The pilot European Alzheimer's Disease Neuroimaging Initiative of the European Alzheimer's Disease Consortium

BackgroundIn North America, the Alzheimer's Disease Neuroimaging Initiative (ADNI) has established a platform to track the brain changes of Alzheimer's disease. A pilot study has been carried out in Europe to test the feasibility of the adoption of the ADNI platform (pilot E-ADNI).MethodsSeven academic sites of the European Alzheimer's Disease Consortium (EADC) enrolled 19 patients with mild cognitive impairment (MCI), 22 with AD, and 18 older healthy persons by using the ADNI clinical and neuropsychological battery. ADNI compliant magnetic resonance imaging (MRI) scans, cerebrospinal fluid, and blood samples were shipped to central repositories. Medial temporal atrophy (MTA) and white matter hyperintensities (WMH) were assessed by a single rater by using visual rating scales.ResultsRecruitment rate was 3.5 subjects per month per site. The cognitive, behavioral, and neuropsychological features of the European subjects were very similar to their U.S. counterparts. Three-dimensional T1-weighted MRI sequences were successfully performed on all subjects, and cerebrospinal fluid samples were obtained from 77%, 68%, and 83% of AD patients, MCI patients, and controls, respectively. Mean MTA score showed a significant increase from controls (left, right: 0.4, 0.3) to MCI patients (0.9, 0.8) to AD patients (2.3, 2.0), whereas mean WMH score did not differ among the three diagnostic groups (between 0.7 and 0.9). The distribution of both MRI markers was comparable to matched US-ADNI subjects.ConclusionsAcademic EADC centers can adopt the ADNI platform to enroll MCI and AD patients and older controls with global cognitive and structural imaging features remarkably similar to those of the US-ADNI.     

Update on the biomarker core of the Alzheimer's Disease Neuroimaging Initiative subjects

Here, we review progress by the Penn Biomarker Core in the Alzheimer's Disease Neuroimaging Initiative (ADNI) toward developing a pathological cerebrospinal fluid (CSF) and plasma biomarker signature for mild Alzheimer's disease (AD) as well as a biomarker profile that predicts conversion of mild cognitive impairment (MCI) and/or normal control subjects to AD. The Penn Biomarker Core also collaborated with other ADNI Cores to integrate data across ADNI to temporally order changes in clinical measures, imaging data, and chemical biomarkers that serve as mileposts and predictors of the conversion of normal control to MCI as well as MCI to AD, and the progression of AD. Initial CSF studies by the ADNI Biomarker Core revealed a pathological CSF biomarker signature of AD defined by the combination of Aβ1-42 and total tau (T-tau) that effectively delineates mild AD in the large multisite prospective clinical investigation conducted in ADNI. This signature appears to predict conversion from MCI to AD. Data fusion efforts across ADNI Cores generated a model for the temporal ordering of AD biomarkers which suggests that Aβ amyloid biomarkers become abnormal first, followed by changes in neurodegenerative biomarkers (CSF tau, F-18 fluorodeoxyglucose-positron emission tomography, magnetic resonance imaging) with the onset of clinical symptoms. The timing of these changes varies in individual patients due to genetic and environmental factors that increase or decrease an individual's resilience in response to progressive accumulations of AD pathologies. Further studies in ADNI will refine this model and render the biomarkers studied in ADNI more applicable to routine diagnosis and to clinical trials of disease modifying therapies.     

The Alzheimer's Disease Neuroimaging Initiative positron emission tomography core

