Targeted metabolomics reveals plasma biomarkers and metabolic alterations of the aging process in healthy young and older adults.
Document Type
Article
Publication Date
12-1-2023
Original Citation
Jasbi P,
Nikolich-Žugich J,
Patterson J,
Knox K,
Jin Y,
Weinstock GM,
Smith P,
Twigg H,
Gu H.
Targeted metabolomics reveals plasma biomarkers and metabolic alterations of the aging process in healthy young and older adults. Geroscience. 2023;45(6):3131-46.
Keywords
Humans, Aged, Cross-Sectional Studies, Biomarkers, Aging, Fatty Acids, Chronic Disease, Health Status
JAX Source
Geroscience. 2023;45(6):3131-46.
ISSN
2509-2723
PMID
37195387
DOI
https://doi.org/10.1007/s11357-023-00823-4
Grant
This work was supported by a grant from the National Institute on Aging U01 AG060900.
Abstract
With the exponential growth in the older population in the coming years, many studies have aimed to further investigate potential biomarkers associated with the aging process and its incumbent morbidities. Age is the largest risk factor for chronic disease, likely due to younger individuals possessing more competent adaptive metabolic networks that result in overall health and homeostasis. With aging, physiological alterations occur throughout the metabolic system that contribute to functional decline. In this cross-sectional analysis, a targeted metabolomic approach was applied to investigate the plasma metabolome of young (21-40y; n = 75) and older adults (65y + ; n = 76). A corrected general linear model (GLM) was generated, with covariates of gender, BMI, and chronic condition score (CCS), to compare the metabolome of the two populations. Among the 109 targeted metabolites, those associated with impaired fatty acid metabolism in the older population were found to be most significant: palmitic acid (p < 0.001), 3-hexenedioic acid (p < 0.001), stearic acid (p = 0.005), and decanoylcarnitine (p = 0.036). Derivatives of amino acid metabolism, 1-methlyhistidine (p = 0.035) and methylhistamine (p = 0.027), were found to be increased in the younger population and several novel metabolites were identified, such as cadaverine (p = 0.034) and 4-ethylbenzoic acid (p = 0.029). Principal component analysis was conducted and highlighted a shift in the metabolome for both groups. Receiver operating characteristic analyses of partial least squares-discriminant analysis models showed the candidate markers to be more powerful indicators of age than chronic disease. Pathway and enrichment analyses uncovered several pathways and enzymes predicted to underlie the aging process, and an integrated hypothesis describing functional characteristics of the aging process was synthesized. Compared to older participants, the young group displayed greater abundance of metabolites related to lipid and nucleotide synthesis; older participants displayed decreased fatty acid oxidation and reduced tryptophan metabolism, relative to the young group. As a result, we offer a better understanding of the aging metabolome and potentially reveal new biomarkers and predicted mechanisms for future study.