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1.  A profile of The Clinical Course of Cognition and Comorbidity in Mild Cognitive Impairment and Dementia Study (The 4C study): two complementary longitudinal, clinical cohorts in the Netherlands 
BMC Neurology  2016;16:242.
Heterogeneous disease trajectories of mild cognitive impairment (MCI) and dementia are frequently encountered in clinical practice, but there is still insufficient knowledge to understand the reasons and mechanisms causing this heterogeneity. In addition to correlates of the disorder, patient characteristics such as their health status, social environment, comorbidities and frailty may contribute to variability in trajectories over time. The current paper outlines the study design and the study population of and provides an overview of the data collected in the Clinical Course of Cognition and Comorbidity in Mild Cognitive Impairment (4C-MCI cohort, n = 315) and Dementia (4C-Dementia cohort, n = 331) Study.
The two complementary longitudinal cohorts part of the 4C study began enrolment in March 2010. Participants were prospectively recruited from three collaborating Dutch Alzheimer Centers, with three annual follow-up assessments after baseline. Extensive neuropsychological assessments, and detailed profiling of comorbidities, health and frailty at each follow up were the key features of the 4C study. As such, the 4C study was designed to study if and how patients’ comorbidities and frailty are associated with the course of MCI and dementia measured with a comprehensive and multidimensional set of outcomes including cognition, daily functioning, quality of life, behavioral disturbances, caregiver burden, institutionalization and death and whether the effects of medical health and frailty differ between MCI and dementia stages of cognitive disorders.
Sampled in a clinical setting, the 4C study complements population-based studies on neurodegenerative disorders in terms of the type of assessment (e.g. comorbidity, frailty, and functional status were repeatedly assessed). The 4C study complements available clinical cohorts of MCI and dementia patients, because the exclusion criteria were kept to a minimum, to obtain a sample that is representative for the average patient visiting a memory clinic.
PMCID: PMC5123233  PMID: 27884130
Mild Cognitive Impairment (MCI); Dementia; Disease progression; Cognition; Comorbidity; Frailty
2.  Thinner temporal and parietal cortex is related to incident clinical progression to dementia in patients with subjective cognitive decline 
We aimed to investigate if thinner cortex of the Alzheimer's disease (AD)-signature region was related to clinical progression in patients with subjective cognitive decline (SCD).
We included 302 SCD patients with clinical follow-up (≥1 year) and three-dimensional T1 magnetic resonance imaging. We estimated AD-signature cortical thickness, consisting of nine frontal, parietal, and temporal gyri and hippocampal volume. We used Cox proportional hazard models (hazard ratios and 95% confidence intervals) to evaluate cortical thickness in relation to clinical progression to mild cognitive impairment (MCI) or dementia.
After a follow-up of the mean (standard deviation) 3 (2) years, 49 patients (16%) showed clinical progression to MCI (n = 32), AD (n = 9), or non-AD dementia (n = 8). Hippocampal volumes, thinner cortex of the AD-signature (hazard ratio [95% confidence interval], 5 [2–17]) and various AD-signature subcomponents were associated with increased risk of clinical progression. Stratified analyses showed that thinner AD-signature cortex was specifically predictive for clinical progression to dementia but not to MCI.
In SCD patients, thinner regional cortex is associated with clinical progression to dementia.
PMCID: PMC5198882  PMID: 28054027
Subjective cognitive decline; Cortical thickness; MRI; Cognitively normal; Cognitive complaint; Dementia; MCI; Alzheimer's disease cortical signature
3.  Alzheimer's disease first symptoms are age dependent: evidence from the NACC dataset 
Determining the relationship between age and Alzheimer's disease (AD) presentation is important to improve understanding and provide better patient services.
We used AD patient data (N=7815) from the National Alzheimer Coordinating Center database and multinomial logistic regression to investigate presentation age and first cognitive / behavioral symptoms.
The odds of having a non-memory first cognitive symptom (including impairment in judgment and problem solving, language and visuospatial function) increased with younger age (p<0.001, all tests). Compared with apathy/withdrawal, the odds of having depression, and “other” behavioral symptoms increased with younger age (p<0.02, both tests), whereas the odds of having psychosis and no behavioral symptom increased with older age (p<0.001, both tests).
There is considerable heterogeneity in the first cognitive / behavioral symptoms experienced by AD patients. Proportions of these symptoms change with age with patients experiencing increasing non-memory cognitive symptoms and more behavioral symptoms at younger ages.
PMCID: PMC4619185  PMID: 25916562
Alzheimer's disease; clinical neurology history; first symptoms; cognition; behavior; neuropsychology; age
4.  ABCA7 p.G215S as potential protective factor for Alzheimer's disease 
Neurobiology of Aging  2016;46:235.e1-235.e9.
Genome-wide association studies (GWASs) have been effective approaches to dissect common genetic variability underlying complex diseases in a systematic and unbiased way. Recently, GWASs have led to the discovery of over 20 susceptibility loci for Alzheimer's disease (AD). Despite the evidence showing the contribution of these loci to AD pathogenesis, their genetic architecture has not been extensively investigated, leaving the possibility that low frequency and rare coding variants may also occur and contribute to the risk of disease. We have used exome and genome sequencing data to analyze the single independent and joint effect of rare and low-frequency protein coding variants in 9 AD GWAS loci with the strongest effect sizes after APOE (BIN1, CLU, CR1, PICALM, MS4A6A, ABCA7, EPHA1, CD33, and CD2AP) in a cohort of 332 sporadic AD cases and 676 elderly controls of British and North-American ancestry. We identified coding variability in ABCA7 as contributing to AD risk. This locus harbors a low-frequency coding variant (p.G215S, rs72973581, minor allele frequency = 4.3%) conferring a modest but statistically significant protection against AD (p-value = 0.024, odds ratio = 0.57, 95% confidence interval = 0.41–0.80). Notably, our results are not driven by an enrichment of loss of function variants in ABCA7, recently reported as main pathogenic factor underlying AD risk at this locus. In summary, our study confirms the role of ABCA7 in AD and provides new insights that should address functional studies.
