Imaging in Alzheimer's disease

Neuroimaging in the early differential diagnosis of dementia has gained considerable interest over the last decade. From being used for exclusive purposes only, neuroimaging is now in the forefront of aiding in the diagnosis of Alzheimer's disease (AD), frontotemporal dementia, vascular dementia, and and dementia with Lewy bodies (DLB). With the exception of dopamine transporter single photon-emission computed tomography imaging in DLB, imaging has not yet been incorporated into the diagnostic criteria for the various dementia syndromes, but that will soon change. The recently formulated research criteria for early AD recently formulated by Dubois et al explicitly mention magnetic resonance imaging and positron emission tomography for AD, and are an example of a new diagnostic process developing. In this review, the various imaging techniques will be highlighted, with an emphasis on their ability to diagnose Alzheimer's disease and separate it from other entities

Attention modulates hemispheric differences in functional connectivity: Evidence from MEG recordings

The present study examined intrahemispheric functional connectivity during rest and dichotic listening in 8 male and 9 female healthy young adults measured with magnetoencephalography (MEG). Generalized synchronization within the separate hemispheres was estimated by means of the synchronization likelihood that is sensitive to linear as well as non-linear coupling of MEG signals. We found higher functional intrahemispheric connectivity of frontal and temporal areas within the right as compared to the left hemisphere in the lower and higher theta band during rest, and in the lower theta band during dichotic listening. In addition, higher synchronization in the lower theta band correlated with better task performance. In the upper alpha band, hemispheric differences in intrahemispheric connectivity of the frontal regions were found to be modulated by focused attention instructions. That is, attention to the right ear exaggerates the pattern of higher synchroniza

Steklov problem on differential forms

In this paper we study spectral properties of Dirichlet-to-Neumann map on differential forms obtained by a slight modification of the definition due to Belishev and Sharafutdinov. The resulting operator $\Lambda$ is shown to be self-adjoint on the subspace of coclosed forms and to have purely discrete spectrum there.We investigate properies of eigenvalues of $\Lambda$ and prove a Hersch-Payne-Schiffer type inequality relating products of those eigenvalues to eigenvalues of Hodge Laplacian on the boundary. Moreover, non-trivial eigenvalues of $\Lambda$ are always at least as large as eigenvalues of Dirichlet-to-Neumann map defined by Raulot and Savo. Finally, we remark that a particular case of $p$-forms on the boundary of $2p+2$-dimensional manifold shares a lot of important properties with the classical Steklov eigenvalue problem on surfaces.Comment: 18 page

A composite measure of cognitive and functional progression in Alzheimer's disease: Design of the Capturing Changes in Cognition study

markdownabstract__Introduction__ Cognitive testing in Alzheimer's disease (AD) is essential for establishing diagnosis, monitoring progression, and evaluating treatments. Assessments should ideally be brief, reliable, valid, and reflect clinically meaningful changes. There is a lack of instruments that meet all these criteria. In the Capturing Changes in Cognition (Catch-Cog) study, we seek to correct these deficiencies through the development and validation of a composite measure combining cognition and function: the cognitive-functional composite (CFC). We expect that the CFC is able to detect clinically relevant changes over time in early dementia stages of AD. __Methods/Design__ We will include patients (n = 350) with mild cognitive impairment or mild dementia due to AD from memory clinics in the Netherlands and the United Kingdom. We will include cognitively healthy volunteers (n = 30) as a control group. The CFC is based on the “cognitive composite” and the Amsterdam instrumental activities of daily living questionnaire. We will investigate test–retest reliability with baseline and 2- to 3-week follow-up assessments (n = 50 patients and n = 30 healthy controls). We will involve experts and participants to evaluate the initial feasibility and refine the CFC if needed. Subsequently, we will perform a longitudinal construct validation study in a prospective cohort (n = 300) with baseline, 3-, 6-, and 12-month follow-up assessments. The main outcome is cognitive and functional progression measured by the CFC. Reference measures for progression include traditional cognitive and functional tests, disease burden measures, and brain imaging methods. Using linear mixed modeling, we will investigate longitudinal changes on the CFC and relate these to the reference measures. Using linear regression analyses, we will evaluate the influence of possible confounders such as age, gender, and education on the CFC. __Discussion__ By performing an independent longitudinal construct validation, the Catch-Cog study of the novel CFC will contribute to the improvement of disease monitoring and treatment evaluation in early dementia stages of AD

