The Parelsnoer Institute is a collaboration between 8 Dutch University Medical Centers in which clinical data and biomaterials from patients suffering from chronic diseases (so called “Pearls”) are collected according to harmonized protocols. The Pearl Neurodegenerative Diseases focuses on the role of biomarkers in the early diagnosis, differential diagnosis and in monitoring the course of neurodegenerative diseases, in particular Alzheimer’s disease.
The objective of this paper is to describe the design and methods of the Pearl Neurodegenerative Diseases, as well as baseline descriptive variables, including their biomarker profile.
The Pearl Neurodegenerative Diseases is a 3-year follow-up study of patients referred to a memory clinic with cognitive complaints. At baseline, all patients are subjected to a standardized examination, including clinical data and biobank materials, e.g. blood samples, MRI and cerebrospinal fluid. At present, in total more than 1000 patients have been included, of which cerebrospinal fluid and DNA samples are available of 211 and 661 patients, respectively. First descriptives of a subsample of the data (n = 665) shows that patients are diagnosed with dementia (45%), mild cognitive impairment (31%), and subjective memory complaints (24%).
The Pearl Neurodegenerative Diseases is an ongoing large network collecting clinical data and biomaterials of more than 1000 patients with cognitive impairments. The project has started with data analyses of the baseline characteristics and biomarkers, which will be the starting point of future specific research questions that can be answered by this unique dataset.
Dementia; Alzheimer’s disease; Design; Biobank; Research infrastructure
Clinical and neuropathological similarities between dementia with Lewy bodies (DLB), Parkinson’s and Alzheimer’s diseases (PD and AD, respectively) suggest that these disorders may share etiology. To test this hypothesis, we have performed an association study of 54 genomic regions, previously implicated in PD or AD, in a large cohort of DLB cases and controls. The cohort comprised 788 DLB cases and 2624 controls. To minimize the issue of potential misdiagnosis, we have also performed the analysis including only neuropathologically proven DLB cases (667 cases). The results show that the APOE is a strong genetic risk factor for DLB, confirming previous findings, and that the SNCA and SCARB2 loci are also associated after a study-wise Bonferroni correction, although these have a different association profile than the associations reported for the same loci in PD. We have previously shown that the p.N370S variant in GBA is associated with DLB, which, together with the findings at the SCARB2 locus, suggests a role for lysosomal dysfunction in this disease. These results indicate that DLB has a unique genetic risk profile when compared with the two most common neurodegenerative diseases and that the lysosome may play an important role in the etiology of this disorder. We make all these data available.
Early-onset Alzheimer’s disease (AD) patients present a different clinical profile than late-onset AD patients. This can be partially explained by cortical atrophy, although brain organization might provide more insight. The aim of this study was to examine functional connectivity in early-onset and late-onset AD patients. Resting-state fMRI scans of 20 early-onset (<65 years old), 28 late-onset (≥65 years old) AD patients and 15 “young” (<65 years old) and 31 “old” (≥65 years old) age-matched controls were available. Resting-state network-masks were used to create subject-specific maps. Group differences were examined using a non-parametric permutation test, accounting for gray-matter. Performance on five cognitive domains were used in a correlation analysis with functional connectivity in AD patients. Functional connectivity was not different in any of the RSNs when comparing the two control groups (young vs. old controls), which implies that there is no general effect of aging on functional connectivity. Functional connectivity in early-onset AD was lower in all networks compared to age-matched controls, where late-onset AD showed lower functional connectivity in the default-mode network. Functional connectivity was lower in early-onset compared to late-onset AD in auditory-, sensory-motor, dorsal-visual systems and the default mode network. Across patients, an association of functional connectivity of the default mode network was found with visuoconstruction. Functional connectivity of the right dorsal visual system was associated with attention across patients. In late-onset AD patients alone, higher functional connectivity of the sensory-motor system was associated with poorer memory performance. Functional brain organization was more widely disrupted in early-onset AD when compared to late-onset AD. This could possibly explain different clinical profiles, although more research into the relationship of functional connectivity and cognitive performance is needed.
Synaptic dysfunction occurs early in the progression of Alzheimer’s disease (AD) and correlates with memory decline. There is emerging evidence that deregulation of Erythropoietin-producing hepatocellular (Eph) receptor tyrosine kinases (RTK) signaling contributes to the aberrant synaptic functions associated with neurodegeneration. The Eph receptor A4 is highly expressed in human adult hippocampal brain tissue and was previously linked to cognitive impairment in a transgenic mouse model for AD. Whether EphA4 levels are altered in AD brain remains elusive. Therefore we investigated the protein levels and localization of EphA4 in human hippocampus derived from AD (n = 29) as well as non-demented control cases (n = 19).
