In order to avoid the situation where two investigators study the same research question, please search our database to determine if your topic has already been studied. If you find that your topic or a related topic has already been submitted, you may wish to contact the investigator to inquire about his/her findings to determine how you might proceed. You may wish to collaborate or modify your request to avoid overlap. The results below reflect requests made since online requests have been accepted. As such, not all fields will have data as certain information, such as aims, were not collected until recently. If an entry has been assigned an ID # (e.g. DIAN-D1004), the full request has been submitted and is either approved, disapproved or in process.
Investigator: Prof Daniel Alexander
Title: Computational Modelling and Inference of Neurodegenerative Disease Propagation (CU-MONDAI)
Date of Request: September 29, 2023
Status: pending approval
ID: DIAN-D2324
Aim 1: To provide new insights into how pathology spread is linked to the brain’s connectivity architecture in autosomal dominant Alzheimer’s disease and validate new computational models of pathology propagation in neurodegenerative diseases.
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Investigator: Junie Saint Clair
Title: Examining the Predictive Value of Synaptic Dysfunction and Neuronal Injury Measures on Imaging Markers of Disease Presentation and Progression in Alzheimer’s Disease
Date of Request: September 26, 2023
Status: pending approval
ID: DIAN-D2323
Aim 1: Evaluate association between rates of longitudinal change in CSF levels of Ng, SNAP-25, VILIP-1 and imaging brain changes and cognition in a DIAD cohort.
Aim 2: Evaluate association between rates of longitudinal change in CSF levels of Ng, SNAP-25, VILIP-1 and imaging brain changes and cognition in aged adults LOAD cohort.
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Investigator: Seonjoo Lee
Title: Evaluating neural correlates of apathy in Alzheimer’s disease
Date of Request: September 18, 2023
Status: pending approval
ID: DIAN-D2322
Aim 1: Aim1. We will seek to determine if apathy is embedded in a larger network of NPS and functional and cognitive impairment using clustering analysis. In the subset of data with neuropathology information, we will identify the association between apathy clusters and neuropathology.
Aim 2: Aim2. We will examine brain morphometry, structural connectivity, metabolism, amyloid PET in reward-sensitive areas, and effort valuation processing areas in apathy and/or its networks.
Aim 3: Aim3. We will evaluate the association between the intrinsic time scale (fMRI) and apathy and apathy networks in the course of disease.
Aim 4: Aim3. We will evaluate the association between the intrinsic time scale (fMRI) and apathy and apathy networks in the course of disease.
Investigator: nil
Title: Prediction of Alzheimer’s Disease through multimodal approach by machine learning
Date of Request: September 7, 2023
Status: pending approval
ID: DIAN-D2321
Aim 1: Develop a multimodal machine learning model to accurately predict Alzheimer’s disease progression using a combination of imaging, genetic, and clinical data.
Aim 2: Investigate the potential biomarkers and features from various modalities that contribute significantly to the early detection and progression tracking of Alzheimer’s disease.
Aim 3: Evaluate the model’s performance in predicting Alzheimer’s risk and progression in a diverse patient population, including individuals with different genetic backgrounds and demographics.
Aim 4: Evaluate the model’s performance in predicting Alzheimer’s risk and progression in a diverse patient population, including individuals with different genetic backgrounds and demographics.
Investigator: Jee Hoon Roh/Jae-Hong Lee
Title: Epigenetic analyses to assess the resilience among DIAN mutation carriers
Date of Request: September 5, 2023
Status: pending approval
ID: DIAN-D2320
Aim 1: To investigate the potential epigenetic causes of resilience among DIAN mutation carriers who are discordant in disease courses measured by biomarkers
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Investigator: Dr Shahid Zaman
Title: Knowledge Guided Machine Learning for Prognosis Forecast ing of Alzheimer’s Disease in People with Down Syndrome
Date of Request: August 17, 2023
Status: pending approval
ID: DIAN-D2319
Aim 1: explore different methods, such as data augmentation, transfer learning, and knowledge-guided generative adversarial networks (GANs), to address the insufficient training data issue thus improve the quality of data representations
Aim 2: the fusion of the valuable domain-specific knowledge of AD and designs of graph neural networks will be explored to improve the robustness and interpretability in diagnosis and prognosis of AD
Aim 3: develop multimodal machine learning frameworks for early diagnosis and prognosis of AD
Aim 4: develop multimodal machine learning frameworks for early diagnosis and prognosis of AD
Investigator: Le Shi
Title: The association of sleep disturbance and β-amyloid pathology among cognitively normal older adults
Date of Request: August 9, 2023
Status: pending approval
ID: DIAN-D2318
Aim 1: Using the data obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) Database and DIAN Observational Database.
Aim 2: The sample consisted of CN individuals aged between 55 and 90 years with Aβ positron emission tomography scan, APOE genotype, and sleep behaviors.
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Investigator: Ruichen Han
Title: Functional connections in the hippocampus subregion of familial Alzheimer’s disease before symptoms as biomarkers for predicting disease status
Date of Request: August 5, 2023
Status: pending approval
ID: DIAN-D2316
Aim 1: To investigate whether there are differences in the damage patterns of brain functional network connections between familial Alzheimer’s disease and sporadic Alzheimer’s disease
Aim 2: To explore can functional connections serve as a biomarker to predict cognitive state
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Investigator: Karin Meeker
Title: Tau Phosphorylation in Preclinical and Symptomatic Autosomal Dominant Alzheimer Disease
Date of Request: August 5, 2023
Status: pending approval
ID: DIAN-D2317
Aim 1: Temporal progression of tauopathy. Tau sites (e.g., pT181, pT202, pT205, pT217) will be assessed in relation to preclinical AD biomarkers (e.g., CSF Ab42) and biomarkers of symptom onset (e.g., CSF total tau, RS-FC, cognitive performance), and EYO. Longitudinal changes in variables will also be plotted against EYO to determine temporal trajectories and to assess how biomarkers change relative to one another across disease progression. It is hypothesized that elevation of each site will occur at varying stages of the disease process and will follow distinct individual trajectories over time. Specifically, it is expected that relative to other tau sites, elevation in CSF pT217 and pT181 levels will arise first and will most strongly associate with preclinical biomarkers, such as CSF Ab42, while other tau sites will become elevated later in the disease process and will most strongly associate with biomarkers of symptom onset.
Aim 2: Spatial progression of tauopathy in ADAD. Compared to established biomarkers (e.g., amyloid and total tau), it is unknown how phosphorylated tau sites differentially relate to and drive alterations in resting state brain network dynamics during the preclinical and clinical phases of ADAD. To determine whether specific tau sites are associated with alterations in brain network RS-FC organization, tau sites will be cross-sectionally correlated with within-network and between-network RS-FC. Longitudinal changes in tau sites and RS-FC will additionally be correlated and plotted against EYO to determine whether changes in tau sites and RS-FC arise in a specific pattern, and more specifically to elucidate the spatial progression of tauopathy. It is hypothesized that elevated levels of CSF tau sites will be associated with a local to diffuse pattern of decreases in RS-FC, and that associations between tau sites and RS-FC will be greatest in regions where tau deposition occurs, as measured by tau positron emission tomography (PET).
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Investigator: Wencai Ding, Huan He.
Title: Association of cortical and subcortical microstructure with disease severity: impact on cognitive decline and language impairments in Dominantly Inherited Alzheimer’s disease.
Date of Request: July 25, 2023
Status: pending approval
ID: DIAN-D2315
Aim 1: We aimed to study the cortical and subcortical microstructural variations using surface-based analysis (cMD and cortical fractional anisotropy (cFA)) and TBSS (MD and FA)
Aim 2: We also explored the relationships between multimodal macrostructural/ microstructural measures and the clinical scale scores representing language abilities (verbal fluency test (VFT) and Boston naming test (BNT)).
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Investigator: song weihong
Title: Study the relationship between Glymphatic function, Aβ protein and cognitive decline in autosomal dominant Alzheimer disease.
Date of Request: July 25, 2023
Status: pending approval
ID: DIAN-D2314
Aim 1: To assess the glymphatic function in mutation carriers and non-carriers
Aim 2: Examine the relationship between Glymphatic function, Aβ protein and cognitive decline in autosomal dominant Alzheimer disease.
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Investigator: Giuseppe Barisano
Title: Evaluating the Role of Perivascular Spaces and White Matter Hyperintensities in Dominantly Inherited Alzheimer’s Disease and their Relationship with Amyloid and Tau
Date of Request: July 19, 2023
Status: pending approval
ID: DIAN-D2313
Aim 1: To assess the spatial distribution of v-PVS and WMH in mutation carriers vs. non-carriers
Aim 2: To assess the prevalence and severity of v-PVS and WMH in asymptomatic mutation carriers vs. non-carriers
Aim 3: To investigate the incidence of MRI-visible v-PVS and WMH in mutation carriers vs. non-carriers along the disease trajectory and their relationship with the incidence of amyloid and tau
Aim 4: To investigate the incidence of MRI-visible v-PVS and WMH in mutation carriers vs. non-carriers along the disease trajectory and their relationship with the incidence of amyloid and tau
Investigator: Matthew Dean
Title: Assessment of Basal Forebrain degeneration using MRI in Alzheimer’s Disease
Date of Request: July 6, 2023
Status: pending approval
ID: DIAN-D2312
Aim 1: To determine the pattern of basal forebrain measured by MRI degeneration in familial Alzheimer’s disease and relationships with biomarkers
Aim 2: To compare the pattern of basal forebrain degeneration measured by MRI in familial Alzheimer’s disease to sporadic disease
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Investigator: Beau Ances
Title: Comparison of Astrocyte-related Markers in Down Syndrome and Autosomal-Dominant Alzheimer Disease Using the Amyloid- Tau-Neurodegeneration (AT(N)) Framework
Date of Request: June 30, 2023
Status: pending approval
ID: DIAN-D2311
Aim 1: Evaluate and compare the association between plasma GFAP and imaging measures of AD in Down syndrome and ADAD.
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Investigator: Cyril Pottier
Title: Modifiers of Alzheimer’s disease: a genetic approach
Date of Request: April 28, 2023
Status: pending
ID: DIAN-D2310
Aim 1: To identify genetic modifiers of disease presentation in PSEN1 mutation carriers
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Investigator: Dr. Tallulah Andrews
Title: Single-nucleus RNAseq of a humanized mouse model of Alzheimer’s disease
Date of Request: April 24, 2023
Status: pending approval
ID: DIAN- D2309
Aim 1: Generate a novel humanized mouse model of AD with disease variants in APP and APOE genes.
Aim 2: Perform deep behavioural and molecular phenotyping of the mouse model
Aim 3: Perform snRNAseq of multiple brain regions of mouse model and compare to human snRNAseq from patients with AD
Aim 4: Perform snRNAseq of multiple brain regions of mouse model and compare to human snRNAseq from patients with AD
Investigator: Nelly Joseph-Mathurin
Title: Evaluation of the neurovascular unit in the setting of pathogenesis and treatment of autosomal dominant Alzheimer disease
Date of Request: April 21, 2023
Status: approved
ID: DIAN-D2308
Aim 1: Perform proteomic characterization of NVU disruption and develop imaging markers of vascular changes in ADAD.
Aim 2: Determine the trajectories of NVU disruption markers and their relation to the pattern of disease progression in ADAD.
Aim 3: Examine influence of NVU disruption on drug efficacy and safety outcome measures in ADAD.
Aim 4: Examine influence of NVU disruption on drug efficacy and safety outcome measures in ADAD.
Investigator: Randall J Bateman
Title: Biomarker progression modeling in autosomal-dominant Alzheimer’s disease and implications for clinical trial design
Date of Request: April 21, 2023
Status: approved
ID: DIAN-D2307
Aim 1: Modeling biomarker progression in the DIAN population
Aim 2: Using biomarker progression modeling to inform clinical trial design
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Investigator: Dr. Eric M McDade
Title: Drug Dose Modeling for potential inclusion in the DIAN-TU 002 trial
Date of Request: April 4, 2023
Status: approved
ID: DIAN-D2306
Aim 1: Conduct dose modeling projections for the patient population of interest in the study to determine dose selection and sample size.
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Investigator: Dr Sarah Bauermeister
Title: Biopsychosocial determinants of cognitive and biomarker trajectories in preclinical Alzheimer’s disease
Date of Request: March 23, 2023
Status: pending review
ID: DIAN-D2305
Aim 1: The first objective is to characterise the biopsychosocial determinants of AD across modifiable and non-modifiable factors throughout the lifespan across multiple cohorts including Memento, DIAN, WRAP, ADNI, BIOCARD, SMC amyloid, and other DPUK databases. The latent constructs, which have not previously been examined in such extensive detail, include physical health, mental health, diet, family history, sex, ethnicity, education, sociality, life functionality, employment, and traumatic brain injury.
Aim 2: The second objective is to explore an AD prediction model utilising PET amyloid data, building on objective 1. Designed utilising the significant constructs, the hypothesis is that this novel disease model will predict preclinical AD with relative accuracy in patient populations to facilitate earlier and more accurate disease diagnoses .
Aim 3: The third objective is to investigate the relationship between the biopsychosocial determinants included in the disease prediction model and structural brain changes (MRI). Utilising the BHC and healthy control cohorts, the study hypothesises that there will be a significant difference in health/lifestyle outcomes between the two populations as well as a significant relationship between these outcomes and level of cognitive/structural impairment, thus strengthening the role of biopsychosocial determinants in disease trajetory
Aim 4: The third objective is to investigate the relationship between the biopsychosocial determinants included in the disease prediction model and structural brain changes (MRI). Utilising the BHC and healthy control cohorts, the study hypothesises that there will be a significant difference in health/lifestyle outcomes between the two populations as well as a significant relationship between these outcomes and level of cognitive/structural impairment, thus strengthening the role of biopsychosocial determinants in disease trajetory
Investigator: Prof Ralph Martins
Title: Temporal ordering of plasma biomarkers and their association with amyloid pathology, cerebral atrophy, cerebral metabolism and cognition in autosomal dominant Alzheimer’s disease
Date of Request: March 8, 2023
Status: withdrawn
ID: DIAN-D2304
Aim 1: Investigate the temporal order of AD-related plasma biomarker (abeta42/40 ratio, p-tau181, GFAP and NFL) divergence between ADAD mutation carriers and non-carriers as a function of EYO.
Aim 2: Investigate the association of AD-related plasma biomarkers with Aβ pathology (PiB-PET) and ADAD severity (CDR global) in mutation carriers.
Aim 3: Investigate the cross-sectional association of plasma biomarkers with neurodegeneration (hippocampal volume and precuneus thickness), cognition (MMSE, CDR-SB and composite cognition score) and cerebral metabolism (FDG-PET).
Aim 4: Investigate the cross-sectional association of plasma biomarkers with neurodegeneration (hippocampal volume and precuneus thickness), cognition (MMSE, CDR-SB and composite cognition score) and cerebral metabolism (FDG-PET).
Investigator: Ben Handen
Title: Comparison of plasma NfL in ABC-DS and DIAN
Date of Request: March 3, 2023
Status: pending review
ID: DIAN-D2303
Aim 1: Compare plasma NfL in ABC-DS and DIAN as a function of brain structure
Aim 2: Examine how plasma NfL and brain structure vary based on DIAN mutation type and location
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Investigator: Chia-Ling Phuah
Title: WMH Spatial Patterns in ADAD
Date of Request: February 21, 2023
Status: approved
ID: DIAN-D2302
Aim 1: Evaluate for difference(s) in WMH topographical distributions between AD and CAA
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Investigator: Randall J. Bateman
Title: DIAN OBS Data for the DIAN-TU OLE
Date of Request: January 31, 2023
Status: approved
ID: DIAN-D2301
Aim 1: Identify participant data to use as external controls for the DIAN-TU OLE
Aim 2: Pull the selected data and analyze as external controls for the DIAN-TU OLE.
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Investigator: Nicole McKay
Title: Investigating how white matter integrity and tauopathy underpin cognitive decline in autosomal dominant Alzheimer disease.
Date of Request: October 24, 2022
Status: approved
ID: DIAN-D2221
Aim 1: Characterize attentional control in autosomal dominant Alzheimer disease
Aim 2: Examine the relationship between attentional control and biomarkers of white matter health in autosomal dominant Alzheimer disease.
Aim 3: Consider the relationship between attentional control and tau in autosomal dominant Alzheimer disease.
Aim 4: Consider the relationship between attentional control and tau in autosomal dominant Alzheimer disease.
Investigator: Haiyan Liu
Title: Estimated Year of Symptoms at Onset in DIAD-A Systemic Review and Meta-analysis
Date of Request: September 28, 2022
Status: approved
ID: DIAN-D2220
Aim 1: 1. To identify newly described highly penetrant DIAD variants using data from DIAN-OBS, DIAN-TU and from a literature review.
Aim 2: 2. To update the DIAD mutation AAO using data from DIAN-OBS, DIAN-TU and from a literature review
Aim 3: 3. To determine the accuracy of the AAO and EYO model to predict the actual symptom onset.
Aim 4: 3. To determine the accuracy of the AAO and EYO model to predict the actual symptom onset.
Investigator: Peter Millar
Title: Modeling brain-predicted age in autosomal dominant Alzheimer disease
Date of Request: September 14, 2022
Status: approved
ID: DIAN-D2219
Aim 1: Generate machine learning model predictions of brain age from functional connectivity MRI and evaluate as a marker of autosomal dominant AD progression
Aim 2: Generate machine learning model predictions of brain age from volumetric MRI and evaluate as a marker of autosomal dominant AD progression
Aim 3: Compare functional and volumetric brain age estimates to existing MRI features in autosomal dominant AD
Aim 4: Compare functional and volumetric brain age estimates to existing MRI features in autosomal dominant AD
Investigator: Randall Bateman
Title: Influence of biological sex and gender identity in the spectrum of Autosomal Dominant Alzheimer’s Disease: An Investigation from the Dominantly Inherited Alzheimer’s Network (DIAN)
Date of Request: August 25, 2022
Status: approved
ID: DIAN-D2218
Aim 1: To compare age at onset, clinical presentation, neuropsychological performance and rate of cognitive decline between women and men.
Aim 2: To investigate possible differences in the spatial and temporal development of cerebral tau & amyloid-β, brain glucose metabolism, and structural atrophy, as well as their relationships, in women and men.
Aim 3: To compare fluid biomarker levels and rates of change between women and men.
Aim 4: To compare fluid biomarker levels and rates of change between women and men.
Investigator: Eileen Crimmins
Title: Race/Ethnicity Demographics of Alzheimers Disease Neuroimaging Studies
Date of Request: August 23, 2022
Status: pending review
ID: DIAN-D2217
Aim 1: Summarize race/ethnicity demographics of the DIAN observational study, in addition to other neuroimaging studies of Alzheimers Disease and aging
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Investigator: Haiyan Liu
Title: Autophagy-Lysosome network proteins and disease staging in DIAN
Date of Request: August 18, 2022
Status: approved
ID: DIAN-D2216
Aim 1: To identify autophagy-lysosome pathway protein changes in DIAD compared with control
Aim 2: To determine the relationship of classic AD biomarkers and relationship with autophagy-lysosome pathway proteins
Aim 3: To compare mitochondria functional protein changes in DIAD with control and their relationships with autophagy-lysosome pathway proteins.
Aim 4: To compare mitochondria functional protein changes in DIAD with control and their relationships with autophagy-lysosome pathway proteins.
