Dynamic changes in the brain’s lateral ventricles on MRI are powerful biomarkers of disease progression in mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Ventricular measures can represent accumulation of diffuse brain atrophy with very high effect sizes. Despite having no direct role in cognition, ventricular expansion co-occurs with volumetric loss in gray and white matter structures. To better understand relationships between ventricular and cortical changes over time, we related ventricular expansion to atrophy in cognitively-relevant cortical gray matter surfaces, which are more challenging to segment. In ADNI participants, percent change in ventricular volumes at one- (N=677) and two-year (N=536) intervals was significantly associated with baseline cortical thickness and volume in the full sample controlling for age, sex, and diagnosis, and in MCI separately. Ventricular expansion in MCI was associated with thinner GM in frontal, temporal, and parietal regions affected by AD. Ventricular expansion reflects cortical atrophy in early AD, offering a useful biomarker for clinical trials of interventions to slow AD progression.
biomarkers; Alzheimer’s disease; mild cognitive impairment; brain imaging; magnetic resonance imaging (MRI); cortical; gray matter; atrophy; thickness; volume; surface area; brain structure; longitudinal
Dementia with Lewy bodies (DLB) is characterized by preserved whole brain and medial temporal lobe volumes compared to Alzheimer’s disease dementia (AD) on MRI. However, frequently coexistent AD-type pathology may influence the pattern of regional brain atrophy rates in DLB patients. We investigated the pattern and magnitude of the atrophy rates from two serial MRIs in autopsy-confirmed DLB (n=20) and mixed DLB/AD patients (n=22), compared to AD (n=30) and elderly non-demented controls (n=15), followed antemortem. DLB patients without significant AD-type pathology were characterized by lower global and regional rates of atrophy, similar to controls. The mixed DLB/AD patients displayed greater rates in the whole brain, temporo-parietal cortices, hippocampus and amygdala, and ventricle expansion, similar to AD patients. In the DLB and DLB/AD patients, the atrophy rates correlated with Braak neurofibrillary tangle stage, cognitive decline and progression of motor symptoms. Global and regional atrophy rates are associated with AD-type pathology in DLB, and can be used as biomarkers of AD progression in patients with LB pathology.
autopsy-confirmed dementia with Lewy bodies; Alzheimer’s disease; serial MRI; atrophy rate; Braak neurofibrillary tangle stage; sample size estimate
In a previous report, we proposed a method for combining multiple markers of atrophy caused by Alzheimer’s Disease (AD) into a single atrophy score that is more powerful than any one feature. We applied the method to expansion rates of the lateral ventricles, achieving the most powerful ventricular atrophy measure to date. Here, we expand our method’s application to Tensor Based Morphometry (TBM) measures. We also combine the volumetric TBM measures with previously computed ventricular surface measures into a combined atrophy score. We further show that our atrophy scores are longitudinally unbiased, with the intercept bias estimated at two orders of magnitude below the mean atrophy of control subjects at one year. Both approaches yield the most powerful biomarker of atrophy not only for ventricular measures, but for all published unbiased imaging measures to date. A two-year trial using our measures requires only 31 [22 43] AD subjects, or 56 [44 64] subjects with Mild Cognitive Impairment (MCI) to detect 25% slowing in atrophy with 80% power and 95% confidence.
Linear Discriminant Analysis; shape analysis; Tensor Based Morphometry; ADNI; lateral ventricles; Alzheimer’s Disease; mild cognitive impairment; biomarker; drug trial; machine learning
Alzheimer’s disease (AD) is characterized by cortical atrophy and disrupted anatomical connectivity, and leads to abnormal interactions between neural systems. Diffusion weighted imaging (DWI) and graph theory can be used to evaluate major brain networks, and detect signs of a breakdown in network connectivity. In a longitudinal study using both DWI and standard MRI, we assessed baseline white matter connectivity patterns in 30 subjects with mild cognitive impairment (MCI; mean age: 71.8+/−7.5 yrs; 18M/12F) from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Using both standard MRI-based cortical parcellations and whole-brain tractography, we computed baseline connectivity maps from which we calculated global “small-world” architecture measures, including mean clustering coefficient (MCC) and characteristic path length (CPL). We evaluated whether these baseline network measures predicted future volumetric brain atrophy in MCI subjects, who are at risk for developing AD, as determined by 3D Jacobian “expansion factor maps” between baseline and 6-month follow-up anatomical scans. This study suggests that DWI-based network measures may be a novel predictor of AD progression.
