Principal Investigator: Professor Svetlana Ukraintseva
Department: Duke UniversityTags: 55337, aging, Alzheimer's Disease, genes, Heterogeneity, interaction, prevention
Alzheimer’s disease (AD) is a complex health disorder, with many biological pathways involved in it. Some of these pathways can be shared between AD and physiological aging. For example, decline in brain resilience (ability to recover, e.g., after damage) is typical of both normal aging and AD; however, in AD such decline is more severe and contributes to AD pathology. The objective of this project is to significantly improve our understanding of the shared genetic mechanisms between aging and AD, and as result suggest new genetic targets for AD prevention/treatment. To fulfil this objective, we will analyze data that have been collected in several large human studies of aging and health, including the UK Biobank containing rich genetic and phenotypic information on thousands of individuals with AD and related traits. The following Aims will be addressed: In Aim 1, we will select genetic variants associated with both AD and aging-related traits and estimate their collective effects on AD risk and survival. We will also describe biological pathways enriched for respective genes and suggest mechanisms connecting these pathways with AD. In Aim 2, we will focus on candidate genes representing the aging-related pathways involved in resilience, and estimate their joint influence on AD risk and survival, to find combinations of the genes that show protective effects against AD, and may also oppose the aging-related decline in brain resilience to damage. In Aim 3, we will further validate the findings of Aims 1-2 using biomarkers of AD pathology available in data, and explore causal relationships between selected genes and AD traits, using Mendelian Randomization and related approaches, to get deeper insights into biological mechanisms of the observed genetic associations. Results of this study will significantly improve our understanding of the etiology of AD and common genetic factors involved in AD and physiological aging, and will help find new genetic targets for personalized prevention of AD and interventions into the brain aging.