Investigator: Chong Yao Feng
Title: Staging amyloid, tau and WMH co-evolution in Alzheimer’s disease
Date of Request: July 28, 2022
Status: approved
ID: DIAN-D2215
Aim 1: Apply machine learning algorithm to a dataset of amyloid PET data
Aim 2: Same as Aim 1, but with tau PET and WMH data added
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Investigator: Sun Lin
Title: Exploration for risk factors of cognitive impairment in non-dementia elderly
Date of Request: June 24, 2022
Status:
ID: DIAN-D2213
Aim 1: The correlation between psychiatry symptoms and cognitive impairment in non-dementia elderly
Aim 2: The effects of daily habits on cognitive impairment in non-dementia elderly
Aim 3: The predictive biomarkers for cognitive impairment in non-dementia elderly
Aim 4: The predictive biomarkers for cognitive impairment in non-dementia elderly
Investigator: Xiaohu Zhao
Title: Multimodal Magnetic Resonance Imaging Study of Abnormal Regulation Machanism of Default Mode Network in AD
Date of Request: June 4, 2022
Status:
ID: DIAN-D2212
Aim 1: To explore the abnormal DMN regulation mechanism in AD patients and its clinical relevance
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Investigator: Kamil A. Grajski, PhD
Title: Medial temporal lobe (MTL) – default-mode network (DMN) functional connectivity disruption in Autosomal Dominant Alzheimer’s Disease (ADAD) progression in a Dominantly Inherited Alzheimer Network (DIAN) cohort
Date of Request: May 1, 2022
Status:
ID: DIAN-D2211
Aim 1: Reprocess DIAN MRI data with FreeSurfer 7 and confirm progression of cortical thickness and subcortical volume results reported in McKay, N. S., et al. (2022).
Aim 2: Process rsfMRI data to characterize the progression of disruption in functional connectivity in the Default-Mode Network and related structures using an hybrid a priori and data-driven identification of ROI pairs of interest using a combination of AFNI and “home-grown” analytics.
Aim 3: Identify the subpopulation of DIAN patients for whom both MRI and rsfMRI data pass stringent quality criteria for inclusion. Establish the temporal correspondence of morphological and functional connectivity changes. For example, Grajski & Bressler (2019) showed in an ADNI cohort that functional connectivity changes may be detected prior to detection of morphological changes. Will the same, similar, or other hold for DIAN cohort(s)?
Aim 4: Identify the subpopulation of DIAN patients for whom both MRI and rsfMRI data pass stringent quality criteria for inclusion. Establish the temporal correspondence of morphological and functional connectivity changes. For example, Grajski & Bressler (2019) showed in an ADNI cohort that functional connectivity changes may be detected prior to detection of morphological changes. Will the same, similar, or other hold for DIAN cohort(s)?
Investigator: NA
Title: Develop an Item Response Theory Based Score for the Clinical Dementia Rating (CDR®)
Date of Request: April 10, 2022
Status:
ID: DIAN-D2210
Aim 1: Develop an item response theory (IRT) based score for the CDR based on the item level data collected for the CDR in DIAN Obs
Aim 2: Demonstrate the superiority of the IRT based score compared to the CDR sum of box in terms of detecting cognitive change and association with other cognitive/clinical, imaging and fluid biomarkers
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Investigator: Jonathan Wagg
Title: : Leverage DIAN data to derive and validate EYO estimation models applicable to Downs Syndrome (DS) populations
Date of Request: April 7, 2022
Status:
ID: DIAN-D2209
Aim 1: Review and analyze DIAN longitudinal clinical endpoint and biomarker measure changes over time that are: (i) of potential utility for development of EYO estimation models; (ii) comparable to measures available in longitudinal DS cohort datasets such as the ABC-DS cohort.
Aim 2: Use measures identified in (1.) to derive alternative model structures for EYO estimation in the DIAN population.
Aim 3: Compare the predictive performance of candidate model structures in the DIAN population.
Aim 4: Compare the predictive performance of candidate model structures in the DIAN population.
Investigator: Brian Gordon
Title: Comparing biomarkers between Down Syndrome, Autosomal Dominant, and Late onset Alzheimer Disease
Date of Request: March 25, 2022
Status: approved
ID: DIAN-D2208
Aim 1: How do measures of tau pathology measured using PET compare among DS, ADAD, and LOAD?
Aim 2: Does the spread of tau pathology over time differ between cohorts?
Aim 3: Are white matter lesions a common finding in all three forms of AD?
Aim 4: Are white matter lesions a common finding in all three forms of AD?
Investigator: kun zhao
Title: Alzheimer’s disease
Date of Request: March 18, 2022
Status:
ID: DIAN-D2207
Aim 1: e want to provide a reference point for each individual during aging to provide a reference at each time of the lifespan.
Aim 2: we also provide a frame for the intersection of multi neurodegenerative disease and mental disorder.
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Investigator: Randy Buckner
Title: Exploration of multimodal MRI Biomarkers in preclinical stage of Alzheimer’s Disease
Date of Request: March 16, 2022
Status:
ID: DIAN-D2206
Aim 1: The goal of this study is to combine multimodal structural imaging biomarkers to optimistically distinguish Alzheimer’s disease and normal aging in the early and mild stages of Alzheimer’s disease.
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Investigator: Professor John Gallacher
Title: The biopsychosocial determinants of cognitive change and Alzheimer’s disease
Date of Request: February 14, 2022
Status:
ID: DIAN-D2205
Aim 1: The overall aim of the project will be to assess the biopsychosocial determinants of Alzheimer’s disease across modifiable and non-modifiable factors
Aim 2: To profile cognitive change by biopsychosocial construct determinants
Aim 3: To profile cognitive change and AD by biopsychosocial construct determinants and genetic stratification
Aim 4: To profile cognitive change and AD by biopsychosocial construct determinants and genetic stratification
Investigator: John Ringman
Title: Biomarker Characterization of the A431E mutation in PSEN1
Date of Request: February 11, 2022
Status: approved
ID: DIAN-D2204
Aim 1: To assess plasma and CSF biomarkers associated with the A431E mutation in PSEN1.
Aim 2: To assess volumetric changes, white matter hyperintensities, and microhemorrhages on MRI seen in association with the A4341E mutation in PSEN1.
Aim 3: To assess cerebral amyloid deposition measured using PiB PET associated with the A4341E mutation in PSEN1.
Aim 4: To assess cerebral amyloid deposition measured using PiB PET associated with the A4341E mutation in PSEN1.
Investigator: Jasmeer Chhatwal
Title: Evaluating ADAD Mutation-specific Biomarker and Cognitive Trajectories (Renewal of 1606A)
Date of Request: February 9, 2022
Status:
ID: DIAN-D2203
Aim 1: Determine if simple categorizations of ADAD mutations can explain variability in biomarker and cognitive trajectories
Aim 2: Determine if biochemical characterizations of individual PSEN1 mutations can elucidate cognitive and biomarker trajectories in DIAN
Aim 3: Determine if there are mutation-specific effects that predict the development of CAA in mutation carriers
Aim 4: Determine if there are mutation-specific effects that predict the development of CAA in mutation carriers
Investigator: Jan Torleif Pedersen, PhD MSc
Title: Investigation of pS396-tau in samples from DIAN-TU biobank
Date of Request: February 1, 2022
Status:
ID: DIAN-D2202
Aim 1: Investigation of pS396-tau in samples from DIAN-TU biobank
Aim 2: To investigate pT217-tau levels in CSF samples from DIAN-TU
Aim 3: To establish potential correlation between pS396-tau, pT217-Tau and clinical progression parameters
Aim 4: To establish potential correlation between pS396-tau, pT217-Tau and clinical progression parameters
Investigator: Christopher Weise
Title: Hypothalamic volume in familial Alzheimer’s disease (FAD) and its associations with body weight and other FAD biomarkers
Date of Request: January 6, 2022
Status:
ID: DIAN-D2201
Aim 1: • To compare hypothalamic volume in symptomatic and asymptomatic FAD with healthy controls
Aim 2: • To investigate potential associations of hypothalamic volume with cross sectional body weight (BMI) and longitudinal body weight changes in participants with FAD
Aim 3: • To explore the relationship of hypothalamic volume with additional biomarkers (Aß-burden, glucose metabolism and CSF based biomarkers), clinical/cognitive parameters and EYO
Aim 4: • To explore the relationship of hypothalamic volume with additional biomarkers (Aß-burden, glucose metabolism and CSF based biomarkers), clinical/cognitive parameters and EYO
Investigator: Jee Hoon Roh/Jae-Hong Lee
Title: Epigenetic analyses to assess the resilience among DIAN mutation carriers
Date of Request: December 15, 2021
Status:
ID:
Aim 1: To investigate the potential epigenetic causes of resilience among DIAN mutation carriers who are discordant in disease courses measured by biomarkers.
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Investigator: Ni Shu
Title: Human brain connectome study with AD biomarkers
Date of Request: December 6, 2021
Status:
ID:
Aim 1: To develop an association analysis method for multi-modal human connectome
Aim 2: To systematically evaluate the damage patterns of the brain network due to AD biomarkers
Aim 3: To establish cross-scale correlation models for different stages of AD
Aim 4: To establish cross-scale correlation models for different stages of AD
Investigator: Rawan Tarawneh
Title: Proteomic and Transcriptomic Measures of Vascular Injury Markers in AD
Date of Request: November 23, 2021
Status:
ID:
Aim 1: Compare differences in CSF and brain RNA levels of the vascular injury markers (GDF-15, MCP-1, RAGE, MPO, IL-18, ST2/IL1R1, CDH5 [VE-cadherin], E-selectin, SDC3) between symptomatic ADAD mutation carriers, asymptomatic ADAD mutation carriers, and healthy controls.
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Investigator: Rawan Tarawneh
Title: Proteomic analyses of inflammatory pathways in ADAD
Date of Request: November 9, 2021
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ID:
Aim 1: Investigate the association of CSF proteomic signatures with cognition in ADAD
Aim 2: Investigate the associations of CSF proteomic signatures with brain atrophy in ADAD
Aim 3: Investigate the associations of CSF proteomics with amyloid and tau imaging in ADAD
Aim 4: Investigate the associations of CSF proteomics with amyloid and tau imaging in ADAD
Investigator: Catherine Kaczorowski
Title: Development of imaging-based biomarkers of resilience to assess the effectiveness of interventions in Alzheimer’s Disease mouse models
Date of Request: November 1, 2021
Status: Approved
ID: DIAN-D2117
Aim 1: develop resilience-based interventions towards promoting cognition resilience in Alzheimer’s Disease patients
Aim 2: identify common image-biomarkers that differentiate both resilient and susceptible AD-BXD mice as well as resilient/susceptible AD patients
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Investigator: Jonathan Kipnis
Title: Parenchymal border macrophages regulate brain physiology via CSF flow dynamics
Date of Request: October 25, 2021
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ID:
Aim 1: Identify key mechanisms driving amyloid beta pathology in both mice and humans.
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Investigator: Johannes Levin
Title: Correlates of synucleinopathy in DIAN mutation carriers
Date of Request: October 15, 2021
Status: Approved
ID: DIAN-D2116
Aim 1: The aim of the project is described in detail in data request DIAN-D1612 and amendment 1 and 2 to DIAN-D1612
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Investigator: Beau Ances and Tammie Benzinger
Title: Imaging Tauopathy in the Dominantly Inherited Alzheimer Network
Date of Request: October 13, 2021
Status:
ID:
Aim 1: To use an accelerated failure time model to see if plasma markers predict tau deposition.
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Investigator: Bateman
Title: Relationship between CSF sTREM2 and Cognitive Decline in AD
Date of Request: September 30, 2021
Status:
ID:
Aim 1: To characterize the relationship between soluble TREM2 (sTREM2) dynamics and the nature and magnitude of cognitive changes in autosomal dominant Alzheimer Disease (ADAD).
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Investigator: Prof. Dr. Johannes Levin
Title: Frequency and longitudinal course of neuropsychiatric symptoms in autosomal dominant Alzheimer’s Disease
Date of Request: September 10, 2021
Status: Approved
ID: DIAN-D2115
Aim 1: Describing neuropsychiatric phenotypes in ADAD mutation carriers using a data driven approach by PCA
Aim 2: Examine the occurence of neuropsychiatric symptoms in the course of the disease
Aim 3: Test whether structural and metabolic brain changes are associated with particular neuropsychiatric symptoms
Aim 4: Test whether structural and metabolic brain changes are associated with particular neuropsychiatric symptoms
Investigator: zhangjing
Title: Variation and study of dynamic effective connection in default model network of DIAN corhort
Date of Request: August 8, 2021
Status: Pending Approval
ID: DIAN-D2114
Aim 1: The dynamic effective connection method was used to study the related brain directed networks in AD patients with autosomal imaging inheritance
Aim 2: Identify relevant effective brain networks, especially the variation of DMN brain network structure, judge their abnormalities within and between networks, and look for specific network image markers
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Investigator: Arunima Kapoor
Title: Small Vessel Disease and Vascular Risk Factors in Dominantly Inherited Alzheimer’s Disease
Date of Request: August 3, 2021
Status: Pending Approval
ID: DIAN-D2113
Aim 1: To examine small vessel disease features, vascular risk factors and angiogenesis in dominantly inherited Alzheimer’s disease
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Investigator: Muriah Wheelock
Title: Network level analysis of progressive brain degeneration in autosomal dominant Alzheimer disease
Date of Request: July 23, 2021
Status: Approved
ID: DIAN-D2112
Aim 1: 1. Characterize the spatio-temporal progression of structural and functional brain network degeneration in AD based on estimated year of symptom onset
Aim 2: 2. Determine the relationship between neuronal injury markers based on blood (e.g., NfL), cerebrospinal fluid (e.g., AB42), and PET (e.g., tau) with MRI markers of brain network dysfunction and clinical symptoms of cognitive decline cross-sectionally and longitudinally.
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Investigator: N/A
Title: Relationship between regional baseline and longitudinal tau PET SUVR, and correlations with change in cognition in participants from the DIAN-TU study
Date of Request: July 19, 2021
Status: Approved
ID: DIAN-D2111
Aim 1: Characterize the spatial patterns of tau deposition at baseline and over time in the DIAD population
Aim 2: Estimate the rate of change in tau deposition in DIAD participants in each of the provided parcellated brain regions
Aim 3: Identify the (meta)ROI(s) at baseline that best correlate with change in tau PET SUVR and change in cognition, respectively, over time
Aim 4: Identify the (meta)ROI(s) at baseline that best correlate with change in tau PET SUVR and change in cognition, respectively, over time
Investigator: Eric Schaeffer
Title: Gene Therapy for ADAD patients harboring PS1 mutations
Date of Request: July 13, 2021
Status: Pending Approval
ID: DIAN-D2109
Aim 1: Develop AAV9 vectors expressing hPSEN1 (completed)
Aim 2: Evaluate AAV-PSEN1 vectors in transfected HEK293 cells and PS1 mutant iPSC lines (ongoing)
Aim 3: Evaluate AAV-PSEN1 vectors in PS1 mutant knock-in mice for rescue of biochemical and neuropathological phenotypes (ongoing)
Aim 4: Evaluate AAV-PSEN1 vectors in PS1 mutant knock-in mice for rescue of biochemical and neuropathological phenotypes (ongoing)
Investigator: NA
Title: Alzheimer’s Research Using Gene Expression Analysis Data
Date of Request: July 9, 2021
Status:
ID: DIAN-D2110
Aim 1: Evaluating transcriptional profile of activated microglia from brains of individuals with Alzheimer’s Disease (AD)
Aim 2: Comparing transcriptional profile from individuals with AD to transcriptional profiles of non AD controls
Aim 3: Comparing gene expression differences in AD cases and controls to the results of GWAS
Aim 4: Comparing gene expression differences in AD cases and controls to the results of GWAS
Investigator: Camille Parent
Title: Association of b-amyloid accumulation and cognitive decline in healthy older adults : a systematic review and meta-analysis
Date of Request: May 27, 2021
Status:
ID: DIAN-D2108
Aim 1: Systematic review and meta-analysis of selected articles studying the longitudinal association between amyloid accumulation and cognitive decline in preclinical Alzheimer’s disease (in cognitively healthy older adults)
Aim 2: Obtain data from the following article : Simultaneously evaluating the effect of baseline levels and longitudinal changes in disease biomarkers on cognition in dominantly inherited Alzheimer’s disease
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Investigator: Qing Wang
Title: Characterization of the Neuroinflammation in Autosomal Dominant Alzheimer Disease Using Neuro-Inflammation Imaging
Date of Request: April 26, 2021
Status:
ID: DIAN-D2107
Aim 1: Determine the trajectory of NII neuroinflammation biomarkers during the natural course of AD in the DIAN cohort.
Aim 2: Examine the association between whole-brain NII neuroinflammation biomarkers and CSF inflammation measures (sTREM2 and YKL40) in the DIAN cohort.
Aim 3: Assess the relationships among neuroinflammation measured by NII, amyloid deposition, and tauopathy measured by PET tracers in the DIAN cohort.
Aim 4: Assess the relationships among neuroinflammation measured by NII, amyloid deposition, and tauopathy measured by PET tracers in the DIAN cohort.
Investigator: Karin Meeker
Title: Plasma biomarkers in Autosomal Dominant AD
Date of Request: March 31, 2021
Status: Approved
ID: DIAN-D2106
Aim 1: Aim 1a: Determine whether plasma markers of amyloid (i.e., Ab42, Ab42/40) at baseline predict current and future CSF and PET markers of amyloid. Aim 1b: Assess longitudinal changes in plasma amyloid in relation to changes in CSF and PET amyloid.
Aim 2: Aim 2a: Determine whether plasma markers of tau (i.e., t-tau, p-tau181) at baseline predict current and future CSF and PET markers of tau. Aim 2b: Assess longitudinal changes in plasma tau in relation to changes in CSF and PET tau.
Aim 3: Aim 3a: Determine if the combination of plasma amyloid and tau markers at baseline predict current and future downstream markers (i.e., neurodegeneration [MRI], cognitive performance, and clinical status [clinical dementia rating (CDR) sum of boxes] in ADAD. Aim 3b: Assess longitudinal changes in plasma amyloid and tau in relation to changes in downstream markers of neurodegeneration and cognitive status.
Aim 4: Aim 3a: Determine if the combination of plasma amyloid and tau markers at baseline predict current and future downstream markers (i.e., neurodegeneration [MRI], cognitive performance, and clinical status [clinical dementia rating (CDR) sum of boxes] in ADAD. Aim 3b: Assess longitudinal changes in plasma amyloid and tau in relation to changes in downstream markers of neurodegeneration and cognitive status.
Investigator: Carlos Cruchaga
Title: Using quantitative traits to identify new genes, biomarkers and drug targets for ADAD and LOAD
Date of Request: September 8, 2020
Status: approved
ID: DIAN-D2018
Aim 1: To identify genetic variants associated with biomarker levels and quantitative traits in ADAD
Aim 2: To identify novel variants and genes associated with onset and progression by using multi-omics QTL data
Aim 3: To identify novel molecular biomarkers and drug targets by combining multi-omic QTL and Mendelian randomization analysis
Aim 4: To identify novel molecular biomarkers and drug targets by combining multi-omic QTL and Mendelian randomization analysis
Investigator: Patrick Lao
Title: Imaging White matter hyperintensities and Tau in Autosomal Dominant Alzheimer’s Disease
Date of Request: September 4, 2020
Status:
ID: DIAN-D2017
Aim 1: To determine the difference in the relationship among tau and WMH, independent or dependent on amyloid, between mutation carriers and controls.
Aim 2: To characterize the timing of the relationship among tau and WMH in mutation carriers compared to controls.
Aim 3: To characterize any added benefit to incorporating spatial information from tau PET in Aims 1 and 2.
Aim 4: To characterize any added benefit to incorporating spatial information from tau PET in Aims 1 and 2.
