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.
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.
In both MCI and CN, baseline Aβ+ scans were associated with greater clinical worsening on the Alzheimer's 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).
Florbetapir PET may help identify individuals at increased risk for progressive cognitive decline.
To characterize and compare measurements of the posterior cingulate glucose metabolism, the hippocampal glucose metabolism, and hippocampal volume so as to distinguish cognitively normal, late-middle-aged persons with 2, 1, or 0 copies of the apolipoprotein E (APOE) ε4 allele, reflecting 3 levels of risk for late-onset Alzheimer disease.
Cross-sectional comparison of measurements of cerebral glucose metabolism using 18F-fluorodeoxy-glucose positron emission tomography and measurements of brain volume using magnetic resonance imaging in cognitively normal ε4 homozygotes, ε4 heterozygotes, and noncarriers.
Academic medical center.
A total of 31 ε4 homozygotes, 42 ε4 heterozygotes, and 76 noncarriers, 49 to 67 years old, matched for sex, age, and educational level.
Main Outcome Measures
The measurements of posterior cingulate and hippocampal glucose metabolism were characterized using automated region-of-interest algorithms and normalized for whole-brain measurements. The hippocampal volume measurements were characterized using a semiautomated algorithm and normalized for total intracranial volume.
Although there were no significant differences among the 3 groups of participants in their clinical ratings, neuropsychological test scores, hippocampal volumes (P=.60), or hippocampal glucose metabolism measurements (P = .12), there were significant group differences in their posterior cingulate glucose metabolism measurements (P=.001). The APOE ε4 gene dose was significantly associated with posterior cingulate glucose metabolism (r=0.29, P=.0003), and this association was significantly greater than those with hippocampal volume or hippocampal glucose metabolism (P<.05, determined by use of pairwise Fisher z tests).
Although our findings may depend in part on the analysis algorithms used, they suggest that a reduction in posterior cingulate glucose metabolism precedes a reduction in hippocampal volume or metabolism in cognitively normal persons at increased genetic risk for Alzheimer disease.
This multicenter study examined 18F-FDG PET measures in the differential diagnosis of Alzheimer’s disease (AD), frontotemporal dementia (FTD), and dementia with Lewy bodies (DLB) from normal aging and from each other and the relation of disease-specific patterns to mild cognitive impairment (MCI).
We examined the 18F-FDG PET scans of 548 subjects, including 110 healthy elderly individuals (“normals” or NLs), 114 MCI, 199 AD,98FTD, and 27 DLB patients, collected at 7 participating centers. Individual PET scans were Z scored using automated voxel-based comparison with generation of disease-specific patterns of cortical and hippocampal 18F-FDG uptake that were then applied to characterize MCI.
Standardized disease-specific PET patterns were developed that correctly classified 95%AD, 92% DLB,94%FTD,and 94%NL. MCI patients showed primarily posterior cingulate cortex and hippocampal hypometabolism (81%), whereas neocortical abnormalities varied according to neuropsychological profiles. An AD PET pattern was observed in 79% MCI with deficits in multiple cognitive domains and 31% amnesic MCI. 18F-FDG PET heterogeneity in MCI with nonmemory deficits ranged from absent hypometabolism to FTD and DLB PET patterns.
Standardized automated analysis of 18F-FDG PET scans may provide an objective and sensitive support to the clinical diagnosis in early dementia.
18F-FDG PET; Alzheimer’s disease; frontotemporal dementia; Lewy body dementia; mild cognitive impairment; normal aging; hippocampus
We introduced a hypometabolic convergence index (HCI) to characterize in a single measurement the extent to which a person’s fluorodeoxyglucose positron emission tomogram (FDG PET) corresponds to that in Alzheimer’s disease (AD). Apolipoprotein E ε4 (APOE ε4) gene dose is associated with three levels of risk for late-onset AD. We explored the association between gene dose and HCI in cognitively normal ε4 homozygotes, heterozygotes, and non-carriers.
An algorithm was used to characterize and compare AD-related HCIs in cognitively normal individuals, including 36 ε4 homozygotes, 46 heterozygotes, and 78 non-carriers.
