Core B evaluates and follows all participants entered into the studies of the program project. It uses an established clinical and psychometric protocol at entry and annually thereafter to obtain clinical, neurological, and behavioral data to carefully characterize each participant in support of each of the 3 Projects of this Program Project Grant (PPG).
Specific Aims of Core B are: 1. Maintain the current active cohort (n=225) of participants, carefully characterized as to the presence or absence of symptomatic AD, to support longitudinal studies of the clinical, cognitive, behavioral and biomedical correlates of symptomatic Alzheimer's disease (AD) in comparison with normal aging, and to mark the transition of cognitively normal participants with preclinical AD to cognitive impairment. 2. Annually enroll and assess 35 new participants (CDR 0=23;CDR 0.5/AD =12) each year who are age e 65 to replenish the Core's cohort to maintain a sufficient sample size (n~250) to support the aims of the PPG and to supply study participants and their data (and DNA to Project 3) to individual Projects: 3. Follow all participants with annual assessments and provide diagnostic and clinical and cognitive data to all Cores and Projects, working closely with Core C: Biostatistics and Core A: Administration to coordinate data acquisition and management to integrate the Core's activities with the scientific goals of the Program Project. In addition to HASD's traditional diagnostic methods, in this application HASD participants will (in accordance with the criteria established by the Alzheimer Disease Neuroimaging Initiative-2) also be classified as significant memory concern, early and late mild cognitive impairment (MCI). 4. Support Core D: Neuropathology through our voluntary autopsy consent program. 5. Support Core E: Imaging and all Projects by referring: a. all HASD participants for MRI and PET amyloid imaging session at baseline and every 3 years thereafter;b. provide Project 1 (Indicators of transition to symptomatic AD) clinical characterizations and data from cognitive measures of all participants;c. refer to Project 2 (Sleep: potential prognostic and theranostic marker for preclinical AD) all participants for sleep and cerebrospinal fluid studies;d. Collect blood from all newly enrolled Core participants for Project 3 (Identification of genetic variants associated with the progression of AD) for their GWAS and variant characterization.
Core B: Clinical Project Narrative As instructed by the funding opportunity announcement for this application (PAR-13-329), only the Overall component contains a project narrative. Cores and projects were instructed not to include this section.
|Roe, Catherine M; Ances, Beau M; Head, Denise et al. (2018) Incident cognitive impairment: longitudinal changes in molecular, structural and cognitive biomarkers. Brain 141:3233-3248|
|Strain, Jeremy F; Smith, Robert X; Beaumont, Helen et al. (2018) Loss of white matter integrity reflects tau accumulation in Alzheimer disease defined regions. Neurology 91:e313-e318|
|Ihara, Ryoko; Vincent, Benjamin D; Baxter, Michael R et al. (2018) Relative neuron loss in hippocampal sclerosis of aging and Alzheimer's disease. Ann Neurol 84:741-753|
|Ogren, Jennifer A; Tripathi, Raghav; Macey, Paul M et al. (2018) Regional cortical thickness changes accompanying generalized tonic-clonic seizures. Neuroimage Clin 20:205-215|
|Sutphen, Courtney L; McCue, Lena; Herries, Elizabeth M et al. (2018) Longitudinal decreases in multiple cerebrospinal fluid biomarkers of neuronal injury in symptomatic late onset Alzheimer's disease. Alzheimers Dement 14:869-879|
|Deming, Yuetiva; Dumitrescu, Logan; Barnes, Lisa L et al. (2018) Sex-specific genetic predictors of Alzheimer's disease biomarkers. Acta Neuropathol 136:857-872|
|Lancour, Daniel; Naj, Adam; Mayeux, Richard et al. (2018) One for all and all for One: Improving replication of genetic studies through network diffusion. PLoS Genet 14:e1007306|
|Li, Zeran; Del-Aguila, Jorge L; Dube, Umber et al. (2018) Genetic variants associated with Alzheimer's disease confer different cerebral cortex cell-type population structure. Genome Med 10:43|
|Blaiotta, Claudia; Freund, Patrick; Cardoso, M Jorge et al. (2018) Generative diffeomorphic modelling of large MRI data sets for probabilistic template construction. Neuroimage 166:117-134|
|Schindler, Suzanne E; Sutphen, Courtney L; Teunissen, Charlotte et al. (2018) Upward drift in cerebrospinal fluid amyloid ? 42 assay values for more than 10 years. Alzheimers Dement 14:62-70|
Showing the most recent 10 out of 911 publications