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.
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.
|Bateman, Randall J; Benzinger, Tammie L; Berry, Scott et al. (2016) The DIAN-TU Next Generation Alzheimer's prevention trial: Adaptive design and disease progression model. Alzheimers Dement :|
|Su, Yi; Blazey, Tyler M; Owen, Christopher J et al. (2016) Correction: Quantitative Amyloid Imaging in Autosomal Dominant Alzheimer's Disease: Results from the DIAN Study Group. PLoS One 11:e0163669|
|Soosman, Steffan K; Joseph-Mathurin, Nelly; Braskie, Meredith N et al. (2016) Widespread white matter and conduction defects in PSEN1-related spastic paraparesis. Neurobiol Aging 47:201-209|
|Lim, Yen Ying; Hassenstab, Jason; Cruchaga, Carlos et al. (2016) BDNF Val66Met moderates memory impairment, hippocampal function and tau in preclinical autosomal dominant Alzheimer's disease. Brain 139:2766-2777|
|Miller-Thomas, Michelle M; Sipe, Adam L; Benzinger, Tammie L S et al. (2016) Multimodality Review of Amyloid-related Diseases of the Central Nervous System. Radiographics 36:1147-63|
|Muenchhoff, Julia; Poljak, Anne; Thalamuthu, Anbupalam et al. (2016) Changes in the plasma proteome at asymptomatic and symptomatic stages of autosomal dominant Alzheimer's disease. Sci Rep 6:29078|
|Tang, Mengxuan; Ryman, Davis C; McDade, Eric et al. (2016) Neurological manifestations of autosomal dominant familial Alzheimer's disease: a comparison of the published literature with the Dominantly Inherited Alzheimer Network observational study (DIAN-OBS). Lancet Neurol 15:1317-1325|
|Su, Yi; Blazey, Tyler M; Owen, Christopher J et al. (2016) Quantitative Amyloid Imaging in Autosomal Dominant Alzheimer's Disease: Results from the DIAN Study Group. PLoS One 11:e0152082|
|Jin, Yan; Su, Yi; Zhou, Xiao-Hua et al. (2016) Heterogeneous multimodal biomarkers analysis for Alzheimer's disease via Bayesian network. EURASIP J Bioinform Syst Biol 2016:12|
|Roe, Catherine M; Barco, Peggy P; Head, Denise M et al. (2016) Amyloid Imaging, Cerebrospinal Fluid Biomarkers Predict Driving Performance Among Cognitively Normal Individuals. Alzheimer Dis Assoc Disord :|
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