This proposal seeks to understand the impact of interactions between socioeconomic status (SES), genotype, and health behaviors on disparities in epigenetic age acceleration and cognitive decline or Alzheimer's disease. Under the guidance of primary mentor Dr. Sharon Kardia, the training and research plan will build upon Dr. Schmitz's expertise in health economics and genetic epidemiology to prepare her for an independent career that integrates social science, genetics, and epigenetics into aging research. The PI will pursue a program of training in epigenetics at the University of Michigan's School of Public Health that will advance her knowledge and skills in (1) epigenomic biology, (2) bioinformatics and related general programming, and (3) preprocessing and analysis of DNA methylation (DNAm) microarray data. The proposed research plan will capitalize on a large sample of epigenome-wide data from the Health and Retirement Study (HRS) (N=4,000) to construct measures of DNAm age in whole blood and test for associations with known genetic, social, and behavioral mechanisms of aging and cognitive decline or Alzheimer's disease. DNAm age been shown to predict age with high accuracy, and studies have linked positive deviations between DNAm age and chronological age (i.e. epigenetic age acceleration (?age)) with age-related diseases and mortality, suggesting that epigenetic processes may play a role in healthy aging. However, few studies have investigated pathways between ?age and SES, and to date no study has evaluated whether the relationship between ?age and SES is moderated by genetic influences or mediated by risky health behaviors. This work builds on Dr. Schmitz's prior HRS research that used whole-genome polygenic scores (PGSs) and objective measures of the social environment to examine the effect of gene-environment interactions on physical health and cognitive function at older ages. During the K99 phase, Dr. Schmitz will construct measures of DNAm age in the HRS to test for associations between ?age and disadvantaged SES, risky health behaviors, and demographic characteristics using longitudinal moderation-mediation methods. During the R00 phase, Dr. Schmitz will incorporate PGSs into the analyses to assess whether genetic propensity for educational attainment or cognition moderates the relationship between SES, ?age, and subsequent declines in cognitive function and incidence of dementia or Alzheimer's disease. Comparative analyses will be conducted in an African American oversample (N?1,000). R00 research will employ instrumental variables (IV) and dynamic panel methods to draw stronger claims regarding causality. Following these analyses, replication of main findings will be pursued in multi-ethnic cohorts that have comparable genetic, epigenetic, and social data. Results from this research program may shed light on the specific social and biological mechanisms that underpin the SES-mortality gradient.

Public Health Relevance

Research that can evaluate the joint effect of social and biological forces on age-related disease is needed to more accurately inform future research and policy intervention that seeks to extend life expectancy and quality of life among older adults. This study capitalizes on a large pilot sample of epigenome-wide data from the Health and Retirement Study (HRS) (N=4,000) to understand the impact of socioeconomic status (SES), genotype, and risky health behaviors on disparities in epigenetic age acceleration and subsequent cognitive decline or Alzheimer's disease. Results from this study will inform future research geared towards connecting social, behavioral, genetic, and epigenetic factors to aging and cognitive function.

Agency
National Institute of Health (NIH)
Institute
National Institute on Aging (NIA)
Type
Career Transition Award (K99)
Project #
1K99AG056599-01
Application #
9370056
Study Section
Neuroscience of Aging Review Committee (NIA)
Program Officer
King, Jonathan W
Project Start
2017-07-15
Project End
2019-06-30
Budget Start
2017-07-15
Budget End
2018-06-30
Support Year
1
Fiscal Year
2017
Total Cost
Indirect Cost
Name
University of Michigan Ann Arbor
Department
Biostatistics & Other Math Sci
Type
Organized Research Units
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109