Graph theory; brain networks; white matter; DTI; tractography; ADNI; TBM; small worldness; connectivity
Brain connectivity is progressively disrupted in Alzheimer’s disease (AD). Here we used a seemingly unrelated regression (SUR) model to enhance the power to identify structural connections related to cognitive scores. We simultaneously solved regression equations with different predictors and used correlated errors among the equations to boost power for associations with brain networks. Connectivity maps were computed to represent the brain’s fiber networks from diffusion-weighted MRI scans of 200 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We first identified a pattern of brain connections related to clinical decline using standard regressions powered by this large sample size. As AD studies with a large number of DTI scans are rare, it is important to detect effects in smaller samples using simultaneous regression modeling like SUR. Diagnosis of MCI or AD is well known to be associated with ApoE genotype and educational level. In a subsample with no apparent associations using the general linear model, power was boosted with our SUR model--combining genotype, educational level, and clinical diagnosis.
Brain connectivity; neuroimaging genetics; HARDI tractography; seemingly unrelated regression (SUR); APOE4; multivariate analysis
Characterizing brain changes in Alzheimer’s disease (AD) is important for patient prognosis, and for assessing brain deterioration in clinical trials. In this diffusion tensor imaging study, we used a new fiber-tract modeling method to investigate white matter integrity in 50 elderly controls (CTL), 113 people with mild cognitive impairment (MCI), and 37 AD patients. After clustering tractography using an ROI atlas, we used a shortest path graph search through each bundle’s fiber density map to derive maximum density paths (MDPs), which we registered across subjects. We calculated the fractional anisotropy (FA) and mean diffusivity (MD) along all MDPs and found significant MD and FA differences between AD patients and CTL subjects as well as MD differences between CTL and late MCI subjects. MD and FA were also associated with widely used clinical scores (MMSE). As an MDP is a compact, low-dimensional representation of white matter organization, we tested the utility of DTI measures along these MDPs as features for support vector machine (SVM) based classification of AD.
ADNI; tractography; DTI; fiber tract modeling; white matter; connectivity; SVM; classification
Measures of network topology and connectivity aid the understanding of network breakdown as the brain degenerates in Alzheimer's disease (AD). We analyzed 3-Tesla diffusion-weighted images from 202 patients scanned by the Alzheimer's Disease Neuroimaging Initiative – 50 healthy controls, 72 with early- and 38 with late-stage mild cognitive impairment (eMCI/lMCI) and 42 with AD. Using whole-brain tractography, we reconstructed structural connectivity networks representing connections between pairs of cortical regions. We examined, for the first time in this context, the network's Laplacian matrix and its Fiedler value, describing the network's algebraic connectivity, and the Fiedler vector, used to partition a graph. We assessed algebraic connectivity and four additional supporting metrics, revealing a decrease in network robustness and increasing disarray among nodes as dementia progressed. Network components became more disconnected and segregated, and their modularity increased. These measures are sensitive to diagnostic group differences, and may help understand the complex changes in AD.
brain network; algebraic connectivity; Fiedler value; modularity; Alzheimer's disease
Structural MRI is widely used for investigating brain atrophy in many neurodegenerative disorders, with several research groups developing and publishing techniques to provide quantitative assessments of this longitudinal change. Often techniques are compared through computation of required sample size estimates for future clinical trials. However interpretation of such comparisons is rendered complex because, despite using the same publicly available cohorts, the various techniques have been assessed with different data exclusions and different statistical analysis models. We created the MIRIAD atrophy challenge in order to test various capabilities of atrophy measurement techniques. The data consisted of 69 subjects (46 Alzheimer's disease, 23 control) who were scanned multiple (up to twelve) times at nine visits over a follow-up period of one to two years, resulting in 708 total image sets. Nine participating groups from 6 countries completed the challenge by providing volumetric measurements of key structures (whole brain, lateral ventricle, left and right hippocampi) for each dataset and atrophy measurements of these structures for each time point pair (both forward and backward) of a given subject. From these results, we formally compared techniques using exactly the same dataset. First, we assessed the repeatability of each technique using rates obtained from short intervals where no measurable atrophy is expected. For those measures that provided direct measures of atrophy between pairs of images, we also assessed symmetry and transitivity. Then, we performed a statistical analysis in a consistent manner using linear mixed effect models. The models, one for repeated measures