The total EphA4 protein levels were not changed in AD patients compared to control cases. However, immunohistochemical localization of EphA4 revealed an altered distribution in AD compared to control hippocampus. EphA4 immunoreactivity was observed in plaque-like structures in AD cases. Double-labelling with phosphorylated tau and amyloid beta indicates that EphA4 co-localizes with neuritic plaques in AD. This altered distribution pattern was observed at early stages (Braak stage II) and correlates with the hallmarks of AD pathology suggesting a reduced availability of EphA4 that is likely to contribute to synaptic dysfunction that occurs early in AD.
Electronic supplementary material
The online version of this article (doi:10.1186/s40478-014-0079-9) contains supplementary material, which is available to authorized users.
Alzheimer’s disease; EphA4 kinase; Synapse; Immunohistochemistry
Clinical and neuropathological similarities between dementia with Lewy bodies (DLB), Parkinson's and Alzheimer's diseases (PD and AD, respectively) suggest that these disorders may share etiology. To test this hypothesis, we have performed an association study of 54 genomic regions, previously implicated in PD or AD, in a large cohort of DLB cases and controls. The cohort comprised 788 DLB cases and 2624 controls. To minimize the issue of potential misdiagnosis, we have also performed the analysis including only neuropathologically proven DLB cases (667 cases). The results show that the APOE is a strong genetic risk factor for DLB, confirming previous findings, and that the SNCA and SCARB2 loci are also associated after a study-wise Bonferroni correction, although these have a different association profile than the associations reported for the same loci in PD. We have previously shown that the p.N370S variant in GBA is associated with DLB, which, together with the findings at the SCARB2 locus, suggests a role for lysosomal dysfunction in this disease. These results indicate that DLB has a unique genetic risk profile when compared with the two most common neurodegenerative diseases and that the lysosome may play an important role in the etiology of this disorder. We make all these data available.
Lower angiotensin-converting enzyme (ACE) activity could increase the risk of Alzheimer’s disease (AD) as ACE functions to degrade amyloid-β (Aβ). Therefore, we investigated whether ACE protein and activity levels in cerebrospinal fluid (CSF) and serum were associated with CSF Aβ, total tau (tau) and tau phosphorylated at threonine 181 (ptau).
We included 118 subjects from our memory clinic-based Amsterdam Dementia Cohort (mean age 66 ± 8 years) with subjective memory complaints (n = 40) or AD (n = 78), who did not use antihypertensive drugs. We measured ACE protein levels (ng/ml) and activity (RFU) in CSF and serum, and amyloid β1–42, tau and ptau (pg/ml) in CSF.
Cross-sectional regression analyses showed that ACE protein level and activity in CSF and serum were lower in patients with AD compared to controls. Lower CSF ACE protein level, and to a lesser extent serum ACE protein level and CSF ACE activity, were associated with lower CSF Aβ, indicating more brain Aβ pathology; adjusted regression coefficients (B) (95% CI) per SD increase were 0.09 (0.04; 0.15), 0.06 (0.00; 0.12) and 0.05 (0.00; 0.11), respectively. Further, lower CSF ACE protein level was associated with lower CSF tau and ptau levels; adjusted B’s (95% CI) per SD increase were 0.15 (0.06; 0.25) and 0.17 (0.10; 0.25), respectively.
These results strengthen the hypothesis that ACE degrades Aβ. This could suggest that lowering ACE levels by for example ACE-inhibitors might have adverse consequences for patients with, or at risk for AD.
Decreased blood–brain barrier P-glycoprotein (Pgp) function has been shown in Alzheimer's disease (AD) patients using positron emission tomography (PET) with the radiotracer (R)-[11C]verapamil. Decreased Pgp function has also been hypothesized to promote cerebral amyloid angiopathy (CAA) development. Here, we used PET and (R)-[11C]verapamil to assess Pgp function in eighteen AD patients, of which six had microbleeds (MBs), presumably reflecting underlying CAA. No differences were found in binding potential and nonspecific volume of distribution of (R)-[11C]verapamil between patient groups. These results provide no evidence for additional Pgp dysfunction in AD patients with MBs.
