The objective of this study was to evaluate the relationship of amyloid burden, as assessed by florbetapir F 18 (18F-AV-45) amyloid PET, and cognition in healthy older control subjects (HC). Seventy-eight HC subjects were assessed with a brief cognitive test battery and PET imaging with florbetapir F 18. A standard uptake value ratio (SUVr) was computed for mean data from six cortical regions using a whole cerebellum reference region. Scans were also visually rated as amyloid positive (Aβ+) or amyloid negative (Aβ−) by three readers. Higher SUVr correlated with lower immediate memory (r=−0.33; p=0.003) and delayed recall scores (r=−0.25; p=0.027). Performance on immediate recall was also lower in the visually rated Aβ+ compared to Aβ− HC (p=0.04), with a similar trend observed in delayed recall (p=0.06). These findings support the hypothesis that higher amyloid burden is associated with lower memory performance among clinically normal older subjects. Longitudinal follow-up is ongoing to determine whether florbetapir F 18 may also predict subsequent cognitive decline.
Structure learning of Bayesian Networks (BNs) is an important topic in machine learning. Driven by modern applications in genetics and brain sciences, accurate and efficient learning of large-scale BN structures from high-dimensional data becomes a challenging problem. To tackle this challenge, we propose a Sparse Bayesian Network (SBN) structure learning algorithm that employs a novel formulation involving one L1-norm penalty term to impose sparsity and another penalty term to ensure that the learned BN is a Directed Acyclic Graph (DAG)—a required property of BNs. Through both theoretical analysis and extensive experiments on 11 moderate and large benchmark networks with various sample sizes, we show that SBN leads to improved learning accuracy, scalability, and efficiency as compared with 10 existing popular BN learning algorithms. We apply SBN to a real-world application of brain connectivity modeling for Alzheimer’s disease (AD) and reveal findings that could lead to advancements in AD research.
Bayesian network; machine learning; data mining
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.
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.
Autopsy series commonly report a high percentage of coincident pathologies in demented patients, including patients with a clinical diagnosis of dementia of the Alzheimer type (DAT). However many clinical and biomarker studies report cases with a single neurodegenerative disease. We examined multimodal biomarker correlates of the consecutive series of the first 22 Alzheimer’s Disease Neuroimaging Initiative autopsies. Clinical data, neuropsychological measures, cerebrospinal fluid Aβ, total and phosphorylated tau and α-synuclein and MRI and FDG-PET scans.
Clinical diagnosis was either probable DAT or Alzheimer’s disease (AD)-type mild cognitive impairment (MCI) at last evaluation prior to death. All patients had a pathological diagnosis of AD, but only four had pure AD. A coincident pathological diagnosis of dementia with Lewy bodies (DLB), medial temporal lobe pathology (TDP-43 proteinopathy, argyrophilic grain disease and hippocampal sclerosis), referred to collectively here as MTL, and vascular pathology were present in 45.5%, 40.0% and 22.7% of these patients, respectively. Hallucinations were a strong predictor of coincident DLB (100% specificity) and a more severe dysexecutive profile was also a useful predictor of coincident DLB (80.0% sensitivity and 83.3% specificity). Occipital FDG-PET hypometabolism accurately classified coincident DLB (80% sensitivity and 100% specificity). Subjects with coincident MTL showed lower hippocampal volume.
Biomarkers can be used to independently predict coincident AD and DLB pathology, a common finding in amnestic MCI and DAT patients. Cohorts with comprehensive neuropathological assessments and multimodal biomarkers are needed to characterize independent predictors for the different neuropathological substrates of cognitive impairment.
Alzheimer’s disease; Mild cognitive impairment; CSF; MRI; Autopsy; Neuropathology; Dementia; Biomarkers; Amyloid; Tau
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.
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.
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.
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
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.
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
This study examined the large-scale connectivity among multiple resting-state networks (RSNs) in the human brain. Independent component analysis was first applied to the resting-state functional MRI (fMRI) data acquired from 12 healthy young subjects for the separation of RSNs. Four sensory (lateral and medial visual, auditory, sensory-motor) RSNs and four cognitive (default-mode, self-referential, dorsal and ventral attention) RSNs were identified. Gaussian Bayesian network (BN) learning approach was then used for the examination of the conditional dependencies among these RSNs and the construction of the network-to-network directional connectivity patterns. The BN based results demonstrated that sensory networks and cognitive networks were hierarchically organized. Specially, we found the sensory networks were highly intra-dependent and the cognitive networks were strongly intra-influenced. In addition, the results depicted dominant bottom-up connectivity from sensory networks to cognitive networks in which the self-referential and the default-mode networks might play respectively important roles in the process of resting-state information transfer and integration. The present study characterized the global connectivity relations among RSNs and delineated more characteristics of spontaneous activity dynamics.