BackgroundThis is a progress report of the Alzheimer's Disease Neuroimaging Initiative (ADNI) positron emission tomography (PET) Core.MethodsThe Core has supervised the acquisition, quality control, and analysis of longitudinal [¹⁸F]fluorodeoxyglucose PET (FDG-PET) data in approximately half of the ADNI cohort. In an “add on” study, approximately 100 subjects also underwent scanning with [¹¹C] Pittsburgh compound B PET for amyloid imaging. The Core developed quality control procedures and standardized image acquisition by developing an imaging protocol that has been widely adopted in academic and pharmaceutical industry studies. Data processing provides users with scans that have identical orientation and resolution characteristics despite acquisition on multiple scanner models. The Core labs have used many different approaches to characterize differences between subject groups (Alzheimer's disease, mild cognitive impairment, controls), to examine longitudinal change over time in glucose metabolism and amyloid deposition, and to assess the use of FDG-PET as a potential outcome measure in clinical trials.ResultsADNI data indicate that FDG-PET increases statistical power over traditional cognitive measures, might aid subject selection, and could substantially reduce the sample size in a clinical trial. Pittsburgh compound B PET data showed expected group differences, and identified subjects with significant annual increases in amyloid load across the subject groups. The next activities of the PET core in ADNI will entail developing standardized protocols for amyloid imaging using the [¹⁸F]-labeled amyloid imaging agent AV45, which can be delivered to virtually all ADNI sites.ConclusionsADNI has demonstrated the feasibility and utility of multicenter PET studies and is helping to clarify the role of biomarkers in the study of aging and dementia.     

Early detection of Alzheimer's disease using MRI hippocampal texture

Cognitive impairment in patients with Alzheimer's disease (AD) is associated with reduction in hippocampal volume in magnetic resonance imaging (MRI). However, it is unknown whether hippocampal texture changes in persons with mild cognitive impairment (MCI) that does not have a change in hippocampal volume. We tested the hypothesis that hippocampal texture has association to early cognitive loss beyond that of volumetric changes. The texture marker was trained and evaluated using T1‐weighted MRI scans from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database, and subsequently applied to score independent data sets from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) and the Metropolit 1953 Danish Male Birth Cohort (Metropolit). Hippocampal texture was superior to volume reduction as predictor of MCI‐to‐AD conversion in ADNI (area under the receiver operating characteristic curve [AUC] 0.74 vs 0.67; DeLong test, p = 0.005), and provided even better prognostic results in AIBL (AUC 0.83). Hippocampal texture, but not volume, correlated with Addenbrooke's cognitive examination score (Pearson correlation, r = ?0.25, p < 0.001) in the Metropolit cohort. The hippocampal texture marker correlated with hippocampal glucose metabolism as indicated by fluorodeoxyglucose‐positron emission tomography (Pearson correlation, r = ?0.57, p < 0.001). Texture statistics remained significant after adjustment for volume in all cases, and the combination of texture and volume did not improve diagnostic or prognostic AUCs significantly. Our study highlights the presence of hippocampal texture abnormalities in MCI, and the possibility that texture may serve as a prognostic neuroimaging biomarker of early cognitive impairment. Hum Brain Mapp 37:1148–1161, 2016. © 2015 Wiley Periodicals, Inc .     

The Alzheimer's Disease Neuroimaging Initiative: Progress report and future plans

The Alzheimer's Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6-year research project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer's disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C-11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid β (Aβ) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C-11 Pittsburgh compound B PET, and CSF measurements of Aβ and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI-like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD.     

The Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151–3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [¹⁸F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.     

Enabling a multidisciplinary approach to the study of ageing and Alzheimer's disease: An update from the Australian Imaging Biomarkers and Lifestyle (AIBL) study

Abstract

The Australian Imaging Biomarkers and Lifestyle (AIBL) study is a longitudinal study of 1,112 volunteers from healthy, mild cognitive impairment (MCI) and Alzheimer's disease (AD) populations who are assessed at 18-month intervals in order to enable prospective research into ageing and AD. Using a multidisciplinary battery, AIBL assessments comprise the extensive study of clinical factors and cognitive function, collection of blood and cerebrospinal fluid (CSF) samples for biomarker discovery, structural and β-amyloid (Aβ) neuroimaging, and obtaining information on diet and physical activity patterns of the cohort. Now in its seventh year, AIBL is part of a substantial international effort to prospectively study the relationships between clinical characteristics and putative AD biomarkers in groups who carry different risk factors for AD. The identification of biomarkers would provide a window of opportunity to assess AD risk in individuals prior to the onset of advanced clinical symptoms, in addition to facilitating testing of therapeutic and lifestyle interventions likely to emerge within the next decade that prevent or delay symptom emergence in those at high risk for developing AD. In this paper, we present key findings from the AIBL study and discuss how they contribute to our understanding of AD pathogenesis and diagnosis.     