Alzheimer's disease; blood–brain barrier; cerebral amyloid angiopathy; P-glycoprotein; positron emission tomography; (R)-[11C]verapamil
Coordinated patterns of cortical morphology have been described as structural graphs and previous research has demonstrated that properties of such graphs are altered in Alzheimer's disease (AD). However, it remains unknown how these alterations are related to cognitive deficits in individuals, as such graphs are restricted to group-level analysis. In the present study we investigated this question in single-subject grey matter networks. This new method extracts large-scale structural graphs where nodes represent small cortical regions that are connected by edges when they show statistical similarity. Using this method, unweighted and undirected networks were extracted from T1 weighted structural magnetic resonance imaging scans of 38 AD patients (19 female, average age 72±4 years) and 38 controls (19 females, average age 72±4 years). Group comparisons of standard graph properties were performed after correcting for grey matter volumetric measurements and were correlated to scores of general cognitive functioning. AD networks were characterised by a more random topology as indicated by a decreased small world coefficient (p = 3.53×10−5), decreased normalized clustering coefficient (p = 7.25×10−6) and decreased normalized path length (p = 1.91×10−7). Reduced normalized path length explained significantly (p = 0.004) more variance in measurements of general cognitive decline (32%) in comparison to volumetric measurements (9%). Altered path length of the parahippocampal gyrus, hippocampus, fusiform gyrus and precuneus showed the strongest relationship with cognitive decline. The present results suggest that single-subject grey matter graphs provide a concise quantification of cortical structure that has clinical value, which might be of particular importance for disease prognosis. These findings contribute to a better understanding of structural alterations and cognitive dysfunction in AD.
Alzheimer's disease (AD) is a devastating disorder of increasing prevalence in modern society. Mild cognitive impairment (MCI) is considered a transitional stage between normal aging and AD; however, not all subjects with MCI progress to AD. Prediction of conversion to AD at an early stage would enable an earlier, and potentially more effective, treatment of AD. Electroencephalography (EEG) biomarkers would provide a non-invasive and relatively cheap screening tool to predict conversion to AD; however, traditional EEG biomarkers have not been considered accurate enough to be useful in clinical practice. Here, we aim to combine the information from multiple EEG biomarkers into a diagnostic classification index in order to improve the accuracy of predicting conversion from MCI to AD within a 2-year period. We followed 86 patients initially diagnosed with MCI for 2 years during which 25 patients converted to AD. We show that multiple EEG biomarkers mainly related to activity in the beta-frequency range (13–30 Hz) can predict conversion from MCI to AD. Importantly, by integrating six EEG biomarkers into a diagnostic index using logistic regression the prediction improved compared with the classification using the individual biomarkers, with a sensitivity of 88% and specificity of 82%, compared with a sensitivity of 64% and specificity of 62% of the best individual biomarker in this index. In order to identify this diagnostic index we developed a data mining approach implemented in the Neurophysiological Biomarker Toolbox (http://www.nbtwiki.net/). We suggest that this approach can be used to identify optimal combinations of biomarkers (integrative biomarkers) also in other modalities. Potentially, these integrative biomarkers could be more sensitive to disease progression and response to therapeutic intervention.
Neurophysiological Biomarkers; Alzheimer's disease; mild cognitive impairment (MCI); electroencephalography; predictive analysis; time series analysis; eyes closed resting state
Although the development of early-onset dementia is a radical and invalidating experience for both patient and family there are hardly any non-pharmacological studies that focus on this group of patients. One type of a non-pharmacological intervention that appears to have a beneficial effect on cognition in older persons without dementia and older persons at risk for dementia is exercise. In view of their younger age early-onset dementia patients may be well able to participate in an exercise program. The main aim of the EXERCISE-ON study is to assess whether exercise slows down the progressive course of the symptoms of dementia.
One hundred and fifty patients with early-onset dementia are recruited. After completion of the baseline measurements, participants living within a 50 kilometre radius to one of the rehabilitation centres are randomly assigned to either an aerobic exercise program in a rehabilitation centre or a flexibility and relaxation program in a rehabilitation centre. Both programs are applied three times a week during 3 months. Participants living outside the 50 kilometre radius are included in a feasibility study where participants join in a daily physical activity program set at home making use of pedometers. Measurements take place at baseline (entry of the study), after three months (end of the exercise program) and after six months (follow-up). Primary outcomes are cognitive functioning; psychomotor speed and executive functioning; (instrumental) activities of daily living, and quality of life. Secondary outcomes include physical, neuropsychological, and rest-activity rhythm measures.