These three groups differed significantly in their HCIs (ANOVA, p = 0.004), and there was a significant association between HCIs and gene dose (linear trend, p = 0.001).
The HCI is associated with three levels of genetic risk for late-onset AD. This supports the possibility of using a single FDG PET measurement to help in the preclinical detection and tracking of AD.
What will it take to develop interventions for the treatment of age-related cognitive
decline? Session V of the Summit provided perspectives on the design of clinical trials to
evaluate promising but unproven interventions, and some of the steps needed to accelerate
the discovery and evaluation of promising treatments. It considered strategies to further
characterize the biological and cognitive changes associated with normal aging and their
translation into the development of new treatments. It provided regulatory, scientific,
and clinical perspectives about neurocognitive aging treatments, their potential benefits
and risks, and the strategies and endpoints needed to evaluate them in the most rapid,
rigorous, and clinically meaningful way. It considered lessons learned from the study of
Alzheimer's disease, the promising roles of biomarkers in neurocognitive aging
research, and ways to help galvanize the scientific study and treatment of neurocognitive
Cognition; Clinical trials; Aging
Over the last 20 years, there has been extraordinary progress in brain imaging research and its application to the study of Alzheimer's disease (AD). Brain imaging researchers have contributed to the scientific understanding, early detection and tracking of AD. They have set the stage for imaging techniques to play growing roles in the clinical setting, the evaluation of disease-modifying treatments, and the identification of demonstrably effective prevention therapies. They have developed ground-breaking methods, including positron emission tomography (PET) ligands to measure fibrillar amyloid-β (Aβ) deposition, new magnetic resonance imaging (MRI) pulse sequences, and powerful image analysis techniques, to help in these endeavors. Additional work is needed to develop even more powerful imaging methods, to further clarify the relationship and time course of Aβ and other disease processes in the predisposition to AD, to establish the role of brain imaging methods in the clinical setting, and to provide the scientific means and regulatory approval pathway needed to evaluate the range of promising disease-modifying and prevention therapies as quickly as possible. Twenty years from now, AD may not yet be a distant memory, but the best is yet to come.
Alzheimer's disease; dementia; mild cognitive impairment; MRI; PET; amyloid; diagnosis; prevention
Complement receptor 1 (CR1) is an Alzheimer's disease (AD) susceptibility locus that also influences AD-related traits such as episodic memory decline and neuritic amyloid plaque deposition. We implemented a functional fine-mapping approach, leveraging intermediate phenotypes to identify functional variant(s) within the CR1 locus. Using 1709 subjects (697 deceased) from the Religious Orders Study and the Rush Memory and Aging Project, we tested 41 single-nucleotide polymorphisms (SNPs) within the linkage disequilibrium block containing the published CR1 AD SNP (rs6656401) for associations with episodic memory decline, and then examined the functional consequences of the top result. We report that a coding variant in the LHR-D (long homologous repeat D) region of the CR1 gene, rs4844609 (Ser1610Thr, minor allele frequency = 0.02), is associated with episodic memory decline and accounts for the known effect of the index SNP rs6656401 (D′ = 1, r2= 0.084) on this trait. Further, we demonstrate that the coding variant's effect is largely dependent on an interaction with APOE-ɛ4 and mediated by an increased burden of AD-related neuropathology. Finally, in our data, this coding variant is also associated with AD susceptibility (joint odds ratio = 1.4). Taken together, our analyses identify a CR1 coding variant that influences episodic memory decline; it is a variant known to alter the conformation of CR1 and points to LHR-D as the functional domain within the CR1 protein that mediates the effect on memory decline. We thus implicate C1q and MBL, which bind to LHR-D, as likely targets of the variant's effect and suggest that CR1 may be an important intermediate in the clearance of Aβ42 particles by C1q.
A method for defining image-derived input function (IDIF) has been introduced and evaluated for the quantification of the regional cerebral metabolic rate of glucose in positron emission tomography studies.