of volume made at multiple time-points and a second for repeated “direct” measures of change in brain volume, appropriately allowed for the correlation between measures made on the same subject and were shown to fit the data well. From these models, we obtained estimates of the distribution of atrophy rates in the Alzheimer's disease (AD) and control groups and of required sample sizes to detect a 25% treatment effect, in relation to healthy ageing, with 95% significance and 80% power over follow-up periods of 6, 12, and 24 months. Uncertainty in these estimates, and head-to-head comparisons between techniques, were carried out using the bootstrap. The lateral ventricles provided the most stable measurements, followed by the brain. The hippocampi had much more variability across participants, likely because of differences in segmentation protocol and less distinct boundaries. Most methods showed no indication of bias based on the short-term interval results, and direct measures provided good consistency in terms of symmetry and transitivity. The resulting annualized rates of change derived from the model ranged from, for whole brain: − 1.4% to − 2.2% (AD) and − 0.35% to − 0.67% (control), for ventricles: 4.6% to 10.2% (AD) and 1.2% to 3.4% (control), and for hippocampi: − 1.5% to − 7.0% (AD) and − 0.4% to − 1.4% (control). There were large and statistically significant differences in the sample size requirements between many of the techniques. The lowest sample sizes for each of these structures, for a trial with a 12 month follow-up period, were 242 (95% CI: 154 to 422) for whole brain, 168 (95% CI: 112 to 282) for ventricles, 190 (95% CI: 146 to 268) for left hippocampi, and 158 (95% CI: 116 to 228) for right hippocampi. This analysis represents one of the most extensive statistical comparisons of a large number of different atrophy measurement techniques from around the globe. The challenge data will remain online and publicly available so that other groups can assess their methods.
•We compared numerous brain atrophy measurement techniques using multiple metrics.•Each participant produced measures on the exact same dataset, blinded to disease.•A central statistical analysis using linear mixed effect models was performed.•Head to head comparisons for each region were performed using sample size estimates.•Brain and ventricle measures were more consistent across groups than for hippocampi.
Inexpensive, non-invasive tools for assessing Alzheimer-type pathophysiologies are needed. Computerized cognitive assessments are prime candidates.
Cognitively normal participants, aged 51-71, with MRI, FDG-PET, amyloid PET, CogState computerized cognitive assessment, and standard neuropsychological tests were included. We first examined the association between the CogState battery and neuroimaging measures. We then compared that association to the one between standard neuropsychological z-scores and neuroimaging.
Slower reaction times for CogState Identification and One Back, and lower memory and attention z-scores, were associated (P<.05) with FDG-PET hypometabolism. Slower time on the Groton Maze Learning Task and worse One Card Learning accuracy were associated (P<.05) with smaller hippocampal volumes. There were no associations with amyloid PET. Associations of CogState and neuropsychological z-scores with neuroimaging were small and of a similar magnitude.
CogState subtests were cross-sectionally comparable to standard neuropsychological tests in their relatively weak associations with neurodegeneration imaging markers.
Preclinical Alzheimer's disease; Neuropsychology; Computerized cognitive battery; Neuroimaging; Amyloid-beta; Hippocampal volume
Several common genetic variants influence cholesterol levels, which play a key role in overall health. Myelin synthesis and maintenance are highly sensitive to cholesterol concentrations, and abnormal cholesterol levels increase the risk for various brain diseases, including Alzheimer's disease (AD). We report significant associations between higher serum cholesterol (CHOL) levels and high-density lipoproteins (HDL) and higher fractional anisotropy in 403 young adults (23.8±2.4 years) scanned with diffusion imaging and anatomical MRI at 4 Tesla. By fitting a multi-locus genetic model within white matter areas associated with CHOL, we found that a set of 18 cholesterol-related SNPs implicated in AD risk predicted FA. We focused on the SNP with the largest individual effects - CETP (rs5882) – and found that increased G-allele dosage was associated with higher FA and lower radial and mean diffusivities in voxel-wise analyses of the whole brain. A follow-up analysis detected WM associations with rs5882 in the opposite direction in 78 older individuals (74.3±7.3 years). Cholesterol levels may influence WM integrity, and cholesterol-related genes may exert age-dependent effects.
brain structure; DTI; imaging genetics; cholesterol; development; aging
Apolipoprotein E epsilon 4 (APOE4) is a risk factor for
β-amyloid deposition in Alzheimer’s dementia. Its influence
on β-amyloid deposition in speech and language disorders, including
primary progressive aphasia (PPA), is unclear.
One hundred and thirty subjects with PPA or speech apraxia underwent
APOE genotyping and Pittsburgh compound B (PiB) PET scanning. The
relationship between APOE4 and PiB status, as well as severity and regional
distribution of PiB, was assessed.
