An estimated 4 to 5 million Americans are living with Alzheimer's disease (AD), the most common form of dementia. This number could rise to 16 million by 2050. With the rapid increase in dementia cases due to an aging population structure there is an urgent need to identify opportunities for preventing or delaying its onset. We propose to test the hypothesis that protective socioeconomic, work and policy environments moderate the genetic risk for dementia and cognitive decline. Identifying modifiable aspects of the environment could provide means to prevent, or slow down, cognitive aging and AD. Few studies, however, have explored such gene-by-environment (GxE) interplay in AD and cognitive impairment. In addition, to our knowledge, no studies have yet attempted to address causality underlying GxE interplay in cognition or model its dynamic nature. Using significant and replicated results from existing genome-wide association studies (GWAS), we will create measures of genetic risk to examine our hypothesis. We will evaluate how GxE interplay evolves over the lifecycle, identify modifiable characteristics of the environment, establish the direction of causality and, when possible, investigate mechanisms that give rise to GxE interplay. We will use data from the Health and Retirement Study (HRS), the English Longitudinal Study of Ageing (ELSA), the Wisconsin Longitudinal Survey (WLS), and the UK Biobank (UKB). These studies are ideal for our purposes because of their large sample sizes, genetic and well-defined life-course cognition and socioeconomic data. The proposed research is innovative in its integrative approach, combining complimentary methods from genetics, epidemiology and social science. Our approach consists of descriptive analyses to explore associations for different measures of genetic risk, environments and stages of life (to explore critical phases; aim 1); exploitation of natural experiments to address environmental causation (aim 2); and estimation of a structural life-course model to better understand GxE interplay, make predictions and evaluate intervention alternatives (aim 3). Combined, we anticipate these methods will provide important insights into the nature of genetic risk and the mechanisms at play in cognitive decline, and point to potential modifiable aspects of the socioeconomic, work and policy environment through an understanding of mechanisms and causality. To the best of our knowledge, our proposed research is unique in addressing causality, modeling life-course dynamics and adopting a structural approach. As a secondary aim of this project, harmonized genetic scores for cognitive function and Alzheimer's disease will be made publicly available for each of the four population studies as researcher-created data to enable replication and comparisons across studies.