The voxels in the brain vasculature are extracted based on the different monotonicity between the input and output function curves. The TACs of such voxels are averaged to get the uncorrected TAC of the brain vasculature. The IDIF was obtained from the raw TAC after correcting for the partial volume and spillover effects by an empirical formula in conjunction with single blood sample and the TAC of the brain tissue. Data from 16 human subjects were used to test the proposed method. The Patlak approach is used to calculate the net FDG clearance with plasma-derived input function (PDIF) and our generated IDIF, respectively.
the net FDG clearances calculated with the image-derived input function generated by our approach are not only highly correlated (correlation coefficients close to 1) to, but also highly comparable (regression slopes close to 1, and intercepts close to 0) with those calculated with plasma-derived input function.
The method used in the present work is feasible and accurate.
regional cerebral metabolic rate of glucose; 18F-fluoro-2-deoxyglucose; image derived input function; positron emission tomography
Age-related cognitive decline is likely promoted by accumulated brain injury due to chronic conditions of aging, including neurodegenerative and vascular disease. Since common neuronal mechanisms may mediate the adaptation to diverse cerebral insults, we hypothesized that susceptibility for age-related cognitive decline may be due in part to a shared genetic network. We have therefore performed a genome-wide association study using a quantitative measure of global cognitive decline slope, based on repeated measures of 17 cognitive tests in 749 subjects from the Religious Orders Study. Top results were evaluated in three independent replication cohorts, consisting of 2,279 additional subjects with repeated cognitive testing. As expected, we find that the Alzheimer’s disease (AD) susceptibility locus, APOE, is strongly associated with rate of cognitive decline (PDISC=5.6×10−9; PJOINT=3.7×10−27). We additionally discover a variant, rs10808746, which shows consistent effects in the replication cohorts and modestly improved evidence of association in the joint analysis (PDISC=6.7×10−5; PREP=9.4×10−3; PJOINT=2.3×10−5). This variant influences the expression of two adjacent genes, PDE7A and MTFR1, which are potential regulators of inflammation and oxidative injury, respectively. Using aggregate measures of genetic risk, we find that known susceptibility loci for cardiovascular disease, type II diabetes, and inflammatory diseases are not significantly associated with cognitive decline in our cohort. Our results suggest that intermediate phenotypes, when coupled with larger sample sizes, may be a useful tool to dissect susceptibility loci for age-related cognitive decline and uncover shared molecular pathways with a role in neuronal injury.
We previously introduced a voxel-based, multi-modal application of the partial least square algorithm (MMPLS) to characterize the linkage between patterns in a person’s complementary complex datasets without the need to correct for multiple regional comparisons. Here we used it to demonstrate a strong correlation between MMPLS scores to characterize the linkage between the covarying patterns of fluorodeoxyglucose positron emission tomography (FDG PET) measurements of regional glucose metabolism and magnetic resonance imaging (MRI) measurements of regional gray matter associated with apolipoprotein E (APOE) ε4 gene dose (i.e., three levels of genetic risk for late-onset Alzheimer’s disease (AD)) in cognitively normal, late-middle-aged persons. Coregistered and spatially normalized FDG PET and MRI images from 70% of the subjects (27 ε4 homozygotes, 36 ε4 heterozygotes and 67 ε4 non-carriers) were used in a hypothesis-generating MMPLS analysis to characterize the covarying pattern of regional gray matter volume and cerebral glucose metabolism most strongly correlated with APOE-ε4 gene dose. Coregistered and spatially normalized FDG PET and MRI images from the remaining 30% of the subjects were used in a hypothesis-testing MMPLS analysis to generate FDG PET-MRI gray matter MMPLS scores blind to their APOE genotype and characterize their relationship to APOE-ε4 gene dose. The hypothesis-generating analysis revealed covarying regional gray matter volume and cerebral glucose metabolism patterns that resembled those in traditional univariate analyses of AD and APOE-ε4 gene dose and PET-MRI scores that were strongly correlated with APOE-ε4 gene dose (p<1×10−16). The hypothesis-testing analysis results showed strong correlations between FDG PET-MRI gray matter scores and APOE-ε4 gene dose (p=8.7×10−4). Our findings support the possibility of using the MMPLS to analyze complementary datasets from the same person in the presymptomatic detection and tracking of AD.