Forty-five subjects had an APOE4 allele and 60 subjects were
PiB-positive. The odds ratio for a subject with APOE4 being PiB-positive
compared to a subject without APOE4 being PiB-positive was 10.2
(4.4–25.5, p<0.0001). APOE4 status did not influence
regional PiB distribution or severity.
APOE4 increases the risk of β-amyloid deposition in PPA and
speech apraxia, but does not influence regional β-amyloid
distribution or severity.
Apolipoprotein; Pittsburgh Compound B; primary progressive aphasia; logopenic aphasia; speech apraxia
Diseases that progress slowly are often studied by observing cohorts at different stages of disease for short periods of time. The Alzheimer’s Disease Neuroimaging Initiative (ADNI) follows elders with various degrees of cognitive impairment, from normal to impaired. The study includes a rich panel of novel cognitive tests, biomarkers, and brain images collected every six months for up to six years. The relative timing of the observations with respect to disease pathology is unknown. We propose a general semi-parametric model and iterative estimation procedure to simultaneously estimate pathologic timing and long-term growth curves. The resulting estimates of long-term progression are fine-tuned using cognitive trajectories derived from the long-term “Personnes Agées QUID” (PAQUID) study.
We demonstrate with simulations that the method can recover long-term disease trends from short-term observations. The method also estimates temporal ordering of individuals with respect to disease pathology, providing subject-specific prognostic estimates of the time until onset of symptoms. When the method is applied to ADNI data, the estimated growth curves are in general agreement with prevailing theories of the Alzheimer’s disease cascade. Other datasets with common outcome measures can be combined using the proposed algorithm.
Software to fit the model and reproduce results with the statistical software R is available as the grace package (http://mdonohue.bitbucket.org/grace/). ADNI data can be downloaded from the Laboratory of NeuroImaging (http://loni.usc.edu).
multiple outcomes; semiparametric regression; self modeling regression
Josephs et al. use a multi-modal approach to assess neuroanatomical and clinical changes over time in primary progressive apraxia of speech. They demonstrate that progressive atrophy of cortex, basal ganglia and midbrain accompanies the clinical progression, including the emergence of progressive supranuclear palsy five years post-onset in some subjects.
Primary progressive apraxia of speech is a recently described neurodegenerative disorder in which patients present with an isolated apraxia of speech and show focal degeneration of superior premotor cortex. Little is known about how these individuals progress over time, making it difficult to provide prognostic estimates. Thirteen subjects with primary progressive apraxia of speech underwent two serial comprehensive clinical and neuroimaging evaluations 2.4 years apart [median age of onset = 67 years (range: 49–76), seven females]. All underwent detailed speech and language, neurological and neuropsychological assessments, and magnetic resonance imaging, diffusion tensor imaging and 18F-fluorodeoxyglucose positron emission tomography at both baseline and follow-up. Rates of change of whole brain, ventricle, and midbrain volumes were calculated using the boundary-shift integral and atlas-based parcellation, and rates of regional grey matter atrophy were assessed using tensor-based morphometry. White matter tract degeneration was assessed on diffusion-tensor imaging at each time-point. Patterns of hypometabolism were assessed at the single subject-level. Neuroimaging findings were compared with a cohort of 20 age, gender, and scan-interval matched healthy controls. All subjects developed extrapyramidal signs. In eight subjects the apraxia of speech remained the predominant feature. In the other five there was a striking progression of symptoms that had evolved into a progressive supranuclear palsy-like syndrome; they showed a combination of severe parkinsonism, near mutism, dysphagia with choking, vertical supranuclear gaze palsy or slowing, balance difficulties with falls and urinary incontinence, and one was wheelchair bound. Rates of whole brain atrophy (1.5% per year; controls = 0.4% per year), ventricular expansion (8.0% per year; controls = 3.3% per year) and midbrain atrophy (1.5% per year; controls = 0.1% per year) were elevated (P ≤ 0.001) in all 13, compared to controls. Increased rates of brain atrophy over time were observed throughout the premotor cortex, as well as prefrontal cortex, motor cortex, basal ganglia and midbrain, while white matter tract degeneration spread into the splenium of the corpus callosum and motor cortex white matter. Hypometabolism progressed over time in almost all subjects. These findings demonstrate that some subjects with primary progressive apraxia of speech will rapidly evolve and develop a devastating progressive supranuclear palsy-like syndrome ∼ 5 years after onset, perhaps related to progressive involvement of neocortex, basal ganglia and midbrain. These findings help improve our understanding of primary progressive apraxia of speech and provide some important prognostic guidelines.
