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 31 - 40 of 291

Investigator:Dr. Eric M McDade


Title:Drug Dose Modeling for potential inclusion in the DIAN-TU 002 trial

Date of Request:04/04/2023

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.










Investigator:Dr Sarah Bauermeister


Title:Biopsychosocial determinants of cognitive and biomarker trajectories in preclinical Alzheimer's disease

Date of Request:03/23/2023

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




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:03/08/2023

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 4Association of plasma biomarkers with subsequent neurodegeneration, cognitive decline, cerebral hypometabolism.

Investigator:Ben Handen


Title:Comparison of plasma NfL in ABC-DS and DIAN

Date of Request:03/03/2023

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







Investigator:Chia-Ling Phuah


Title:WMH Spatial Patterns in ADAD

Date of Request:02/21/2023

Status:approved

ID:DIAN-D2302




Aim 1:Evaluate for difference(s) in WMH topographical distributions between AD and CAA










Investigator:Randall J. Bateman


Title:DIAN OBS Data for the DIAN-TU OLE

Date of Request:01/31/2023

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.







Investigator:Nicole McKay


Title:Investigating how white matter integrity and tauopathy underpin cognitive decline in autosomal dominant Alzheimer disease.

Date of Request:10/24/2022

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.




Investigator:Haiyan Liu


Title:Estimated Year of Symptoms at Onset in DIAD-A Systemic Review and Meta-analysis

Date of Request:09/28/2022

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 44. To explore the relationship of EYO with CSF biomarkers, FDG PET, brain MRI, PiB PET and survival duration

Investigator:Peter Millar


Title:Modeling brain-predicted age in autosomal dominant Alzheimer disease

Date of Request:09/14/2022

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




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:08/25/2022

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.