Characterization of a temporoparietal junction subtype of Alzheimer's disease

Alzheimer's disease (AD) subtypes have been described according to genetics, neuropsychology, neuropathology, and neuroimaging. Thirty‐one patients with clinically probable AD were selected based on perisylvian metabolic decrease on FDG‐PET. They were compared to 25 patients with a typical pattern of decreased posterior metabolism. Tree‐based machine learning was used on those 56 images to create a classifier that was subsequently applied to 207 Alzheimer's Disease Neuroimaging Initiative (ADNI) patients with AD. Machine learning was also used to discriminate between the two ADNI groups based on neuropsychological scores. Compared to AD patients with a typical precuneus metabolic decrease, the new subtype showed stronger hypometabolism in the temporoparietal junction. The classifier was able to distinguish the two groups in the ADNI population. Both groups could only be distinguished cognitively by Trail Making Test‐A scores. This study further confirms that there is more than a typical metabolic pattern in probable AD with amnestic presentation.     

The Alzheimer's Disease Neuroimaging Initiative: Annual change in biomarkers and clinical outcomes

BackgroundThe Alzheimer's Disease Neuroimaging Initiative Phase 1 (ADNI-1) is a multisite prospective study designed to examine potential cerebrospinal fluid and imaging markers of Alzheimer's disease (AD) and their relationship to cognitive change. The objective of this study was to provide a global summary of the overall results and patterns of change observed in candidate markers and clinical measures over the first 2 years of follow-up.MethodsChange was summarized for 210 normal controls, 357 mild cognitive impairment, and 162 AD subjects, with baseline and at least one cognitive follow-up assessment. Repeated measures and survival models were used to assess baseline biomarker levels as predictors. Potential for improving clinical trials was assessed by comparison of precision of markers for capturing change in hypothetical trial designs.ResultsThe first 12 months of complete data on ADNI participants demonstrated the potential for substantial advances in characterizing trajectories of change in a range of biomarkers and clinical outcomes, examining their relationship and timing, and assessing the potential for improvements in clinical trial design. Reduced metabolism and greater brain atrophy in the mild cognitive impairment at baseline are associated with more rapid cognitive decline and a higher rate of conversion to AD. Use of biomarkers as study entry criteria or as outcomes could reduce the number of participants required for clinical trials.ConclusionsAnalyses and comparisons of ADNI data strongly support the hypothesis that measurable change occurs in cerebrospinal fluid, positron emission tomography, and magnetic resonance imaging well in advance of the actual diagnosis of AD.     

Influence of magnetic field strength and image registration strategy on voxel‐based morphometry in a study of Alzheimer's disease

Multi‐centre data repositories like the Alzheimer's Disease Neuroimaging Initiative (ADNI) offer a unique research platform, but pose questions concerning comparability of results when using a range of imaging protocols and data processing algorithms. The variability is mainly due to the non‐quantitative character of the widely used structural T1‐weighted magnetic resonance (MR) images. Although the stability of the main effect of Alzheimer's disease (AD) on brain structure across platforms and field strength has been addressed in previous studies using multi‐site MR images, there are only sparse empirically‐based recommendations for processing and analysis of pooled multi‐centre structural MR data acquired at different magnetic field strengths (MFS). Aiming to minimise potential systematic bias when using ADNI data we investigate the specific contributions of spatial registration strategies and the impact of MFS on voxel‐based morphometry in AD. We perform a whole‐brain analysis within the framework of Statistical Parametric Mapping, testing for main effects of various diffeomorphic spatial registration strategies, of MFS and their interaction with disease status. Beyond the confirmation of medial temporal lobe volume loss in AD, we detect a significant impact of spatial registration strategy on estimation of AD related atrophy. Additionally, we report a significant effect of MFS on the assessment of brain anatomy (i) in the cerebellum, (ii) the precentral gyrus and (iii) the thalamus bilaterally, showing no interaction with the disease status. We provide empirical evidence in support of pooling data in multi‐centre VBM studies irrespective of disease status or MFS. Hum Brain Mapp 35:1865–1874, 2014. © 2013 Wiley Periodicals, Inc.     