PMCID: PMC5024078  PMID: 27289440
Alzheimer's disease (AD); Genome-wide association studies (GWASs); ABCA7; Whole exome sequencing (WES); Whole genome sequencing (WGS); Protective variant
5.  The behavioural/dysexecutive variant of Alzheimer’s disease: clinical, neuroimaging and pathological features 
Brain  2015;138(9):2732-2749.
Relatively little is known about behavioural- and dysexecutive-predominant presentations of Alzheimer’s disease, collectively known as ‘frontal’ Alzheimer’s disease. Ossenkoppele et al. compare these two syndromes, revealing classical temporoparietal atrophy and relative sparing of frontal cortex in both, and propose that they are redefined as the ‘behavioural/dysexecutive variant of Alzheimer’s disease’.
Relatively little is known about behavioural- and dysexecutive-predominant presentations of Alzheimer’s disease, collectively known as ‘frontal’ Alzheimer’s disease. Ossenkoppele et al. compare these two syndromes, revealing classical temporoparietal atrophy and relative sparing of frontal cortex in both, and propose that they are redefined as the ‘behavioural/dysexecutive variant of Alzheimer’s disease’.
A ‘frontal variant of Alzheimer’s disease’ has been described in patients with predominant behavioural or dysexecutive deficits caused by Alzheimer’s disease pathology. The description of this rare Alzheimer’s disease phenotype has been limited to case reports and small series, and many clinical, neuroimaging and neuropathological characteristics are not well understood. In this retrospective study, we included 55 patients with Alzheimer’s disease with a behavioural-predominant presentation (behavioural Alzheimer’s disease) and a neuropathological diagnosis of high-likelihood Alzheimer’s disease (n = 17) and/or biomarker evidence of Alzheimer’s disease pathology (n = 44). In addition, we included 29 patients with autopsy/biomarker-defined Alzheimer’s disease with a dysexecutive-predominant syndrome (dysexecutive Alzheimer’s disease). We performed structured chart reviews to ascertain clinical features. First symptoms were more often cognitive (behavioural Alzheimer’s disease: 53%; dysexecutive Alzheimer’s disease: 83%) than behavioural (behavioural Alzheimer’s disease: 25%; dysexecutive Alzheimer’s disease: 3%). Apathy was the most common behavioural feature, while hyperorality and perseverative/compulsive behaviours were less prevalent. Fifty-two per cent of patients with behavioural Alzheimer’s disease met diagnostic criteria for possible behavioural-variant frontotemporal dementia. Overlap between behavioural and dysexecutive Alzheimer’s disease was modest (9/75 patients). Sixty per cent of patients with behavioural Alzheimer’s disease and 40% of those with the dysexecutive syndrome carried at least one APOE ε4 allele. We also compared neuropsychological test performance and brain atrophy (applying voxel-based morphometry) with matched autopsy/biomarker-defined typical (amnestic-predominant) Alzheimer’s disease (typical Alzheimer’s disease, n = 58), autopsy-confirmed/Alzheimer’s disease biomarker-negative behavioural variant frontotemporal dementia (n = 59), and controls (n = 61). Patients with behavioural Alzheimer’s disease showed worse memory scores than behavioural variant frontotemporal dementia and did not differ from typical Alzheimer’s disease, while executive function composite scores were lower compared to behavioural variant frontotemporal dementia and typical Alzheimer’s disease. Voxel-wise contrasts between behavioural and dysexecutive Alzheimer’s disease patients and controls revealed marked atrophy in bilateral temporoparietal regions and only limited atrophy in the frontal cortex. In direct comparison with behavioural and those with dysexecutive Alzheimer’s disease, patients with behavioural variant frontotemporal dementia showed more frontal atrophy and less posterior involvement, whereas patients with typical Alzheimer’s disease were slightly more affected posteriorly and showed less frontal atrophy (P < 0.001 uncorrected). Among 24 autopsied behavioural Alzheimer’s disease/dysexecutive Alzheimer’s disease patients, only two had primary co-morbid FTD-spectrum pathology (progressive supranuclear palsy). In conclusion, behavioural Alzheimer’s disease presentations are characterized by a milder and more restricted behavioural profile than in behavioural variant frontotemporal dementia, co-occurrence of memory dysfunction and high APOE ε4 prevalence. Dysexecutive Alzheimer’s disease presented as a primarily cognitive phenotype with minimal behavioural abnormalities and intermediate APOE ε4 prevalence. Both behavioural Alzheimer’s disease and dysexecutive Alzheimer’s disease presentations are distinguished by temporoparietal-predominant atrophy. Based on the relative sparing of frontal grey matter, we propose to redefine these clinical syndromes as ‘the behavioural/dysexecutive variant of Alzheimer’s disease’ rather than frontal variant Alzheimer’s disease. Further work is needed to determine whether behavioural and dysexecutive-predominant presentations of Alzheimer’s disease represent distinct phenotypes or a single continuum.
PMCID: PMC4623840  PMID: 26141491
Alzheimer’s disease; frontotemporal dementia; frontal, behaviour; executive function
6.  Alzheimer’s disease cerebrospinal fluid biomarker in cognitively normal subjects 
Brain  2015;138(9):2701-2715.
In a large multicentre study, Toledo et al. examine core Alzheimer’s disease CSF biomarkers in 1233 cognitively normal subjects aged 40–85 years. Alzheimer disease-like changes in Aβ1-42 are seen as early as middle age, while APOE genotype strongly modifies age-related effects on both Aβ1–42 and phosphorylated/total tau.
