Research Paper
APOE genotype and biological age impact inter-omic associations related to bioenergetics
- 1 Institute for Systems Biology, Seattle, WA 98109, USA
- 2 Metabolism and Basic Biology of Aging, Jean Mayer USDA Human Nutrition Research Center On Aging at Tufts University, Boston, MA 02111, USA
- 3 Jean Mayer USDA Human Nutrition Research Center On Aging at Tufts University, Boston, MA 02111, USA
- 4 Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA
- 5 West Coast Metabolomics Center, University of California, Davis, CA 95616, USA
- 6 Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA 02111, USA
- 7 Department of Bioengineering, University of Washington, Seattle, WA 98195, USA
- 8 Phenome Health, Seattle, WA 98109, USA
- 9 Thorne HealthTech, New York, NY 10019, USA
- 10 Department of Immunology, University of Washington, Seattle, WA 98195, USA
- 11 Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, WA 98195, USA
- 12 Buck Institute for Research on Aging, Novato, CA 94945, USA
- 13 eScience Institute, University of Washington, Seattle, WA 98195, USA
- 14 Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA
- 15 Present address: Department of Medical Artificial Intelligence and Data Science, Graduate School of Biomedical Sciences, Tokushima University, Tokushima 770-8503, Japan
- 16 Present address: School of Health Sciences, Purdue University, West Lafayette, IN 47907, USA
Received: December 16, 2024 Accepted: April 22, 2025
https://doi.org/10.18632/aging.How to Cite
Copyright: © 2025 Ellis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Apolipoprotein E (APOE) modifies human aging; specifically, the ε2 and ε4 alleles are among the strongest genetic predictors of longevity and Alzheimer’s disease (AD) risk, respectively. However, detailed mechanisms for their influence on aging remain unclear. In the present study, we analyzed multi-omic association patterns across APOE genotypes, sex, and biological age (BA) axes in 2,229 community dwelling individuals. Our analysis, supported by validation in an independent cohort, identified diacylglycerols as the top APOE-associated plasma metabolites. However, despite the known opposing aging effects of the allele variants, both ε2- and ε4-carriers showed higher diacylglycerols compared to ε3-homozygotes. ‘Omics association patterns of ε2-carriers and increased biological age were also counter-intuitively similar, displaying significantly increased associations between insulin resistance markers and energy-generating pathway metabolites. These results demonstrate the context-dependence of the influence of APOE, with ε2 potentially strengthening insulin resistance-like pathways in the decades prior to imparting its longevity benefits. Additionally, they provide an atlas of APOE-related ‘omic associations and support the involvement of bioenergetic pathways in mediating the impact of APOE on aging.
Abbreviations
1,5-AG: 1,5-anhydroglucitol; Aβ: amyloid beta; AD: Alzheimer’s disease; ADNI: Alzheimer’s Disease Neuroimaging Initiative; APOE: apolipoprotein E (protein); APOE: apolipoprotein E (gene); (APOE) E2: APOE ε2/ε2 or ε2/ε3; (APOE) E3: APOE ε2/ε2 or ε3/ε3; (APOE) E4: APOE ε3/ε4 or ε4/ε4; BA: biological age; BMI: body mass index; CA: chronological age; DAG: diacylglycerol; FDR: false discovery rate; GLM: generalized linear model; GPCR: G protein-coupled receptor; HbA1c: hemoglobin A1c; IRB: Institutional Review Board; KD: Klemera-Doubal; PC: principal component; PKC: protein kinase C; ROS: reactive oxygen species; SNP: single nucleotide polymorphism; T2D: type 2 diabetes; VLDL: very low density lipoprotein; WIRB: Western Institutional Review Board.