Abner EL, Schmitt FA, Nelson PT, Lou W, Wan L, Gauriglia R, Dodge HH, Woltjer RL, Yu L, Bennett DA, Schneider JA, Chen R, Masaki K, Katz MJ, Lipton RB, Dickson DW, Lim KO, Hemmy LS, Cairns NJ, Grant E, Tyas SL, Xiong C, Fardo DW, Kryscio RJ. The Statistical Modeling of Aging and Risk of Transition Project: Data Collection and Harmonization Across 11 Longitudinal Cohort Studies of Aging, Cognition, and Dementia.
OBSERVATIONAL STUDIES 2015;
1:56-73. [PMID:
25984574 PMCID:
PMC4431579]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
Longitudinal cognitive trajectories and other factors associated with mixed neuropathologies (such as Alzheimer's disease with co-occurring cerebrovascular disease) remain incompletely understood, despite being the rule and not the exception in older populations. The Statistical Modeling of Aging and Risk of Transition study (SMART) is a consortium of 11 different high-quality longitudinal studies of aging and cognition (N=11,541 participants) established for the purpose of characterizing risk and protective factors associated with subtypes of age-associated mixed neuropathologies (N=3,001 autopsies). While brain donation was not required for participation in all SMART cohorts, most achieved substantial autopsy rates (i.e., > 50%). Moreover, the studies comprising SMART have large numbers of participants who were followed from intact cognition and transitioned to cognitive impairment and dementia, as well as participants who remained cognitively intact until death. These data provide an exciting opportunity to apply sophisticated statistical methods, like Markov processes, that require large, well-characterized samples. Thus, SMART will serve as an important resource for the field of mixed dementia epidemiology and neuropathology.
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