In a large multicentre study, Toledo et al. examine core Alzheimer’s disease CSF biomarkers in 1233 cognitively normal subjects aged 40–85 years. Alzheimer disease-like changes in Aβ1-42 are seen as early as middle age, while APOE genotype strongly modifies age-related effects on both Aβ1–42 and phosphorylated/total tau.
In a large multicentre sample of cognitively normal subjects, as a function of age, gender and APOE genotype, we studied the frequency of abnormal cerebrospinal fluid levels of Alzheimer’s disease biomarkers including: total tau, phosphorylated tau and amyloid-β1-42. Fifteen cohorts from 12 different centres with either enzyme-linked immunosorbent assays or Luminex® measurements were selected for this study. Each centre sent nine new cerebrospinal fluid aliquots that were used to measure total tau, phosphorylated tau and amyloid-β1-42 in the Gothenburg laboratory. Seven centres showed a high correlation with the new Gothenburg measurements; therefore, 10 cohorts from these centres are included in the analyses here (1233 healthy control subjects, 40–84 years old). Amyloid-β amyloid status (negative or positive) and neurodegeneration status (negative or positive) was established based on the pathological cerebrospinal fluid Alzheimer’s disease cut-off values for cerebrospinal fluid amyloid-β1-42 and total tau, respectively. While gender did not affect these biomarker values, APOE genotype modified the age-associated changes in cerebrospinal fluid biomarkers such that APOE ε4 carriers showed stronger age-related changes in cerebrospinal fluid phosphorylated tau, total tau and amyloid-β1-42 values and APOE ε2 carriers showed the opposite effect. At 40 years of age, 76% of the subjects were classified as amyloid negative, neurodegeneration negative and their frequency decreased to 32% at 85 years. The amyloid-positive neurodegeneration-negative group remained stable. The amyloid-negative neurodegeneration-positive group frequency increased slowly from 1% at 44 years to 16% at 85 years, but its frequency was not affected by APOE genotype. The amyloid-positive neurodegeneration-positive frequency increased from 1% at 53 years to 28% at 85 years. Abnormally low cerebrospinal fluid amyloid-β1-42 levels were already frequent in midlife and APOE genotype strongly affects the levels of cerebrospinal fluid amyloid-β1-42, phosphorylated tau and total tau across the lifespan without influencing the frequency of subjects with suspected non-amyloid pathology.
PMCID: PMC4643624  PMID: 26220940
Alzheimer’s disease; dementia; biomarkers; cognitive ageing; imaging
7.  Suspected non-Alzheimer disease pathophysiology—concept and controversy 
Nature reviews. Neurology  2016;12(2):117-124.
Suspected non-Alzheimer disease pathophysiology (SNAP) is a biomarker-based concept that applies to individuals with normal levels of amyloid-β biomarkers in the brain, but in whom biomarkers of neurodegeneration are abnormal. The term SNAP has been applied to individuals who are clinically normal for their age and to individuals with mild cognitive impairment, but is applicable to any amyloid-negative, neurodegeneration-positive individual regardless of clinical status, except when the pathology underlying neurodegeneration can be confidently inferred from the clinical presentation. SNAP is present in ~23% of clinically normal individuals aged >65 years and in ~25% of mildly cognitively impaired individuals. APOE4 is underrepresented in individuals with SNAP compared with amyloid-positive individuals. Clinically normal and mildly impaired individuals with SNAP have worse clinical and/or cognitive outcomes than individuals with normal levels of neurodegeneration and amyloid-β biomarkers. In this Perspectives article we describe the available data on SNAP and address topical controversies in the field.
PMCID: PMC4784257  PMID: 26782335
8.  Genetic risk factors for the posterior cortical atrophy variant of Alzheimer's disease 
Alzheimer's & Dementia  2016;12(8):862-871.
The genetics underlying posterior cortical atrophy (PCA), typically a rare variant of Alzheimer's disease (AD), remain uncertain.
We genotyped 302 PCA patients from 11 centers, calculated risk at 24 loci for AD/DLB and performed an exploratory genome-wide association study.
We confirm that variation in/near APOE/TOMM40 (P = 6 × 10−14) alters PCA risk, but with smaller effect than for typical AD (PCA: odds ratio [OR] = 2.03, typical AD: OR = 2.83, P = .0007). We found evidence for risk in/near CR1 (P = 7 × 10−4), ABCA7 (P = .02) and BIN1 (P = .04). ORs at variants near INPP5D and NME8 did not overlap between PCA and typical AD. Exploratory genome-wide association studies confirmed APOE and identified three novel loci: rs76854344 near CNTNAP5 (P = 8 × 10−10 OR = 1.9 [1.5–2.3]); rs72907046 near FAM46A (P = 1 × 10−9 OR = 3.2 [2.1–4.9]); and rs2525776 near SEMA3C (P = 1 × 10−8, OR = 3.3 [2.1–5.1]).
We provide evidence for genetic risk factors specifically related to PCA. We identify three candidate loci that, if replicated, may provide insights into selective vulnerability and phenotypic diversity in AD.
PMCID: PMC4982482  PMID: 26993346
Posterior cortical atrophy; Alzheimer's disease; Genetics; GWAS; Selective vulnerability; APOE
9.  Standardized evaluation of algorithms for computer-aided diagnosis of dementia based on structural MRI: the CADDementia challenge 
NeuroImage  2015;111:562-579.
