Location: Jean Mayer Human Nutrition Research Center On Aging
Project Number: 8050-10700-005-000-D
Project Type: In-House Appropriated
Start Date: Apr 18, 2024
End Date: Apr 17, 2029
Objective:
Objective 1: Examine the role of community factors in moderating the relationship between diet/diet quality and health outcomes in older adults. [NP107, C5, PS5A]
Sub-objective 1.A: Examine the role of community factors in relation to diet/diet quality and health outcomes in older adults.
Sub-Objective 1.B: Perform secondary analyses of the entire existing Geisinger Rural Aging Study dataset to report disease incidence broadly within the cohort across time and identify the disease(s) with the highest prevalence; identify individuals who remained disease free; and assess the correlation between dietary quality/nutrient status and incidence of highly prevalent disease(s).
Objective 2: Identify all previously collected Geisinger Rural Aging Study data and leverage the collected and stored serum blood samples from cohort participants to measure genetic and epigenome-wide DNA methylation signatures relevant to aging.
Sub-objective 2.A: Identify all previously collected Geisinger Rural Aging Study data and leverage the collected and stored serum blood samples from cohort participants to measure epigenome-wide DNA methylation that will be used to calculate biomarkers of epigenetic aging. (NP107, C5, PS5B)
Sub-objective 2.B: Identify all Geisinger Rural Aging Study participants for whom genomic data is available and leverage the MyCode biorepository from cohort participants to evaluate whole-exome sequencing data for clonal hematopoiesis of indeterminate potential (CHIP) and its association with diet quality and health outcomes.
Approach:
The approach for Objective 1 will continue to capitalize on the ongoing Geisinger Rural Aging (GRAS) cohort study. Sub-objective 1A will investigate community factors including structural determinants of health (e.g., rural vs. urban; proximity to grocery stores, community socio-economic deprivation); social determinants of health (e.g., income, education, neighborhood safety, food security, housing); and health system exposure in relation to diet quality and health. These new data will be added to the GRAS database and will be available for dissemination. Sub-objective 1B will investigate disease prevalence and incidence for previously uncharacterized diseases in this cohort. It is through this cataloguing that we aim to understand and subsequently compare the co-morbidities and diseases experienced by GRAS participants to data on aging adults across the U.S.
The use of geomapping and geocoding of individuals based on last known and historical addresses to classify their community features in a cohort of individuals of advanced age will serve to further broaden applicability and will specifically target key components of the NP107 Action Plan for Human Nutrition (2024-2029) by providing longitudinal data on normal development and aging in the context of diet, nutrient intake, and health outcomes. We will use address at time of study entry and any available historic addresses for individuals collated across the GRAS database or the EHR. Potentially, being able to use both historic addresses and longitudinal addresses is an advantage in contextualizing how people move within and across communities. Furthermore, such data allows for sensitivity analyses of non-movers or static community residents in comparison to individuals who are transient from community to community.
In a preliminary effort, we will leverage the previously collected and stored serum blood samples from a small subset of cohort participants to quantify epigenome-wide DNA methylation at >850,000 CpG sites with the use of the Infinium Methylation EPIC Beadchip (Illumina Platform) and subsequently calculate biomarkers of epigenetic aging. These new data will be added to the GRAS database and will be available for dissemination. The primary outcome of sub-objective 2A is to generate epigenome-wide DNA methylation data for this cohort and to investigate relationships between DNAm-derived markers of epigenetic age with diet and outcomes. As approaches vary across the literature relative to epigenetic age and markers of the epigenetic clock, our aim is to test several of the validated epigenetic clocks from the literature. The approach for sub-objective 2B includes evaluating whole-exome sequencing data on a subset of GRAS participants for the prevalence of CHIP, a novel risk factor relative to diet and cardiovascular disease. As an emerging factor of importance in predicting the risk of negative health outcomes, CHIP prevalence among a proportion of GRAS participants will provide a unique understanding of this association among a rural population of advanced age.