Using machine learning to quantify structural MRI neurodegeneration patterns of Alzheimer's disease into dementia score: Independent validation on 8,834 images from ADNI,AIBL, OASIS,and MIRIAD databases

Biomarkers for dementia of Alzheimer's type (DAT) are sought to facilitate accurate prediction of the disease onset, ideally predating the onset of cognitive deterioration. T1‐weighted magnetic resonance imaging (MRI) is a commonly used neuroimaging modality for measuring brain structure in vivo, potentially providing information enabling the design of biomarkers for DAT. We propose a novel biomarker using structural MRI volume‐based features to compute a similarity score for the individual's structural patterns relative to those observed in the DAT group. We employed ensemble‐learning framework that combines structural features in most discriminative ROIs to create an aggregate measure of neurodegeneration in the brain. This classifier is trained on 423 stable normal control (NC) and 330 DAT subjects, where clinical diagnosis is likely to have the highest certainty. Independent validation on 8,834 unseen images from ADNI, AIBL, OASIS, and MIRIAD Alzheimer's disease (AD) databases showed promising potential to predict the development of DAT depending on the time‐to‐conversion (TTC). Classification performance on stable versus progressive mild cognitive impairment (MCI) groups achieved an AUC of 0.81 for TTC of 6 months and 0.73 for TTC of up to 7 years, achieving state‐of‐the‐art results. The output score, indicating similarity to patterns seen in DAT, provides an intuitive measure of how closely the individual's brain features resemble the DAT group. This score can be used for assessing the presence of AD structural atrophy patterns in normal aging and MCI stages, as well as monitoring the progression of the individual's brain along with the disease course.     

Imaging genomics discovery of a new risk variant for Alzheimer's disease in the postsynaptic SHARPIN gene

Molecular mechanisms underlying Alzheimer's disease (AD) are difficult to investigate, partly because diagnosis lags behind the insidious pathological processes. Therefore, identifying AD neuroimaging markers and their genetic modifiers may help study early mechanisms of neurodegeneration. We aimed to identify brain regions of the highest vulnerability to AD using a data‐driven search in the AD Neuroimaging Initiative (ADNI, n = 1,100 subjects), and further explored genetic variants affecting this critical brain trait using both ADNI and the younger UK Biobank cohort (n = 8,428 subjects). Tensor‐Based Morphometry (TBM) and Independent Component Analysis (ICA) identified the limbic system and its interconnecting white‐matter as the most AD‐vulnerable brain feature. Whole‐genome analysis revealed a common variant in SHARPIN that was associated with this imaging feature (rs34173062, p = 2.1 × 10^?10). This genetic association was validated in the UK Biobank, where it was correlated with entorhinal cortical thickness bilaterally (p = .002 left and p = 8.6 × 10^?4 right), and with parental history of AD (p = 2.3 × 10^?6). Our findings suggest that neuroanatomical variation in the limbic system and AD risk are associated with a novel variant in SHARPIN. The role of this postsynaptic density gene product in β1‐integrin adhesion is in line with the amyloid precursor protein (APP) intracellular signaling pathway and the recent genome‐wide evidence.     