The Alzheimer’s Disease Drug Development Landscape

Background: Alzheimer’s disease (AD) is a devastating neurodegenerative disease leading to dementia. The field has made significant progress over the last 15 years. AD diagnosis has shifted from syndromal, based on signs and symptoms, to a biomarker construct based on the pathological hallmarks of the disease: amyloid β deposition, pathologic tau, and neurodegeneration. Numerous genetic risk factors for sporadic AD have been identified, providing further insight into the molecular underpinnings of the disease. For the last two decades, however, drug development for AD has been proven to be particularly challenging. Here, we provide a unique overview of the drug development landscape for AD. By comparing preclinical and clinical drug development pipelines, we aim to describe trends and differences regarding target classes and therapeutic modalities in preclinical and clinical development. Methods: We analyzed proprietary and public databases and company websites for drugs in preclinical development for AD by the pharmaceutical industry and major clinical trial registries for drugs in clinical development for AD. Drugs were categorized by target class and treatment modality. Results: We found a higher proportion of preclinical interventions targeting molecular pathways associated with sporadic AD genetic risk variants, compared to clinical stage interventions. These include apolipoprotein E (ApoE) and lipids, lysosomal/endosomal targets, and proteostasis. Further, we observed a trend suggesting that more traditional therapeutic modalities are developed for these novel targets, while more novel treatment modalities such as gene therapies and enzyme treatments are in development for more traditional targets such as amyloid β and tau. Interestingly, the percentage of amyloid β targeting therapies in preclinical development (19.2%) is even higher than the percentage in clinical development (10.7%), indicating that diversification away from interventions targeting amyloid-beta has not materialized. Inflammation is the second most popular target class in both preclinical and clinical development. Conclusions: Our observations show that the AD drug development pipeline is diversifying in terms of targets and treatment modalities, while amyloid-targeting therapies remain a prominent avenue of development as well. To further advance AD drug development, novel companion diagnostics are needed that are directed at disease mechanisms related to genetic risk factors of AD, both for patient stratification and assessment of therapeutic efficacy in clinical trials

Association of Education and Intracranial Volume With Cognitive Trajectories and Mortality Rates Across the Alzheimer Disease Continuum

OBJECTIVE: To investigate relationships of education and intracranial volume (factors related to cognitive versus brain reserve, respectively) with cognitive trajectories and mortality in individuals with biomarker-defined Alzheimer's disease (AD). METHODS: We selected 1,298 amyloid-β-positive memory clinic patients with subjective cognitive decline (SCD, n=142), mild cognitive impairment (MCI, n=274) and AD dementia (n=882) from the Amsterdam Dementia Cohort. All participants underwent baseline MRI and neuropsychological assessment, and 68% received cognitive follow-up (median=2.3 years, interquartile range=2.4). Mortality data were collected from the Central Public Administration. In the total sample and stratified by disease stage (i.e., SCD/MCI versus dementia), we examined education and intracranial volume as predictors of baseline and longitudinal cognitive performance on five cognitive domains [memory, attention, executive, language and visuospatial functions] (linear mixed models) and time-to-death (Cox proportional hazard models). Analyses were adjusted for age, sex, whole-brain gray matter atrophy and MRI field strength. RESULTS: Education and intracranial volume showed consistent positive associations with baseline cognition across disease stages. Longitudinally, we observed a relationship between higher education and faster cognitive decline among dementia patients on global cognition, memory, executive function and language (range β=-0.06-[-0.13], all p<0.05). Furthermore, in the total sample, both higher education and intracranial volume related to lower mortality risk (hazard ratio=0.84 and 0.82, respectively, p<0.05). CONCLUSIONS: In this amyloid-β-positive memory clinic sample, both reserve factors were positively associated with baseline cognition, whereas only education related to longitudinal cognition (i.e., accelerated decline among higher-educated patients with dementia). Moreover, higher education and intracranial volume both moderately attenuated overall mortality risk in AD

Reproducibility of quantitative (R)-[11C]verapamil studies

Background P-glycoprotein [Pgp] dysfunction may be involved in neurodegenerative diseases, such as Alzheimer's disease, and in drug resistant epilepsy. Positron emission tomography using the Pgp substrate tracer (R)-[11C]verapamil enables in vivo quantification of Pgp function at the human blood-brain barrier. Knowledge of test-retest variability is important for assessing changes over time or after treatment with disease-modifying drugs. The purpose of this study was to assess reproducibility of several tracer kinetic models used for analysis of (R)-[11C]verapamil data. Methods Dynamic (R)-[11C]verapamil scans with arterial sampling were performed twice on the same day in 13 healthy controls. Data were reconstructed using both filtered back projection [FBP] and partial volume corrected ordered subset expectation maximization [PVC OSEM]. All data were analysed using single-tissue and two-tissue compartment models. Global and regional test-retest variability was determined for various outcome measures. Results Analysis using the Akaike information criterion showed that a constrained two-tissue compartment model provided the best fits to the data. Global test-retest variability of the volume of distribution was comparable for single-tissue (6%) and constrained two-tissue (9%) compartment models. Using a single-tissue compartment model covering the first 10 min of data yielded acceptable global test-retest variability (9%) for the outcome measure K1. Test-retest variability of binding potential derived from the constrained two-tissue compartment model was less robust, but still acceptable (22%). Test-retest variability was comparable for PVC OSEM and FBP reconstructed data. Conclusion The model of choice for analysing (R)-[11C]verapamil data is a constrained two-tissue compartment model