Investigator: Anna Dieffenbacher
Title: Specific facets of Personality traits in Autosomal Dominant Alzheimer disease
Date of Request: August 30, 2020
Status: approved
ID: DIAN-D2016
Aim 1: 1) to determine the different baseline differences between mutation carriers and non-mutation carriers in respect to the facets within each Personality Factor (OCEAN: openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism). 2) to analyze longitudinal changes of facets within mutation-carriers and non-carriers.
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Investigator: Suman Jayadev
Title: Investigating microRNA and immune gene regulation in fAD gene carriers
Date of Request: July 30, 2020
Status: approved
ID: DIAN-D2015
Aim 1: To determine if AD pathogenesis involves altered gene regulation of peripheral macrophage function, we will profile miRNA/mRNA expression in monocytes isolated from ADAD gene carriers or age-matched controls. We hypothesize that dysregulated peripheral immune cells in ADAD further contribute to disease. In collaboration with the Wash U DIAN site, we have collected CD14 cells from DIAN participants. We will use computational approaches to characterize the impact of ADAD mutations on peripheral cells. We include DIAN collected variables for analyses.
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Investigator: Disha Shah
Title: Functional connectivity disruptions at early stages in Alzheimer’s Disease: a comparison of brain networks in mouse models and humans.
Date of Request: July 20, 2020
Status: approved
ID: DIAN-D2014
Aim 1: We would like to access rsfMRI data from APP and PSEN1/2 carriers versus non carriers to compare functional connectivity disruptions in human AD with functional connectivity disruptions we observe in mouse models of Alzheimer’s pathology. We would like to compare whether the same brain regions are involved, to study the extent to which our findings in mice can be translated to humans.
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Investigator: n.a.
Title: Neurological examination findings in Alzheimer disease
Date of Request: June 22, 2020
Status: approved
ID: DIAN-D2013
Aim 1: to determine a muster of neurological examination findings in AD and to investigate their prevalences over the disease course
Aim 2: evaluate the capability of neurological examinations findings in Alzheimer disease to distinguish mutation carriers from non mutation carriers among mildly cognitive symptomatic at risk individuals
Aim 3: to analyze cross-sectional and
Aim 4: to analyze cross-sectional and
Investigator: Jeremy Strain
Title: Functional and Structural Correlates of Genetics in ADAD
Date of Request: June 15, 2020
Status:
ID: DIAN-D2012
Aim 1: Does connectivity strength change based on APOE status or associate with the polygenetic risk score in an ADAD cohort.
Aim 2: Does structural connectivity change based on APOE status or associate with the polygenetic risk score in an ADAD cohort.
Aim 3: Does structural or functional connectivity temporally associate with proteomic data.
Aim 4: Does structural or functional connectivity temporally associate with proteomic data.
Investigator: NA
Title: Changes in personality in DIAN
Date of Request: May 8, 2020
Status: Approved
ID: DIAN-D2011
Aim 1: To evaluate the magnitude of within person personality change in DIAN.
Aim 2: To establish a causal link between personality change and AD biomarkers
Aim 3: Evaluate which specific “facets” of personality shown the most reliable change in preclinical ADAD.
Aim 4: Evaluate which specific “facets” of personality shown the most reliable change in preclinical ADAD.
Investigator: Patrick Luckett
Title: Effects of HIV and Aging on Resting-state Networks
Date of Request: May 6, 2020
Status:
ID: DIAN-2010
Aim 1: Combine data from numerous studies to investigate changes in resting state networks and volumetrics that occur over the lifespan in healthy controls and people living with HIV with machine learning.
Aim 2: Utilize data driven machine learning based feature selection methods to search for complex relationships among volumetrics, resting state, and genetic data.
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Investigator: Ruth Peters
Title: Blood pressure and Alzheimer’s pathology, the next step in understanding the relationship
Date of Request: May 4, 2020
Status: Approved
ID: DIAN-D2009
Aim 1: To examine the impact of blood pressure on cognitive function in the well characterised DIAN population
Aim 2: To evaluate the relationship between BP and Aß accumulation
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Investigator: Xiaolei Shi
Title: The investigation of cerebral small vessel disease in The Dominantly Inherited Alzheimer Network
Date of Request: May 3, 2020
Status: Approved
ID: DIAN-D2008
Aim 1: To study the burden of cerebral small vessel disease in DIAN
Aim 2: To study the associations of cerebral small vessel disease neuroimaging markers with PSEN1, PSEN2, or APP gene mutations
Aim 3: To investigate the longitudinal changes of cerebral small vessel disease in DIAN
Aim 4: To investigate the longitudinal changes of cerebral small vessel disease in DIAN
Investigator: Prof. dr. G.J. Biessels
Title: Critical white matter connections in AD: unraveling their sensitivity to AD pathology and functional relevance
Date of Request: April 6, 2020
Status: Approved
ID: DIAN-D2007
Aim 1: To examine if critical and non-critical white matter connections are differentially affected by AD in mutation carriers as compared to non-carriers, also considering burden of AD pathology and disease stage.
Aim 2: To explore if critical and non-critical white matter connections differentially affect cognition in AD mutation carriers, again also considering disease stage.
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Investigator: Bret Bostwick
Title: Biomarker Modeling in Dominantly Inherited Alzheimer’s Disease
Date of Request: March 17, 2020
Status: Approved
ID: DIAN-D2006
Aim 1: Compare longitudinal changes in CSF biomarkers, serum biomarkers and neuroimaging biomarkers.
Aim 2: Analyze longitudinal changes in CSF biomarkers, serum biomarkers and neuroimaging biomarkers.
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Investigator: Nelly Joseph-Mathurin
Title: Genotype in dominantly inherited AD for clinical trial design
Date of Request: March 4, 2020
Status: Approved
ID: DIAN-D2005
Aim 1: Describe A/T/N trajectories per mutation type (APP, PS1, and PS2)
Aim 2: Define risk factors for ARIA per mutation type (APP, PS1, and PS2)
Aim 3: Develop and validate a prediction model for positive or adverse outcomes of anti-Aβ disease modifying treatment for DIAD individuals in clinical trials
Aim 4: Develop and validate a prediction model for positive or adverse outcomes of anti-Aβ disease modifying treatment for DIAD individuals in clinical trials
Investigator: –
Title: Cortical diffusion analysis in Dominantly Inherited Alzheimer’s disease (DIAD)
Date of Request: February 27, 2020
Status: Approved
ID: DIAN-D2004
Aim 1: Test a novel MRI analysis tool to investigate the cortical architecture
Aim 2: Identify neural cortical architecture signature in DIAD
Aim 3: Test the discrimination power of the novel cortical diffusivity measures in Alzhiemer’s disease groups
Aim 4: Test the discrimination power of the novel cortical diffusivity measures in Alzhiemer’s disease groups
Investigator: Yakeel T. Quiroz
Title: Sex differences in Alzheimer’s disease pathology, neurodegeneration and cognition in autosomal dominant Alzheimer’s disease
Date of Request: February 18, 2020
Status: Approved
ID: DIAN-D2003
Aim 1: 1. To extend our study on sex differences to other ADAD mutations and confirm our preliminary findings in a much larger sample of ADAD mutation carriers;
Aim 2: 2. To inform power calculations for appropriate sample size, based on estimated effects, for an upcoming 2020 grant submission on sex differences in ADAD (i.e. career development award of postdoctoral fellow, Dr. Vila-Castelar).
Aim 3: 3. To examine sex differences in ADAD mutation carriers at different clinical stages, from asymptomatic to symptomatic stages, with available biomarker and imaging data, and compare with age-matched noncarriers, which is not yet available in our group.
Aim 4: 3. To examine sex differences in ADAD mutation carriers at different clinical stages, from asymptomatic to symptomatic stages, with available biomarker and imaging data, and compare with age-matched noncarriers, which is not yet available in our group.
Investigator: Ruchika S Prakash
Title: Brain-based model of Alzheimer’s disease pathology
Date of Request: February 5, 2020
Status:
ID: DIAN-D2002
Aim 1: To externally validate a brain based model of Alzheimer’s disease pathology
Aim 2:
Aim 3:
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Investigator: Prof. Dr. Martin Hofmann-Apitius
Title: The Virtual Brain Cloud
Date of Request: January 20, 2020
Status:
ID: DIAN-D2001
Aim 1: Providing an overview on all accessible AD/dementia clinical cohort datasets. Systematically compare them by looking at the actual data, not only metadata. Assess the state of data sharing in the dementia field.
Aim 2: Multi-study comparative modeling of longitudinal patient trajectories.
Aim 3: Include longitudinal models into The Virtual Brain platform to allow for individual patient brain simulations.
Aim 4: Include longitudinal models into The Virtual Brain platform to allow for individual patient brain simulations.
Investigator: Jae Seung Kim
Title: The effect of resilience related life experiences on individual age-at-symptom onset in Dominantly Inherited Alzheimer’s Disease
Date of Request: December 31, 2019
Status:
ID:
Aim 1: To investigate the effect of resilience related life experiences, such as leisure time physical activity, lifetime cognitive engagement and social gathering, on individual variation in age-at-symptom onset from the age of parental onset in Dominantly Inherited Alzheimer’s Disease.
Aim 2: among the modifiable lifestyle factors including leisure time physical activity, lifetime cognitive engagement and social gathering, we determine which of these behavioral factors may be associated with the brain’s ability to cope with the pathological burden of AD.
Aim 3: we present how lifestyle factors affect the individual variation in age-at-symptom onset through cognitive and brain resilience, despite the presence of adverse heritable and acquired factors.
Aim 4: we present how lifestyle factors affect the individual variation in age-at-symptom onset through cognitive and brain resilience, despite the presence of adverse heritable and acquired factors.
Investigator: Xenia Kobeleva
Title: Modelling brain dynamics in dominantly inherited Alzheimer’s disease
Date of Request: December 16, 2019
Status:
ID:
Aim 1: 1. Modelling the effect of amyloid-beta and tau on neural dynamics in two models (dynamic mean-field model and Hopf model)
Aim 2: 2. Modelling the effect of tau and amyloid beta in a model of effective connectivity
Aim 3:
Aim 4:
Investigator: DUC KHANH TO
Title: Estimating ROC surface and selecting an optimal pair of thresholds for CSF markers
Date of Request: December 13, 2019
Status:
ID:
Aim 1: Estimate the ROC surfaces for visualizing the accuracy of CSF biomarkers in the clustered data setting
Aim 2: Obtain the optimal pairs of thresholds that can be used in practice for screening purposes.
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Investigator: Colin Masters
Title: Alzheimer’s Dementia Onset and Progression in International Cohorts
Date of Request: December 11, 2019
Status:
ID:
Aim 1: To determine cutpoints for preclinical, prodromal and clinical AD in relation to age, cognition, Aβ, tau and neurodegeneration markers
Aim 2: To determine rates of progression in preclinical, prodromal and clinical AD in relation to age, sex, cognition, Aβ, tau and neurodegeneration markers
Aim 3: To determine moderators of disease in preclinical, prodromal and clinical AD
Aim 4: To determine moderators of disease in preclinical, prodromal and clinical AD
Investigator: Jason Hassenstab
Title: Optimizing Cognitive Assessment in DIAN with Smartphone-Based Burst Testing
Date of Request: November 22, 2019
Status:
ID:
Aim 1: Determine if ARC burst assessments will better characterize the nature and magnitude of cognitive decline in DIAD mutation carriers than traditional in-clinic cognitive assessments
Aim 2: Compare cross-sectional and longitudinal associations between ARC assessments and neuroimaging and fluid biomarkers in DIAD
Aim 3: Examine the role of environment, mood, fatigue, and sleep patterns on cognition in DIAD
Aim 4: Examine the role of environment, mood, fatigue, and sleep patterns on cognition in DIAD
Investigator: Jane Osbourn
Title: Protective autoantibodies in Alzheimer’s disease
Date of Request: November 1, 2019
Status:
ID:
Aim 1: To evaulate the DIAN database for individuals with unexpected protection form a genetic predisposition to Alzheimer’s
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Aim 3:
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Investigator: Prof. Dr. Martin Hofmann-Apitius
Title: The Virtual Brain Cloud
Date of Request: October 29, 2019
Status:
ID:
Aim 1: Provide an overview on all accessible AD/dementia clinical cohort datasets. Systematically compare them by looking at the actual data and not only meta-data. Assess the state of data sharing in the dementia field.
Aim 2: Multi-study comparative modeling of longitudinal patient trajectories.
Aim 3: Include longitudinal models into The Virtual Brain platform to allow for individual patient brain simulations.
Aim 4: Include longitudinal models into The Virtual Brain platform to allow for individual patient brain simulations.
Investigator: Sheng Luo
Title: Integrative modeling and dynamic prediction of Alzheimer’s disease
Date of Request: October 24, 2019
Status:
ID:
Aim 1: To develop a novel integrative modeling framework for clinical studies of AD that collect longitudinal clinical data.
Aim 2: To generalize the integrative modeling framework for the joint analysis of longitudinal clinical data and high-dimensional MRI data.
Aim 3: To advance the integrative modeling framework to incorporate relevant genetic markers from genome-wide association studies
Aim 4: To advance the integrative modeling framework to incorporate relevant genetic markers from genome-wide association studies
Investigator: Victoria Fernandez
Title: Functional evaluation of a novel Alzheimer disease candidate gene, AGFG2.
Date of Request: October 6, 2019
Status:
ID:
Aim 1: Evaluation of AGFG2 as a potential disease driver in Alzheimer Disease
Aim 2:
Aim 3:
Aim 4:
Investigator: Victoria Fernandez
Title: Identification of common pathways across Alzheimer Disease phenotypes.
Date of Request: October 6, 2019
Status:
ID:
Aim 1: Transcriptomic profiling of AD brains
Aim 2: eQTL profiling of AD brains
Aim 3:
Aim 4:
Investigator: Colin L Masters
Title: Alzheimer’s dementia onset and progression in international cohorts
Date of Request: September 23, 2019
Status:
ID:
Aim 1: Using unsupervised machine learning techniques (latent Gaussian processes, auto encoders, disentanglement) in order to identify ‘pure’ (and potentially highly non-linear) Alzheimer factors using DIAN cohort.
Aim 2: Study the utility of the resulting latent structure for progression prediction of the late-onset patients.
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Investigator: LD Sibley
Title: Role of toxoplasmosis in AD
Date of Request: September 9, 2019
Status:
ID:
Aim 1: Evaluate differences in amyloid PET based on Toxoplasma serological status
Aim 2: Evaluate differences in cognative function based on Toxoplasma serological status
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Aim 4:
Investigator: Belinda Brown
Title: The effect of exercise participation on Aβ accumulation, CSF biomarkers and brain atrophy and age at onset
Date of Request: August 27, 2019
Status:
ID:
Aim 1: 1. Compare the rates of brain Aβ accumulation between exercising and sedentary asymptomatic mutation carriers.
Aim 2: 2. Compare longitudinal changes in CSF levels of Aβ and tau between exercising and sedentary asymptomatic mutation carriers.
Aim 3: 3. Compare rates of hippocampal and prefrontal cortex atrophy between exercising and sedentary asymptomatic mutation carriers.
Aim 4: 3. Compare rates of hippocampal and prefrontal cortex atrophy between exercising and sedentary asymptomatic mutation carriers.
Investigator: Anne Fagan
Title: Head to head comparison of CSF assay platforms for identifying amyloid positivity
Date of Request: August 20, 2019
Status:
ID:
Aim 1: To compare the analytic performance of the two automated assay platforms (Elecsys and Lumipulse) for measurement of CSF AB40, AB42, total tau and ptau181 in a common sub-cohort of DIAN samples
Aim 2: To define the best-performing CSF biomarker cut-point(s) for amyloid PET positivity for each of the assay platforms
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Aim 4:
Investigator: Martha Brumfield
Title: Drug-disease-trial model for Alzheimer’s prevention drug development
Date of Request: July 22, 2019
Status:
ID:
Aim 1: Develop a drug-disease trial model to optimize clinical trial design in Alzheimer’s prevention
Aim 2: Submit the model for regulatory endorsement at FDA and EMA
Aim 3: Develop a graphical user interface for the model
Aim 4: Develop a graphical user interface for the model
Investigator: Andrew Yoo
Title: Modelling Alzheimer’s disease with human neurons generated by direct conversion (reprogramming) of patient fibroblasts
Date of Request: July 14, 2019
Status:
ID:
Aim 1: Developing cellular models of AD through direct neuronal reprogramming
Aim 2: Application of direct neuronal reprogramming in patient fibroblasts
Aim 3:
Aim 4:
Investigator: Helena Chui
Title: Biomarker Characterization of a Novel Truncation Mutation in PSEN1
Date of Request: July 13, 2019
Status: approved
ID: DIAN-D1920
Aim 1: To describe CSF profile of AD biomarkers including but not limited to Abeta and tau subspecies in a patient with a novel truncation mutation in PSEN1
Aim 2: To describe imaging characteristics (MRI, FDG, Amyloid PET) of the novel PSEN1 truncation mutation
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Aim 4:
Investigator: Guoqiao Wang
Title: Select Eligible DIAN-OBS Participants for the DIAN-TU Primary Analysis
Date of Request: July 10, 2019
Status:
ID:
Aim 1: Select Eligible DIAN-OBS Participants for the DIAN-TU Primary Analysis
Aim 2:
Aim 3:
Aim 4:
Investigator: Nick Fox
Title: Psychosis in dominantly inherited Alzheimer’s disease
Date of Request: July 8, 2019
Status:
ID:
Aim 1: To determine the frequency of psychosis in DIAN family members, and to explore associations between psychosis and different genotypes
Aim 2: To examine the relationship between neuropsychiatric symptoms and estimated years to and from cognitive symptom onse
Aim 3: 3. To determine if there is a relationship, and any potential interaction, between psychotic symptoms and previously reported risk/modifier alleles (5HT2A receptor polymorphism, SNPs in RP11-541P9.3, ApoE status) and environmental risk factors (e.g. history of substance abuse)
Aim 4: 3. To determine if there is a relationship, and any potential interaction, between psychotic symptoms and previously reported risk/modifier alleles (5HT2A receptor polymorphism, SNPs in RP11-541P9.3, ApoE status) and environmental risk factors (e.g. history of substance abuse)
Investigator: Nick Fox
Title: Longitudinal tau PET in dominantly inherited Alzheimer’s disease
Date of Request: July 4, 2019
Status:
ID:
Aim 1: a) to understand the role tau PET imaging can play as a marker of early Alzheimer’s disease for clinical diagnostic purposes and also as a biomarker in trials of individuals with autosomal dominantly inherited forms of Alzheimer’s disease (ADAD)
Aim 2: b) to optimize static and dynamic methods of tau PET analysis in order to achieve better longitudinal consistency and reduce sources of within-subject variability
Aim 3: c) to improve understanding of when and where tau deposition occurs, and how these relationships change over time;
Aim 4: c) to improve understanding of when and where tau deposition occurs, and how these relationships change over time;
Investigator: Ben Handen, Bradley Christian, William Klunk
Title: Comparing CSF biomarkers of AD in Down Syndrome and autosomal dominant AD
Date of Request: June 21, 2019
Status:
ID:
Aim 1: To analyze and compare levels of established and novel CSF biomarkers (Aβ40, Aβ42, tTau, pTau, VILIP-1, Ng, SNAP-25, YKL-40, NfL, and sTREM2) between ABC-DS and DIAN cohorts.
Aim 2:
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Investigator: Randall Bateman and Gil Ribinovici
Title: Comparison between Dominant Inherit Alzheimer Disease and sporadic early-onset Alzheimer’s disease.
Date of Request: June 3, 2019
Status:
ID:
Aim 1: To compare clinical presentation, neuropsychological performance and cognitive decline rate between DIAD and sporadic EOAD.