Algorithms for computer-aided diagnosis of dementia based on structural MRI have demonstrated high performance in the literature, but are difficult to compare as different data sets and methodology were used for evaluation. In addition, it is unclear how the algorithms would perform on previously unseen data, and thus, how they would perform in clinical practice when there is no real opportunity to adapt the algorithm to the data at hand. To address these comparability, generalizability and clinical applicability issues, we organized a grand challenge that aimed to objectively compare algorithms based on a clinically representative multi-center data set. Using clinical practice as starting point, the goal was to reproduce the clinical diagnosis. Therefore, we evaluated algorithms for multi-class classification of three diagnostic groups: patients with probable Alzheimer’s disease, patients with mild cognitive impairment and healthy controls. The diagnosis based on clinical criteria was used as reference standard, as it was the best available reference despite its known limitations. For evaluation, a previously unseen test set was used consisting of 354 T1-weighted MRI scans with the diagnoses blinded. Fifteen research teams participated with in total 29 algorithms. The algorithms were trained on a small training set (n=30) and optionally on data from other sources (e.g., the Alzheimer’s Disease Neuroimaging Initiative, the Australian Imaging Biomarkers and Lifestyle flagship study of aging). The best performing algorithm yielded an accuracy of 63.0% and an area under the receiver-operating-characteristic curve (AUC) of 78.8%. In general, the best performances were achieved using feature extraction based on voxel-based morphometry or a combination of features that included volume, cortical thickness, shape and intensity. The challenge is open for new submissions via the web-based framework:
Graphical abstract
PMCID: PMC4943029  PMID: 25652394
Alzheimer’s disease; Challenge; Classification; Computer-aided diagnosis; Mild cognitive impairment; Structural MRI
10.  The effect of amyloid pathology and glucose metabolism on cortical volume loss over time in Alzheimer’s disease 
The present multimodal neuroimaging study examined whether amyloid pathology and glucose metabolism are related to cortical volume loss over time in Alzheimer’s disease (AD) patients and healthy elderly controls.
Structural MRI scans of eleven AD patients and ten controls were available at baseline and follow-up (mean interval 2.5 years). Change in brain structure over time was defined as percent change of cortical volume within seven a-priori defined regions that typically show the strongest structural loss in AD. In addition, two PET scans were performed at baseline: [11C]PIB to assess amyloid-β plaque load and [18F]FDG to assess glucose metabolism. [11C]PIB binding and [18F]FDG uptake were measured in the precuneus, a region in which both amyloid deposition and glucose hypometabolism occur early in the course of AD.
While amyloid-β plaque load at baseline was not related to cortical volume loss over time in either group, glucose metabolism within the group of AD patients was significantly related to volume loss over time (rho=0.56, p<0.05).
The present study shows that in a group of AD patients amyloid-β plaque load as measured by [11C]PIB behaves as a trait marker (i.e., all AD patients showed elevated levels of amyloid, not related to subsequent disease course), whilst hypometabolism as measured by [18F]FDG changed over time indicating that it could serve as a state marker that is predictive of neurodegeneration.
PMCID: PMC4917377  PMID: 24615466
Alzheimer’s disease; Amyloid plaques; Hypometabolism; Atrophy; Longitudinal study
11.  Mild cognitive impairment with suspected nonamyloid pathology (SNAP) 
Neurology  2015;84(5):508-515.
The aim of this study was to investigate predictors of progressive cognitive deterioration in patients with suspected non–Alzheimer disease pathology (SNAP) and mild cognitive impairment (MCI).
We measured markers of amyloid pathology (CSF β-amyloid 42) and neurodegeneration (hippocampal volume on MRI and cortical metabolism on [18F]-fluorodeoxyglucose–PET) in 201 patients with MCI clinically followed for up to 6 years to detect progressive cognitive deterioration. We categorized patients with MCI as A+/A− and N+/N− based on presence/absence of amyloid pathology and neurodegeneration. SNAPs were A−N+ cases.
The proportion of progressors was 11% (8/41), 34% (14/41), 56% (19/34), and 71% (60/85) in A−N−, A+N−, SNAP, and A+N+, respectively; the proportion of APOE ε4 carriers was 29%, 70%, 31%, and 71%, respectively, with the SNAP group featuring a significantly different proportion than both A+N− and A+N+ groups (p ≤ 0.005). Hypometabolism in SNAP patients was comparable to A+N+ patients (p = 0.154), while hippocampal atrophy was more severe in SNAP patients (p = 0.002). Compared with A−N−, SNAP and A+N+ patients had significant risk of progressive cognitive deterioration (hazard ratio = 2.7 and 3.8, p = 0.016 and p < 0.001), while A+N− patients did not (hazard ratio = 1.13, p = 0.771). In A+N− and A+N+ groups, none of the biomarkers predicted time to progression. In the SNAP group, lower time to progression was correlated with greater hypometabolism (r = 0.42, p = 0.073).
Our findings support the notion that patients with SNAP MCI feature a specific risk progression profile.
PMCID: PMC4336071  PMID: 25568301
12.  Slowing of Hippocampal Activity Correlates with Cognitive Decline in Early Onset Alzheimer’s Disease. An MEG Study with Virtual Electrodes 
Pathology in Alzheimer’s disease (AD) starts in the entorhinal cortex and hippocampus. Because of their deep location, activity from these areas is difficult to record with conventional electro- or magnetoencephalography (EEG/MEG). The purpose of this study was to explore hippocampal activity in AD patients and healthy controls using “virtual MEG electrodes”. We used resting-state MEG recordings from 27 early onset AD patients [age 60.6 ± 5.4, 12 females, mini-mental state examination (MMSE) range: 19–28] and 26 cognitively healthy age- and gender-matched controls (age 61.8 ± 5.5, 14 females). Activity was reconstructed using beamformer-based virtual electrodes for 78 cortical regions and 6 hippocampal regions. Group differences in peak frequency and relative power in six frequency bands were identified using permutation testing. For the patients, spearman correlations between the MMSE scores and peak frequency or relative power were calculated. Moreover, receiver operator characteristic curves were plotted to estimate the diagnostic accuracy. We found a lower hippocampal peak frequency in AD compared to controls, which, in the patients, correlated positively with MMSE [r(25) = 0.61; p < 0.01] whereas hippocampal relative theta power correlated negatively with MMSE [r(25) = -0.54; p < 0.01]. Cortical peak frequency was also lower in AD in association areas. Furthermore, cortical peak frequency correlated positively with MMSE [r(25) = 0.43; p < 0.05]. In line with this finding, relative theta power was higher in AD across the cortex, and relative alpha and beta power was lower in more circumscribed areas. The average cortical relative theta power was the best discriminator between AD and controls (sensitivity 82%; specificity 81%). Using beamformer-based virtual electrodes, we were able to detect hippocampal activity in AD. In AD, this hippocampal activity is slowed, and correlates better with cognition than the (slowed) activity in cortical areas. On the other hand, the average cortical relative power in the theta band was shown to be the best diagnostic discriminator. We postulate that this novel approach using virtual electrodes can be used in future research to quantify functional interactions between the hippocampi and cortical areas.