The EXERCISE-ON study is the first study to offer exercise programs to patients with early-onset dementia. We expect this study to supply evidence regarding the effects of exercise on the symptoms of early-onset dementia, influencing quality of life.
The present study is registered within The Netherlands National Trial Register (ref: NTR2124)
Dementia; Early-onset dementia; Presenile dementia; Intervention; Physical activity; Exercise; Randomized controlled trial
White matter hyperintensities (WMH) can lead to dementia but the underlying physiological mechanisms are unclear. We compared relative oscillatory power from electroencephalographic studies (EEGs) of 17 patients with subcortical ischemic vascular dementia, based on extensive white matter hyperintensities (SIVD-WMH) with 17 controls to investigate physiological changes underlying this diagnosis.
Differences between the groups were large, with a decrease of relative power of fast activity in patients (alpha power 0.25 ± 0.12 versus 0.38 ± 0.13, p = 0.01; beta power 0.08 ± 0.04 versus 0.19 ± 0.07; p<0.001) and an increase in relative powers of slow activity in patients (theta power 0.32 ± 0.11 versus 0.14 ± 0.09; p<0.001 and delta power 0.31 ± 0.14 versus 0.23 ± 0.09; p<0.05). Lower relative beta power was related to worse cognitive performance in a linear regression analysis (standardized beta = 0.67, p<0.01).
This pattern of disturbance in oscillatory brain activity indicate loss of connections between neurons, providing a first step in the understanding of cognitive dysfunction in SIVD-WMH.
EEG; Oscillations; Spectral analysis; Relative power; Vascular dementia; Cognition; White matter
Although studies show a negative relationship between physical activity and the risk for cognitive impairment and late-onset Alzheimer's disease, studies concerning early-onset Alzheimer's disease (EOAD) are lacking. This review aims to justify the value of exercise interventions in EOAD by providing theoretical considerations that include neurobiological processes.
A literature search on key words related to early-onset dementia, exercise, imaging, neurobiological mechanisms, and cognitive reserve was performed. Results/Conclusion: Brain regions and neurobiological processes contributing to the positive effects of exercise are affected in EOAD and, thus, provide theoretical support for exercise interventions in EOAD. Finally, we present the design of a randomized controlled trial currently being conducted in early-onset dementia patients.
Dementia; Early-onset Alzheimer's disease; Early-onset dementia; Intervention; Physical activity; Presenile dementia
To develop a visual rating scale for posterior atrophy (PA) assessment and to analyse whether this scale aids in the discrimination between Alzheimer’s disease (AD) and other dementias.
Magnetic resonance imaging of 118 memory clinic patients were analysed for PA (range 0–3), medial temporal lobe atrophy (MTA) (range 0–4) and global cortical atrophy (range 0–3) by different raters. Weighted-kappas were calculated for inter- and intra-rater agreement. Relationships between PA and MTA with the MMSE and age were estimated with linear-regression analysis.
Intra-rater agreement ranged between 0.93 and 0.95 and inter-rater agreement between 0.65 and 0.84. Mean PA scores were higher in AD compared to controls (1.6 ± 0.9 and 0.6 ± 0.7, p < 0.01), and other dementias (0.8 ± 0.8, p < 0.01). PA was not associated with age compared to MTA (B = 1.1 (0.8) versus B = 3.1 (0.7), p < 0.01)). PA and MTA were independently negatively associated with the MMSE (B = −1.6 (0.5), p < 0.01 versus B = −1.4 (0.5), p < 0.01).
This robust and reproducible scale for PA assessment conveys independent information in a clinical setting and may be useful in the discrimination of AD from other dementias.
Alzheimer; Dementia; MRI; Posterior atrophy
We investigated progression of atrophy in vivo, in Alzheimer’s disease (AD), and mild cognitive impairment (MCI). We included 64 patients with AD, 44 with MCI and 34 controls with serial MRI examinations (interval 1.8 ± 0.7 years). A nonlinear registration algorithm (fluid) was used to calculate atrophy rates in six regions: frontal, medial temporal, temporal (extramedial), parietal, occipital lobes and insular cortex. In MCI, the highest atrophy rate was observed in the medial temporal lobe, comparable with AD. AD patients showed even higher atrophy rates in the extramedial temporal lobe. Additionally, atrophy rates in frontal, parietal and occipital lobes were increased. Cox proportional hazard models showed that all regional atrophy rates predicted conversion to AD. Hazard ratios varied between 2.6 (95% confidence interval (CI) = 1.1–6.2) for occipital atrophy and 15.8 (95% CI = 3.5–71.8) for medial temporal lobe atrophy. In conclusion, atrophy spreads through the brain with development of AD. MCI is marked by temporal lobe atrophy. In AD, atrophy rate in the extramedial temporal lobe was even higher. Moreover, atrophy rates also accelerated in parietal, frontal, insular and occipital lobes. Finally, in nondemented elderly, medial temporal lobe atrophy was most predictive of progression to AD, demonstrating the involvement of this region in the development of AD.
