Alzheimer?s disease (AD) is a global crisis facing the aging population and society as a whole. With the number of people living with AD predicted to rise dramatically in the coming decades, it is imperative to pursue research that aims to reduce the expected incidence of dementia, such as identifying modifiable risk factors for lifestyle interventions. A prerequisite to establishing lifestyle interventions is demonstrating a causal effect of the proposed exposure (a risk factor) on AD or AD endophenotypes. The overarching objective of this research program is to enhance our understanding of the causal relationships underlying Alzheimer?s disease by utilizing genetically informed causal inference methods. We will use state-of-the-art techniques in statistical genetics that exploit the polygenic risk scoring (PRS) and Mendelian randomization (MR) approaches. PRS provide an estimate of an individual's genetic propensity to a trait and can be used to infer genetic overlap between phenotypes via predicting one phenotype from the PRS of another.
The first aim will identify traits that have a shared genetic etiology with AD outcomes by conducting a phenome-wide PRS analysis. This will prioritize putative disease-modifying traits for AD outcomes.
The second aim will conduct an MR phenome-wide association study to identify novel risk factors for AD that have not been identified using previous epidemiological approaches, while prioritizing hypotheses identified in the current literature (e.g. vascular health). MR uses genetic variants as proxies for exposures to provide an estimate of the causal association between an intermediate exposure and an outcome and conceptually similar to a ?genetic randomized control trial? due to the random allocation of genotypes from parents to offspring. In the final aim, PRS and MR will be used to determine if individual risk factors differentially contribute to the development of AD in at-risk subgroups by performing sex, ancestry, age, and APOE ?4 stratified analyses to identify subgroup- specific risk profiles and predictors. The proposed research will elucidate the risk factors underlying AD, which will have a significant impact on the development of lifestyle interventions to prevent AD and may explain differences in risk by sex and ancestry. Under the guidance of his mentor Dr. Alison Goate and co-mentor Dr. Kristine Yaffe, and a team of other advisors, Dr. Andrews will pursue a rigorous training program to accomplish the aims of this award and to develop into an independent researcher. This training will focus on developing skills in (1) causal inference, (2) big data analytics, (3) computational genomics, and (4) professional development. Development in these domains will be accomplished via coursework, attendance at conferences and workshops, gaining experience in providing mentoring and leading teams, and regular feedback from his advisory committee. Overall, the proposed study addresses a crucial and timely unmet need, and the additional skills developed during this award will provide a strong foundation for the candidate to establish independent leadership in the genetic epidemiology of Alzheimer?s disease.
Alzheimer's disease is a neurodegenerative disease with devastating personal, familial, societal and economic burdens for which there is currently no effective means of prevention or treatment. In this proposal, we will use genetic analyses to systematically infer causal relationships between health, lifestyle, psychosocial, disease and molecular (gene expression, protein levels, metabolites) traits for Alzheimer?s disease outcomes. Completion of this proposal has the potential to identify novel causes of Alzheimer?s disease that have not been previously captured using traditional epidemiological approaches and to prioritize factors for immediate intervention to reduce risk now.