PMCID: PMC4873509  PMID: 27242496
Alzheimer’s disease; MEG; source-space; beamformer; virtual electrode; hippocampus; relative power; peak frequency
13.  Neurogranin as a Cerebrospinal Fluid Biomarker for Synaptic Loss in Symptomatic Alzheimer Disease 
JAMA neurology  2015;72(11):1275-1280.
Neurogranin (NGRN) seems to be a promising novel cerebrospinal fluid (CSF) biomarker for synaptic loss; however, clinical, and especially longitudinal, data are sparse.
To examine the utility of NGRN, with repeated CSF sampling, for diagnosis, prognosis, and monitoring of Alzheimer disease (AD).
Longitudinal study of consecutive patients who underwent 2 lumbar punctures between the beginning of 1995 and the end of 2010 within the memory clinic–based Amsterdam Dementia Cohort. The study included 163 patients: 37 cognitively normal participants (mean [SE] age, 64 [2] years; 38% female; and mean [SE] Mini-Mental State Examination [MMSE] score, 28 [0.3]), 61 patients with mild cognitive impairment (MCI) (mean [SE] age, 68 [1] years; 38% female; and mean [SE] MMSE score, 27 [0.3]), and 65 patients with AD (mean [SE] age, 65 [1] years; 45% female; and mean [SE] MMSE score, 22 [0.7]). The mean (SE) interval between lumbar punctures was 2.0 (0.1) years, and the mean (SE) duration of cognitive follow-up was 3.8 (0.2) years. Measurements of CSF NGRN levels were obtained in January and February 2014.
Levels of NGRN in CSF samples.
Baseline CSF levels of NGRN in patients with AD (median level, 2381 pg/mL [interquartile range, 1651-3416 pg/mL]) were higher than in cognitively normal participants (median level, 1712 pg/mL [interquartile range, 1206-2724 pg/mL]) (P = .04). Baseline NGRN levels were highly correlated with total tau and tau phosphorylated at threonine 181 in all patient groups (all P < .001), but not with Aβ42. Baseline CSF levels of NGRN were also higher in patients with MCI who progressed to AD (median level, 2842 pg/mL [interquartile range, 1882-3950 pg/mL]) compared with those with stable MCI (median level, 1752 pg/mL [interquartile range, 1024-2438 pg/mL]) (P = .004), and they were predictive of progression from MCI to AD (hazard ratio, 1.8 [95% CI, 1.1-2.9]; stratified by tertiles). Linear mixed-model analyses demonstrated that within-person levels of NGRN increased over time in cognitively normal participants (mean [SE] level, 90 [45] pg/mL per year; P < .05) but not in patients with MCI or AD.
Neurogranin is a promising biomarker for AD because levels were elevated in patients with AD compared with cognitively normal participants and predicted progression from MCI to AD. Within-person levels of NGRN increased in cognitively normal participants but not in patients with later stage MCI or AD, which suggests that NGRN may reflect presymptomatic synaptic dysfunction or loss.
PMCID: PMC4694558  PMID: 26366630
14.  Atrophy Patterns in Early Clinical Stages Across Distinct Phenotypes of Alzheimer’s Disease 
Human brain mapping  2015;36(11):4421-4437.
Alzheimer’s disease (AD) can present with distinct clinical variants. Identifying the earliest neurodegenerative changes associated with each variant has implications for early diagnosis, and for understanding the mechanisms that underlie regional vulnerability and disease progression in AD. We performed voxel-based morphometry to detect atrophy patterns in early clinical stages of four AD phenotypes: Posterior cortical atrophy (PCA, “visual variant,” n = 93), logopenic variant primary progressive aphasia (lvPPA, “language variant,” n = 74), and memory-predominant AD categorized as early age-of-onset (EOAD, <65 years, n = 114) and late age-of-onset (LOAD, >65 years, n = 114). Patients with each syndrome were stratified based on: (1) degree of functional impairment, as measured by the clinical dementia rating (CDR) scale, and (2) overall extent of brain atrophy, as measured by a neuroimaging approach that sums the number of brain voxels showing significantly lower gray matter volume than cognitively normal controls (n = 80). Even at the earliest clinical stage (CDR =0.5 or bottom quartile of overall atrophy), patients with each syndrome showed both common and variant-specific atrophy. Common atrophy across variants was found in temporoparietal regions that comprise the posterior default mode network (DMN). Early syndrome-specific atrophy mirrored functional brain networks underlying functions that are uniquely affected in each variant: Language network in lvPPA, posterior cingulate cortex-hippocampal circuit in amnestic EOAD and LOAD, and visual networks in PCA. At more advanced stages, atrophy patterns largely converged across AD variants. These findings support a model in which neurodegeneration selectively targets both the DMN and syndrome-specific vulnerable networks at the earliest clinical stages of AD.