Bayesian network; fMRI; connectivity; resting-state network; spontaneous activity
In a genome-wide association study (GWAS) of late-onset Alzheimer's disease (AD), we found an association between common haplotypes of the GAB2 gene and AD risk in carriers of the apolipoprotein E (APOE) ε4 allele, the major late-onset AD susceptibility gene. We previously proposed the use of fluorodeoxyglucose positron emission tomography (FDG-PET) measurements as a quantitative presymptomatic endophenotype, more closely related to disease risk than the clinical syndrome itself, to help evaluate putative genetic and non-genetic modifiers of AD risk. In this study, we examined the relationship between the presence or absence of the relatively protective GAB2 haplotype and PET measurements of regional-to-whole brain FDG uptake in several AD-affected brain regions in 158 cognitively normal late-middle-aged APOEε4 homozygotes, heterozygotes, and non-carriers. GAB2 haplotypes were characterized using Affymetrix Genome-Wide Human SNP 6.0 Array data from each of these subjects. As predicted, the possibly protective GAB2 haplotype was associated with higher regional-to-whole brain FDG uptake in AD-affected brain regions in APOEε4 carriers. While additional studies are needed, this study supports the association between the possibly protective GAB2 haplotype and the risk of late-onset AD in APOEε4 carriers. It also supports the use of brain-imaging endophenotypes to help assess possible modifiers of AD risk.
Alzheimer's disease; fluorodeoxyglucose positron emission tomography
Fluorodeoxyglucose positron emission tomography (FDG-PET) studies report characteristic patterns of cerebral hypometabolism in probable Alzheimer's disease (pAD) and amnestic mild cognitive impairment (aMCI). This study aims to characterize the consistency of regional hypometabolism in pAD and aMCI patients enrolled in the AD Neuroimaging Initiative (ADNI) using statistical parametric mapping (SPM) and bootstrap resampling, and to compare bootstrap based reliability index to the commonly used type-I error approach with or without correction for multiple comparisons. Batched SPM5 was run for each of 1,000 bootstrap iterations to compare FDG-PET images from 74 pAD and 142 aMCI patients, respectively, to 82 normal controls. Maps of the hypometabolic voxels detected for at least a specific percentage of times over the 1000 runs were examined and compared to an overlap of the hypometabolic maps obtained from 3 randomly partitioned independent sub-datasets. The results from the bootstrap derived reliability of regional hypometabolism in the overall data set were similar to that observed in each of the three non-overlapping sub-sets using family-wise error. Strong but non-linear association was found between the bootstrap based reliability index and the type-I error. For threshold p=0.0005, pAD was associated with extensive hypometabolic voxels in the posterior cingulate/precuneus and parietotemporal regions with reliability between 90% and 100%. Bootstrap analysis provides an alternative to the parametric family-wise error approach used to examine consistency of hypometabolic brain voxels in pAD and aMCI patients. These results provide a foundation for the use of bootstrap analysis characterize statistical ROIs or search regions in both cross-sectional and longitudinal FDG PET studies. This approach offers promise in the early detection and tracking of AD, the evaluation of AD-modifying treatments, and other biologically or clinical important measurements using brain images and voxel-based data analysis techniques.
Alzheimer's Disease; MCI; FDG PET; Reproducibility of Results; Reliability; Bootstrap Resampling; Familywise Error; SPM
Apolipoprotein E ε4 (APOEε4) allele carrier status has been well established as a risk factor for developing Alzheimer’s disease. However, the specific influence of APOEε4 allele status on cognitive and functional rates of decline in MCI is poorly understood. We examine the prospective association of APOEε4 allele status on measures of cognitive and functional decline in subjects with amnestic Mild Cognitive Impairment (aMCI).
516 aMCI participants aged 55 to 90 who received placebo or Vitamin E from the Alzheimer’s Disease Cooperative Study’s MCI treatment trial were evaluated. During the 36 month study period, neurocognitive and functional measures were collected. These measures were assessed over time for change and association with APOEε4 status. Generalized Estimating Equations were performed to model each outcome measure over the study period.
APOEε4 status had a significant impact on cognitive and functional decline on multiple measures; those who were APOEε4 positive had significantly more rapid decline in performance on all cognitive and functional measures except Number Cancellation and Maze tracing (p<0.05). The greatest decline was seen in global measures of cognition and function including the Clinical Diagnostic Rating scale, followed by the MMSE, Global Deterioration scale, and the ADAS-cog.
These findings demonstrate that APOEε4 genotype is predictive of increased general rates of decline with global measures of cognition and function most affected. With accelerated declines in common clinical trial primary efficacy measures, APOEε4 status needs to be accounted for in treatment trials of mild cognitive impairment.