Alzheimer’s disease; Magnetic resonance imaging; Atrophy; Image processing; Computer-assisted
Although a large body of knowledge about both brain structure and function has been gathered over the last decades, we still have a poor understanding of their exact relationship. Graph theory provides a method to study the relation between network structure and function, and its application to neuroscientific data is an emerging research field. We investigated topological changes in large-scale functional brain networks in patients with Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD) by means of graph theoretical analysis of resting-state EEG recordings. EEGs of 20 patients with mild to moderate AD, 15 FTLD patients, and 23 non-demented individuals were recorded in an eyes-closed resting-state. The synchronization likelihood (SL), a measure of functional connectivity, was calculated for each sensor pair in 0.5–4 Hz, 4–8 Hz, 8–10 Hz, 10–13 Hz, 13–30 Hz and 30–45 Hz frequency bands. The resulting connectivity matrices were converted to unweighted graphs, whose structure was characterized with several measures: mean clustering coefficient (local connectivity), characteristic path length (global connectivity) and degree correlation (network 'assortativity'). All results were normalized for network size and compared with random control networks.
In AD, the clustering coefficient decreased in the lower alpha and beta bands (p < 0.001), and the characteristic path length decreased in the lower alpha and gamma bands (p < 0.05) compared to controls. In FTLD no significant differences with controls were found in these measures. The degree correlation decreased in both alpha bands in AD compared to controls (p < 0.05), but increased in the FTLD lower alpha band compared with controls (p < 0.01).
With decreasing local and global connectivity parameters, the large-scale functional brain network organization in AD deviates from the optimal 'small-world' network structure towards a more 'random' type. This is associated with less efficient information exchange between brain areas, supporting the disconnection hypothesis of AD. Surprisingly, FTLD patients show changes in the opposite direction, towards a (perhaps excessively) more 'ordered' network structure, possibly reflecting a different underlying pathophysiological process.
Alzheimer disease (AD) can now be diagnosed in subjects with mild cognitive impairment (MCI) using biomarkers. However, little is known about the rate of decline in those subjects. In this cohort study, we aimed to assess the conversion rate to dementia and identify prognostic markers in subjects with MCI and evidence of amyloid pathology.
We pooled subjects from the VU University Medical Center Alzheimer Center and the Development of Screening Guidelines and Criteria for Predementia Alzheimer's Disease (DESCRIPA) study. We included subjects with MCI, an abnormal level of β-amyloid1−42 (Aβ1–42) in the CSF, and at least one diagnostic follow-up visit. We assessed the effect of APOE genotype, CSF total tau (t-tau) and tau phosphorylated at threonine 181 (p-tau) and hippocampal volume on time to AD-type dementia using Cox proportional hazards models and on decline on the Mini-Mental State Examination (MMSE) using linear mixed models.
We included 110 subjects with MCI with abnormal CSF Aβ1–42 and a mean MMSE score of 26.3 ± 2.8. During a mean follow-up of 2.2 ± 1.0 (range 0.4–5.0) years, 63 subjects (57%) progressed to AD-type dementia. Abnormal CSF t-tau (hazard ratio [HR] 2.3, 95% confidence interval [CI] 1.1–4.6, p = 0.03) and CSF p-tau (HR 3.5, 95% CI 1.3–9.2, p = 0.01) concentration and hippocampal atrophy (HR 2.5, 95% CI 1.1–5.6, p = 0.02) predicted time to dementia. For subjects with both abnormal t-tau concentration and hippocampal atrophy, HR was 7.3 (95% CI 1.0–55.9, p = 0.06). Furthermore, abnormal CSF t-tau and p-tau concentrations and hippocampal atrophy predicted decline in MMSE score.
In subjects with MCI and evidence of amyloid pathology, the injury markers CSF t-tau and p-tau and hippocampal atrophy can predict further cognitive decline.