PMCID: PMC4692964  PMID: 26260856
Alzheimer’s disease; magnetic resonance imaging (MRI); posterior cortical atrophy; logopenic variant primary progressive aphasia; early-onset dementia; default mode network; language; memory; vision; atrophy; voxel-based morphometry
15.  Discriminative and prognostic potential of cerebrospinal fluid phosphoTau/tau ratio and neurofilaments for frontotemporal dementia subtypes 
A decreased cerebrospinal fluid (CSF) p-Tau181 to total tau ratio (p/t-tau) is a biomarker for frontotemporal lobar degeneration with TDP43 inclusions (FTLD-TDP) and for amyotrophic lateral sclerosis (ALS). CSF light chain neurofilaments (NfL) are increased in ALS. We examined whether CSF p/t-tau and NfL are related to ALS status in FTLD-TDP.
We compared CSF p/t-tau and NfL levels between patients with FTLD-TDP with ALS (n = 15), FTLD-TDP without ALS (n = 17), FTLD-Tau (n = 6), Alzheimer's disease (AD; n = 25), and subjective memory complaints (SMC, n = 24).
Apart from FTLD-Tau, all groups differed significantly with increasing p/t-tau ratios from FTLD-TDP with ALS to FTLD-TDP without ALS to AD and SMC. CSF NfL was very high in FTLD-TDP with ALS followed by FTLD-TDP without ALS, AD, and SMC. Both biomarkers correlated with survival.
CSF p/t-tau ratio and NfL levels are strongly driven by ALS status. These markers, therefore, appear to be more of prognostic than diagnostic significance.
PMCID: PMC4879490  PMID: 27239528
Frontotemporal dementia; Cerebrospinal fluid; Biomarker; Disease monitoring; Neurofilament; p/t tau ratio
16.  SUCLG2 identified as both a determinator of CSF Aβ1–42 levels and an attenuator of cognitive decline in Alzheimer's disease 
Human Molecular Genetics  2014;23(24):6644-6658.
Cerebrospinal fluid amyloid-beta 1–42 (Aβ1–42) and phosphorylated Tau at position 181 (pTau181) are biomarkers of Alzheimer's disease (AD). We performed an analysis and meta-analysis of genome-wide association study data on Aβ1–42 and pTau181 in AD dementia patients followed by independent replication. An association was found between Aβ1–42 level and a single-nucleotide polymorphism in SUCLG2 (rs62256378) (P = 2.5×10−12). An interaction between APOE genotype and rs62256378 was detected (P = 9.5 × 10−5), with the strongest effect being observed in APOE-ε4 noncarriers. Clinically, rs62256378 was associated with rate of cognitive decline in AD dementia patients (P = 3.1 × 10−3). Functional microglia experiments showed that SUCLG2 was involved in clearance of Aβ1–42.
PMCID: PMC4240204  PMID: 25027320
17.  Prevalence of Amyloid PET Positivity in Dementia Syndromes 
JAMA  2015;313(19):1939-1949.
Amyloid-β positron emission tomography (PET) imaging allows in vivo detection of fibrillar plaques, a core neuropathological feature of Alzheimer disease (AD). Its diagnostic utility is still unclear because amyloid plaques also occur in patients with non–AD dementia.
To use individual participant data meta-analysis to estimate the prevalence of amyloid positivity on PET in a wide variety of dementia syndromes.
The MEDLINE and Web of Science databases were searched from January 2004 to April 2015 for amyloid PET studies.
Case reports and studies on neurological or psychiatric diseases other than dementia were excluded. Corresponding authors of eligible cohorts were invited to provide individual participant data.
Data were provided for 1359 participants with clinically diagnosed AD and 538 participants with non–AD dementia. The reference groups were 1849 healthy control participants (based on amyloid PET) and an independent sample of 1369 AD participants (based on autopsy).
Estimated prevalence of positive amyloid PET scans according to diagnosis, age, and apolipoprotein E (APOE) ε4 status, using the generalized estimating equations method.
The likelihood of amyloid positivity was associated with age and APOE ε4 status. In AD dementia, the prevalence of amyloid positivity decreased from age 50 to 90 years in APOE ε4 noncarriers(86%[95%CI,73%–94%]at 50 years to 68% [95% CI,57%–77%] at 90 years; n = 377) and to a lesser degree in APOE ε4 carriers (97% [95% CI, 92%–99%] at 50 years to 90% [95% CI, 83%–94%] at 90 years; n = 593; P < .01). Similar associations of age and APOE ε4 with amyloid positivity were observed in participants with AD dementia at autopsy. In most non–AD dementias, amyloid positivity increased with both age (from 60 to 80 years) and APOE ε4 carriership. Total ParticipantsAmyloid Positivity, % (95% CI) Age 60 yAge 80 y Dementia with Lewy bodies  emsp;APOE ε4 carrier  1663 (48–80)83 (67–92)  emsp;APOE ε4 noncarrier  1829 (15–50)54 (30–77) Frontotemporal dementia  emsp;APOE ε4 carrier  4819 (12–28)43 (35–50)  emsp;APOE ε4 noncarrier160  5 (3–8)14 (11–18) Vascular dementia  emsp;APOE ε4 carrier  3025 (9–52)64 (49–77)  emsp;APOE ε4 noncarrier  77  7 (3–18)29 (17–43)
Among participants with dementia, the prevalence of amyloid positivity was associated with clinical diagnosis, age, and APOE genotype. These findings indicate the potential clinical utility of amyloid imaging for differential diagnosis in early-onset dementia and to support the clinical diagnosis of participants with AD dementia and noncarrier APOE ε4 status who are older than 70 years.