non-fluent speech; parkinsonism; progressive supranuclear palsy; disease progression; magnetic resonance imaging
Our objective was to examine associations between glucose metabolism, as measured by 18F-fluorodeoxyglucose positron emission tomography (FDG PET), and age and to evaluate the impact of carriage of an apolipoprotein E (APOE) ε4 allele on glucose metabolism and on the associations between glucose metabolism and age. We studied 806 cognitively normal (CN) and 70 amyloid-imaging-positive cognitively impaired participants (35 with mild cognitive impairment and 35 with Alzheimer’s disease [AD] dementia) from the Mayo Clinic Study of Aging, Mayo Alzheimer’s Disease Research Center and an ancillary study who had undergone structural MRI, FDG PET, and 11C-Pittsburgh compound B (PiB) PET. Using partial volume corrected and uncorrected FDG PET glucose uptake ratios, we evaluated associations of regional FDG ratios with age and carriage of an APOE ε4 allele in CN participants between the ages of 30 and 95 years, and compared those findings with the cognitively impaired participants. In region-of-interest (ROI) analyses, we found modest but statistically significant declines in FDG ratio in most cortical and subcortical regions as a function of age. We also found a main effect of APOE ε4 genotype on FDG ratio, with greater uptake in ε4 noncarriers compared with carriers but only in the posterior cingulate and/or precuneus, lateral parietal, and AD-signature meta-ROI. The latter consisted of voxels from posterior cingulate and/or precuneus, lateral parietal, and inferior temporal. In age- and sex-matched CN participants the magnitude of the difference in partial volume corrected FDG ratio in the AD-signature meta-ROI for APOE ε4 carriers compared with noncarriers was about 4 times smaller than the magnitude of the difference between age- and sex-matched elderly APOE ε4 carrier CN compared with AD dementia participants. In an analysis in participants older than 70 years (31.3% of whom had elevated PiB), there was no interaction between PiB status and APOE ε4 genotype with respect to glucose metabolism. Glucose metabolism declines with age in many brain regions. Carriage of an APOE ε4 allele was associated with reductions in FDG ratio in the posterior cingulate and/or precuneus, lateral parietal, and AD-signature ROIs, and there was no interaction between age and APOE ε4 status. The posterior cingulate and/or precuneus and lateral parietal regions have a unique vulnerability to reductions in glucose metabolic rate as a function both of age and carriage of an APOE ε4 allele.
Aging; Alzheimer’s disease; FDG positron emission tomography; Apolipoprotein E
As treatment of pre-clinical Alzheimer's disease (AD) becomes a focus of therapeutic intervention, observational research studies should recognize the overlap between imaging abnormalities associated with typical aging vs those associated with AD. Our objective was to characterize how typical aging and pre-clinical AD blend together with advancing age in terms of neurodegeneration and b-amyloidosis.
We measured age-specific frequencies of amyloidosis and neurodegeneration in 985 cognitively normal subjects age 50 to 89 from a population-based study of cognitive aging. Potential participants were randomly selected from the Olmsted County, Minnesota population by age- and sex-stratification and invited to participate in cognitive evaluations and undergo multimodality imaging. To be eligible for inclusion, subjects must have been judged clinically to have no cognitive impairment and have undergone amyloid PET, FDG PET and MRI. Imaging studies were obtained from March 2006 to December 2013. Amyloid positive/negative status (A+/A−) was determined by amyloid PET using Pittsburgh Compound B. Neurodegeneration positive/negative status (N+/N−) was determined by an AD-signature FDG PET measure and/or hippocampal volume on MRI. We labeled subjects positive or negative for neurodegeneration (FDG PET or MRI) or amyloidosis by using cutpoints defined such that 90% of 75 clinically diagnosed AD dementia subjects were categorized as abnormal. APOE genotype was assessed using DNA extracted from blood. Every individual was assigned to one of four groups: A−N−, A+N−, A−N+, or A+N+. Age specific frequencies of the 4 A/N groups were determined cross-sectionally using multinomial regression models. Associations with APOE ε4 and sex effects were evaluated by including these covariates in the multinomial models.
The population frequency of A−N− was 100% (n=985) at age 50 and declined thereafter. The frequency of A+N− increased to a maximum of 28% (95% CI, 24%-32%) at age 74 then decreased to 17% (95% CI, 11%-25%) by age 89. A−N+ increased from age 60 onward reaching a frequency of 24% (95% CI, 16%-34%) by age 89. A+N+ increased from age 65 onward reaching a frequency of 42% (95% CI, 31%-52%) by age 89. A+N− and A+N+ were more frequent in APOE ε4 carriers. A+N+ was more, and A+N− less frequent in men.