All Cognitive Disorders/Dementia; MCI (mild cognitive impairment); Alzheimer's disease; Risk factors in epidemiology; All genetics
Alzheimer's disease (AD) is characterized by specific and progressive reductions in fluorodeoxyglucose positron emission tomography (FDG PET) measurements of the cerebral metabolic rate for glucose (CMRgl), some of which may precede the onset of symptoms. In this report, we describe twelve-month CMRgl declines in 69 probable AD patients, 154 amnestic mild cognitive impairment (MCI) patients, and 79 cognitively normal controls (NCs) from the AD Neuroimaging Initiative (ADNI) using statistical parametric mapping (SPM). We introduce the use of an empirically predefined statistical region-of-interest (sROI) to characterize CMRgl declines with optimal power and freedom from multiple comparisons, and we estimate the number of patients needed to characterize AD-slowing treatment effects in multi-center randomized clinical trials (RCTs). The AD and MCI groups each had significant twelve-month CMRgl declines bilaterally in posterior cingulate, medial and lateral parietal, medial and lateral temporal, frontal and occipital cortex, which were significantly greater than those in the NC group and correlated with measures of clinical decline. Using sROIs defined based on training sets of baseline and follow-up images to assess CMRgl declines in independent test sets from each patient group, we estimate the need for 66 AD patients or 217 MCI patients per treatment group to detect a 25% AD-slowing treatment effect in a twelve-month, multi-center RCT with 80% power and two-tailed alpha=0.05, roughly one-tenth the number of the patients needed to study MCI patients using clinical endpoints. Our findings support the use of FDG PET, brain-mapping algorithms and empirically pre-defined sROIs in RCTs of AD-slowing treatments.
The extent to which the apolipoprotein E (APOE) ε4 allele is a susceptibility gene for late-onset Alzheimer's disease (AD) in Latino individuals continues to be clarified. In this study, fluorodeoxyglucose positron emission tomography (PET) was used to investigate whether regional reductions in the cerebral metabolic rate for glucose (CMRgl) previously found in cognitively normal late-middle-aged APOE ε4 carriers extends to members of the Latino Mexican-American community.
A brain mapping algorithm (SPM5) was used to compare cross-sectional regional CMRgl in Latino APOE ε4 carriers versus noncarriers.
11 APOE ε4 carriers and 16 noncarriers from Arizona's Latino community (mean age 54.6±6.4 years) matched for sex, mean age and educational level, and who were predominantly of self-designated Mexican origin.
Participant groups had similar distributions for age, gender, education, family history of dementia, clinical ratings and neuropsychological test scores. Latino APOE ε4 carriers had lower CMRgl than the noncarriers in posterior cingulate, precuneus and parietal regions previously found to be preferentially affected in AD patients and cognitively normal non-Latino APOE ε4 carriers. Additionally, the Latino APOE ε4 carriers had lower CMRgl in middle and anterior cingulate cortex, hippocampus and thalamus.
This study provides support for the relationship between APOE ε4 and risk of AD in Latinos. It illustrates the role of PET as a presymptomatic endophenotype for the assessment of AD risk factors, and supports the inclusion of Latino APOE ε4 carriers in proof-of-concept studies using FDG PET to evaluate promising presymptomatic treatments in cognitively normal carriers of this common AD susceptibility gene.
Rapid advances in neuroimaging techniques provide great potentials for study of Alzheimer’s disease (AD). Existing findings have shown that AD is closely related to alteration in the functional brain network, i.e., the functional connectivity between different brain regions. In this paper, we propose a method based on sparse inverse covariance estimation (SICE) to identify functional brain connectivity networks from PET data. Our method is able to identify both the connectivity network structure and strength for a large number o f brain regions with small sample sizes. We apply the proposed method to the PET data of AD, mild cognitive impairment (MCI), and normal control (NC) subjects. Compared with NC, AD shows decrease in the amount of inter-region functional connectivity within the temporal lobe especially between the area around hippocampus and other regions and increase in the amount of connectivity within the frontal lobe as well as between the parietal and occipital lobes. Also, AD shows weaker between-lobe connectivity than within-lobe connectivity and weaker between-hemisphere connectivity, compared with NC. In addition to being a method for knowledge discovery about AD, the proposed SICE method can also be used for classifying new subjects, which makes it a suitable approach for novel connectivity-based AD biomarker identification. Our experiments show that the best sensitivity and specificity our method can achieve in AD vs. NC classification are 88% and 88%, respectively.