PMCID: PMC4517678  PMID: 25988463
18.  A conceptual framework for research on subjective cognitive decline in preclinical Alzheimer’s disease 
There is increasing evidence that subjective cognitive decline (SCD) in individuals with unimpaired performance on cognitive tests may represent the first symptomatic manifestation of Alzheimer’s disease (AD). The research on SCD in early AD, however, is limited by the absence of common standards. The working group of the Subjective Cognitive Decline Initiative (SCD-I) addressed this deficiency by reaching consensus on terminology and on a conceptual framework for research on SCD in AD. In this publication, research criteria for SCD in pre-mild cognitive impairment (MCI) are presented. In addition, a list of core features proposed for reporting in SCD studies is provided, which will enable comparability of research across different settings. Finally, a set of features is presented, which in accordance with current knowledge, increases the likelihood of the presence of preclinical AD in individuals with SCD. This list is referred to as SCD plus.
PMCID: PMC4317324  PMID: 24798886
Alzheimer’s disease; Subjective cognitive decline; Preclinical Alzheimer’s disease; Mild cognitive impairment; Prodromal Alzheimer ’s disease; Research criteria
19.  Subjective Cognitive Decline in Older Adults: An Overview of Self-Report Measures Used Across 19 International Research Studies 
Journal of Alzheimer's disease : JAD  2015;48(0 1):S63-S86.
Research increasingly suggests that subjective cognitive decline (SCD) in older adults, in the absence of objective cognitive dysfunction or depression, may be a harbinger of non-normative cognitive decline and eventual progression to dementia. Little is known, however, about the key features of self-report measures currently used to assess SCD. The Subjective Cognitive Decline Initiative (SCD-I) Working Group is an international consortium established to develop a conceptual framework and research criteria for SCD (Jessen et al., 2014, Alzheimers Dement 10, 844–852). In the current study we systematically compared cognitive self-report items used by 19 SCD-I Working Group studies, representing 8 countries and 5 languages. We identified 34 self-report measures comprising 640 cognitive self-report items. There was little overlap among measures—approximately 75% of measures were used by only one study. Wide variation existed in response options and item content. Items pertaining to the memory domain predominated, accounting for about 60% of items surveyed, followed by executive function and attention, with 16% and 11% of the items, respectively. Items relating to memory for the names of people and the placement of common objects were represented on the greatest percentage of measures (56% each). Working group members reported that instrument selection decisions were often based on practical considerations beyond the study of SCD specifically, such as availability and brevity of measures. Results document the heterogeneity of approaches across studies to the emerging construct of SCD. We offer preliminary recommendations for instrument selection and future research directions including identifying items and measure formats associated with important clinical outcomes.
PMCID: PMC4617342  PMID: 26402085
Cognition; cognitive complaints; dementia; early detection; memory complaints; subjective cognition; mild cognitive impairment; preclinical Alzheimer’s disease; questionnaire; subjective cognitive impairment; subjective memory complaints
21.  Hypertensive Disorders of Pregnancy Appear Not to Be Associated with Alzheimer's Disease Later in Life 
After hypertensive disorders of pregnancy, more subjective cognitive complaints and white matter lesions are reported compared to women after normal pregnancies. Both have a causal relationship with Alzheimer's disease (AD).
To investigate if women whose pregnancy was complicated by hypertensive disorders have an increased risk of AD.
A case-control study in women with AD from the Alzheimer Center of the VU University Medical Center Amsterdam and women without AD. Paper and telephone surveys were performed.
The response rate was 85.2%. No relation between women with (n = 104) and without AD (n = 129) reporting pregnancies complicated by hypertensive disorders (p = 0.11) was found. Women with early-onset AD reported hypertensive disorders of pregnancy more often (p = 0.02) compared to women with late-onset AD.
A reported history of hypertensive disorders of pregnancy appears not to be associated with AD later in life.
PMCID: PMC4637816  PMID: 26557136
Alzheimer's disease; Magnetic resonance imaging; Preeclampsia; Pregnancy-induced hypertension; Early-onset dementia
22.  Cerebrospinal fluid VILIP-1 and YKL-40, candidate biomarkers to diagnose, predict and monitor Alzheimer’s disease in a memory clinic cohort 
We examined the utility of cerebrospinal fluid (CSF) proteins, Chitinase-3-like protein 1 (CHI3L1 or YKL-40), a putative marker of inflammation, and Visinin-like protein-1 (VILIP-1), a marker for neuronal injury, for diagnostic classification and monitoring of disease progression in a memory clinic cohort.
CSF levels of YKL-40 and VILIP-1 were measured in 37 cognitively normal, 61 Mild Cognitive Impairment (MCI) and 65 Alzheimer’s disease (AD) patients from the memory clinic-based Amsterdam Dementia Cohort who underwent two lumbar punctures, with minimum interval of 6 months and a mean(SE) interval of 2.0(0.1) years. Mean(SE) cognitive follow-up was 3.8 (0.2) years. ANOVA was used to compare baseline differences of log-transformed CSF measures. Cox proportional hazard models were used to evaluate disease progression as a function of CSF tertiles. Linear mixed models were used to evaluate longitudinal change over time. All analyses were sex and age adjusted.
Baseline levels of YKL-40, but not VILIP-1, were higher in MCI and AD patients compared to cognitively normal individuals (mean (SE) pg/mL, 304 (16) and 288 (12) vs. 231 (16), p = 0.03 and p = 0.006). Baseline levels of both YKL-40 and VILIP-1 in MCI predicted progression to AD (HR 95 % CI = 3.0 (1.1–7.9) and 4.4 (1.5–13.0), respectively, for highest vs. lowest tertile). YKL-40 increased longitudinally in patients with MCI and AD (mean (SE) pg/mL per year, 8.9 (3.0) and 7.1 (3.1), respectively), but not in cognitively normal individuals, whereas levels of VILIP-1 increased only in MCI (mean (SE), 10.7 (2.6) pg/mL per year).
CSF levels of YKL-40 may have utility for discriminating between cognitively normal individuals and patients with MCI or AD. Increased levels of both YKL-40 and VILIP-1 may be associated with disease progression. These CSF biomarkers should be considered for future evaluation in the characterization of the natural history of AD.