Accumulation of A/N imaging abnormalities is nearly inevitable by old age yet people are able to remain cognitively normal despite these abnormalities. . The multinomial models suggest the A/N frequency trends by age are modified by APOE ε4 , which increases risk for amyloidosis, and male sex, which increases risk for neurodegeneration. Changing A/N frequencies with age suggest that individuals may follow different pathophysiological sequences.
National Institute on Aging; Alexander Family Professorship of Alzheimer's Disease Research.
Cognitive aging; Brain aging; Amyloid imaging; Alzheimer disease; Brain atrophy and Alzheimer disease; FDG PET and Alzheimer disease
To investigate clinical, imaging, and pathologic associations of the cingulate island sign (CIS) in dementia with Lewy bodies (DLB).
We retrospectively identified and compared patients with a clinical diagnosis of DLB (n = 39); patients with Alzheimer disease (AD) matched by age, sex, and education (n = 39); and cognitively normal controls (n = 78) who underwent 18F-fluorodeoxyglucose (FDG) and C11 Pittsburgh compound B (PiB)-PET scans. Among these patients, we studied those who came to autopsy and underwent Braak neurofibrillary tangle (NFT) staging (n = 10).
Patients with a clinical diagnosis of DLB had a higher ratio of posterior cingulate to precuneus plus cuneus metabolism, cingulate island sign (CIS), on FDG-PET than patients with AD (p < 0.001), a finding independent of β-amyloid load on PiB-PET (p = 0.56). Patients with CIS positivity on visual assessment of FDG-PET fit into the group of high- or intermediate-probability DLB pathology and received clinical diagnosis of DLB, not AD. Higher CIS ratio correlated with lower Braak NFT stage (r = −0.96; p < 0.001).
Our study found that CIS on FDG-PET is not associated with fibrillar β-amyloid deposition but indicates lower Braak NFT stage in patients with DLB. Identifying biomarkers that measure relative contributions of underlying pathologies to dementia is critical as neurotherapeutics move toward targeted treatments.
A subset of patients with Alzheimer’s disease (AD) present with early and prominent language deficits. It is unclear whether the burden of underlying β-amyloid pathology is associated with language or general cognitive impairment in these subjects.
Here, we assess the relationship between cortical β-amyloid burden on [11C]Pittsburgh compound B (PiB) PET and performance on the Montreal Cognitive Assessment (MoCA), the Wechsler Memory Scale-Third Edition (WMS-III), the Boston Naming Test (BNT), and the Western Aphasia Battery (WAB) using regression and correlation analyses in subjects presenting with aphasia that showed β-amyloid deposition on PiB PET.
The global PiB ratio was inversely correlated with MoCA (p = 0.02) and the WMS-III Visual Reproduction (VR) subtest (VR I, p = 0.02; VR II, p = 0.04). However, the correlations between PiB ratio, BNT (p = 0.13), WAB aphasia quotient (p = 0.11), and WAB repetition scores (p = 0.34) were not significant.
This study demonstrates that an increased cortical β-amyloid burden is associated with cognitive impairment, but not language deficits, in AD subjects presenting with aphasia. The results suggest that β-amyloid deposition may partly contribute to impaired cognition in such patients while language dysfunction may be influenced by other pathologic mechanisms, perhaps downstream pathways of β-amyloid deposition.
Dementia; Aphasia; PET; Beta-amyloid; PiB
Widespread deposition of TAR DNA-binding protein of 43 kDa (TDP-43), a major protein inclusion commonly found in frontotemporal lobar degeneration (FTLD) and amyotrophic lateral sclerosis (ALS) can also be seen in a subset of cases with Alzheimer’s disease (AD). Some of these AD cases have TDP-43 immunoreactivity in basal ganglia (BG) and substantia nigra (SN), regions that when affected can be associated with parkinsonian signs or symptoms, or even features suggestive of frontotemporal dementia. Here, we examined the presence of clinical features of FTLD, parkinsonian signs and symptoms, and BG atrophy on MRI, in 51 pathologically confirmed AD cases (Braak neurofibrillary tangle stage IV–VI) with widespread TDP-43 deposition, with and without BG and SN involvement. All 51 cases had presented with progressive cognitive impairment with prominent memory deficits. None of the patients demonstrated early behavioral disinhibition, apathy, loss of empathy, stereotyped behavior, hyperorality, and/or executive deficits. Furthermore, TDP-43 deposition in BG or SN had no significant association with tremor (p = 0.80), rigidity (p = 0.19), bradykinesia (p = 0.19), and gait/postural instability (p = 0.39). Volumes of the BG structures were not associated with TDP-43 deposition in the BG. The present study demonstrates that TDP-43 deposition in pathologically confirmed AD cases is not associated with a clinical manifestation suggestive of FTLD, or parkinsonian features.