Aim 2: To examine the regional distribution of tau, amyloid-β, glucose metabolism, and structural atrophy in DIAD and sEOAD.
Aim 3: To determine CSF biomarkers levels and biomarkers rate of change in DIAD and sEOAD.
Aim 4: To determine CSF biomarkers levels and biomarkers rate of change in DIAD and sEOAD.
Investigator: FEI HUA
Title: Development of a robust quantitative systems pharmacology model of amyloid beta and tau pathways for clinical trial design and decision making in Alzheimer’s disease and dementia
Date of Request: May 24, 2019
Status:
ID:
Aim 1: Calibrate the QSP model to longitudinal biomarker changes for different mutation status
Aim 2: Virtual patient creation to capture the patient variability
Aim 3: Predict drug treatment effect with virtual patient population
Aim 4: Predict drug treatment effect with virtual patient population
Investigator: Julia TCW
Title: Isogenic APOE isoform glia response to amyloid in brain organoids
Date of Request: May 16, 2019
Status:
ID:
Aim 1: Generation of induced pluripotent stem cells from APP (and/or PS1) mutations
Aim 2: Differentiation of the iPSC to organoids to generate beta-amyloid aggregates and differentiation of isogenic APOE iPSC to microglia
Aim 3: Co-culture isogenic APOE 33 and APOE 44 microglia with the organoids from APP (and/or PS1) mutations
Aim 4: Co-culture isogenic APOE 33 and APOE 44 microglia with the organoids from APP (and/or PS1) mutations
Investigator: NA
Title: Protective Factors in DIAN
Date of Request: May 15, 2019
Status:
ID:
Aim 1: Analyze the rates of change in cognition and AD biomarkers in ADAD mutation carriers that are past expected age of onset and are not showing any symptoms
Aim 2:
Aim 3:
Aim 4:
Investigator: Joana B. Pereira
Title: Alterations of the Brain Connectome in Familial Alzheimer’s disease
Date of Request: May 14, 2019
Status:
ID:
Aim 1: To define the changes in the structural and functional connectomes in symptomatic and asymptomatic mutation carriers with ADAD
Aim 2: To map these changes as a function of estimated years to onset of AD
Aim 3: To assess whether the connectome alterations are associated with cerebrospinal fluid and blood biomarkers, voxel-wise amyloid, tau and glucose metabolism PET, and clinical measures
Aim 4: To assess whether the connectome alterations are associated with cerebrospinal fluid and blood biomarkers, voxel-wise amyloid, tau and glucose metabolism PET, and clinical measures
Investigator: Joana B. Pereira
Title: Alterations of the Brain Connectome in Familial Alzheimer’s disease
Date of Request: May 14, 2019
Status:
ID:
Aim 1: To define the changes in the structural and functional connectomes in symptomatic and asymptomatic mutation carriers with ADAD
Aim 2: To map these changes as a function of estimated years to onset of AD
Aim 3: To assess whether the connectome alterations are associated with cerebrospinal fluid and blood biomarkers, voxel-wise amyloid, tau and glucose metabolism PET, and clinical measures
Aim 4: To assess whether the connectome alterations are associated with cerebrospinal fluid and blood biomarkers, voxel-wise amyloid, tau and glucose metabolism PET, and clinical measures
Investigator: Jet Vonk
Title: Cognitive markers of preclinical Alzheimer’s disease through psycholinguistic semantic measures
Date of Request: May 3, 2019
Status:
ID:
Aim 1: To estimate the temporality of semantic impairment in the preclinical phase of Alzheimer’s disease
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Investigator: Daniel C Alexander
Title: Sequencing cognitive decline within familial AD progression
Date of Request: April 9, 2019
Status: Pending
ID: DIAN-D1909
Aim 1: Construct an event-based model of cognitive decline in dominantly-inherited AD from DIAN data using a similar set of outcomes to those in [Baker–AlzDem:DADM-2017]. This will include separating subscores into cognitive domains which will allow us to validate the new technique against current thinking in neurology and neuropsychology.
Aim 2: Compare different versions of the event-based model to determine which limitations are important to address, which elements of the model are essential, which variants of the model (and its parameters/settings) are feasible, and how much complexity can be supported by different-sized data sets.
Aim 3: Extend the model to include a broader set of biomarker data including tau PET, amyloid PET, CSF (molecular changes), MRI, DTI (atrophy and microstructural changes) and other factors. This will enable cognitive decline to be positioned within the pathophysiological cascade.
Aim 4: Extend the model to include a broader set of biomarker data including tau PET, amyloid PET, CSF (molecular changes), MRI, DTI (atrophy and microstructural changes) and other factors. This will enable cognitive decline to be positioned within the pathophysiological cascade.
Investigator: Only me.
Title: Prediction of AD converter during preclinical stage only using MR brain morphometry.
Date of Request: April 7, 2019
Status: Pending
ID: DIAN-D1908
Aim 1: I have read the new paper entitled “Staging biomarkers in preclinical autosomal dominant Alzheimer’s disease by estimated years to symptom onset “. For about brain MRI, the study measured hippocampal volume and precnuneus cortical thickness, but I think, ADAD may have advanced cortical atrophy relative to hippocampal volume change. So, let me try to analyze using more advanced AI-drived brain morphometry method, it might prove positive significance at the trasitional stage (EYO 13-7).
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Investigator: Professor John Gallacher
Title: Traumatic brain injury, emotional adversity and the long-term effects on adult outcomes and dementia
Date of Request: March 28, 2019
Status: Pending
ID: DIAN-D1907
Aim 1: Assess the relationship between retrospective self-report ACEs, TBIs and multiple adult biomedical, psychosocial, cognitive, and dementia outcomes in adults age 40-70 years. The consequences of traumatic brain injuries (TBI) on long-term cognitive outcomes is poorly understood however, there is support for evidence which suggests those who have experienced a TBI in younger adulthood experience diminished cognitive reserve which may accelerate cognitive deficits, premature cognitive decline and dementia risk (Wood, 2017). Furthermore, individuals who have experienced traumatic emotional experiences in younger years, also known as adverse childhood experiences (ACEs), a broad construct encompassing overall extreme difficulties and adverse experiences during childhood such as sexual, physical and emotional abuse, deprivation, and family dysfunction (e.g., McLaughlin, 2016) are at risk of adult depression (Liu, 2017), lower adult life satisfaction (Hughes et al., 2016) and dementia (Radford et al., 2017).
Aim 2: Investigate the longitudinal association between ACEs, TBIs and, cognitive decline and dementia outcomes across multiple time points in adults aged 40 to 70 years, testing the hypothesis that there may be an accumulative neurobiological load response associated with ACEs and TBIs. We propose a cross-platform cross-cohort investigation interrogating population cohorts to investigate self-report retrospective TBIs and ACEs as determinants of adult outcomes including cognition and dementia.
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Investigator: Perminder S Sachdev
Title: CSF and blood protein biomarkers and APOE genotype status of early-onset Alzheimer’s disease variants: A systematic review and meta-analysis
Date of Request: March 20, 2019
Status: Pending
ID: DIAN-D1906
Aim 1: We have performed a meta-analysis and systematic review to compare core biomarkers (CSF Aβ42 and tau) across early-onset AD (EOAD) subtypes i.e. autosomal dominant Alzheimer’s disease (ADAD) and early onset sporadic Alzheimer’s disease (EOsAD). Furthermore, we are exploring several other potential markers of neurodegeneration in EOAD, including NFL, IgG and IL-6 which are emerging in the literature. A recent published article from DIAN group “Serum neurofilament dynamics predicts neurodegeneration and clinical progression in presymptomatic Alzheimer’s disease” Nature Medicine volume 25, pages 277–283 (2019)”. This article includes data for measurement of NFL in serum and CSF, provided data in graphical format. We need data in mean and standard deviation format to perform meta-analysis on NFL serum and CSF.
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Investigator: Prof. Vijayalakshmi Ravindranath
Title: Sex-specific differences in cognitive decline in AD
Date of Request: March 5, 2019
Status: Pending
ID: DIAN-D1905
Aim 1: Study differences in trajectory of cognitive decline in males and females from DIAN dataset
Aim 2: Study differences in age of onset in AD between males and females
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Investigator: Steven L. Wagner
Title: Dedifferentiation and neuronal lineage repression orchestrated through remodeling of the chromatin landscape define PSEN1 mutation-induced Alzheimer’s Disease
Date of Request: February 27, 2019
Status: Pending
ID: DIAN-D1904
Aim 1: Compare gene signature profiles and changes in chromatin topology observed in iPSC-derived EOFAD neurons to those reported in EOFAD subject post-mortem brain tissue
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Investigator: Ting Ma
Title: Association of morphology and network connectivity of degenerative disease
Date of Request: February 21, 2019
Status: Pending
ID: DIAN-D1903
Aim 1: Morphological change mechanism of Alzheimer’s continuum
Aim 2: Structural connectivity change mechanism of Alzheimer’s continuum
Aim 3: Brain function connectivity variation of Alzheimer’s continuum
Aim 4: Brain function connectivity variation of Alzheimer’s continuum
Investigator: Adam L. Boxer, MD, PhD
Title: Individualized prediction of symptom onset in familial AD using structural MRI
Date of Request: February 11, 2019
Status: Approved
ID: DIAN-1803A
Aim 1: create individualized atrophy maps in patients with fAD
Aim 2: investigate the utility of these maps for predicting the likelihood of developing symptoms of dementia on longitudinal follow-up
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Investigator: Randall Bateman MD
Title: Dominantly Inherited Alzheimer’s Disease Protective Factor Study
Date of Request: January 29, 2019
Status: Approved
ID: DIAN-D1902
Aim 1: The overall objective is to identify factors that protect mutation-carriers from AD symptoms.
Aim 2: 1. Obtaining the clinical, cognitive, biomarker and genetic results from the DIAN research study .
Aim 3: 2. Administering a number of questionnaires assessing health and lifestyle factors to include the following: Current Health Status, Medical Conditions, Physical Functioning, Exposure History Form, Occupational and Environmental Exposure History.
Aim 4: 2. Administering a number of questionnaires assessing health and lifestyle factors to include the following: Current Health Status, Medical Conditions, Physical Functioning, Exposure History Form, Occupational and Environmental Exposure History.
Investigator: na
Title: Advanced analytics on DIAN imaging data
Date of Request: January 28, 2019
Status: Pending
ID: DIAN-D1901
Aim 1: Use advanced analytics to predict mutation carrier status of DIAN patients by vMRI data only
Aim 2: Use advanced analytics to predict mutation carrier status of DIAN patients by amyloid PET data only
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Investigator: Randall Bateman. MD
Title: Relationship between literacy, socio-economic status, Alzheimer pathology and cognitive decline in autosomal dominant Alzheimer’s disease.
Date of Request: December 27, 2018
Status: Approved
ID: DIAN-D1822
Aim 1: Aim 1: To examine the extent to which environmental risk factors like level of education and SES influence age of onset in ADAD. Hypothesis 1a: Age at symptom onset will be earlier in those with a lower level of education or lower SES.
Aim 2: Aim 2: To determine the influence of educational level (EL) and SES on cognitive decline, disease progression and mortality rate. Hypothesis 2a: Educational Level and SES has a significant effect on cognitive decline and mortality rate after diagnosis, so cognitive decline rate and mortality rate will be faster in those with less than 9 years of education and lower SES.
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Investigator: Randall Bateman. MD
Title: Relationship between clinical heterogeneity and neuroanatomical variability in Autosomal dominant familial Alzheimer disease.
Date of Request: December 12, 2018
Status: Approved
ID: DIAN-D1821
Aim 1: Examine the extent to which factors like atrophy pattern, regional brain metabolism and underlying pathology (regional AB and TAU) influence clinical heterogeneity in ADAD. Hypothesis 1a: Regional brain atrophy, hypometabolism, and underlying pathology will correlate with distinct clinical phenotypes in ADAD.
Aim 2: To determine the influence of underlying pathology (regional AB and TAU) on cognitive decline and neuropsychological profiles. Hypothesis 2a: the amount and distribution of 18F-AV1451 retention will correlate with cognitive decline rate and neuropsychological performance.
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Investigator: Ali Ezzati, MD
Title: Predictive analytics in DIAN study based on biomarker data.
Date of Request: December 10, 2018
Status: Approved
ID: DIAN-D1820
Aim 1: To tests the hypothesis that in comparison with traditional MRI biomarkers, subgroups identified by latent class analysis based on multidimensional biomarker data, will have higher accuracy for predicting longitudinal cognitive trajectories and cognitive events.
Aim 2: 2) To develop a machine learning framework for prediction of time to conversion to AD (or MCI) in preclinical AD stage in participants with and without AD mutations and comparing effect of individual features (indicators) in the computational models.
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Investigator: NA
Title: Relationship between functional connectivity and cognition in sporadic and autosomal dominant Alzheimer disease
Date of Request: October 22, 2018
Status: Approved
ID: DIAN-D1819
Aim 1: evaluate how resting state functional connectivity relates to cognition
Aim 2: compare the connectivity – cognition relationship across LOAD and DIAN
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Investigator: Maxime Descoteaux
Title: Tractometry informed dementia predictor
Date of Request: October 17, 2018
Status: Pending
ID: DIAN-D1818
Aim 1: Look at longitudinal values of white matter tractometry to find which metrics or combination of metrics predicts best incoming dementia symptoms. Our tractometry algorithm will look at 12 metrics (DTI, HARDI, Freewater and microstructure) inside 33 white matter bundles each split in multiple subsections.
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Investigator: Barbara Bendlin/Vikas Singh
Title: Characterizing disease propagation in autosomal dominant Alzheimer’s disease
Date of Request: October 3, 2018
Status: Pending
ID: DIAN-D1817
Aim 1: To utilize a non-Euclidean wavelet transform for connectivity signature (WaCS) to characterize structural connectivity alterations in autosomal AD.
Aim 2: To create subject specific propagation maps utilizing PET data in order to predict the spread of AD pathophysiologic markers over time.
Aim 3: To predict longitudinal cognitive decline or end-stage disease (EYO) using markers of AD pathology (CSF and PET based).
Aim 4: To predict longitudinal cognitive decline or end-stage disease (EYO) using markers of AD pathology (CSF and PET based).
Investigator: Prof Dr Baris Topcular
Title: Amyloid Imagıng in Familial and Non-Familial AD
Date of Request: September 29, 2018
Status: Pending
ID: DIAN-D1816
Aim 1: Detection of similarities in terms of Amyloid Imaging
Aim 2: Detection of differences in terms of Amyloid Imaging
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Investigator: Sarah Eisenstein
Title: Neuroinflammation in Obesity
Date of Request: September 13, 2018
Status: Pending
ID: DIAN-D1815
Aim 1: The first aim is to replicate in the DIAN controls cohort our finding that DTI-based indicators of neuroinflammation are greater in obese individuals compared to normal-weight individuals.
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Investigator: Guoqiao Wang
Title: Build a predictive model to estimate EYO for sporadic Alzheimer disease
Date of Request: September 5, 2018
Status: Approved
ID: DIAN-D1814
Aim 1: Validate the generalizability of the EYO estimation models using the ACS study
Aim 2: Evaluate the goodness-of-estimation of these statistical models by comparing the model estimate EYO with the mutation/parent EYO (calculated using mutation mean age of onset or parent age of onset) using the DIAN observational study
Aim 3: Improve the accuracy of the EYO for the ADAD population by modifying the statistical model to estimate a shift in the EYO using the biomarker, imaging, and cognition information.
Aim 4: Improve the accuracy of the EYO for the ADAD population by modifying the statistical model to estimate a shift in the EYO using the biomarker, imaging, and cognition information.
Investigator: Steve Petersen
Title: How the brain breaks: Non-linear network level changes in neurodegenerative diseases.
Date of Request: August 23, 2018
Status: Pending
ID: DIAN-D1813
Aim 1: To see how resting state networks change as a function of estimated years to symptom onset
Aim 2: To explore the idea of “cascading network failure” in DIAN
Aim 3: To relate changes in resting state functional connectivity to other AD biomarkers
Aim 4: To relate changes in resting state functional connectivity to other AD biomarkers
Investigator: N/A
Title: QMENTA Data Request
Date of Request: July 6, 2018
Status: Pending
ID: DIAN-D1812
Aim 1: run data analysis
Aim 2: internal R&D purposes
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Investigator: Raquel Sánchez-Valle
Title: Early cortical micro and macrostructural changes in autosomal dominant Alzheimer’s disease
Date of Request: May 30, 2018
Status: Pending
ID: DIAN-D1811
Aim 1: Assess the micro and macrostructrure cortical changes in ADAD. We will investigate these changes in relation to the estimated years to symptom onset.
Aim 2: Study the relationship between CSF biomarker levels, plasma NfL levels and the aforementioned cortical micro and macrostructural changes. We will investigate the effect of CSF Aß1-42 and PIB values, t-tau, p-tau, NfL levels and plasma NfL levels on the trajectory of changes.
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Investigator: Tammie Benzinger
Title: Aging Independent Detection of Atrophy: Validating A Structural MR-based Diagnostic Tool
Date of Request: May 17, 2018
Status: Pending
ID: DIAN-D1810
Aim 1: Improve the Individual Longitudinal Participant Report (clinical tool used to analyze structural MR data currently in use at Barnes-Jewish Hospital) in order to maximize its diagnostic utility.
Aim 2: Determine how effectively the ILP can use structural MR data to distinguish different dementia types in a clinical setting.
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Investigator: Marco Duering
Title: Disentangling brain damage due to Alzheimer’s and vascular disease using a novel diffusion bitensor model
Date of Request: April 19, 2018
Status: Approved
ID: DIAN-D1809
Aim 1: To determine the diffusion signature in different patient samples, covering the entire spectrum of neurodegenerative and small vessel pathology
Aim 2: To assess the association between the bitensor DTI measures and biomarkers for AD and SVD
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Investigator: Corey Bolton
Title: Neuropsychological differentiation of autosomal dominant and sporadic early-onset Alzheimer’s disease
Date of Request: March 29, 2018
Status: Pending
ID: DIAN-D1808
Aim 1: To describe the typical neurocognitive profile of autosomal-dominant Alzheimer’s disease
Aim 2: To distinguish differences in neurocognitive presentation between patients with autosomal-dominant Alzheimer’s disease from the DIAN database and those with sporadic, early-onset Alzheimer’s disease from the NACC database.
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Investigator: Michele Cavallari
Title: Assessing the association between perivascular dysfunction and beta-amyloid burden in subjects with or at risk for dementia
Date of Request: March 21, 2018
Status: Approved
ID: DIAN-D1807
Aim 1: To assess group differences in perivascular dysfunction, under the hypothesis that the number of MRI-evident ePVS is: symptomatic carriers > asymptomatic carriers > mutation non-carriers.
Aim 2: To estimate the association between MRI-evident ePVS and PET-derived measures of beta-amyloid load in cross-sectional and longitudinal analyses, under the hypothesis that perivascular dysfunction contributes to the accrual of beta-amyloid.