PMCID: PMC4574487  PMID: 26383836
23.  Joint assessment of white matter integrity, cortical and subcortical atrophy to distinguish AD from behavioral variant FTD: A two-center study 
NeuroImage : Clinical  2015;9:418-429.
We investigated the ability of cortical and subcortical gray matter (GM) atrophy in combination with white matter (WM) integrity to distinguish behavioral variant frontotemporal dementia (bvFTD) from Alzheimer's disease (AD) and from controls using voxel-based morphometry, subcortical structure segmentation, and tract-based spatial statistics. To determine which combination of MR markers differentiated the three groups with the highest accuracy, we conducted discriminant function analyses. Adjusted for age, sex and center, both types of dementia had more GM atrophy, lower fractional anisotropy (FA) and higher mean (MD), axial (L1) and radial diffusivity (L23) values than controls. BvFTD patients had more GM atrophy in orbitofrontal and inferior frontal areas than AD patients. In addition, caudate nucleus and nucleus accumbens were smaller in bvFTD than in AD. FA values were lower; MD, L1 and L23 values were higher, especially in frontal areas of the brain for bvFTD compared to AD patients. The combination of cortical GM, hippocampal volume and WM integrity measurements, classified 97–100% of controls, 81–100% of AD and 67–75% of bvFTD patients correctly. Our results suggest that WM integrity measures add complementary information to measures of GM atrophy, thereby improving the classification between AD and bvFTD.
•There are gray and clear white matter differences between AD and bvFTD.•Gray matter atrophy contributed most to distinguish controls from dementia patients.•White matter integrity contributed most to distinguish bvFTD from controls and AD.•White matter integrity supports the hypothesis of a network disorder in bvFTD.•White matter integrity allows more precise differentiation between AD and bvFTD.
PMCID: PMC4600847  PMID: 26594624
Alzheimer's disease; Frontotemporal dementia; Gray matter atrophy; White matter integrity; Discriminant analyses; Diagnosis
24.  Declining functional connectivity and changing hub locations in Alzheimer’s disease: an EEG study 
BMC Neurology  2015;15:145.
EEG studies have shown that patients with Alzheimer’s disease (AD) have weaker functional connectivity than controls, especially in higher frequency bands. Furthermore, active regions seem more prone to AD pathology. How functional connectivity is affected in AD subgroups of disease severity and how network hubs (highly connected brain areas) change is not known. We compared AD patients with different disease severity and controls in terms of functional connections, hub strength and hub location.
We studied routine 21-channel resting-state electroencephalography (EEG) of 318 AD patients (divided into tertiles based on disease severity: mild, moderate and severe AD) and 133 age-matched controls. Functional connectivity between EEG channels was estimated with the Phase Lag Index (PLI). From the PLI-based connectivity matrix, the minimum spanning tree (MST) was derived. For each node (EEG channel) in the MST, the betweenness centrality (BC) was computed, a measure to quantify the relative importance of a node within the network. Then we derived color-coded head plots based on BC values and calculated the center of mass (the exact middle had x and y values of 0). A shifting of the hub locations was defined as a shift of the center of mass on the y-axis across groups. Multivariate general linear models with PLI or BC values as dependent variables and the groups as continuous variables were used in the five conventional frequency bands.
We found that functional connectivity decreases with increasing disease severity in the alpha band. All, except for posterior, regions showed increasing BC values with increasing disease severity. The center of mass shifted from posterior to more anterior regions with increasing disease severity in the higher frequency bands, indicating a loss of relative functional importance of the posterior brain regions.
In conclusion, we observed decreasing functional connectivity in the posterior regions, together with a shifted hub location from posterior to central regions with increasing AD severity. Relative hub strength decreases in posterior regions while other regions show a relative rise with increasing AD severity, which is in accordance with the activity-dependent degeneration theory. Our results indicate that hubs are disproportionally affected in AD.
Electronic supplementary material
The online version of this article (doi:10.1186/s12883-015-0400-7) contains supplementary material, which is available to authorized users.
PMCID: PMC4545875  PMID: 26289045
25.  Cerebrospinal Fluid Biomarkers and Cerebral Atrophy in Distinct Clinical Variants of Probable Alzheimer’s Disease 
Neurobiology of aging  2015;36(8):2340-2347.
Different clinical variants of probable Alzheimer’s disease (AD) share underlying plaques and tangles but show distinct atrophy patterns. We included 52 posterior cortical atrophy (PCA), 29 logopenic variant primary progressive aphasia (lvPPA), 53 early-onset (EOAD) and 42 late-onset AD (LOAD) patients, selected for abnormal CSF-Aβ42, with CSF and MRI data available. Bootstrapping revealed no differences in the prevalence of abnormal CSF total-tau and phosphorylated-tau between probable AD variants (range total-tau: 84.9–92.3%, phosphorylated-tau: 79.2–93.1%, p>0.05). Voxel-wise linear regressions showed various relationships between lower CSF-Aβ42 and syndrome-specific atrophy, involving precuneus, posterior cingulate, and medial temporal lobe (MTL) in EOAD, occipital cortex and middle temporal gyrus in PCA; anterior cingulate, insular cortex and precentral gyrus (left>right) in lvPPA; and MTL, thalamus, and temporal pole in LOAD (all at p<0.001 uncorrected). In contrast, CSF-tau was not related to gray matter atrophy in any group. Our findings suggest that lower CSF-Aβ42 – and not increased total-tau and phosphorylated-tau – relates to reduced gray matter volumes, mostly in regions that are typically atrophied in distinct clinical variants of probable AD.
PMCID: PMC4465267  PMID: 25990306
Alzheimer’s disease; cerebrospinal fluid; magnetic resonance imaging; amyloid; tau; atrophy

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