TDP-43; Alzheimer’s disease; Frontotemporal dementia; Parkinsonism
Davunetide (AL-108, NAP) is an eightamino acid peptide that promotes microtubule stability and decreases tau phosphorylation in pre-clinical studies. Since PSP is tightly linked to tau pathology, davunetide could be an effective treatment for PSP.The goals of this study were to evaluate the efficacy and safety of davunetide in PSP.
A phase 2/3 double-blind, parallel group, clinical trial of davunetide 30 mg or placebo (randomized 1:1) administered intranasally twice daily for 52 weeks was conducted at 48centers. Participants met modifiedNNIPPS criteria for possible or probable PSP. Co-primary endpointswere the change from baseline in PSP Rating Scale (PSPRS) and Schwab and England ADL(SEADL) scale at up to 52 weeks. Data from all individuals who received at least one dose of medication and had a post-baseline efficacy assessment were compared using a rank-based method.Secondary outcomes included the Clinical Global Impression of Change (CGIC) and the change in regional brain volumeon MRI. Clinicaltrials.gov identifier: NCT01110720.
360 participants were screened, 313 were randomized and 243 (77.6%) completed the study. There were no group differences in PSPRS (mean difference: 0.49 [95% CI: −1.5, 2.5], p = 0.72) or SEADL (1% [−2, 4%], p = 0.76) change from baseline (CFB) and mean 52 week CFB PSPRS scores were similar between the davunetide (11.3 [9.8,12.8]) and placebo groups (10.9 [9.1, 13.0]). There wereno differences in any of the secondary or exploratory endpoints. There were 11deaths in the davunetide group and tenin the placebo group. There were more nasal adverse events in the davunetide group.
Davunetide is well tolerated but is not an effective treatment for PSP. Clinical trials of disease modifying therapy are feasible in PSP and should be pursued with other promising tau-directed therapies.
Our primary objective was to compare the performance of unaccelerated vs. accelerated structural MRI for measuring disease progression using serial scans in Alzheimer’s disease (AD).
We identified cognitively normal (CN), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI) and AD subjects from all available Alzheimer’s Disease Neuroimaging Initiative (ADNI) subjects with usable pairs of accelerated and unaccelerated scans. There were a total of 696 subjects with baseline and 3 month scans, 628 subjects with baseline and 6 month scans and 464 subjects with baseline and 12 month scans available. We employed the Symmetric Diffeomorphic Image Normalization method (SyN) for normalization of the serial scans to obtain Tensor Based Morphometry (TBM) maps which indicate the structural changes between pairs of scans. We computed a TBM-SyN summary score of annualized structural changes over 31 regions of interest (ROIs) that are characteristically affected in AD. TBM-SyN scores were computed using accelerated and unaccelerated scan pairs and compared in terms of agreement, group-wise discrimination, and sample size estimates for a hypothetical therapeutic trial.
We observed a number of systematic differences between TBM-SyN scores computed from accelerated and unaccelerated pairs of scans. TBM-SyN scores computed from accelerated scans tended to have overall higher estimated values than those from unaccelerated scans. However, the performance of accelerated scans was comparable to unaccelerated scans in terms of discrimination between clinical groups and sample sizes required in each clinical group for a therapeutic trial. We also found that the quality of both accelerated vs. unaccelerated scans were similar.
Accelerated scanning protocols reduce scan time considerably. Their group-wise discrimination and sample size estimates were comparable to those obtained with unaccelerated scans. The two protocols did not produce interchangeable TBM-SyN estimates, so it is arguably important to use either accelerated pairs of scans or unaccelerated pairs of scans throughout the study duration.
To determine antemortem MRI findings associated with microinfarcts at autopsy.
Patients with microinfarcts (n = 22) and patients without microinfarcts (n = 44) who underwent antemortem MRI were identified from a dementia clinic–based, population–based, and community clinic–based autopsy cohort. The microinfarct and no-microinfarct groups were matched on age at MRI, age at death, sex, APOE status, Mini-Mental State Examination score, and pathologic diagnosis of Alzheimer disease. Brain infarcts were assessed on fluid-attenuated inversion recovery (FLAIR) MRI. White matter hyperintensities on FLAIR MRI and hippocampal volumes on T1-weighted MRI were quantified using automated methods. A subset of subjects with microinfarcts (n = 15) and a matched group of subjects without microinfarcts (n = 15) had serial T1-weighted MRIs and were included in an analysis of global and regional brain atrophy rates using automated methods.
