Cardiometabolic Risk Factors and Risk of Dementia

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Project Summary/Abstract The cause of dementia is unknown, but it is considered to be a multifactorial disease, resulting from the interaction of both genetic and environmental factors, which contribute to its occurrence and expression. Genome­wide association studies and population­based studies have confirmed that the ε4 allele of APOE is the strongest genetic risk factor for dementia. However, APOE ε4 is thought to be responsible for less than 50% of dementia risk, suggesting that environmental factors contribute to development of dementia in the genetically predisposed. Given the absence of sufficient treatment options for dementia, strategies to prevent or delay the disease onset are urgently needed. Among potentially modifiable determinants of dementia, appropriate control of cardiometabolic risk factors [Body Mass Index (BMI), systolic and diastolic blood pressure, diabetes and hypercholesterolemia] could be a primary strategy to reduce the incidence of dementia. However, cardiometabolic risk factors in later life have been inconsistently associated with dementia with both increased and decreased risk for dementia. The reasons for this discordance in findings are unclear and perhaps partially due to not only the differing lengths of follow­up between the assessments of cardiometabolic risk factors and dementia onset (reverse causation bias), but also population heterogeneity. Prior studies have used either one­time baseline cardiometabolic risk factor measurements or longitudinal measurements targeting only on mean­level changes (i.e., population average trajectory) with only one trajectory while ignoring population heterogeneity. We propose to use a nested case­control design with group­based trajectory analysis approach to analyze a large, multisite, longitudinal aging and dementia dataset—Uniform Data Set (UDS) provided by the National Alzheimer’s Coordinating Center (NACC). Aim 1): To apply a nested case­control approach to identify distinct trajectories of cardiometabolic risk factors preceding the diagnosis of dementia (up to 15 years) and matched control group using group­based trajectory model, and to examine the effects of distinct trajectories of cardiometabolic risk factors, APOE genotype, and their interaction on the risk of dementia using matched case­control subsamples nested in UDS cohort. Aim 2): To investigate the reverse causation bias for the associations between cardiometabolic risk factors and dementia in aim 1. Aim 3). To explore whether the trajectories of cardiometabolic risk factors and their interaction with APOE genotype on the risk of dementia differ by race, sex, baseline age, and Alzheimer’s disease (AD) subtype.