Studies of asymptomatic carriers of genes that are known to predispose to Alzheimer’s disease (AD) have facilitated the characterization of preclinical AD. The most prevalent genetic risk factor is the e4 allele of apolipoprotein E (APOE). Neuropathological studies of young deceased e4 carriers have shown modest but abnormal amounts of neocortical amyloid and medial temporal neurofibrillary tangles that is also reflected in cerebrospinal fluid (CSF) biomarkers, abeta-amyloid and phosphotau in particular. MRI studies have shown progressive hippocampal and gray matter atrophy with the advent of mild cognitive impairment (MCI), and fluorodeoxyglucose PET scans show reduced cerebral metabolism in posterior cingulate and related AD regions evident even in 30 year olds. Cerebral amyloidosis disclosed by more recent amyloid ligand PET studies in asymptomatic 60 year olds increases in parallel with e4 gene dose. Longitudinal neuropsychological studies have revealed accelerated memory decline in e4 carriers beginning around age 55–60 years whose severity again parallels e4 gene dose. The clinico-pathological correlation of declining memory and AD-like neuropathological change defines preclinical AD and has set the stage for the accelerated evaluation of presymptomatic AD treatments. In this article, we briefly consider some of the earliest detectable changes associated with the predisposition to AD, and some of the prevention trial strategies that have been proposed to help find treatments to reduce the risk, postpone the onset of, or completely prevent AD symptoms as soon as possible.
preclinical; APOE; normal aging; prevention
Epidemiological studies suggest that elevated blood pressure (BP) in mid-life is associated with increased risk of Alzheimer’s disease (AD) in late-life. In this preliminary study, we investigated the extent to which BP measurements are related to positron emission tomography (PET) measurements of fibrillar amyloid-beta burden using Pittsburgh Compound-B (PiB) and fluorodeoxyglucose (FDG) PET measures of cerebral metabolic rate for glucose metabolism (CMRgl) in cognitively normal, late-middle-aged to older adult apolipoprotein E (APOE) ε4 homozygotes, heterozygotes and non-carriers. PiB PET results revealed that systolic BP (SBP) and pulse pressure (PP) were each positively correlated with cerebral-to-cerebellar PiB distribution volume ratio (DVR) in frontal, temporal and posterior-cingulate/precuneus regions, whereas no significant positive correlations were found between PiB DVRs and diastolic BP (DBP). FDG PET results revealed significant inverse correlations between each of the BP measures and lower CMRgl in frontal and temporal brain regions. These preliminary findings provide additional evidence that higher BP, likely a reflection of arterial stiffness, during late-mid-life may be associated with increased risk of presymptomatic AD.
APOE; blood pressure; arterial stiffness; brain imaging; PET; Alzheimer’s disease; amyloid; PiB; Pittsburgh Compound-B
Fibrillar amyloid-β (Aβ) is thought to begin accumulating in the brain many years before the onset of clinical impairment in patients with Alzheimer’s disease. By assessing the accumulation of Aβ in people at risk of genetic forms of Alzheimer’s disease, we can identify how early preclinical changes start in individuals certain to develop dementia later in life. We sought to characterise the age-related accumulation of Aβ deposition in presenilin 1 (PSEN1) E280A mutation carriers across the spectrum of preclinical disease.
Between Aug 1 and Dec 6, 2011, members of the familial Alzheimer’s disease Colombian kindred aged 18–60 years were recruited from the Alzheimer’s Prevention Initiative’s registry at the University of Antioquia, Medellín, Colombia. Cross-sectional assessment using florbetapir PET was done in symptomatic mutation carriers with mild cognitive impairment or mild dementia, asymptomatic carriers, and asymptomatic non-carriers. These assessments were done at the Banner Alzheimer’s Institute in Phoenix, AZ, USA. A cortical grey matter mask consisting of six predefined regions. was used to measure mean cortical florbetapir PET binding. Cortical-to-pontine standard-uptake value ratios were used to characterise the cross-sectional accumulation of fibrillar Aβ deposition in carriers and non-carriers with regression analysis and to estimate the trajectories of fibrillar Aβ deposition.