Data‐driven approaches for tau‐PET imaging biomarkers in Alzheimer's disease

Previous positron emission tomography (PET) studies have quantified filamentous tau pathology using regions‐of‐interest (ROIs) based on observations of the topographical distribution of neurofibrillary tangles in post‐mortem tissue. However, such approaches may not take full advantage of information contained in neuroimaging data. The present study employs an unsupervised data‐driven method to identify spatial patterns of tau‐PET distribution, and to compare these patterns to previously published “pathology‐driven” ROIs. Tau‐PET patterns were identified from a discovery sample comprised of 123 normal controls and patients with mild cognitive impairment or Alzheimer's disease (AD) dementia from the Swedish BioFINDER cohort, who underwent [¹⁸F]AV1451 PET scanning. Associations with cognition were tested in a separate sample of 90 individuals from ADNI. BioFINDER [¹⁸F]AV1451 images were entered into a robust voxelwise stable clustering algorithm, which resulted in five clusters. Mean [¹⁸F]AV1451 uptake in the data‐driven clusters, and in 35 previously published pathology‐driven ROIs, was extracted from ADNI [¹⁸F]AV1451 scans. We performed linear models comparing [¹⁸F]AV1451 signal across all 40 ROIs to tests of global cognition and episodic memory, adjusting for age, sex, and education. Two data‐driven ROIs consistently demonstrated the strongest or near‐strongest effect sizes across all cognitive tests. Inputting all regions plus demographics into a feature selection routine resulted in selection of two ROIs (one data‐driven, one pathology‐driven) and education, which together explained 28% of the variance of a global cognitive composite score. Our findings suggest that [¹⁸F]AV1451‐PET data naturally clusters into spatial patterns that are biologically meaningful and that may offer advantages as clinical tools.     

A harmonized longitudinal biomarkers and cognition database for assessing the natural history of preclinical Alzheimer's disease from young adulthood and for designing prevention trials

IntroductionLarge longitudinal biomarkers database focusing on middle age is needed for Alzheimer's disease (AD) prevention.MethodsData for cerebrospinal fluid analytes, molecular imaging of cerebral fibrillar β-amyloid with positron emission tomography, magnetic resonance imaging–based brain structures, and clinical/cognitive outcomes were harmonized across eight AD biomarker studies. Statistical power was estimated.ResultsThe harmonized database included 7779 participants with clinical/cognitive data: 3542 were 18∼65 years at the baseline, 5865 had longitudinal cognitive data for a median of 4.7 years, 2473 participated in the cerebrospinal fluid studies (906 had longitudinal data), 2496 participated in the magnetic resonance imaging studies (1283 had longitudinal data), and 1498 participated in the positron emission tomography amyloid studies (849 had longitudinal data). The database provides adequate power for detecting early biomarker changes, and demonstrates the feasibility of AD prevention trials on middle-aged individuals.DiscussionThe harmonized database is an optimum resource to design AD prevention trials decades before symptomatic onset.     

Abnormal connectivity in the posterior cingulate and hippocampus in early Alzheimer's disease and mild cognitive impairment

BackgroundBrain imaging studies of early Alzheimer's disease (AD) have shown decreased metabolism predominantly in the posterior cingulate cortex (PCC), medial temporal lobe, and inferior parietal lobe. This study investigated functional connectivity between these regions, as well as connectivity between these regions and the whole brain.MethodsFunctional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) studies were performed in subjects with early AD, mild cognitive impairment (MCI), and normal controls.ResultsThe data indicate both decreased fiber connections and disrupted connectivity between the hippocampus and PCC in early AD. The MCI group showed reduced fiber numbers derived from PCC and hippocampus to the whole brain.ConclusionsThe fMRI and DTI results confirmed decreased connectivity from both the PCC and hippocampus to the whole brain in MCI and AD and reduction in connectivity between these two regions, which plausibly represents an early imaging biomarker for AD.     

Three presenile patients in which neuropsychological and neuroimaging examinations suggest possible progression to dementia with Lewy bodies