The presence of cortical (p = 0.03) and subcortical (p = 0.02) infarcts on antemortem MRI was associated with presence of microinfarcts at autopsy. Higher numbers of cortical (p = 0.05) and subcortical (p = 0.03) infarcts on antemortem MRI were also associated with presence of microinfarcts. Presence of microinfarcts was not associated with white matter hyperintensities and cross-sectional hippocampal volume on antemortem MRI. Whole-brain and regional precuneus, motor, and somatosensory atrophy rates were higher in subjects with microinfarcts compared to subjects without microinfarcts.
Microinfarcts increase brain atrophy rates independent of Alzheimer disease pathology. Association between microinfarct pathology and macroinfarcts on MRI suggests either common risk factors or a shared pathophysiology and potentially common preventive targets.
We evaluated the relationship of amyloid, seen on Pittsburgh compound B (PiB)-PET, and metabolism, seen on [18F]-fluorodeoxyglucose (FDG)-PET, in normal subjects to better understand pathogenesis and biomarker selection in presymptomatic subjects.
Normal participants (aged 70–95 years; 600 with PiB-PET, FDG-PET, and MRI) were included. We performed a cross-sectional evaluation and subcategorized participants into amyloid-negative (<1.4), high-normal (1.4–1.5), positive (1.5–2.0), and markedly positive (>2.0) PiB standardized uptake value ratio groups representing different levels of amyloid brain load. Associations with metabolism were assessed in each group. Relationships with APOE ε4 carriage were evaluated.
Hypometabolism in “Alzheimer disease (AD)-signature” regions was strongly associated with PiB load. Hypometabolism was greater with more positive PiB levels. Additional, more-diffuse cortical hypometabolism was also found to be associated with PiB, although less so. No hypermetabolism was seen in any subset. No significant incremental hypometabolism was seen in APOE-positive vs -negative subjects.
Hypometabolism in PiB-positive, cognitively normal subjects in a population-based cohort occurs in AD-signature cortical regions and to a lesser extent in other cortical regions. It is more pronounced with higher amyloid load and supports a dose-dependent association. The effect of APOE ε4 carriage in this group of subjects does not appear to modify their hypometabolic “AD-like” neurodegeneration. Consideration of hypometabolism associated with amyloid load may aid trials of AD drug therapy.
Proton magnetic resonance spectroscopy (1H-MRS) is sensitive to early neurodegenerative processes associated with Alzheimer's disease (AD). Although 1H-MRS metabolite ratios of N-acetyl aspartate (NAA)/creatine (Cr), NAA/myoinositol (mI), and mI/Cr measured in the posterior cingulate gyrus reveal evidence of disease progression in AD, pathologic underpinnings of the 1H-MRS metabolite changes in AD are unknown. Pathologically diagnosed human cases ranging from no likelihood to high likelihood AD (n = 41, 16 females and 25 males) who underwent antemortem 1H-MRS of the posterior cingulate gyrus at 3 tesla were included in this study. Immunohistochemical evaluation was performed on the posterior cingulate gyrus using antibodies to synaptic vesicles, hyperphosphorylated tau (pTau), neurofibrillary tangle conformational-epitope (cNFT), amyloid-β, astrocytes, and microglia. The slides were digitally analyzed using Aperio software, which allows neuropathologic quantification in the posterior cingulate gray matter. MRS and pathology associations were adjusted for time from scan to death. Significant associations across AD and control subjects were found between reduced synaptic immunoreactivity and both NAA/Cr and NAA/mI in the posterior cingulate gyrus. Higher pTau burden was associated with lower NAA/Cr and NAA/mI. Higher amyloid-β burden was associated with elevated mI/Cr and lower NAA/mI ratios, but not with NAA/Cr. 1H-MRS metabolite levels reveal early neurodegenerative changes associated with AD pathology. Our findings support the hypothesis that a decrease in NAA/Cr is associated with loss of synapses and early pTau pathology, but not with amyloid-β or later accumulation of cNFT pathology in the posterior cingulate gyrus. In addition, elevation of mI/Cr is associated with the occurrence of amyloid-β plaques in AD.
Alzheimer's disease; digital microscopy; magnetic resonance spectroscopy; neuropathology; posterior cingulate; tau