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Investigator: Simone Wahl
Title: DIAN Elecsys CSF and Amyloid Imaging Concordance
Date of Request: February 21, 2018
Status: Approved
ID: DIAN-D1806
Aim 1: Determine the concordance between CSF measures obtained via the Elecsys platform
Aim 2: Assess Elecsys CSF measure relative to other clinical and cognitive variables
Aim 3: Assess how well Elecsys measures predict clinical and cognitive progression
Aim 4: Assess how well Elecsys measures predict clinical and cognitive progression
Investigator: Viktoria Andreeva
Title: DIAN data analysis in a tranSMART platform
Date of Request: February 16, 2018
Status: Pending
ID: DIAN-D1805
Aim 1: Curate the DIAN data and prepare for tranSMART loading
Aim 2: Perform investigation of data in tranSMART platform
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Aim 4:
Investigator: Dr. Alan C. Evans
Title: Comparing Multifactorial Pathologic Trajectories in Asymptomatic Autosomal Dominant Alzheimer’s Disease Mutation Carriers and Late-Onset Alzheimer’s Disease patients
Date of Request: February 4, 2018
Status: Approved
ID: DIAN-D1804
Aim 1: Identify disease triggering events in each DIAN subject, using all the available multimodal neuroimaging data
Aim 2: Subdivide and stage the DIAN subjects based on the identified individual causal pathological mechanisms (from Aim 1)
Aim 3: Compare both the obtained potential triggering events and the subjects’ subdivision/staging (from Aims 1 and 2 respectively) with the equivalent results previously obtained for LOAD patients from ADNI database.
Aim 4: Compare both the obtained potential triggering events and the subjects’ subdivision/staging (from Aims 1 and 2 respectively) with the equivalent results previously obtained for LOAD patients from ADNI database.
Investigator: Howard Rosen, Brad Boeve, Adam Boxer
Title: Quantification of Longitudinal Volume Change in Familial FTD (fFTD)
Date of Request: January 28, 2018
Status: Approved
ID: DIAN-D1803
Aim 1: To quantify rates of change in structural (T1w) imaging in symptomatic fFTD
Aim 2: To quantify rates of change in structural (T1w) imaging in presymptomatic fFTD
Aim 3: To derive subject-specific maps of volumetric change in fFTD
Aim 4: To derive subject-specific maps of volumetric change in fFTD
Investigator: Betty Tijms
Title: Linking brain connectivity changes to development of symptoms in autosomal dominant AD
Date of Request: January 27, 2018
Status: Approved
ID: DIAN-D1802
Aim 1: To study the association of grey matter connectivity in autosomal dominant AD with estimated year of onset and cognitive decline.
Aim 2: To study associations between grey matter connectivity alterations and AD and injury markers in CSF (aβ42, aβ40, p-tau, t-tau, neurogranin, VLIP-1, SNAP-25, NRGN, YKL-40) and PET (aβ, FDG, and tau) cross-sectionally and longitudinally.
Aim 3: Compare cross-sectional findings in grey matter connectivity with longitudinal changes.
Aim 4: Compare cross-sectional findings in grey matter connectivity with longitudinal changes.
Investigator: Benzinger
Title: Updated analyses of Dominantly Inherited Alzheimer Disease (AD) neuroimaging data using new biomarker, clinical, genetic, and psychometric data
Date of Request: January 26, 2018
Status: Approved
ID: DIAN-D1801
Aim 1: Cross-sectional evaluation of the temporal ordering of imaging biomarkers in asymptomatic ADAD with current biomarker, clinical, genetic, and psychometric data.
Aim 2: Harmonization of refined ADAD imaging processed values with the ADNI sporadic AD studies (ADNI)
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Investigator: Carlos Cruchaga/Celeste Karch
Title: Clinical and Molecular Characterization of PSEN1 and PSEN2 Variants of Unknown Pathogenicity
Date of Request: December 21, 2017
Status: Approved
ID: DIAN-D1729
Aim 1: To describe imaging and fluid biomarkers for PSEN1 and PSEN2 variants of unknown pathogenicity
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Investigator: Michael Ewers
Title: Developing a machine-learning based biomarker model to predict Alzheimer’s disease progression
Date of Request: November 30, 2017
Status: Approved
ID: DIAN-D1728
Aim 1: 1. To train a machine learning algorithm that sensitively predicts ADAD stage (i.e. EYO) based on cross-sectional biomarker and imaging data in the DIAN cohort. The trained algorithm will be cross-validated in sporadic AD (ADNI) as a predictor of a. baseline cognition b. longitudinal disease progression
Aim 2: 1. To train a machine learning algorithm that discriminates between mutation carrier (MC) and non-mutation carriers (NC) based on cross-sectional biomarker and imaging data in the DIAN cohort. Cross-validation of the trained model for diagnostic classification will be applied to cases with sporadic AD and controls from the ADNI data set.
Aim 3:
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Investigator: Juan Manuel Górriz Sáez
Title: Time course of imaging markers of neurodegeneration in autosomal dominantly inherited Alzheimer’s disease assessed by Linear mixed effects models
Date of Request: November 29, 2017
Status: Approved
ID: DIAN-D1727
Aim 1: The specific aim for the proposed work with the DIAN dataset is to make use of the machine learning paradigm for classification in combination with feature extraction methods such as partial least squares (PLS) algorithm [4] on a combined set of different imaging modalities. PLS is a very well-known algorithm in the neuroimaging field.
Aim 2: Additionally we aim for the examination of some other covariates which are known to affect neurodegeneration such as gender or genetic status by a LME approach, which represents a model of a response variable with fixed and random effects. These models comprise fitted coefficients, covariance parameters, design matrices, residuals and other diagnostic information.
Aim 3: Furthermore we are planning to follow an enhanced approach by querying the evolution of the selected features and by proposing predictive models based on supervised learning applied to the reference controls.
Aim 4: Furthermore we are planning to follow an enhanced approach by querying the evolution of the selected features and by proposing predictive models based on supervised learning applied to the reference controls.
Investigator: Joseph Therriault
Title: Determination of Voxel-based Receiver Operating Characteristic thresholds of amyloid- deposition
Date of Request: November 7, 2017
Status: Approved
ID: DIAN-D1726
Aim 1: Determine the extent to which the patterns of amyloid burden that optimally differentiate between sporadic AD patients and controls are observed in ADAD.
Aim 2: Determine whether amyloid burden in structures that optimally differentiate between controls and AD patients, determined by the results of the voxel-wise ROC curve, can provide additional information about disease severity as measured by neuropsychological test scores and [18F]FDG-PET
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Investigator: David Cash and Nick Fox
Title: Sample size estimates for imaging biomarkers in prevention trials: exploring different modalities, enrichment strategies and trial designs
Date of Request: October 2, 2017
Status: Approved
ID: DIAN-D1725
Aim 1: Assess and optimise imaging measures of preclinical AD for use as trial inclusion, staging criteria and outcome measures
Aim 2: Assess the rate and variance of serial imaging measures in the Dominantly Inherited Alzheimer Network (DIAN) study
Aim 3: Assess the different power and design requirements for studies using different potential trial inclusion criteria – including, but not limited to a) estimated years to onset (based on from parental age in familial AD); b) amyloid PET imaging; c) amyloid PET positivity plus hippocampal volume
Aim 4: Assess the different power and design requirements for studies using different potential trial inclusion criteria – including, but not limited to a) estimated years to onset (based on from parental age in familial AD); b) amyloid PET imaging; c) amyloid PET positivity plus hippocampal volume
Investigator: Mikael Simons
Title: Lipidomics study of preclinical plasma biomarkers for Alzheimer´s disease
Date of Request: September 28, 2017
Status: Incorrect submission-resubmit as sample request
ID: DIAN-D1724
Aim 1: Establish a preclinical biomarker for AD
Aim 2: Determine lipid profiles in preclinical AD
Aim 3: Compare lipid profiles in DIAN and Framingham
Aim 4: Compare lipid profiles in DIAN and Framingham
Investigator: Hamied Haroon
Title: “Quantima – Diagnostics Imaging Biomarkers
Date of Request: September 13, 2017
Status: Approved
ID: DIAN-D1723
Aim 1: Generate diffusion atlas for healthy controls and participants diagnosed with Alzheimer’s disease.
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Investigator: Anne Fagan
Title: Evaluation of longitudinal trajectories of novel CSF markers of neuronal injury/neuroinflammation
Date of Request: September 13, 2017
Status: Approved
ID: DIAN-D1722
Aim 1: Perform cross-sectional and longitudinal analyses of clinical, cognitive, structural imaging and biochemical changes according to estimated age of symptomatic onset for standard CSF biomarkers (tau, ptau, and Aβ42) as well as novel ones (VILIP-1, Ng, SNAP-25, YKL-40) in order to evaluate the rate of change of the novel CSF biomarkers as a function of baseline estimated age of symptomatic onset
Aim 2: Compare their rates of change with those of the standard biomarkers
Aim 3: Evaluate the association of cross-sectional and longitudinal patterns of all CSF biomarkers with regional brain atrophy measures.
Aim 4: Evaluate the association of cross-sectional and longitudinal patterns of all CSF biomarkers with regional brain atrophy measures.
Investigator: Mindi Messmer
Title: Amyloid variabilty
Date of Request: July 20, 2017
Status: Pending
ID: DIAN-D1721
Aim 1: Look at longitudinal amyloid in ADAD
Aim 2:
Aim 3:
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Investigator: N/A
Title: Factors associated with CDR>0 diagnosis in Non-carriers
Date of Request: July 6, 2017
Status:
ID: DIAN-D1720
Aim 1: Examine features associatd with a CDR.0 diagnosis in non-carriers
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Investigator: Tammie Benzinger, M.D. Ph.D.
Title: Development of a multi-modality deep convolutional neural network feature extraction algorithm for prediction of longitudinal biomarker evolution in Alzheimer’s disease.
Date of Request: June 28, 2017
Status:
ID: DIAN-D1719
Aim 1: Develop and implement an in-lab processing pipeline for using deep neural networks for analysis of cross-sectional and longitudinal MRI, PET, clinical, and psychometric data, with both single and multi-modality implementations.
Aim 2: Replicate findings from previous studies showing successful cross-sectional disease-state classification of subjects using single modality (volumetric MRI) and multi-modality data in the DIAN, Knight ADRC, ADNI reprocessed, and AIBL reprocessed (when available) cohorts.
Aim 3: Utilize the developed platform for deeper exploration of the dynamics of Alzheimer’s biomarkers between ADAD and LOAD cohorts.
Aim 4: Utilize the developed platform for deeper exploration of the dynamics of Alzheimer’s biomarkers between ADAD and LOAD cohorts.
Investigator: William Shannon
Title: DIAN fMRI Longitudinal Data Analysis Proposal
Date of Request: June 28, 2017
Status:
ID: DIAN-D1718
Aim 1: Analysis of longitudinal connectome data
Aim 2: Statistical methods
Aim 3: Improve tracking of brain deterioration and identify earlier prognostic biomarkers
Aim 4: Improve tracking of brain deterioration and identify earlier prognostic biomarkers
Investigator: Christoph Laske and Mathias Jucker
Title: Association between cognition and physical activity in autosomal dominant Alzheimer`s disease
Date of Request: June 6, 2017
Status:
ID: DIAN-D1715
Aim 1: To compare cross-sectional and longitudinal physical activity between mutation carriers (MC) and non-mutation carriers (NC) as a function of estimated years to symptom onset (EYO) and at different clinical stages as assessed with Clinical Dementia Rating (CDR) scale.
Aim 2: To determine the association between cross-sectional and longitudinal physical activity and cognitive parameters (MMSE, CDR global, CDR sum of boxes, Logical Memory, delayed recall).
Aim 3: To determine the minimum and optimum level of physical activity that may have beneficial effects on cognitive functioning and cognitive decline.
Aim 4: To determine the minimum and optimum level of physical activity that may have beneficial effects on cognitive functioning and cognitive decline.
Investigator: Paul Delmar
Title: Understand Disease Progression and iAD patient population characteristics
Date of Request: May 30, 2017
Status: Approved
ID: DIAN-D1714
Aim 1: Better Understand the Disease Progression DIAD population
Aim 2: Better understand the DIAD patient population characteristics
Aim 3: Better Understand the Disease Progression proposed as primary analysis of the DIAN-TU clinical trial
Aim 4: Better Understand the Disease Progression proposed as primary analysis of the DIAN-TU clinical trial
Investigator: Suman Jayadev
Title: MicroRNA regulation of central nervous system and systemic inflammation in AD
Date of Request: May 25, 2017
Status:
ID: DIAN-D1716
Aim 1: Determine if FAD and SAD brain develop distinct patterns of myeloid cell heterogeneity.
Aim 2:
Aim 3:
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Investigator: NA
Title: DIAN Observational Study Exploration
Date of Request: May 15, 2017
Status:
ID: DIAN-D1713
Aim 1: To carry out longitudinal analysis to understand the disease progression in subjects at different phases (prodromal, mild or moderate AD)
Aim 2: To explore the relationship between EYO and onset of disease
Aim 3: To explore the relationship between biomakers (PET, CSF etc) and disease progression
Aim 4: To explore the relationship between biomakers (PET, CSF etc) and disease progression
Investigator: Thomas Liebmann
Title: Validation of quantitative virtual microscopy as a novel tool for early detection of neurodegeneration and Alzheimer’s disease from magnetic resonance imaging data
Date of Request: May 4, 2017
Status:
ID: DIAN-D1717
Aim 1: Establish diagnosis accuracy on confirmed Alzheimer’s disease patient MRI scans using quantitative virtual microscopy
Aim 2: Establish early detection accuracy for discriminating pre-symptomatic degeneration from non-degenerating healthy individuals using quantitative virtual microscopy analysis on MRI scans
Aim 3:
Aim 4:
Investigator: Thomas Liebmann
Title: Validation of quantitative virtual microscopy as a novel tool for early detection of neurodegeneration and Alzheimer�s disease from magnetic resonance imaging data
Date of Request: May 4, 2017
Status:
ID: DIAN-D1712
Aim 1: Establish diagnosis accuracy on confirmed Alzheimer�s disease patient MRI scans using quantitative virtual microscopy
Aim 2: Establish early detection accuracy for discriminating pre-symptomatic degeneration from non-degenerating healthy individuals using quantitative virtual microscopy analysis on MRI scans
Aim 3:
Aim 4:
Investigator: Randall Bateman
Title: Preliminary data to assess viability of potential CSF biomarker study (Pfizer collaboration)
Date of Request: March 23, 2017
Status: Approved
ID: DIAN-D1710
Aim 1: Identify mutations by site to assess feasibility of possibly conducting this study.
Aim 2:
Aim 3:
Aim 4:
Investigator: Benoit Lehallier
Title: Large-scale screening of preclinical biomarkers of Alzheimer�s disease
Date of Request: March 23, 2017
Status: Pending
ID: DIAN-D1711
Aim 1: To develop new algorithms to identify reliable biomarkers of Alzheimer’s disease (AD)
Aim 2: To accurately predict time to MCI or to AD
Aim 3: To investigate the relative interest of imaging, proteomics, clinical and demographics
Aim 4: To investigate the relative interest of imaging, proteomics, clinical and demographics
Investigator: Berislav Zlokovic, Arthur Toga
Title: Vascular Contributions to Dementia and Genetic Risk Factors for Alzheimer�s Disease
Date of Request: March 14, 2017
Status: Approved
ID: DIAN-D1709
Aim 1: To show that loss of blood-brain barrier (BBB) integrity links vascular injury to neuronal injury in AD, and provide data implicating specific brain regions in the association between BBB damage and cognitive decline as influenced by APOE4 and PSEN1 mutations
Aim 2: Examine temporal relationship between BBB permeability, cerebral blood flow (CBF) and white matter lesions (WML).
Aim 3:
Aim 4:
Investigator: Dr. Pieter Jelle Visser
Title: AD pathology and demographic, lifestyle, and comorbid factors: a subject level meta-analysis
Date of Request: March 9, 2017
Status: Approved
ID: DIAN-D1707
Aim 1: To develop an amyloid positivity screening score in subjects with normal cognition, subjective cognitive decline (SCD), mild cognitive impairment (MCI) and dementia. The screening score will be based on demographic variables, lifestyle, and comorbidity.
Aim 2: To evaluate the relation between biomarkers of amyloid positivity and other AD biomarkers in participants with normal cognition, SCD, MCI and dementia
Aim 3: To assess the impact of amyloid positivity on the course of cognitive decline in participants with normal cognition, SCD, MCI and dementia, and investigate how this is affected by demographic, lifestyle and comorbid variables.
Aim 4: To assess the impact of amyloid positivity on the course of cognitive decline in participants with normal cognition, SCD, MCI and dementia, and investigate how this is affected by demographic, lifestyle and comorbid variables.
Investigator: Dr. David B. Pushkin
Title: Theoretical Framework Characterizing Onset of Neurodegenerative Conditions
Date of Request: March 8, 2017
Status: Not Approved
ID: DIAN-D1708
Aim 1: To generate a mathematical model explaining onset and progression of PD, CTE and other related neurological conditions as a consequence of CNS trauma
Aim 2: Generate a tentative mathematical rubric for analyzing individual CSF protein biomarker concentrations with existing data pool from ongoing and published research studies
Aim 3: Generate a more comprehensive explaination regarding onset and progression of neurodegenerative conditions merging principles of neuroscience, neuropathology, statistical thermodynamics, kinetics and equilibrium
Aim 4: Generate a more comprehensive explaination regarding onset and progression of neurodegenerative conditions merging principles of neuroscience, neuropathology, statistical thermodynamics, kinetics and equilibrium
Investigator: Eric McDade
Title: Baseline beta-amyloid and longitudinal non-amyloid biomarker changes
Date of Request: February 2, 2017
Status: Approved
ID: DIAN-D1705
Aim 1: To explore the relantionship of baseline measures of amyloid pathology and subsequent change in non-amyloid biomarkers.
Aim 2:
Aim 3:
Aim 4:
Investigator: Josephine Barnes
Title: Baseline volumes and rates of WMH accrual in familial AD: relationships with brain atrophy and cognitive measures
Date of Request: January 26, 2017
Status:
ID: –
Aim 1: to quantify WMH accrual in FAD using our longitudinal WMH measurement tool
Aim 2: to assess whether WMH accrual is related to concurrent atrophy of the brain and hippocampus, estimated using the boundary shift integral, and also to change in cognition.
Aim 3: to investigate whether any potential relationships from aims 1) and 2) differ according to genetic status (APP vs. PSEN1 vs. PSEN2).
Aim 4: to investigate whether any potential relationships from aims 1) and 2) differ according to genetic status (APP vs. PSEN1 vs. PSEN2).
Investigator: Andrew McKenzie
Title: The role of PSEN1 coding mutations on white matter neuroimaging volumes
Date of Request: January 5, 2017
Status:
ID: DIAN-D1702
Aim 1: Test the hypothesis that individuals with PSEN1 FAD-causative mutations have alterations in their white matter volume sizes compared to individuals without PSEN1 FAD-causative mutations.
Aim 2:
Aim 3:
Aim 4:
Investigator: Mathias Jucker, Johannes Levin, Igor Yakushev
Title: Regional pattern of longitudinal A� accumulation in autosomal dominant Alzheimer’s disease
Date of Request: December 31, 2016
Status:
ID: DIAN-D1701
Aim 1: To investigate regional patterns of longitudinal Aβ accumulation in autosomal dominant AD
Aim 2: To establish a set of target brain regions for antiamyloid clinical trials such as the DIAN-TU
Aim 3:
Aim 4:
Investigator: Elena Rodriguez-Vieitez
Title: Early hypermetabolism in Alzheimer?s disease? Investigating longitudinal multivariate associations between in vivo metabolism, pathophysiology, cognition and genotype
Date of Request: December 23, 2016
Status:
ID: DIAN-D1703
Aim 1: Test the hypothesis of early hypermetabolism in autosomal dominant AD, and investigate longitudinal multivariate associations between in vivo metabolism, pathophysiology and cognition.
Aim 2: Test how cognitive reserve may modulate the longitudinal associations between in vivo biomarkers and cognition investigated in Aim 1.
Aim 3: Investigate the effect of genotype (familial gene type, mutation type, APOE) on the longitudinal associations investigated in Aims 1 and 2.
Aim 4: Investigate the effect of genotype (familial gene type, mutation type, APOE) on the longitudinal associations investigated in Aims 1 and 2.
