Unpacking the Emergence of Dementia Etiology Across the Life Course

Moderate to severe impairments in cognitive functioning are a primary hallmark of Alzheimer's disease (AD) and Alzheimer's Disease Related Dementias (ADRD), a class of disorders affecting ~30% of the population by age 90. Currently, scientists hypothesize that the AD/ADRD disease process begins decades prior to the low functioning observed at the time of diagnosis. The ideal study design to gain insight into liability in prodromal and preclinical stages of AD/ADRD would involve collecting data on a wide range of measures from a large group of participants across the entirety of the life course. However, this data collection strategy includes major pragmatic barriers. Longitudinal study designs that might identify prospective risk factors of later life disease onset carry high participant and financial costs and take decades to produce conclusive results. Because of these limitations, much of the literature has been left to speculate in a piecemeal fashion on what characterizes the AD/ADRD prodromal period. However, research into these prodromal and preclinical periods holds significant promise for improving prevention and intervention efforts by identifying at-risk individuals and those who are at an earlier, and likely more intervenable, stage of disease.

We will analyze the links between genotypes and phenotypes to investigate the onset times of risk factors for AD/ADRD across the life course using data from the HRS. Our insights will focus on pinpointing specific periods when these outcomes manifest as individuals age. We hypothesize that genetic data and structural equation modeling can help identify the specific times when Alzheimer's risk factors emerge as individuals age throughout their lives. Our team proposes to leverage the Genomic Structural Equation Modeling (Genomic SEM) framework to identify genetic risk pathways to AD/ADRD across the life course using existing data from large epidemiological studies that index different age ranges. Results from this study will add previously unseen levels of precision to our understanding of when genetic risk for AD/ADRD emerges across the life course and which specific risk factors index its onset.\

We will analyze the links between genotypes and phenotypes to investigate the onset times of risk factors for Alzheimer's and Dementia (AD) across the life course using data from the Health and Retirement Study (HRS). Our insights will focus on pinpointing specific periods when these outcomes manifest as individuals age. We hypothesize that genetic data and structural equation modeling can help identify the specific times when Alzheimer's risk factors emerge as individuals age throughout their lives.