The imaging data set collected in the Dominantly Inherited Alzheimer Network (DIAN) participants to date represents a highly valuable resource for Alzheimers disease (AD) research. It has supported cross sectional analysis of PET and MRI data to develop a timeline for imaging biomarkers in autosomal dominant AD (ADAD). With this renewal application, the DIAN Imaging Core will continue to obtain and analyze longitudinal imaging data that is fully integrated with clinical, psychometric and cerebrospinal fluid (CSF) biomarkers, and will allow for mutation-specific genotype-phenotype analysis. The Core G: Imaging Core will be responsible for the acquisition, quality control, and analysis of the MRI and PET neuroimaging for DIAN. Carriers of AD-causing mutations and their non-carrier siblings are enrolled and followed in the Clinical Core through the international DIAN performance sites. Participants will undergo structural and functional MRI, amyloid PET, and metabolic PET imaging every 2 years, in conjunction with their clinical visits. The source imaging data and post-processed data will be available to collaborating and outside investigators and will be distributed by the Informatics and Biostatistics cores.
Specific aims are to: (1) Collect structural and functional MRI, amyloid PET and metabolic PET imaging. (2) Process image data, including segmentation and matched regions of interest across all modalities. (3) Follow up novel findings identified in DIAN participants, including (a) an imaging biomarker timeline in asymptomatic ADAD, (b) an early hypermetabolic phase of the disease, (c) similarities between decreased cerebral blood flow and hypometabolism near the onset of symptoms, and (d) a late stage with accelerated accumulation of microhemorrhages. (4) Conduct comparisons to late onset AD (LOAD), evaluate new imaging approaches, and perform exploratory genotypic-phenotypic analysis, to include imaging and pathology.

Public Health Relevance

Society will benefit from research that works to develop biomarkers, or indicators, of diseases such as Alzheimer disease. As researchers develop treatments and strategies to prevent Alzheimer disease, imaging biomarkers that help identify individuals that are at high risk for developing Alzheimer disease will be greatly beneficial to these individuals.

National Institute of Health (NIH)
National Institute on Aging (NIA)
Multi-Year Funded Research Project Cooperative Agreement (UF1)
Project #
Application #
Study Section
Special Emphasis Panel (ZAG1)
Project Start
Project End
Budget Start
Budget End
Support Year
Fiscal Year
Total Cost
Indirect Cost
Washington University
Saint Louis
United States
Zip Code
Suárez-Calvet, Marc; Capell, Anja; Araque Caballero, Miguel Ángel et al. (2018) CSF progranulin increases in the course of Alzheimer's disease and is associated with sTREM2, neurodegeneration and cognitive decline. EMBO Mol Med 10:
Besser, Lilah; Kukull, Walter; Knopman, David S et al. (2018) Version 3 of the National Alzheimer's Coordinating Center's Uniform Data Set. Alzheimer Dis Assoc Disord 32:351-358
Kinnunen, Kirsi M; Cash, David M; Poole, Teresa et al. (2018) Presymptomatic atrophy in autosomal dominant Alzheimer's disease: A serial magnetic resonance imaging study. Alzheimers Dement 14:43-53
Lee, Seonjoo; Zimmerman, Molly E; Narkhede, Atul et al. (2018) White matter hyperintensities and the mediating role of cerebral amyloid angiopathy in dominantly-inherited Alzheimer's disease. PLoS One 13:e0195838
Xiong, Chengjie; Luo, Jingqin; Chen, Ling et al. (2018) Estimating diagnostic accuracy for clustered ordinal diagnostic groups in the three-class case-Application to the early diagnosis of Alzheimer disease. Stat Methods Med Res 27:701-714
Karch, Celeste M; Hernández, Damián; Wang, Jen-Chyong et al. (2018) Human fibroblast and stem cell resource from the Dominantly Inherited Alzheimer Network. Alzheimers Res Ther 10:69
Day, Gregory S; Gordon, Brian A; Perrin, Richard J et al. (2018) In vivo [18F]-AV-1451 tau-PET imaging in sporadic Creutzfeldt-Jakob disease. Neurology 90:e896-e906
Oxtoby, Neil P; Young, Alexandra L; Cash, David M et al. (2018) Data-driven models of dominantly-inherited Alzheimer's disease progression. Brain 141:1529-1544
Chhatwal, Jasmeer P; Schultz, Aaron P; Johnson, Keith A et al. (2018) Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing. Brain 141:1486-1500
Franzmeier, Nicolai; Düzel, Emrah; Jessen, Frank et al. (2018) Left frontal hub connectivity delays cognitive impairment in autosomal-dominant and sporadic Alzheimer's disease. Brain 141:1186-1200

Showing the most recent 10 out of 59 publications