Research Paper Volume 11, Issue 4 pp 1262—1282
Longitudinal plasma metabolomics of aging and sex
- 1 Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, Madison, WI 53726, USA
- 2 Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, Madison, WI 53726, USA
- 3 Department of Anesthesiology, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
- 4 Geriatric Research Education and Clinical Center, Wm. S. Middleton Memorial VA Hospital, Madison, WI 53705, USA
- 5 Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI 53792, USA
received: September 20, 2018 ; accepted: February 17, 2019 ; published: February 24, 2019 ;https://doi.org/10.18632/aging.101837
How to Cite
Copyright: Darst et al. This is an open‐access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Understanding how metabolites are longitudinally influenced by age and sex could facilitate the identification of metabolomic profiles and trajectories that indicate disease risk. We investigated the metabolomics of age and sex using longitudinal plasma samples from the Wisconsin Registry for Alzheimer’s Prevention (WRAP), a cohort of participants who were dementia free at enrollment. Metabolomic profiles were quantified for 2,344 fasting plasma samples among 1,212 participants, each with up to three study visits. Of 1,097 metabolites tested, 623 (56.8%) were associated with age and 695 (63.4%) with sex after correcting for multiple testing. Approximately twice as many metabolites were associated with age in stratified analyses of women versus men, and 68 metabolite trajectories significantly differed by sex, most notably including sphingolipids, which tended to increase in women and decrease in men with age. Using genome-wide genotyping, we also report the heritabilities of metabolites investigated, which ranged dramatically (0.2–99.2%); however, the median heritability of 36.2% suggests that many metabolites are highly influenced by a complex combination of genomic and environmental influences. These findings offer a more profound description of the aging process and may inform many new hypotheses regarding the role metabolites play in healthy and accelerated aging.