We report three presenile patients who were initially suspected of having Alzheimer's disease (AD) or being in the prodromal stage of AD, regardless of visuoperceptual dysfunctions in daily living, because they lacked the core features and prodromal non‐motor symptoms of dementia with Lewy bodies. Subsequently, progression to dementia with Lewy bodies was suspected based on neuropsychological and neuroimaging findings; additionally, one of the three patients suffered from visual hallucinations. Neuropsychological examinations such as subjective contours, cube copying and block design in the Wechsler Adult Intelligence Scale‐III revealed visuoperceptual dysfunction in all three patients even when other cognitive functions were rather preserved. Brain magnetic resonance imaging revealed no significant brain atrophy, including in the parieto‐occipital area and the hippocampus, while brain ¹⁸F‐fluorodeoxyglucose positron emission tomography demonstrated right dominant metabolic reductions in the occipital lobe, including the primary visual cortex, in all three patients. We suggest the possibility of progression to dementia with Lewy bodies, but not AD or posterior cortical atrophy. Regardless of the presence of core features and prodromal non‐motor symptoms, this progression is suggested when there are difficulties only in higher‐level visual processing such as subjective contours and block design in the Wechsler Adult Intelligence Scale‐III, no significant atrophy of the parieto‐occipital area and hippocampus on brain magnetic resonance imaging, and hypometabolism in the occipital lobe including the primary visual cortex on brain ¹⁸F‐fluorodeoxyglucose positron emission tomography.     

Quantitative Evidence for Neuroanatomic and Neuropsychological Markers in Dementia of the Alzheimer's Type

Meta-analytic methods were used to determine the sensitivity of neuropsychological, structural, and physiological measures to temporal-hippocampal system function in dementia of the Alzheimer's type. Effect sizes are reported for the California Verbal Learning Test, the Wechsler Memory Scale-Revised, structural (i.e., magnetic resonance imaging [MRI]), and functional (i.e., positron emission tomography [PET], single photon emission computed tomography [SPECT]) neuroimaging methods. Overall, effect sizes from MRI studies are larger than those obtained from SPECT and PET, respectively, but not as large as those obtained from the neuropsychological measures. On the basis of this finding, the neuropsychological and gross pathologic similarities between Alzheimer's disease, other dementing conditions, and mixed dementias, warrants the coupling of neuropsychological evaluation for its sensitivity with neuroimaging visualization for its specificity in improving diagnostic and differential accuracy.     

Alzheimer's disease and corticobasal degeneration presenting as corticobasal syndrome

The aim of this article is to compare patients with Alzheimer's disease (AD) pathology and corticobasal degeneration pathology (CBD) presenting as corticobasal syndrome (CBS). Clinicopathologic series was used. Five patients with AD and 11 patients with CBD were clinically diagnosed with CBS. Patients with AD pathology had an earlier age of onset than patients with CBD pathology (58 vs. 68 years, P = 0.004), but the two groups had similar disease duration and core features of CBS. Tremors were only present in CBD cases (73%, P = 0.026), but myoclonus was more common in AD than CBD (80 vs. 18%, P = 0.036). Neuropsychological testing showed similar degrees of memory impairment and attentional deficits. ^99mTc‐HMPAO SPECT imaging demonstrated parietal hypoperfusion in AD patients and frontotemporal hypoperfusion in CBD patients. AD patients with clinical CBS have similar characteristics to CBD patients. Functional brain imaging may have greater utility than the clinical and neuropsychological features in differentiating AD presenting as CBS from CBD. © 2009 Movement Disorder Society     

Biological heterogeneity in ADNI amnestic mild cognitive impairment

BackgroundPrevious work examining normal controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI) identified substantial biological heterogeneity. We hypothesized that ADNI mild cognitive impairment (MCI) subjects would also exhibit heterogeneity with possible clinical implications.MethodsADNI subjects diagnosed with amnestic MCI (n = 138) were clustered based on baseline magnetic resonance imaging, cerebrospinal fluid, and serum biomarkers. The clusters were compared with respect to longitudinal atrophy, cognitive trajectory, and time to conversion.ResultsFour clusters emerged with distinct biomarker patterns: The first cluster was biologically similar to normal controls and rarely converted to Alzheimer's disease (AD) during follow-up. The second cluster had characteristics of early Alzheimer's pathology. The third cluster showed the most severe atrophy but barely abnormal tau levels and a substantial proportion converted to clinical AD. The fourth cluster appeared to be pre-AD and nearly all converted to AD.ConclusionsSubjects with MCI who were clinically similar showed substantial heterogeneity in biomarkers.