We enrolled a cohort of 11 symptomatic individuals, 19 presymptomatic mutation carriers, and 20 asymptomatic non-carriers, ranging in age from 20 to 56 years. There was greater florbetapir binding in asymptomatic PSEN1 E280A mutation carriers than in age matched non-carriers. Fibrillar Aβ began to accumulate in PSEN 1E280A mutation carriers at a mean age of 28·2 years (95% CI 27·3–33·4), about 16 years and 21 years before the predicted median ages at mild cognitive impairment and dementia onset, respectively. 18F florbetapir binding rose steeply over the next 9·4 years and plateaued at a mean age of 37·6 years (95% CI 35·3–40·2), about 6 and 11 years before the expected respective median ages at mild cognitive impairment and dementia onset. Prominent florbetapir binding was seen in the anterior and posterior cingulate, precuneus, and parietotemporal and frontal grey matter, as well as in the basal ganglia. Binding in the basal ganglia was not seen earlier or more prominently than in other regions.
These findings contribute to the understanding of preclinical familial Alzheimer’s disease and help set the stage for assessment of amyloid-modifying treatments in the prevention of familial Alzheimer’s disease.
Avid Radiopharmaceuticals, Banner Alzheimer’s Foundation, Nomis Foundation, Anonymous Foundation, Forget Me Not Initiative, Colciencias, National Institute on Aging, and the State of Arizona.
Copy number variations (CNVs) are genomic regions that have added (duplications) or deleted (deletions) genetic material. They may overlap genes affecting their function and have been shown to be associated with disease. We previously investigated the role of CNVs in late-onset Alzheimer's disease (AD) and mild cognitive impairment using Alzheimer’s Disease Neuroimaging Initiative (ADNI) and National Institute of Aging-Late Onset AD/National Cell Repository for AD (NIA-LOAD/NCRAD) Family Study participants, and identified a number of genes overlapped by CNV calls. To confirm the findings and identify other potential candidate regions, we analyzed array data from a unique cohort of 1617 Caucasian participants (1022 AD cases and 595 controls) who were clinically characterized and whose diagnosis was neuropathologically verified. All DNA samples were extracted from brain tissue. CNV calls were generated and subjected to quality control (QC). 728 cases and 438 controls who passed all QC measures were included in case/control association analyses including candidate gene and genome-wide approaches. Rates of deletions and duplications did not significantly differ between cases and controls. Case-control association identified a number of previously reported regions (CHRFAM7A, RELN and DOPEY2) as well as a new gene (HLA-DRA). Meta-analysis of CHRFAM7A indicated a significant association of the gene with AD and/or MCI risk (P = 0.006, odds ratio = 3.986 (95% confidence interval 1.490–10.667)). A novel APP gene duplication was observed in one case sample. Further investigation of the identified genes in independent and larger samples is warranted.
Alzheimer’s disease (AD) is associated with characteristic and progressive reductions in flourodeoxyglucose positron emission tomography (FDG PET) measurements of the regional cerebral metabolic rate for glucose. These reductions begin years before the onset of symptoms, are correlated with clinical severity, and may help predict an affected patient’s clinical course and neuropathological diagnosis. Like several other AD biomarkers, FDG PET has the potential to accelerate the evaluation of these treatments, particularly in the earliest clinical and preclinical stages. This article considers FDG PET’s role in the detection and tracking of AD, its emerging roles in the evaluation of disease-slowing treatments, some of the issues involved in the acquisition, analysis, and interpretation of FDG PET data, and the evidence needed to help qualify FDG PET and other biomarkers for use in the accelerated approval of AD-slowing treatments. It recommends scientific strategies and public policies to further establish the role of FDG PET and other AD biomarkers in therapeutic trials and find demonstrably effective disease-modifying and presymptomatic AD treatments as quickly as possible.
