Location: Jean Mayer Human Nutrition Research Center On Aging
2025 Annual Report
Objectives
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.
Progress Report
The approach for Objective 1 continued to capitalize on the ongoing Geisinger Rural Aging (GRAS) cohort study. Geisinger Health System investigated 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 were added to the GRAS database and are available for dissemination. The Geisinger Medical Clinic also investigated 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 served to further broaden applicability and specifically targeted 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 used address at time of study entry and any available historic addresses for individuals collated across the GRAS database or the Electronic Health Record (EHR).
In a preliminary effort, we have begun to leverage previously collected and stored blood samples from a small subset of cohort participants to quantify epigenome-wide DNA methylation and whole exome sequencing of the clonal haematopoiesis of indeterminate potential (CHIP). We have successfully identified these patients with these biospecimens and incorporated these data into the GRAS database.
Accomplishments
1. Geomapping of rural adults. Located 99% of addresses for Geisinger Rural Aging Study (GRAS) participants. This is a sizable accomplishment, given the age of many of the addresses and their predating of digital census and methods for geomapping. Addresses for participants and their geomapping method were added to our GRAS database. Began the process of applying and evaluating addresses for contextual factors including socioeconomic, social, neighborhood, and healthcare environment. These contextual factors are and will be an important part of understanding the whole picture of aging and aging well in a rural community, and the findings will positively impact preventive care in the clinical space.
2. Acquisition of biospecimens previously collected on Geisinger Rural Aging Study (GRAS) participants. Many GRAS participants were also part of a study at Geisinger that collected biospecimens including blood and for whom whole exome sequencing was evaluated. Participants with these data were identified and approval received to use these samples for our proposed epigenome-wide and exome specific analysis. It is novel and important to leverage stored biospecimen samples and to evaluate different biological components. Pairing epigenetics with genomic data in the same individual provides a much broader picture of biological processes than one alone.
Review Publications
Shukitt Hale, B., Prior, R.L., Burton-Freeman, B. 2024. Polyphenols: With a focus on Flavonoids. In: Tucker, K.L., Duggan, C.P., Jensen, G.L, Peterson, K.E., editors. Modern Nutrition in Health and Disease 12 edition. Jones & Bartlett Learning. P. 511-512.
Zheng, T., Marschall, S., Weinberg, J., Fu, X., Tarr, A., Shukitt Hale, B., Booth, S. 2025. Low vitamin K intake impairs cognition, neurogenesis and elevates neuroinflammation in C57BL/6 mice. Journal of Nutrition. https://doi.org/10.1016/j.tjnut.2025.01.023.
Shukitt Hale, B., Fisher, D.R., Cahoon, D.S., Miller, M.G., Carey, A.N., Zheng, T. 2025. Intermittent vs. continuous wild blueberry feeding alters inflammation and behavior in aged rats. Journal of Medicinal Food. https://doi.org/10.1089/jmf.2025.0001.