Search DIAN Data Resource Requests

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.

Displaying 281 - 290 of 294

Investigator:Serge Gauthier

Title:Neuropsychiatric Symptoms Predicting Neurodegeneration In Asymptomatic Autosomal Dominant Alzheimer?s Disease Mutation Carriers

Date of Request:8/25/2016


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.

Investigator:JC Morris

Title:APOE4 effect on brains tructure and function in cognitively normal young-to-middle age adults

Date of Request:8/26/2016


Aim 1:DIAN NCs with an E4 allele will have greater risk of having an "Alzheimer signature"

Investigator:Timothy Hohman

Title:Building a Resilience Phenotype in DIAN

Date of Request:9/1/2016


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

Investigator:Hungbo Luo

Title:Tauopathy in Autosomal Dominant and Late-Onset Alzheimer Disease

Date of Request:9/27/2016


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.


Title:Attentional Control in Dominantly Inherited Alzheimer disease

Date of Request:9/28/2016


Aim 1:Establish rates of change in attentional control in DIAN

Aim 2:Evaluate alternative measures of performance using compuational modelling

Investigator:Jonathan Voeglein

Title:Effect of cigarette smoking on cognition and amyloid burden in the DIAN-OBS (Amendment for DIAN-D1610)

Date of Request:10/24/2016


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

Investigator:Sylvia Villeneuve

Title:The role of heredity in pre-clinical AD biomarkers: comparison of sporadic AD and autosomal dominant AD

Date of Request:10/25/2016


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

Investigator:Chengjie Xiong, PhD

Title:PreClinical Biomarker Signature RF1

Date of Request:11/4/2016


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 4Assess how MRI white matter hyperintensities, infarcts, microbleeds, Body Mass Index (BMI) & HbA1c contribute to the preclinical changes in biomarkers and cognition, and further neuropathologically validate findings of Aim 1 & 2

Investigator:Mirza Faisal Beg

Title:Characterizing neuroimaging patterns in subjects with MCI progressing to frank AD

Date of Request:11/24/2016


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

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:12/6/2016


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