Investigator: Chengjie Xiong
Title: Cross-sectional and Longitudinal Comparison of DIAN MC and those in the ACS on Biomarkers and Cognitions when Baseline Ages are Matched
Date of Request: December 6, 2016
Status:
ID: DIAN-D1704
Aim 1: To compare DIAN MC to those with a positive family history in the ACS on baseline Biomarkers and Cognitions when their age were matched
Aim 2: To compare DIAN MC to those with a positive family history in the ACS on the longitudinal rates of changes in Biomarkers and Cognitions when their baseline age were matched
Aim 3:
Aim 4:
Investigator: Mirza Faisal Beg
Title: Characterizing neuroimaging patterns in subjects with MCI progressing to frank AD
Date of Request: November 24, 2016
Status:
ID: DIAN-D1626
Aim 1: 1. To identify neuroimaging biomarkers that can predict the subset of subjects with MCI converting to AD
Aim 2: 2. To identify the timing (age) of conversion from MCI to AD by predicting cognitive decline and change in CSF measures
Aim 3:
Aim 4:
Investigator: Chengjie Xiong, PhD
Title: PreClinical Biomarker Signature RF1
Date of Request: November 4, 2016
Status:
ID: DIAN-D1625
Aim 1: Integrate the biomarkers and clinical and cognitive databases from ACS+, AIBL, BIOCARD, and WRAP, and develop novel statistical methods for testing the ordering of all biomarkers, both cross-sectionally and longitudinally, to determine which biomarkers indicate the highest likelihood of preclinical
Aim 2: Statistically validate the preclinical stages of AD as proposed by the National Institute on Aging Alzheimer’s Association (NIA-AA) Workgroup (Sperling et al. 2011) using data from ACS+, AIBL, BIOCARD, and WRAP, and quantify the amount of preclinical biomarker signature (PBS) through optimum weight
Aim 3: Optimize the design of modern randomized clinical trials (RCTs) in preclinical or early-stage AD by identifying the cognitive composite that minimizes the sample sizes required to adequately power such trials.
Aim 4: Optimize the design of modern randomized clinical trials (RCTs) in preclinical or early-stage AD by identifying the cognitive composite that minimizes the sample sizes required to adequately power such trials.
Investigator: Sylvia Villeneuve
Title: The role of heredity in pre-clinical AD biomarkers: comparison of sporadic AD and autosomal dominant AD
Date of Request: October 25, 2016
Status:
ID: DIAN-D1624
Aim 1: Compare severity of AD biomarkers changes (including cognition, blood, beta-amyloid and tau CSF, functional and structural MRI; beta-amyloid and tau PET) between asymptomatic individuals with a familial risk of sporadic AD and preclinical ADAD
Aim 2: Compare annual rate of change in AD biomarkers (longitudinal analyses) between asymptomatic individuals with a familial risk of sporadic AD and preclinical ADAD
Aim 3: Assess the influence of other risk factors (APOE, sex, etc.) on AD biomarkers trajectories in both populations
Aim 4: Assess the influence of other risk factors (APOE, sex, etc.) on AD biomarkers trajectories in both populations
Investigator: Jonathan Voeglein
Title: Effect of cigarette smoking on cognition and amyloid burden in the DIAN-OBS (Amendment for DIAN-D1610)
Date of Request: October 24, 2016
Status:
ID: –
Aim 1: To find out whether there is an influence of cigarette smoking on cognition and on amyloid burden measured by PIB-PET in participants of the DIAN-OBS
Aim 2:
Aim 3:
Aim 4:
Investigator: NA
Title: Attentional Control in Dominantly Inherited Alzheimer disease
Date of Request: September 28, 2016
Status:
ID: DIAN-D1623
Aim 1: Establish rates of change in attentional control in DIAN
Aim 2: Evaluate alternative measures of performance using compuational modelling
Aim 3:
Aim 4:
Investigator: Hungbo Luo
Title: Tauopathy in Autosomal Dominant and Late-Onset Alzheimer Disease
Date of Request: September 27, 2016
Status:
ID: DIAN-D1622
Aim 1: Determine the relative burden of tauopathy in archicortical and neocortical areas in ADAD and LOAD using unbiased stereologic methods.
Aim 2: Determine the contribution of different lesions (neuropil threads, dystrophic neurites, and neurofibrillary tangles) to the overall tau burden in neocortical and archicortical regions.
Aim 3: Determine the relationship between the clinical phenotypes of LOAD and ADAD and spatial patterns of tauopathy.
Aim 4: Determine the relationship between the clinical phenotypes of LOAD and ADAD and spatial patterns of tauopathy.
Investigator: Timothy Hohman
Title: Building a Resilience Phenotype in DIAN
Date of Request: September 1, 2016
Status:
ID: DIAN-D1621
Aim 1: Define a resilience phenotype in the cohort based on better-than-expected cognition and hippocampal volume given an individuals level of AD biomarkers
Aim 2:
Aim 3:
Aim 4:
Investigator: JC Morris
Title: APOE4 effect on brains tructure and function in cognitively normal young-to-middle age adults
Date of Request: August 26, 2016
Status:
ID: DIAN-D1620
Aim 1: DIAN NCs with an E4 allele will have greater risk of having an “Alzheimer signature”
Aim 2:
Aim 3:
Aim 4:
Investigator: Serge Gauthier
Title: Neuropsychiatric Symptoms Predicting Neurodegeneration In Asymptomatic Autosomal Dominant Alzheimer?s Disease Mutation Carriers
Date of Request: August 25, 2016
Status:
ID: DIAN-D1619
Aim 1: Test the hypothesis that the magnitude of neuropsychiatric symptoms predicts subsequent cingulate hypometabolism in asymptomatic ADAD mutation carriers over 24 months.
Aim 2: Replicate our findings obtained from the ADNI cohort in which baseline Neuropsychiatric Inventory (NPI) predicts neurodegeneration in cognitively normal individuals with preclinical AD.
Aim 3:
Aim 4:
Investigator: Jason Hassenstab
Title: Developing the DIAN-TU Cognitive Endpoint
Date of Request: August 17, 2016
Status:
ID: DIAN-D1617
Aim 1: Evaluate combinations of cognitive tests in order to develop the most sensitive composite score for use as the primary cognitive endpoint in the DIAN-TU trial.
Aim 2:
Aim 3:
Aim 4:
Investigator: Jason Hassenstab
Title: Evaluating the utility of �run-in� data for use in AD prevention trials: Results from the DIAN observational study
Date of Request: August 17, 2016
Status:
ID: DIAN-D1618
Aim 1: To evaluate the utility of including �run-in� data to increase power to detect a treatment effect.
Aim 2:
Aim 3:
Aim 4:
Investigator: Michael Ewers
Title: Is global connectivity of the left frontal cortex a neural substrate of reserve in subjects with autosomal dominant Alzheimer’s disease?
Date of Request: August 7, 2016
Status:
ID: DIAN-D1615
Aim 1: To test whether LFC connectivity is associated with protective factors such as years of education, IQ, leisure activities (i.e. years of education, IQ)
Aim 2: To test whether LFC connectivity is associated with higher cognitive performance at any given level of disease severity
Aim 3: To test whether LFC changes with disease severity during the course of AD and relates to dementia symptom onset
Aim 4: To test whether LFC changes with disease severity during the course of AD and relates to dementia symptom onset
Investigator: M Ewers
Title: Association between CSF sTREM2 and white matter changes
Date of Request: August 5, 2016
Status:
ID: DIAN-D1616
Aim 1: Test whether higher CSF sTREM2 is associated with stronger WMH volume, fiber tract damage (DTI) and lower functional connetivity
Aim 2:
Aim 3:
Aim 4:
Investigator: Katrina Paumier
Title: Antidepressant-mediated disease-modifying effects in ADAD
Date of Request: July 5, 2016
Status:
ID: DIAN-D1614
Aim 1: Determine whether antidepressant treatment reduces brain amyloid deposition (PET)
Aim 2: Determine if antidepressants alter CSF biomarkers (A-beta, tau, ptau, etc.)
Aim 3: Determine if the onset of symptoms is delayed in antidepressant treated individuals.
Aim 4: Determine if the onset of symptoms is delayed in antidepressant treated individuals.
Investigator: E Coulson
Title: Basal forebrain degeneration in familial AD
Date of Request: June 13, 2016
Status:
ID: DIAN-D1613
Aim 1: Determine whether basal forebrain (BF) degeneration occurs in familial AD
Aim 2: Determine the relationship between BF degeneration and cognitive decline
Aim 3: Determine the relationship between BF degeneration and hippocampal/cortical degneration
Aim 4: Determine the relationship between BF degeneration and hippocampal/cortical degneration
Investigator: John C Morris
Title: Correlates of synucleinopathy in DIAN mutation carriers
Date of Request: June 1, 2016
Status:
ID: DIAN-D1612
Aim 1: Determine in autopsied DIAN participants and their autopsied family members wherther synculeinopathy is associated with particular mutations
Aim 2: In the same sample as for Aim 1, determine whether autopsied DIAN participants with synculeinopathy had clinical (behavioral, cognitive, neurological) features of Lewy body disease
Aim 3: Examine clinical (behavioral, cognitive, neurological) features of Lewy body disease in DIAN mutation carriers (asymptomatic and symptomatic)
Aim 4: Examine clinical (behavioral, cognitive, neurological) features of Lewy body disease in DIAN mutation carriers (asymptomatic and symptomatic)
Investigator: Beau Ances
Title: Structure Function of Amyloid Progression
Date of Request: May 17, 2016
Status:
ID: –
Aim 1: Can function alone predict Amyloid Progression across time.
Aim 2: Can structure alone predict Amyloid Progression across time.
Aim 3: Can structure and function predict Amyloid Progression across time.
Aim 4: Can structure and function predict Amyloid Progression across time.
Investigator: Beau Ances
Title: Structure Function of Amyloid Progression
Date of Request: April 15, 2016
Status:
ID: DIAN-D1611
Aim 1: Can function alone predict Amyloid Progression across time.
Aim 2: Can structure alone predict Amyloid Progression across time.
Aim 3: Can structure and function predict Amyloid Progression across time.
Aim 4: Can structure and function predict Amyloid Progression across time.
Investigator: Jonathan V�glein
Title: Effect of cigarette smoking on the age of onset in ADAD
Date of Request: March 29, 2016
Status:
ID: DIAN-D1610
Aim 1: The specific aim for the proposed work with the DIAN data set is to find out whether there is an influence of cigarette smoking on the age of onset in individuals with ADAD.
Aim 2:
Aim 3:
Aim 4:
Investigator: John C. Morris, MD
Title: Prevelence and growth of microbleeds in autosomal dominant Alzheimer’s disease: link with amyloidosis and white matter disease
Date of Request: March 8, 2016
Status:
ID: DIAN-D1609
Aim 1: Evaluate correspondance between microbleeds oberved in vivo and vascular abnormalities (as CAA) observed at autopsie
Aim 2: Evaluate impact of the mutation type on microbleeds and CAA observed on imaging and at autopsie
Aim 3:
Aim 4:
Investigator: PD Dr. Johannes Levin
Title: Frequency of movement disorders in ADAD mutation carriers
Date of Request: February 24, 2016
Status:
ID: DIAN-D1608
Aim 1: The specific aim for the proposed work with the DIAN data set is to find out whether there is a difference in frequency of movement disorders in ADAD mutation carriers compared to non-carriers.
Aim 2: Additionally we aim for the examination of the kind of movement disorders respectively their particular frequency and the time of occurrence in the course of the disease.
Aim 3: Furthermore we are planning to follow an enhanced approach by querying the NACC data base for a comparison of frequency of movement disorders between patients with sporadic Alzheimer�s disease, ADAD mutation carriers and non-carriers.
Aim 4: Furthermore we are planning to follow an enhanced approach by querying the NACC data base for a comparison of frequency of movement disorders between patients with sporadic Alzheimer�s disease, ADAD mutation carriers and non-carriers.
Investigator: Carlos Cruchaga
Title: Genetic Studies Using CSF biomarker levels
Date of Request: February 19, 2016
Status:
ID: DIAN-D1607
Aim 1: to identify novel genetic modifiers factors using use the CSF biomarker levels (tau, ptau, AB, YKL40, VILIP1, GRN and TREM2) as endophenotype for genetic studies
Aim 2: to determine whether we can incorporate genetic information to increase the sensitivity and specify of the CSF biomarkers
Aim 3:
Aim 4:
Investigator: Jasmeer Chhatwal
Title: Evaluating Mutation Type and Genotype Specific Amyloid Trajectories in DIAN
Date of Request: February 9, 2016
Status:
ID: DIAN-D1606
Aim 1: Determine if mutation genotype significantly interacts with EYO in predicting amyloid burden measured by PET and CSF.
Aim 2:
Aim 3:
Aim 4:
Investigator: John M. Ringman, M.D., M.S.
Title: Description of a novel pathogenic PSEN1 mutation (S230N)
Date of Request: January 31, 2016
Status:
ID: DIAN-D1605
Aim 1: We want to write a manuscript presenting the comprehensive descriptions of 3 persons from a family featuring a novel PSEN1 mutation, including PiB scans, quantification of MRI and CSF variables.
Aim 2:
Aim 3:
Aim 4:
Investigator: Eric McDade
Title: Task Based Functional MRI in Preclinical Autosomal Dominant Alzheimer Dementia
Date of Request: January 27, 2016
Status:
ID: DIAN-D1604
Aim 1: To identify differences in neuronal network function during working memory and learning in preclinical ADAD
Aim 2: To explore the association of task-based functional MRI activity in preclinical mutation carriers with imaging and CSF based AD pathology.
Aim 3: To explore task-based function MRI activity with longitudinal PET amyloid deposition.
Aim 4: To explore task-based function MRI activity with longitudinal PET amyloid deposition.
Investigator: Dawn Matthews
Title: Multimodality Imaging Diagnostic for Preclinical and Prodromal AD
Date of Request: January 25, 2016
Status:
ID: DIAN-D1603
Aim 1: Further refine and validate our use of early frame amyloid data as a marker of disease and predictor of functional change
Aim 2: Refine and validate PET and structural MRI classifiers in differentiating amyloid positive and negative populations and predicting rate of clinical decline.
Aim 3: Optimize processing and classification approaches to functional MRI data as available to characterize disease state and progression
Aim 4: Optimize processing and classification approaches to functional MRI data as available to characterize disease state and progression
Investigator: NA
Title: State space modeling of the clinical and biomarker changes in Dominantly Inherited Alzheimer?s Disease
Date of Request: January 15, 2016
Status:
ID: DIAN-D1602
Aim 1: Apply state space model to DIAN data to estimate the clinical and biomarker changes in Dominantly Inherited Alzheimer’s Disease
Aim 2: Compare the results from state space model with the result from the mixed model
Aim 3: Simulate Alzheimer’s disease clinical trials based on the DIAN data and to propose statistical test methods for efficacy
Aim 4: Simulate Alzheimer’s disease clinical trials based on the DIAN data and to propose statistical test methods for efficacy
Investigator: Karch
Title: Clinical and Molecular Characterization of Novel PSEN1 Mutation
Date of Request: January 8, 2016
Status: Pending
ID: DIAN-D1601
Aim 1: To describe the biomarker (fluid and imaging) profile for research participants from a family with a novel PSEN1 mutation
Aim 2:
Aim 3:
Aim 4:
Investigator: Randall J Bateman
Title: DIAN-TU NexGen Trial Design Manuscript
Date of Request: December 29, 2015
Status:
ID: DIAN-D1517
Aim 1: Disseminate DIAN-TU NexGen trial design analyses
Aim 2: Optimize DIAN-TU cognitive composite for the primary endpoint
Aim 3: Develop a desease progression model for autosomal dominant Alzheimer’s disease
Aim 4: Develop a desease progression model for autosomal dominant Alzheimer’s disease
Investigator: Prof. Dr. Adrian Danek
Title: Frequency of seizures in the DIAN cohort: A comparison between mutation carriers and non-carriers
Date of Request: November 23, 2015
Status:
ID: DIAN-D1516
Aim 1: Our specific aim for our proposed work with the DIAN data set is to find out whether there is a difference in frequency of seizures in mutation carriers of familial Alzheimer?s disease in comparison to non-carriers.
Aim 2: Furthermore we are planning to follow an enhanced approach by querying the NACC data base for a comparison of frequency of seizures between patients with sporadic Alzheimer?s disease, mutation carriers for the familial Alzheimer?s disease and non-carriers.
Aim 3: A further possibility is to additionally include patients with frontotemporal lobar degeneration for comparison of frequency of seizures.
Aim 4: A further possibility is to additionally include patients with frontotemporal lobar degeneration for comparison of frequency of seizures.
Investigator: John Ringman/JJ Wang
Title: Microhemorrhages and vascular compliance
Date of Request: November 9, 2015
Status:
ID: DIAN-D1515
Aim 1: To relate number of micro hemorrhages to cerebrovascular compliance for UCLA DIAN subjects
Aim 2:
Aim 3:
Aim 4:
Investigator: NA
Title: Examining the relationship between exercise, Aβ accumulation, brain atrophy and age at onset: A study of autosomal-dominant Alzheimer?s disease mutation carriers
Date of Request: November 3, 2015
Status:
ID: DIAN-D1514
Aim 1: 1. Examine the rates of brain Aβ accumulation between exercising and sedentary asymptomatic mutation carriers, versus aged matched non-mutation carriers.
Aim 2: 2. Examine rates of hippocampal and prefrontal cortex atrophy between exercising and sedentary asymptomatic mutation carriers, versus aged matched non-mutation carriers.
Aim 3: 3. Examine the relationship between baseline exercise levels and age at onset in symptomatic mutation carriers.
Aim 4: 3. Examine the relationship between baseline exercise levels and age at onset in symptomatic mutation carriers.
Investigator: Serge Gauthier
Title: Neurobiological Markers of Suicide Vulnerability in Alzheimer?s Disease Patients
Date of Request: September 3, 2015
Status:
ID: DIAN-D1513
Aim 1: to characterize neurobiological markers (socio-demographic, clinical, neuropsychological, and biological profile) of asymptomatic ADAD mutation carriers and symptomatic ADAD mutation carriers with suicidal ideations (suicidal patients).
Aim 2: to compare neurobiological markers (socio-demographic, clinical, neuropsychological, and biological) in a) asymptomatic ADAD mutation carriers suicidal patients, b) symptomatic ADAD mutation carriers suicidal patients, c) asymptomatic non-mutation carrier non-suicidal controls, and to d) symptomatic
Aim 3:
Aim 4:
Investigator: Ryoko Ihara
Title: Outcomes from awareness of mutation status in DIAN study
Date of Request: August 21, 2015
Status:
ID: DIAN-D1512
Aim 1: To investigate how awareness of mutation status affects mental status and cognitive decline both in short term and long term
Aim 2: To investigate how awareness of mutation status before participation affects motivation for the study participation afterwards
Aim 3:
Aim 4:
Investigator: Dr Vincent de la Sayette
Title: Amyloid imaging in young to middle-aged adults
Date of Request: August 17, 2015
Status:
ID: DIAN-D1511
Aim 1: understand AB deposition and progression in young to middle-aged cognitively normal adults
Aim 2:
Aim 3:
Aim 4:
Investigator: Jason Hassenstab
Title: Using Run-in Data for Cognitive Endpoint Secondary Prevention Trials
Date of Request: August 12, 2015
Status:
ID: DIAN-D1510
Aim 1: Determine if data collected prior to randomization can increase power of seconday prevention trials.