Alzheimer’s disease; brain imaging; biomarkers; clinical trials; positron emission tomography; magnetic resonance imaging; cerebrospinal fluid; dementia; mild cognitive impairment; preclinical; presymptomatic; treatment; prevention
A number of functional magnetic resonance imaging (fMRI) studies reported the existence of default mode network (DMN) and its disruption due to the presence of a disease such as Alzheimer’s disease (AD). In this current investigation, firstly, we used the independent component analysis (ICA) technique to confirm the DMN difference between patients with AD and normal control (NC) reported in previous studies. Consistent with previous studies, the decreased resting-state functional connectivity of DMN in AD was identified in posterior cingulated cortex (PCC), medial prefrontal cortex (MPFC), inferior parietal cortex (IPC), inferior temporal cortex (ITC) and hippocampus (HC). Moreover, we introduced Bayesian Network (BN) to study the effective connectivity of DMN and the difference between AD and NC. Compared the DMN effective connectivity in AD to the one in NC using a non-parametric random permutation test, we found that connections from left HC to left IPC, left ITC to right HC, right HC to left IPC, to MPFC and to PCC were all lost. In addition, in AD group, the connection directions between right HC and left HC, between left HC and left ITC, and between right IPC and right ITC were opposite to those in NC group. The connections of right HC to other regions, except left HC, within the BN were all statistically in-distinguishable from 0, suggesting an increased right hippocampal pathological and functional burden in AD. The altered effective connectivity in patients with AD may reveal more characteristics of the disease and may serve as a potential biomarker.
biomarker; effective connectivity; functional connectivity; resting state; fMRI
Down syndrome appears to be associated with a virtually certain risk of fibrillar amyloid-β (Aβ) pathology by the age of 40 and a very high risk of dementia at older ages. The positron emission tomography (PET) ligand florbetapir F18 has been shown to characterize fibrillar Aβ in the living human brain and to provide a close correlation with subsequent Aβ neuropathology in individuals proximate to and after the end of life. The extent to which the most frequently used PET ligands can be used to detect fibrillar Aβ in patients with Down syndrome remains to be determined.
To characterize PET estimates of fibrillar Aβ burden in a Down syndrome patient very close to the end of life and to compare them with neuropathologic assessment made after his death.
With the family’s informed consent, florbetapir PET was used to study a 55-year-old Down syndrome patient with Alzheimer disease near the end of life; his brain was donated for neuropathologic assessment when he died 14 days later. Visual ratings of cerebral florbetapir uptake were performed by trained readers who were masked to the patient’s diagnosis as part of a larger study, and an automated algorithm was used to characterize regional-to-cerebellar standard uptake value ratios in 6 cerebral regions of interest. Neuropathologic assessments were performed masked to the patient’s diagnosis or PET measurements.
Visual ratings and automated analyses of the PET image revealed a heavy fibrillar Aβ burden in cortical, striatal, and thalamic regions, similar to that reported for patients with late-onset Alzheimer disease. This matched neuropathologic findings of frequent neuritic and diffuse plaques, as well as frequent amyloid angiopathy, except for neuropathologically demonstrated frequent cerebellar diffuse plaques and amyloid angiopathy that were not detected by the PET scan.
Florbetapir PET can be used to detect increased cerebral-to-cerebellar fibrillar Aβ burden in a Down syndrome patient with Alzheimer disease, even in the presence of frequent amyloid angiopathy and diffuse plaques in the cerebellum. Additional studies are needed to determine the extent to which PET could be used to detect and to track fibrillar Aβ and to evaluate investigational Aβ-modifying treatments in the presymptomatic and symptomatic stages of Alzheimer disease.
This paper responds to Thompson and Holland (2011), who challenged our tensor-based morphometry (TBM) method for estimating rates of brain changes in serial MRI from 431 subjects scanned every 6 months, for 2 years. Thompson and Holland noted an unexplained jump in our atrophy rate estimates: an offset between 0-6 months that may bias clinical trial power calculations. We identified why this jump occurs and propose a solution. By enforcing inverse-consistency in our TBM method, the offset dropped from 1.4% to 0.28%, giving plausible anatomical trajectories. Transitivity error accounted for the minimal remaining offset. Drug trial sample size estimates with the revised TBM-derived metrics are highly competitive with other methods, though higher than previously reported sample size estimates by a factor of 1.6 to 2.4. Importantly, estimates are far below those given in the critique. To demonstrate a 25% slowing of atrophic rates with 80% power, 62 AD and 129 MCI subjects would be required for a 2-year trial, and 91 AD and 192 MCI subjects for a 1-year trial.
