ABSTRACT
BACKGROUND: Cerebral vascular pathology may contribute to cognitive decline experienced by some elderly near death. Given evidence for mixed neuropathologies in advanced age, preventing or reducing cerebrovascular burden in late life may be beneficial. OBJECTIVE: To correlate measures of cerebral vascular pathology with cognitive trajectories. SETTING: Observational study. PARTICIPANTS: A cohort of 2,274 individuals who came to autopsy at a mean age of 89.3 years and 82 percent of whom had at least two cognitive assessments within the last six years of life was compiled from six centers conducting longitudinal studies. MEASUREMENTS: For each cognitive domain: immediate and delayed memory, language, and naming, three trajectories were examined: good, intermediate, and poor cognition. The probability of a participant belonging to each trajectory was associated with measures of cerebral vascular pathology after adjustment for demographics, APOE, and Alzheimer neuropathology. RESULTS: A large proportion of the cohort (72-94%) experienced good or intermediate cognition in the four domains examined. The presence of arteriolosclerosis and the presence of lacunar infarcts doubled the odds of belonging to the poor cognitive trajectory for language when compared to the good trajectory. The presence of lacunar infarcts increased the odds of an intermediate or poor trajectory for immediate and delayed recall while the presence of large artery infarcts increased the odds of poor trajectories for all four cognitive domains examined. Microinfarcts and cerebral amyloid angiopathy had little effect on the trajectories. CONCLUSION: Indicators of cerebral vascular pathology act differently on late life cognition.
ABSTRACT
BACKGROUND: Subjective memory complaints are common in aged persons, indicating an increased, but incompletely understood, risk for dementia. OBJECTIVE: To compare cognitive trajectories and autopsy results of individuals with subjective complaints after stratifying by whether a subsequent clinical dementia occurred. DESIGN: Observational study. SETTING: University of Kentucky cohort with yearly longitudinal assessments and eventual autopsies. PARTICIPANTS: Among 516 patients who were cognitively intact and depression-free at enrollment, 296 declared a memory complaint during follow-up. Among those who came to autopsy, 118 died but never developed dementia, while 36 died following dementia diagnosis. MEASUREMENTS: Cognitive domain trajectories were compared using linear mixed models adjusted for age, gender, years of education and APOE status. Neuropathological findings were compared cross-sectionally after adjustment for age at death. RESULTS: While the groups had comparable cognitive test scores at enrollment and the time of the first declaration of a complaint, the group with subsequent dementia development had steeper slopes of decline in episodic memory and naming but not fluency or sequencing. Autopsies showed the dementia group had more severe Alzheimer pathology and a higher proportion of subjects with hippocampal sclerosis of aging and arteriolosclerosis, whereas the non-demented group had a higher proportion expressing primary age related tauopathy (PART). CONCLUSIONS: While memory complaints are common among the elderly, not all individuals progress to dementia. This study indicates that biomarkers are needed to predict whether a complaint will lead to dementia if this is used as enrollment criteria in future clinical trials.
ABSTRACT
Population substructure is a well-known confounder in population-based case-control genetic studies, but its impact in family-based studies is unclear. We performed population substructure analysis using extended families of admixed population to evaluate power and Type I error in an association study framework. Our analysis shows that power was improved by 1.5% after principal components adjustment. Type I error was also reduced by 2.2% after adjusting for family substratification. The presence of population substructure was underscored by discriminant analysis, in which over 92% of individuals were correctly assigned to their actual family using only 100 principal components. This study demonstrates the importance of adjusting for population substructure in family-based studies of admixed populations.
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.