Aim 2:
Aim 3:
Aim 4:
Investigator: Alex Whittington
Title: Spatiotemporal Modelling of misfolded proteins in AD
Date of Request: July 22, 2015
Status:
ID: DIAN-D1509
Aim 1: Characterising the spatiotemporal pattern of Beta-amyloid in AD in vivo
Aim 2: Temporal ordering of subjects in AD
Aim 3: Using temporal ordering as a classifier
Aim 4: Using temporal ordering as a classifier
Investigator: Suprateek Kundu
Title: Statistical approaches for early detection of Alzheimer’s Disease
Date of Request: July 17, 2015
Status:
ID: DIAN-D1507
Aim 1: Based on previous data on amyloids, predict if a future subject is likely to have Alzheimer’s
Aim 2: Develop flexible statistical methodology for detecting the time of onset of Alzheimer’s disease based on studying amyloid levels
Aim 3:
Aim 4:
Investigator: John Ringman
Title: White matter pathology in PSEN1-related spastic paraparesis
Date of Request: July 17, 2015
Status:
ID: DIAN-D1508
Aim 1: To assess MRI measures of white matter pathology in PSEN1 mutation carriers with spastic paraparesis relative to those without
Aim 2:
Aim 3:
Aim 4:
Investigator: Anne Poljak
Title: Amyloid-beta blood levels as an early marker of neurodegenerative disease
Date of Request: June 16, 2015
Status:
ID: DIAN-D1506
Aim 1: Explore correlation of clinical covariates with Aβ levels
Aim 2: Compare corrected Aβ levels (all cohorts) across neurodegenerative diseases AD, PD, MCI, vascular dementia
Aim 3: Effects of soluble Aβ levels on brain volumetric parameters
Aim 4: Effects of soluble Aβ levels on brain volumetric parameters
Investigator: Walter A. Kukull, PhD; Scott Hofer, Andrea Piccinin, Jeffrey Kaye, and Diana Kuh
Title: Using DIAN to motivate statistical methods in aging and dementia research
Date of Request: June 11, 2015
Status:
ID: DIAN-D1505
Aim 1: Use DIAN as an example dataset for the upcoming “Statistical Methods Conference on Aging & Dementia”. The dataset will be used to stimulate discussion and novel ideas on the development of better statistical methods for study design and analysis in aging and dementia research.
Aim 2: As an particular example, DIAN will be investigated for building prediction models of conversion from normal/MCI to MCI/dementia
Aim 3:
Aim 4:
Investigator: n/a
Title: to be decided
Date of Request: March 27, 2015
Status:
ID: DIAN-D1504
Aim 1: exploration of data using the structural equation modeling
Aim 2:
Aim 3:
Aim 4:
Investigator: Simon Duchesne
Title: Neuromorphometric phenotypes in sporadic and dominantly inherited forms of Alzheimer’s disease
Date of Request: March 16, 2015
Status:
ID: DIAN-D1503
Aim 1: To compare the patterns of neuromorphometric changes throughout the predementia and dementia stages of dominantly inherited AD (diAD) and sporadic AD (sAD)
Aim 2:
Aim 3:
Aim 4:
Investigator: Roy Anderson
Title: Phase II and III trial simulators: Using mathematical, computational and statistical techniques to simulate trial design for new products in the treatment, vaccination and immunoprophylaxis of disease
Date of Request: March 5, 2015
Status:
ID: DIAN-D1502
Aim 1: To develop mathematical models of the progression of Alzheimer’s disease
Aim 2: To establish a database of Alzheimer’s data, and to perform meta-analyses of this data
Aim 3: To create a clinical trial simulator of phase I and II trials of Alzheimer’s interventions
Aim 4: To create a clinical trial simulator of phase I and II trials of Alzheimer’s interventions
Investigator: N/A
Title: Comparison of graph characteristics in resting state fMRI in LOAD and DIAN participants
Date of Request: January 28, 2015
Status:
ID: DIAN-D1501
Aim 1: Determine graph characteristics (wavelet-based coherence, binary graph diagnostics, weighted and cynamic graph diagnostics in LOAD and DIAN
Aim 2: Determine similarities and differences in these graph characteristics
Aim 3:
Aim 4:
Investigator: Eric M. Reiman
Title: evaluation of various biomarker longitudinal changes
Date of Request: November 18, 2014
Status:
ID: DIAN-D1413
Aim 1: The possible use of ASL as a perfusion biomarker as possible replacement of FDG-PET
Aim 2: the possible use of perfusion PiB (early frames) as possible replacement of FDG-PET
Aim 3: comparison of ASL, perfusion PiB and FDG-PET
Aim 4: comparison of ASL, perfusion PiB and FDG-PET
Investigator: not applicable
Title: Clinical and cognitive comparison of LOAD and ADAD
Date of Request: November 17, 2014
Status:
ID: DIAN-D1412
Aim 1: Determine whether change in cognition and clinical measures of the UDS is similar in LOAD and ADAD
Aim 2:
Aim 3:
Aim 4:
Investigator: Dale Bredesen
Title: Self-report and informant report personality change in familial Alzheimer’s disease in the Dominantly Inherited Alzheimer Network
Date of Request: October 31, 2014
Status:
ID: DIAN-D1411
Aim 1: Examine longitudinal change in different domains of personality in carriers and noncarriers of ADAD mutations.
Aim 2: Compare self-report and informant report personality ratings at different CDR levels.
Aim 3: Identify differences in baseline personality traits between entirely presymptomatic ADAD mutation carriers and non-carriers.
Aim 4: Identify differences in baseline personality traits between entirely presymptomatic ADAD mutation carriers and non-carriers.
Investigator: Clifford R. Jack, Jr., M.D.
Title: TBM-SyN in DIAN
Date of Request: October 2, 2014
Status:
ID: DIAN-D1410
Aim 1: Measure atrophy rates in DIAN subjects with a new algorithm called TBM-SyN
Aim 2: Test hypothesis that sample size estimates will be superior with TBM-SyN than with longitudinal freesurfer
Aim 3:
Aim 4:
Investigator: Dr Kirsi Kinnunen
Title: Fronto-thalamic effective connectivity in familial Alzheimer?s disease
Date of Request: September 18, 2014
Status:
ID: DIAN-D1409
Aim 1: To investigate effective connectivity of three anatomically defined fronto-thalamic circuits in the DIAN baseline data. Specifically, we propose to use stochastic dynamic causal modelling (sDCM) of regional time-courses extracted from resting-state functional MRI (rs-fMRI).
Aim 2: To determine whether abnormalities of effective connectivity within these neural circuits can be detected during presymptomatic or early-stage familial Alzheimers disease (FAD), and to evaluate the utility of different metrics as potential imaging biomarkers.
Aim 3: To explore the (cross-sectional) relationships between the imaging metrics and measures of cognitive function and behaviour.
Aim 4: To explore the (cross-sectional) relationships between the imaging metrics and measures of cognitive function and behaviour.
Investigator: Paul Thompson, Ph.D.
Title: Growth factors, neuroinflammation, exercise, and brain integrity
Date of Request: September 18, 2014
Status:
ID: DIAN-D1408
Aim 1: Determine how inflammation gene risk variants influence inflammation marker TNFα, and how genes and TNFα together relate to brain volume.
Aim 2: Show how growth factors and homocysteine relate ROI (hippocampus, cingulate gyrus, prefrontal cortex) volumes.
Aim 3: Determine (1) how our ROI volumes relate to measures of exercise (2) how growth factors and TNFα modulate any relationship between exercise and these ROIs.
Aim 4: Determine (1) how our ROI volumes relate to measures of exercise (2) how growth factors and TNFα modulate any relationship between exercise and these ROIs.
Investigator: Anders Martin Fjell
Title: Patterns and mechanisms of brain atrophy in healthy aging and dementia
Date of Request: August 13, 2014
Status: IP
ID: DIAN-D1407
Aim 1: To test the relationship between structural brain measures, amyloid levels and cognitive function
Aim 2:
Aim 3:
Aim 4:
Investigator: Randall Bateman
Title: Phenotypic Variability in Autosomal Dominant Alzheimer’s Disease
Date of Request: June 30, 2014
Status: IP
ID: DIAN-D1406
Aim 1: Establish correlations between specific ADAD mutation types and clinical presentation, taking into account the familial genetic background.
Aim 2: Aim 2. Identify groups of mutations which have similarities in both clinical phenotype and biomarker and imaging profiles.
Aim 3:
Aim 4:
Investigator: Joshua Grill
Title: Understanding attitudes toward clinical trials among persons at risk for autosomal dominant Alzheimer’s disease
Date of Request: June 3, 2014
Status: IP
ID: DIAN-D1405
Aim 1: To characterize the differences in DIAN participants who do and do not want to know their genetic status
Aim 2: To examine the proportion of at-risk individuals who would change their mind whether to undergo genetic testing in the setting of a clinical trial and to characterize differences in these participants, compared to those continue to refuse genetic testing
Aim 3: To assess the effects of the possibility of receiving placebo and varying drug/placebo ratios on persons’ desire to undergo genetic testing and participate in a clinical trial
Aim 4: To assess the effects of the possibility of receiving placebo and varying drug/placebo ratios on persons’ desire to undergo genetic testing and participate in a clinical trial
Investigator: Peter Nestor
Title: QSM analysis of susceptibility weighted imaging data
Date of Request: March 26, 2014
Status: A
ID: DIAN-D1404
Aim 1: development of quantitative susceptibility mapping as a novel biomarker in preclinical AD
Aim 2: To examine whether early basal ganglia PIB ligand uptake is associated with altered iron levels
Aim 3:
Aim 4:
Investigator: Mathias Jucker
Title: Vital signs in the different stages of dominantly inherited Alzheimer`s disease
Date of Request: February 17, 2014
Status: A
ID: DIAN-D1403
Aim 1: To compare vital signs between mutation carriers (MC) and non-mutation carriers (NMC) at different clinical stages as assessed with Clinical Dementia Rating (CDR) scale.
Aim 2: To compare vital signs between MC and NMC as a function of estimated years to onset (EYO).
Aim 3: To determine the association between vital signs and clinical parameters (age, gender, EYO, GDS), psychometric parameters (MMSE, CDR global, CDR sum of boxes, Logical Memory, delayed recall), biochemical biomarkers (CSF levels of Abeta 1-42 and tau) and neuro-imaging biomarkers (PiB-PET SUVR).
Aim 4: To determine the association between vital signs and clinical parameters (age, gender, EYO, GDS), psychometric parameters (MMSE, CDR global, CDR sum of boxes, Logical Memory, delayed recall), biochemical biomarkers (CSF levels of Abeta 1-42 and tau) and neuro-imaging biomarkers (PiB-PET SUVR).
Investigator: Ralph Martins
Title: Brain and cognitive reserve capacities in DIAN participants
Date of Request: January 8, 2014
Status: IP
ID: DIAN-D1402
Aim 1: 1. To examine whether DIAN participants differ in terms of their brain reserve (as indicated by brain volume, cortical thickness, white matter hyper intensities etc.) and cognitive reserve (as indicated by education years and Hollingshead Index of Social Position).
Aim 2: 2. 2. To examine if cognitive and brain reserves indices are associated with delay in clinical manifestation of the AD.
Aim 3: 3. 3. To Compare these groups on blood and CSF biomarkers and imaging results at baseline and follow ups
Aim 4: 3. 3. To Compare these groups on blood and CSF biomarkers and imaging results at baseline and follow ups
Investigator: Ralph Martins
Title: Cerebral Amyloid Angiopathy due to APP mutation: Clinicopathological manifestations and brain imaging findings
Date of Request: January 7, 2014
Status: IP
ID: DIAN-D1401
Aim 1: 1. To investigate the clinicopathological features of cerebral amyloid angiopathy in an HCHWA-Dutch Type kindred
Aim 2: 2. To investigate the CSF and Blood biomarkers related to Alzheimer’s disease in the APP Dutch Type mutation carriers and non-carriers
Aim 3: 3. To compare the mutation carriers and non-carriers’ on MRI, FDG and PiB PET imaging results
Aim 4: 3. To compare the mutation carriers and non-carriers’ on MRI, FDG and PiB PET imaging results
Investigator: Serena McCalla
Title: Patch-Based Analysis of Anatomical Brain Asymmetry
Date of Request: December 19, 2013
Status: IA
ID: DIAN-D1319
Aim 1: Identify characteristic structural asymmetry patterns in diseased individuals versus healthy controls
Aim 2:
Aim 3:
Aim 4:
Investigator: Arthur Toga
Title: Alzheimer’s Disease Biomarkers via a Multimodal statistical approach
Date of Request: December 11, 2013
Status: IP
ID: DIAN-D1318
Aim 1: Determine imaging and clinical biomarkers for the risk of Alzheimer’s Diease
Aim 2: Conceputalize a target sample size that could be used for clinical trials based on the power of targeted biomarkers
Aim 3:
Aim 4:
Investigator: Prof. Ralph Martins
Title: Plasma and cerebrospinal fluid phospholipid profiles in a DIAN cohort subset
Date of Request: November 22, 2013
Status: A
ID: DIAN-D1317
Aim 1: To find phospholipid species which significantly differ in concentrations between mutation carriers and non carriers.
Aim 2: To correlate the phospholipid species obtained in aim 1, with the established gold standard biomarkers such as PiB-PET SUVR, cerebrospinal fluid concentrations of total-tau, phosphorylated-tau and Aβ42.
Aim 3: correlate the plasma phospholipid species obtained in aim 1, with FDG-PET SUVR, MRI data and plasma Abeta levels.
Aim 4: correlate the plasma phospholipid species obtained in aim 1, with FDG-PET SUVR, MRI data and plasma Abeta levels.
Investigator: David Teplow
Title: Imaging and biomarker correlates of spastic paraparesis associated with PSEN1 mutations
Date of Request: November 21, 2013
Status: IP
ID: DIAN-D1316
Aim 1: To compare white matter, among persons with PSEN1 mutations, between those with and without spastic paraparesis using DTI
Aim 2: To compare cerebral amyloidosis, among persons with PSEN1 mutations, between those with and without spastic paraparesis using PIB images
Aim 3:
Aim 4:
Investigator: Nick Fox
Title: Rates of longitudinal microstructural change in familial AD using diffusion weighted imaging
Date of Request: November 11, 2013
Status: IP
ID: DIAN-D1315
Aim 1: Estimate rates of change in microstructure diffusion measurements (FA, MD, radial and axial diffusivity) in familial Alzheimer’s disease
Aim 2: Determine at what point in time do these changes diverge from non-carriers
Aim 3: Calculate sample sizes needed to detect a substantial treatment effect within a clinical trial similar to the population that will enter the DIAN clinical trials
Aim 4: Calculate sample sizes needed to detect a substantial treatment effect within a clinical trial similar to the population that will enter the DIAN clinical trials
Investigator: Mathias Jucker
Title: Sample sizes for different EYO intervals with and without amyloid
Date of Request: November 1, 2013
Status: IP
ID: DIAN-D1314
Aim 1: Determine sample sizes for different EYO intervals with and without amyloid
Aim 2:
Aim 3:
Aim 4:
Investigator: Juergen Dukart
Title: Linking connectivity and structural patterns in AD
Date of Request: October 11, 2013
Status: IP
ID: DIAN-D1313
Aim 1: Establishing a resting state connectivity pattern in AD
Aim 2: Linking structural and resting state connectivity biomarkers
Aim 3:
Aim 4:
Investigator: Jeffrey Petrella
Title: The Alzheimer’s Connectome: Relationships between structural and functional changes in the DIAN population
Date of Request: October 9, 2013
Status: A
ID: DIAN-D1312
Aim 1: Determine whether changes in the structural connectome are associated with changes in the functional connectome across diagnostic groups in the DIAN population
Aim 2: Determine whether changes in the structural connectome are affected by increasing beta amyloid burden in the DIAN population.
Aim 3:
Aim 4:
Investigator: Jurgen Claassen
Title: Association between amyloid-beta, systemic (blood pressure) and brain vascular changes.
Date of Request: September 24, 2013
Status: A
ID: DIAN-D1311
Aim 1: To investigate associations between amyloid-β accumulation (carrier vs non-carrier) and baseline blood pressure changes
Aim 2: To investigate associations between amyloid-β accumulation (carrier vs non-carrier) and visit to visit blood pressure variability
Aim 3: To investigate associations between amyloid-β accumulation (carrier vs non-carrier) and cerebral blood flow (derived from PET)
Aim 4: To investigate associations between amyloid-β accumulation (carrier vs non-carrier) and cerebral blood flow (derived from PET)
Investigator: Tammie Benzinger
Title: Analysis of cortical volume as a risk factor for post lumbar puncture headache
Date of Request: July 24, 2013
Status: A
ID: DIAN-D1310
Aim 1: To determine whether cortical volume is a risk factor for post lumbar puncture headache
Aim 2:
Aim 3:
Aim 4:
Investigator: Anne Fagan
Title: Relationship between CSF cell counts and biomarkers
Date of Request: July 18, 2013
Status: A
ID: DIAN-D1309
Aim 1: To assess the relationship between CSF cell counts and biomarker levels
Aim 2:
Aim 3:
Aim 4:
Investigator: Randall Bateman
Title: Clinical and cognitive measures of the DIAN cohort
Date of Request: July 12, 2013
Status: A
ID: DIAN-D1308
Aim 1: Determine the longitudinal rate of clinical conversion from cognitively normal to dementia in a carefully studied population of DIAN participants including average age of onset and CDR and psychometric rate of progression.
Aim 2: Evaluate the cognitive and clinical change, including rate of change, by multifactorial analysis including age, estimated years to onset (parental age of onset), ApoE4, average familial onset, genetic risk factors and biomarkers.
Aim 3:
Aim 4:
Investigator: Randall Bateman
Title: Post-dural puncture headache: An analysis of the risks of experiencing headaches after a Lumbar Puncture procedure on the Dominantly Inherited Alzheimer Network (DIAN) participants
Date of Request: June 17, 2013
Status: A
ID: DIAN-D1307
Aim 1: Analyze the relationships between factors of CSF collection of LP procedures on and adverse events of DIAN participants.
Aim 2:
Aim 3:
Aim 4:
Investigator: Yen Ying Lim
Title: Relationship between BDNF Val66Met, Aβ, cognitive function and hippocampal volume in patients who are at risk of developing autosomal dominant Alzheimer’s disease
Date of Request: April 30, 2013
Status: A
ID: DIAN-D1306
Aim 1: Examine the association between BDNF Val66Met, Aβ, disease classification (healthy and MCI), memory function and hippocampal volume cross-sectionally and prospectively
Aim 2: Examine whether physical activity modifies the relationship between BDNF Val66Met and Aβ-related decline in memory function and reductions in hippocampal volume
Aim 3: Examine whether changes in other areas of cognition are associated with BDNF Val66Met and Aβ
Aim 4: Examine whether changes in other areas of cognition are associated with BDNF Val66Met and Aβ
Investigator: Dr. Christian Gaser
Title: BrainAGE in dominantly inherited Alzheimer’s disease
Date of Request: April 16, 2013
Status: IP
ID: DIAN-D1305
Aim 1: Exploring the brain aging pattern in subjects with DIAN and controls (cross-sectionally & longitudinally)
Aim 2: Disentangling the age-related atrophy pattern from the disease-specific atrophy pattern in the brain (structural MRI)
Aim 3: Estimating BrainAGE scores in subjects with DIAN and controls to predict conversion to AD
Aim 4: Estimating BrainAGE scores in subjects with DIAN and controls to predict conversion to AD
Investigator: Beth Snitz
Title: Five factor personality dimensions and the Alzheimer pathology spectrum in Autosomal Dominant Alzheimer Disease
Date of Request: April 12, 2013
Status: A
ID: DIAN-D1304
Aim 1: 1) Determine whether Five-Factor personality dimensions are associated with biomarkers a-beta and tau (global PiB SUVR and CSF markers), cross-sectionally in mutation carriers, along a symptom spectrum from asymptomatic to mild AD.