The Functional Activities Questionnaire (FAQ) and Alzheimer’s Disease Assessment Scale – cognitive subscale (ADAS-cog) are frequently-used indices of cognitive decline in Alzheimer’s disease (AD). The goal of this study was to compare FDG-PET and clinical measurements in a large sample of elderly subjects with memory disturbance. We examined relationships between glucose metabolism in FDG-PET regions of interest (FDG-ROIs), and ADAS-cog and FAQ scores in AD and mild cognitive impairment (MCI) patients enrolled in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Low glucose metabolism at baseline predicted subsequent ADAS-cog and FAQ decline. In addition, longitudinal glucose metabolism decline was associated with concurrent ADAS-cog and FAQ decline. Additionally, a power analysis revealed that FDG-ROI values have greater statistical power than ADAS-cog to detect attenuation of cognitive decline in AD and MCI patients. Glucose metabolism is a sensitive measure of change in cognition and functional ability in AD and MCI, and has value in predicting future cognitive decline.
FDG-PET; Alzheimer’s disease; Mild Cognitive Impairment
Aβ (amyloid beta peptide) is an important contributor to Alzheimer’s disease (AD). We modeled Aβ toxicity in yeast by directing the peptide to the secretory pathway. A genome-wide screen for toxicity modifiers identified the yeast homolog of phosphatidylinositol binding clathrin assembly protein (PICALM) and other endocytic factors connected to AD whose relationship to Aβ was previously unknown. The factors identified in yeast modified Aβ toxicity in glutamatergic neurons of Caenorhabditis elegans and in primary rat cortical neurons. In yeast, Aβ impaired the endocytic trafficking of a plasma membrane receptor, which was ameliorated by endocytic pathway factors identified in the yeast screen. These links between Aβ, endocytosis, and human AD risk factors can be ascertained using yeast as a model system.
There is an urgent need to find effective presymptomatic Alzheimer’s disease (AD) treatments that reduce the risk of AD symptoms or prevent them completely. It currently takes too many healthy people, too much money and too many years to evaluate the range of promising presymptomatic treatments using clinical endpoints. We have used brain imaging and other measurements to track some of the earliest changes associated with the predisposition to AD. We have proposed the Alzheimer’s Prevention Initiative (API) to evaluate investigational amyloid-modifying treatments in healthy people who, based on their age and genetic background, are at the highest imminent risk of developing symptomatic AD using brain imaging, cerebrospinal fluid (CSF), and cognitive endpoints. In one trial, we propose to study AD-causing presenilin 1 [PS1] mutation carriers from the world’s largest early-onset AD kindred in Antioquia, Colombia, close to their estimated average age at clinical onset. In another trial, we propose to study apolipoprotein E (APOE)ε4 homozygotes (and possibly heterozygotes) close to their estimated average age at clinical onset. The API has several goals: 1) to evaluate investigational AD-modifying treatments sooner than otherwise possible; 2) to determine the extent to which the treatment’s brain imaging and other biomarker effects predict a clinical benefit—information needed to help qualify biomarker endpoints for use in pivotal prevention trials; 3) to provide a better test of the amyloid hypothesis than clinical trials in symptomatic patients, when these treatments may be too little too late to exert their most profound effect; 4) to establish AD prevention registries needed to support these and other presymptomatic AD trials; and 5) to give those individuals at highest imminent risk of AD symptoms access to the most promising investigational treatments in clinical trials.
brain imaging; cerebral spinal fluid; biomarkers; surrogate markers; presymptomatic Alzheimer’s disease; early-onset Alzheimer’s disease; late-onset Alzheimer’s disease; presenilin 1; apolipoprotein E; clinical trials
This article introduces a hypometabolic convergence index (HCI) for the assessment of Alzheimer’s disease (AD), compares it to other biological, cognitive and clinical measures, and demonstrate its promise to predict clinical decline in mild cognitive impairment (MCI) patients using data from the AD Neuroimaging Initiative (ADNI). The HCI is intended to reflect in a single measurement the extent to which the pattern and magnitude of cerebral hypometabolism in an individual’s fluorodeoxyglucose positron emission tomography (FDG PET) image corresponds to that in probable AD patients, and is generated using a fully automated voxel-based image analysis algorithm. HCIs, magnetic resonance imaging (MRI) hippocampal volume measurements, cerebrospinal fluid (CSF) assays, memory test scores, and clinical ratings were compared in 47 probable AD patients, 21 MCI patients who converted to probable AD within the next 18 months, 76 MCI patients who did not, and 47 normal controls (NCs) in terms of their ability to characterize clinical disease severity and predict conversion rates from MCI to probable AD. HCIs were significantly different in the probable AD, MCI converter, MCI stable and NC groups (p = 9e-17) and correlated with clinical disease severity. Using retrospectively characterized threshold criteria, MCI patients with either higher HCI’s or smaller hippocampal volumes had the highest hazard ratios (HRs) for 18-month progression to probable AD (7.38 and 6.34, respectively), and those with both had an even higher HR (36.72). In conclusion, the HCI, alone or in combination with certain other biomarker measurements, have the potential to help characterize AD and predict subsequent rates of clinical decline. More generally, our conversion index strategy could be applied to a range of imaging modalities and voxel-based image-analysis algorithms.
hypometabolic convergence index; Alzheimer’s disease; FDG; PET; MCI; hippocampal volume
In addition to memory deficits, attentional impairment is a common manifestation of Alzheimer’s disease (AD). The present study examines the abnormalities of attention-related functional networks in AD using resting functional MRI (fMRI) technique and evaluates the sensitivity and specificity of these networks as potential biomarkers compared to the default mode network (DMN). Group independent component analysis (Group ICA) was applied to fMRI data from 15 AD patients and 16 normal healthy elderly controls (NC) to derive the dorsal attention network (DAN) and the ventral attention network (VAN) which are respectively responsible for the endogenous attention orienting (“top-down”) process and the exogenous attention re-orienting (“bottom-up”) process. Receiver operating characteristic (ROC) curve analysis was performed for activity in core regions within each of these networks. Functional connectivity analysis revealed disrupted DAN and preserved (less impaired) VAN in AD patients compared with NC, which might indicate impairment of a “top-down” and intact “bottom-up” attentional processing mechanisms in AD. ROC curve analysis suggested that activity in the left intraparietal sulcus and left frontal eye field from DAN as well as the posterior cingulate cortex from the DMN could serve as sensitive and specific biomarkers distinguishing AD from NC.
fMRI; functional connectivity; resting state network; biomarker; sensitivity; specificity
The pathophysiological process of Alzheimer's disease (AD) is thought to begin many years before the diagnosis of AD dementia. This long “preclinical” phase of AD would provide a critical opportunity for therapeutic intervention; however, we need to further elucidate the link between the pathological cascade of AD and the emergence of clinical symptoms. The National Institute on Aging and the Alzheimer's Association convened an international workgroup to review the biomarker, epidemiological, and neuropsychological evidence, and to develop recommendations to determine the factors which best predict the risk of progression from “normal” cognition to mild cognitive impairment and AD dementia. We propose a conceptual framework and operational research criteria, based on the prevailing scientific evidence to date, to test and refine these models with longitudinal clinical research studies. These recommendations are solely intended for research purposes and do not have any clinical implications at this time. It is hoped that these recommendations will provide a common rubric to advance the study of preclinical AD, and ultimately, aid the field in moving toward earlier intervention at a stage of AD when some disease-modifying therapies may be most efficacious.
Preclinical Alzheimer's disease; Biomarker; Amyloid; Neurodegeneration; Prevention