# Application of plasma lipidomics to identify novel biomarkers of muscle and hepatic adiposity in population-based cohorts of older Black Caribbeans, Black Americans, and White Americans > **NIH NIH K01** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2024 · $125,928 ## Abstract ABSTRACT: Physical disability is common in U.S. older adults, with a higher prevalence in Black vs. White Americans. Physical functioning declines with aging due to biomechanical and biochemical effects. Skeletal muscle and the liver are highly active metabolic organs contributing to biochemical effects involved in multiple physiologic processes. However, with aging, excess fat accumulates ectopically in and around muscle and the liver, impairing normal functioning and causing negative metabolic consequences. In fact, skeletal muscle and the liver share common pathophysiological mechanisms, e.g., insulin resistance and chronic inflammation, that predict physical disability. Individuals of African ancestry have more muscle adiposity, but paradoxically, less liver adiposity than White Americans. A better understanding of the underlying biology of muscle and liver adi- posity in Black vs. White older adults could potentially explain health disparities. Lipidomics is a promising method to better understand metabolic mechanisms underlying muscle and liver adiposity since it directly measures lipids left behind from cellular processes that have shown to have extensive biological relevance. The Principal Investigator, Dr. Marron, previously found several triglycerides were higher and several were lower in older adults with high vs. low walking ability, where the direction in associations directly depended on degree of fatty acid saturation. These findings led to this project, to investigate lipid pathways associated with muscle and liver adiposity, since ectopic fat depots are likely major drivers of functional capacity with aging and both muscle and liver share common pathophysiologic processes that predict disability. Thus, Dr. Marron pro- poses to apply lipidomics to measure >1000 plasma lipids and use existing computed tomography of skeletal muscle and the liver in a subset ages 50+ from the Tobago Study, a Black Caribbean cohort and the Coronary Artery Risk Development in Young Adults (CARDIA) study, a Black and White American cohort. This proposal will: 1) characterize, for the first time, differences in muscle and liver composition in Black Caribbeans, Black Americans, and White Americans; 2) compare associations between lipids and muscle and liver adiposity in Black Caribbeans, Black Americans, and White Americans and assess if differences are driven by ancestry admixture or environment/behavior; and 3) develop and validate a metabolite composite score indicative of muscle and liver health. The career development award will provide protected time for Dr. Marron to cultivate her emerging research program and initiate a path towards independence. The proposal has been designed to 1) gain didactic training in biochemistry, lipid metabolism, and body composition by race/ethnicity; 2) leverage cutting-edge techniques, i.e., untargeted lipidomics with a novel isotope dilution approach and computed to- mography, to expand existing knowledge of underlyi... ## Key facts - **NIH application ID:** 10828918 - **Project number:** 5K01AG075143-03 - **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH - **Principal Investigator:** Megan Michelle Marron - **Activity code:** K01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2024 - **Award amount:** $125,928 - **Award type:** 5 - **Project period:** 2022-08-15 → 2027-04-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10828918 ## Citation > US National Institutes of Health, RePORTER application 10828918, Application of plasma lipidomics to identify novel biomarkers of muscle and hepatic adiposity in population-based cohorts of older Black Caribbeans, Black Americans, and White Americans (5K01AG075143-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10828918. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*