Integrating Genomic and Contextual Determinants to Investigate Disparities in Alzheimer’s Disease and Dementia

Abstract

One in three older adults dies with dementia. Alzheimer’s disease (AD), a progressive neurodegenerative disorder influenced by genetic and environmental risk factors, is the most common cause of dementia. By 2050, >12 million people in the United States will have AD, and the risk for AD is not evenly distributed across the population. To predict and prevent AD and related dementia, identify precision treatments, and reduce disparities, it is crucial to understand the influence of genetic and environmental risk factors on disease susceptibility. In the following papers, we investigated the racial/ethnic representation of participants in United States-based AD genetic studies, characterized the predictive accuracy of various polygenic risk scores for AD in a multi-ethnic cohort, and identified social, built, and physical environment determinants associated with dementia and cognition independent of and modified by genetic risk. We demonstrate that the lack of diversity in current genetic datasets results in insufficient statistical power to detect genetic variants associated with AD in non-European ancestry populations, particularly for variants with small to moderate effect sizes. Beyond the potential for the lack of diversity to exacerbate inequalities in AD outcomes, it also leads to an incomplete understanding of the genetic architecture of AD – an argument supported by our polygenic risk score comparisons. We show that while variants identified by genome-wide associated studies are meaningful for capturing genetic risk in some populations, the overall predictive accuracy of current polygenic risk score models are limited. Finally, we show that after controlling for individual-level genetic and demographic risk factors, contextual determinants actionable at the population-level are associated with cognition and dementia risk. There is evidence that neighborhood socioeconomic status is differentially associated with dementia across groups with different genetic risk. In sum, this body of work contributes toward a better understanding of the etiology of AD in diverse populations, with an emphasis on how systemic population-level solutions can help reduce disparities in AD outcomes from both genetic and environmental perspectives.