Aim 2: 2) Quantify the degree of longitudinal change in Five-Factor personality dimensions in mutation carriers, stratified by baseline clinical stage.
Aim 3: 3) Investigate whether personality dimensions are associated with estimated time-to-symptom onset.
Aim 4: 3) Investigate whether personality dimensions are associated with estimated time-to-symptom onset.
Investigator: Erik Roberson
Title: A Novel PS1 Mutation (PSEN1 N135Y)
Date of Request: March 13, 2013
Status: A
ID: DIAN-D1303
Aim 1: Describe clinical and histopathological features of AD resulting from mutation (autopsy on patient’s father)
Aim 2: Describe biomarker evaluation of the patient (PET, CSF)
Aim 3: Evaluate production of A-beta 1-42 production resulting from the mutation in vitro
Aim 4: Evaluate production of A-beta 1-42 production resulting from the mutation in vitro
Investigator: Chengjie Xiong
Title: Correlation coefficients in Clustered data
Date of Request: February 19, 2013
Status: A
ID: DIAN-D1302
Aim 1: We propose a statistical bivariate linear mixed model (BLMM) to evaluate correlation among AD markers at all levels systematically.
Aim 2: We will also evaluate the analysis in comparison to existing alternative methods.
Aim 3: We will provide easy-to-use correlation analysis tool for the DIAN study.
Aim 4: We will provide easy-to-use correlation analysis tool for the DIAN study.
Investigator: Mathias Jucker
Title: Subjective memory complaints in prodromal familial Alzheimer’s disease and its association with amyloid burden in the brain
Date of Request: January 21, 2013
Status: A
ID: DIAN-D1301
Aim 1: Find out whether presymptomatic FAD mutation carriers (CDR=0) with subjective memory complaints show a higher percentage and degree of pathological (positive) amyloid load in the brain (precuneus) measured by PIB-PET than those without subjective memory complaints.
Aim 2: Find out the time relation between subjective memory complaints and estimated years from symptom onset respectively development of clear deficits in cognitive tests (e.g., pathological logical memory test), MCI and dementia.
Aim 3: Find out the time relation between subjective memory complaints and development of pathological (positive) amyloid load in the brain (precuneus) measured by PIB-PET.
Aim 4: Find out the time relation between subjective memory complaints and development of pathological (positive) amyloid load in the brain (precuneus) measured by PIB-PET.
Investigator: Daniel Alexander
Title: Event-based models of disease progression
Date of Request: December 23, 2012
Status: A
ID: DIAN-D1213
Aim 1: Validate the event-based model against previous results from DIAN data
Aim 2: Construct a multi-model event-based model of familial AD progression
Aim 3: Examine the effects of various factors (age, lifestyle, genetics, etc)
Aim 4: Examine the effects of various factors (age, lifestyle, genetics, etc)
Investigator: Anne Fagan
Title: Comparison of Biofluid Markers of Dominantly Inherited Alzheimer Disease (AD) with Sporadic Late Onset AD
Date of Request: December 6, 2012
Status: IP
ID: DIAN-D1216
Aim 1: To compare biofluid markers of Dominantly Inherited Alzheimer Disease (AD) with sporadic Late Onset AD
Aim 2:
Aim 3:
Aim 4:
Investigator: Tammie Benzinger
Title: Comparison of Neuroimaging Features of Dominantly Inherited Alzheimer Disease (AD) with Sporadic Late Onset AD
Date of Request: December 6, 2012
Status: IP
ID: DIAN-D1215
Aim 1: To compare neuroimaging features of Dominantly Inherited Alzheimer Disease (AD) with sporadic Late Onset AD
Aim 2: To compare structural MRI features of Dominantly Inherited Alzheimer Disease (AD) with sporadic Late Onset AD
Aim 3: To compare FDG PET imaging features of Dominantly Inherited Alzheimer Disease (AD) with sporadic Late Onset AD
Aim 4: To compare FDG PET imaging features of Dominantly Inherited Alzheimer Disease (AD) with sporadic Late Onset AD
Investigator: John C. Morris
Title: Comparison of Clinical and Cognitive Phenotypes of Dominantly Inherited Alzheimer Disease (AD) with Sporadic Late Onset AD
Date of Request: December 6, 2012
Status: IP
ID: DIAN-D1214
Aim 1: To compare clinical and cognitive phenotypes of Dominantly Inherited Alzheimer Disease (DIAD) with sporadic Late Onset Alzheimer Disease (LOAD)
Aim 2:
Aim 3:
Aim 4:
Investigator: John Ringman
Title: Pilot data for R01 Proposal, “Anti-amyloid vaccine in preclinical FAD mutation carriers in Mexico and the U.S.”
Date of Request: November 30, 2012
Status: A
ID: DIAN-D1212
Aim 1: To characterize longitudinal change in levels of tau and p-tau in the CSF in FAD mutation carriers.
Aim 2: To characterize longitudinal changes in amyloid signal on PIB scans in FAD mutation carriers.
Aim 3:
Aim 4:
Investigator: David Teplow, Ph.D.
Title: Generalization of Acquired Memory Pairings in Preclinical Familial Alzheimer’s Disease
Date of Request: November 27, 2012
Status: IA
ID: –
Aim 1: To establish if generalization of learned arbitrary pairings is impaired in preclinical familial Alzheimer’s disease
Aim 2: This is a statement of intent to analyze local data.
Aim 3: This is not a request for data.
Aim 4: This is not a request for data.
Investigator: David Teplow, Ph.D.
Title: Peripheral gene expression in familial AD
Date of Request: November 26, 2012
Status: IA
ID: –
Aim 1: To compare the expression of genes in peripheral leukocytes between non-demented FAD mutation carriers and at-risk non-carriers
Aim 2: No actual data is being requested.
Aim 3:
Aim 4:
Investigator: Mayeux
Title: WHITE MATTER HYPERINTENSITIES AND CEREBRAL MICROBLEEDS IN DIAN
Date of Request: November 7, 2012
Status: A
ID: DIAN-1211
Aim 1: 1. To examine the natural history of WMH in the preclinical course of AD.
Aim 2: 2. To examine the relationship between regionally distributed WMH and markers of AD pathology.
Aim 3:
Aim 4:
Investigator: Chengjie Xiong
Title: Wavelet-based statistical analysis on brain functional connectivity
Date of Request: October 24, 2012
Status: IA
ID: DIAN-D1210
Aim 1: Develop novel quantitative tools to comprehensively measure brain functional connectivity
Aim 2: Develop novel stat. methods to identify impairments of brain func. connectivity in elderly individuals
Aim 3:
Aim 4:
Investigator: Paul Thompson
Title: Preclinical familial and late-onset Alzheimer’s disease brain changes
Date of Request: October 18, 2012
Status: IA
ID: DIAN-D1209
Aim 1: Determine which sMRI, rs-fMRI, and DTI brain measures together best distinguish FAD mutation non-carriers from FAD mutation carriers within 10 years from their estimated age of disease onset.
Aim 2: Identify which sMRI, rs-fMRI, and DTI brain measures change faster over three years in FAD mutation carriers within 10 years from their estimated age of disease onset compared with age-matched FAD mutation non-carriers.
Aim 3: Discover whether Aim 1 effects are seen in higher AD risk ADNI adults (based on CSF Aβ42 levels and memory scores) versus lower risk ADNI adults (based on CSF Aβ42 levels), and whether the measures predict cognitive decline over 3 years.
Aim 4: Discover whether Aim 1 effects are seen in higher AD risk ADNI adults (based on CSF Aβ42 levels and memory scores) versus lower risk ADNI adults (based on CSF Aβ42 levels), and whether the measures predict cognitive decline over 3 years.
Investigator: Paul Thompson
Title: Preclinical familial and late-onset Alzheimer’s disease brain changes
Date of Request: October 17, 2012
Status: IA
ID: DIAN-D1209
Aim 1: Determine which sMRI, rs-fMRI, and DTI brain measures together best distinguish FAD mutation non-carriers from FAD mutation carriers within 10 years from their estimated age of disease onset.
Aim 2: Identify which sMRI, rs-fMRI, and DTI brain measures change faster over three years in FAD mutation carriers within 10 years from their estimated age of disease onset compared with age-matched FAD mutation non-carriers.
Aim 3: Discover whether Aim 1 effects are seen in higher AD risk ADNI adults (based on CSF Aβ42 levels and memory scores) versus lower risk ADNI adults (based on CSF Aβ42 levels), and whether the measures predict cognitive decline over 3 years.
Aim 4: Discover whether Aim 1 effects are seen in higher AD risk ADNI adults (based on CSF Aβ42 levels and memory scores) versus lower risk ADNI adults (based on CSF Aβ42 levels), and whether the measures predict cognitive decline over 3 years.
Investigator: Prof. Ralph Martins
Title: Platelet APP Isoform Ratios in a subset of the Dominantly Inherited Alzheimer’s disease Network
Date of Request: October 12, 2012
Status: A
ID: DIAN-D1208
Aim 1: Aim to observe whether platelet APP isoform ratios are lower in Mutation Carriers (mutation responsible for ADAD) compared to Non Carriers
Aim 2: Aim to observe whether platelet APP ratios correlate with neuropsychometric test scores and PiB-PET SUVR
Aim 3:
Aim 4:
Investigator: Koeppe
Title: Centiloids Project
Date of Request: October 8, 2012
Status: A
ID: DIAN-D1206
Aim 1: Standardize amyloid imaging outcome measures
Aim 2:
Aim 3:
Aim 4:
Investigator: Koeppe
Title: Standardizing Biomarker Reporting for Amyloid Plaque Estimation by PET
Date of Request: September 27, 2012
Status: A
ID: DIAN-D1206
Aim 1: To provide a standard method for quantifying scaling of amyloid burden with PET
Aim 2: The quantification scale would be applicable to different radiotracers
Aim 3: The quantification scale would be applicable to different analysis methods
Aim 4: The quantification scale would be applicable to different analysis methods
Investigator: Ivo Dinov
Title: Neuroimaging-Genetics Study of Early-Onset Alzheimer’s Disease
Date of Request: September 27, 2012
Status: IA
ID: DIAN-D1207
Aim 1: Obtain shape and volume derived neuroimaigng biomarkers
Aim 2: Obtain Genetics/SNP Cleaned data and Identify significant predictors of MCI/AD
Aim 3: Integrate genetics and biomedical imaging correlated/post-hoc analysis
Aim 4: Integrate genetics and biomedical imaging correlated/post-hoc analysis
Investigator: Beau Ances
Title: Comparison of Early and Late Onset AD Using rs-fcMRI
Date of Request: September 17, 2012
Status: A
ID: DIAN-D1205
Aim 1: To characterize the RSNs affected in early onset AD
Aim 2: To charterize the RSNs affected in late onset AD
Aim 3: To understand the temporal course of changes in RSNs in early onset AD
Aim 4: To understand the temporal course of changes in RSNs in early onset AD
Investigator: Jeff Prescott
Title: Relationship between fibrillar amyloid deposition and functional connectivity in the DIAN population
Date of Request: September 11, 2012
Status: IA
ID: DIAN-D1204
Aim 1: Analyze the cross-sectional relationship between fibrillar amyloid deposition and whole brain functional connectivity in homogeneous subsets of the DIAN population.
Aim 2: Analyze the relationship between baseline fibrillar amyloid deposition and future changes in whole brain functional connectivity in the DIAN population.
Aim 3:
Aim 4:
Investigator: Randall J. Bateman, M.D.
Title: DIAN Treatment Trials – Cognitive Test Battery
Date of Request: August 8, 2012
Status: A
ID: DIAN-D1100
Aim 1: Analyze the DIAN cognitive data set to determine the most effective cognitive test measures to use in the DIAN Treatment Trials while allowing for historical run-in comparisons and some measure of continuity between the studies.
Aim 2: Compare the DIAN Data to existing, published data (e.g. RUSH, ABEL) to determine a cognitive composite test battery that overlaps well with those measures selected for use in other large, planned secondary prevention trials (i.e., A4 and API trials).
Aim 3:
Aim 4:
Investigator: Reisa Sperling, MD
Title: Relationship of CSF markers to Functional Connectivity in DIAN
Date of Request: August 7, 2012
Status: A
ID: DIAN-D1101
Aim 1: (This is an amendment to add the CSF biomarkers to our approved PiB-fc-MRI project). To elucidate the temporal relationship of the emergence of default network dysfunction in ADAD mutation carriers to CSF markers of Abeta, phospho-tau and tau.
Aim 2:
Aim 3:
Aim 4:
Investigator: David Teplow
Title: Behavioral and mood disturbances in prodromal familial Alzheimer’s disease
Date of Request: March 15, 2012
Status: A
ID: DIAN-D1203
Aim 1: Compare the frequency of behavioral disturbances on the NPI-Q between asymptomatic FAD mutation carriers and non-carriers
Aim 2: Compare the severity of behavioral disturbances on the NPI-Q between asymptomatic FAD mutation carriers and non-carriers
Aim 3: Compare the level of self-rated depression (GDS) between asymptomatic FAD mutation carriers and non-carriers
Aim 4: Compare the level of self-rated depression (GDS) between asymptomatic FAD mutation carriers and non-carriers
Investigator: Christopher Leatherday
Title: An Investigation of Optimised Hippocampal Masking Techniques in Alzheimer’s Disease Diagnosis.
Date of Request: March 7, 2012
Status: IA
ID: DIAN-D1202
Aim 1: Verify the optimised pes hippocampal masking results obtained by Mosconi et al. in their 2005 paper: “Reduced hippocampal metabolism in MCI and AD: Automated FDG-PET image analysis”.
Aim 2: Compare the efficacy of a volumetric pes hippocampal mask to one that includes the whole hippocampus; in terms of their ability to distinguish between functional brain images of Alzheimer’s disease, mild cognitive impairment and healthy elderly subjects.
Aim 3:
Aim 4:
Investigator: Andrei Vlassenko
Title: Regional beta-amyloid deposition in cognitively normal adults
Date of Request: February 7, 2012
Status: IP
ID: DIAN-D1201
Aim 1: Examine regional differences in PIB BP in PIB-negative older compared to younger adults
Aim 2:
Aim 3:
Aim 4:
Investigator: Morris
Title: Imaging Committee Presentations at 2012 Human Amyloid Imaging Meeting
Date of Request: December 19, 2011
Status: A
ID: –
Aim 1: The DIAN Imaging Committee is presenting 2 abstracts at the 2012 Human Amyloid Imaging Meeting, titiles are listed below.
Aim 2: [11C] PIB, FDG and MR findings of preclinical AD in the DIAN cohort
Aim 3: Reference tissue normalization in autosomal dominant AD: Comparison of cerebellar versus brainstem referencing for [11C]PIBin the DIAN cohort
Aim 4: Reference tissue normalization in autosomal dominant AD: Comparison of cerebellar versus brainstem referencing for [11C]PIBin the DIAN cohort
Investigator: Randall Bateman MD
Title: Development and validation of evidence-based criteria for estimating age of onset in the DIAN study
Date of Request: November 27, 2011
Status: A
ID: DIAN-D1110
Aim 1: Development and validation of evidence-based estimates for expected age of onset within ADAD families
Aim 2: Pedigree analysis of DIAN families to directly assess heritability and examine the effects of additional prognostic variables in modifying familial age of onset
Aim 3:
Aim 4:
Investigator: Reisa Sperling
Title: Relationship of PiB-PET amyloid imaging and default network fc-MRI in DIAN subjects
Date of Request: November 15, 2011
Status: A
ID: DIAN-D1101
Aim 1: To investigate whether level of cortical PiB retention is related to default network dysconnectivity across the spectrum of DIAN participants (ADAD mutation carriers, non-carriers, asymptomatic and symptomatic).
Aim 2: To determine whether ADAD mutation carriers demonstrate impaired connectivity compared to non-carriers, independent of PiB retention.
Aim 3: To elucidate the temporal relationship of the emergence of default network dysfunction in ADAD mutation carriers to their expected age of onset.
Aim 4: To elucidate the temporal relationship of the emergence of default network dysfunction in ADAD mutation carriers to their expected age of onset.
Investigator: John Ringman
Title: Prevalence of REM Sleep Behavior Disorder and other DLB symptoms in Familial Alzheimers Disease
Date of Request: November 2, 2011
Status: A
ID: z
Aim 1: ascertain how common symptoms of RBD are in early symptomatic and demented persons carrying FAD mutations
Aim 2: to assess whether symptoms of RBD are more common in FAD mutation carriers relative to their non-mutation carrying kin
Aim 3: to compare the prevalence of other symptoms of DLB (hallucinations, fluctuations, and Parkinsonism) between FAD mutation carriers (MCs) and non-carriers (NCs).
Aim 4: to compare the prevalence of other symptoms of DLB (hallucinations, fluctuations, and Parkinsonism) between FAD mutation carriers (MCs) and non-carriers (NCs).
Investigator: John Ringman
Title: Clinical and Imaging Characteristics of the I238M Mutation in Presenilin-1: Report of a New Mutation
Date of Request: August 22, 2011
Status: A
ID: DIAN-D1106
Aim 1: The goal of this study is to describe, in depth, the clinical and imaging characteristics of this novel mutation.
Aim 2:
Aim 3:
Aim 4:
Investigator: John Ringman
Title: Identification of cerebral microhemorrhages in persons carrying familial AD mutations
Date of Request: August 22, 2011
Status: Pending
ID: DIAN-D1104
Aim 1: Ascertain the prevalence of CAA in FAD using the clinical radiological interpretation of the presence of microhemorrhages on susceptibility-weighted MRI images (SWI)
Aim 2: to relate the location of microhemorrhages to amyloid deposition as measured using PIB scans
Aim 3: explore the relationship of microhemorrhages to FAD mutation type, adjusted age, CDR sum of boxes score, gender, and APOE genotype.
Aim 4: explore the relationship of microhemorrhages to FAD mutation type, adjusted age, CDR sum of boxes score, gender, and APOE genotype.
Investigator: John Ringman
Title: Request for individual identifiable data for Case Report
Date of Request: August 3, 2011
Status: A
ID: DIAN-D1102
Aim 1: Sole purpose is to write up a case report of a severely demented woman with a novel PSEN1 mutation.
Aim 2:
Aim 3:
Aim 4:
Investigator: Mark Raichle
Title: Resting Brain Metabolism in Familial Alzheimer’s Disease
Date of Request: June 1, 2011
Status: IA
ID: DIAN-D1109
Aim 1: Examine the relationship between oxygen and glucose in the brain.
Aim 2:
Aim 3:
Aim 4:
Investigator: Nick Fox
Title: Innate Immune System Dysfunction in Neurodegeneration
Date of Request: May 23, 2011
Status: A
ID: DIAN-D1103
Aim 1: Registration and subtraction-based methods of volume change.
Aim 2: Use Voxel-based morphometry to look for patterns of difference between gene-positive and gene-negative individuals as well as differences between genetic sub-types.
Aim 3: Tensor-based morphometry. The power of non-linear registration to provide a realistic and very precise matching of serial data.
Aim 4: Tensor-based morphometry. The power of non-linear registration to provide a realistic and very precise matching of serial data.
Investigator: Anthony Stevens
Title: Pharmacological chaperones effects on PS1 levels with the specific PS1 mutations
Date of Request: February 21, 2011
Status: A
ID: DIAN-D1108
Aim 1: To investigate our pharmacological chaperones effects on PS1 levels with the specific PS1 mutations of patients currently enrolled in the DIAN studies, using our in-house cell based PS1 EOFAD models.
Aim 2: Knowledge of the mutations and pedigree size will help us prioritize which PS1 mutations to test in our models.
Aim 3:
Aim 4: