community setting and can help physicians separate those patients who do not have AD from those who have pathological signs and should be evaluated further. Additionally, there are a large number of patients who, upon comprehensive diagnostic testing, are found to have cognitive impairment but are not demented and thus, do not meet diagnostic criteria for AD (e.g., patients with mild cognitive impairment, MCI). Some, but not all of these patients will go on to develop AD within 3-5 years. A reliable biomarker might aid prognostic evaluation by documenting the presence or absence of AD related pathology. Based on the definitions of AD endorsed by the American Academy of Neurology, American Psychiatric Association (DSM-IV) and others, patients without abnormal amyloid plaque levels do not meet currently accepted neuropathological criteria for AD. This definition of AD, which includes amyloid plaques as a required feature, is supported by more than 100 years of autopsy data. Therefore, based on this widely-endorsed definition of AD, the use of a test for ruling-out the presence of amyloid plaque pathology in subjects with clinical signs and symptoms of cognitive impairment will, effectively, rule-out the diagnosis of AD, and lead to more careful evaluation and appropriate treatment for alternative causes of cognitive deficits. Moreover, the use of a test for ruling-in the presence of abnormal levels of Aβ plaques in the brain of subjects with signs and symptoms of cognitive impairment will lead to the selection of patients who warrant more detailed work-up for the possible diagnosis of AD or MCI. The differential diagnosis for AD includes a large number of other diseases. At early stages of disease (e.g. MCI), frequent confounds include cognitive impairment as a result of underlying depression, effects of CNS active medications, inadequately treated or end stage medical conditions affecting other organ systems, and even normal age-related changes. At later stages of disease, more common confounds include vascular dementia, frontal temporal lobar dementia (FTLD) complex, dementia with Lewy bodies (DLB) as well as rarer neurodegenerative diseases such as Creutzfeld Jacob Disease (CJD). Importantly, AD subjects will always have Aβ plaques, whereas amyloid is seen not at all, or only sporadically in most of these other diseases. In each case, appropriate prognosis and treatment requires accurate diagnostic assessment.