Brain connectivity; Sparse inverse covariance; Alzheimer’s; PET; Biomarker
Noninvasive MRI biomarkers for Alzheimer's disease (AD) may enable earlier clinical diagnosis and the monitoring of therapeutic effectiveness. To assess potential neuroimaging biomarkers, the Alzheimer's Disease Neuroimaging Initiative is following normal controls (NC) and individuals with mild cognitive impairment (MCI) or AD. We applied high-throughput image analyses procedures to these data to demonstrate the feasibility of detecting subtle structural changes in prodromal AD. Raw DICOM scans (139 NC, 175 MCI, and 84 AD) were downloaded for analysis. Volumetric segmentation and cortical surface reconstruction produced continuous cortical surface maps and region-of-interest (ROI) measures. The MCI cohort was subdivided into single- (SMCI) and multiple-domain MCI (MMCI) based on neuropsychological performance. Repeated measures analyses of covariance were used to examine group and hemispheric effects while controlling for age, sex, and, for volumetric measures, intracranial vault. ROI analyses showed group differences for ventricular, temporal, posterior and rostral anterior cingulate, posterior parietal, and frontal regions. SMCI and NC differed within temporal, rostral posterior cingulate, inferior parietal, precuneus, and caudal midfrontal regions. With MMCI and AD, greater differences were evident in these regions and additional frontal and retrosplenial cortices; evidence for non-AD pathology in MMCI also was suggested. Mesial temporal right-dominant asymmetries were evident and did not interact with diagnosis. Our findings demonstrate that high-throughput methods provide numerous measures to detect subtle effects of prodromal AD, suggesting early and later stages of the preclinical state in this cross-sectional sample. These methods will enable a more complete longitudinal characterization and allow us to identify changes that are predictive of conversion to AD.
MRI; Alzheimer's disease; mild cognitive impairment; morphometry; brain imaging
To assess the ability of resting state functional magnetic resonance imaging to distinguish known risk factors for AD, we evaluated 17 cognitively normal individuals with a family history of AD and at least one copy of the apolipoprotein e4 allele compared to 12 individuals who were not carriers of the APOE4 gene and did not have a family history of AD. Blood oxygen level dependent fMRI was performed evaluating encoding-associated signal and resting state default mode network signal differences between the two risk groups. Neurocognitive testing revealed that the high risk group performed worse on category fluency testing, but the groups were equivalent on all other cognitive measures. During encoding of novel face-name pairs, there were no regions of encoding-associated BOLD activations that were different in the high risk group. Encoding-associated deactivations were greater in magnitude in the low risk group in the medial and right lateral parietal cortex, similar to findings in AD studies. The resting state DMN analysis demonstrated nine regions in the prefrontal, orbital frontal, temporal and parietal lobes that distinguished the two risk groups. Resting state DMN analysis could distinguish risk groups with an effect size of 3.35, compared to an effect size of 1.39 using encoding-associated fMRI techniques. Imaging of the resting state avoids performance related variability seen in activation fMRI, is less complicated to acquire and standardize, does not require radio-isotopes, and may be more effective at identifying functional pathology associated with AD risk compared to non-resting fMRI techniques.
fMRI; Alzheimer's disease; APOE4; default network
In mostly small single-center studies, Alzheimer’s disease (AD) is associated with characteristic and progressive reductions in fluorodeoxyglucose positron emission tomography (PET) measurements of the regional cerebral metabolic rate for glucose (CMRgl). The AD Neuroimaging Initiative (ADNI) is acquiring FDG PET, volumetric magnetic resonance imaging, and other biomarker measurements in a large longitudinal multi-center study of initially mildly affected probable AD (pAD) patients, amnestic mild cognitive impairment (aMCI) patients, who are at increased AD risk, and cognitively normal controls (NC), and we are responsible for analyzing the PET images using statistical parametric mapping (SPM). Here we compare baseline CMRgl measurements from 74 pAD patients and 142 aMCI patients to those from 82 NC, we correlate CMRgl with categorical and continuous measures of clinical disease severity, and we compare apolipoprotein E (APOE) ε4 carriers to non-carriers in each of these subject groups. In comparison with NC, the pAD and aMCI groups each had significantly lower CMRgl bilaterally in posterior cingulate, precuneus, parietotemporal and frontal cortex. Similar reductions were observed when categories of disease severity or lower Mini-Mental State Exam (MMSE) scores were correlated with lower CMRgl. However, when analyses were restricted to the pAD patients, lower MMSE scores were significantly correlated with lower left frontal and temporal CMRgl. These findings from a large, multi-site study support previous single-site findings, supports the characteristic pattern of baseline CMRgl reductions in AD and aMCI patients, as well as preferential anterior CMRgl reductions after the onset of AD dementia.
Alzheimer’s disease; MCI; MMSE; Positron Emission Tomography