Cross‐sectional analysis of healthy individuals across decades: Aging signatures across multiple physiological compartments

The study of age‐related biomarkers from different biofluids and tissues within the same individual might provide a more comprehensive understanding of age‐related changes within and between compartments as these changes are likely highly interconnected. Understanding age‐related differences by comp...

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Veröffentlicht in:Aging cell Jg. 23; H. 1; S. e13902 - n/a
Hauptverfasser: Moaddel, Ruin, Ubaida‐Mohien, Ceereena, Tanaka, Toshiko, Tian, Qu, Candia, Julián, Moore, Ann Zenobia, Lovett, Jacqueline, Fantoni, Giovanna, Shehadeh, Nader, Turek, Lisa, Collingham, Victoria, Kaileh, Mary, Chia, Chee W., Sen, Ranjan, Egan, Josephine M., Ferrucci, Luigi
Format: Journal Article
Sprache:Englisch
Veröffentlicht: England John Wiley & Sons, Inc 01.01.2024
John Wiley and Sons Inc
Schlagworte:
Adult
Age
Aged
Aged, 80 and over
Aging
Bioavailability
Biomarkers
Biomarkers - metabolism
Biopsy
Body mass index
Cellular Senescence
Creatinine
Cross-Sectional Studies
Enrollments
Epigenetics
Humans
inflammation
kidney function
Lipid metabolism
Metabolic pathways
Metabolism
Metabolites
Metabolomics
Middle Aged
mitochondrial health
muscle metabolomics
Musculoskeletal system
Plasma
plasma metabolomics
Senescence
Skeletal muscle
Urine
urine metabolomics
Young Adult
senescence
kidney function
inflammation
mitochondrial health
muscle metabolomics
plasma metabolomics
aging
urine metabolomics
ISSN:1474-9718, 1474-9726, 1474-9726
Online-Zugang:Volltext
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Zusammenfassung:The study of age‐related biomarkers from different biofluids and tissues within the same individual might provide a more comprehensive understanding of age‐related changes within and between compartments as these changes are likely highly interconnected. Understanding age‐related differences by compartments may shed light on the mechanism of their reciprocal interactions, which may contribute to the phenotypic manifestations of aging. To study such possible interactions, we carried out a targeted metabolomic analysis of plasma, skeletal muscle, and urine collected from healthy participants, age 22–92 years, and identified 92, 34, and 35 age‐associated metabolites, respectively. The metabolic pathways that were identified across compartments included inflammation and cellular senescence, microbial metabolism, mitochondrial health, sphingolipid metabolism, lysosomal membrane permeabilization, vascular aging, and kidney function. A targeted metabolomic analysis of plasma, skeletal muscle, and urine from healthy participants was carried out to compare and contrast metabolite changes with aging across and within compartments. The metabolic pathways that were identified included inflammation and cellular senescence, microbial metabolism, mitochondrial health, sphingolipid metabolism, lysosomal membrane permeabilization, vascular aging, and kidney function.
Bibliographie:R. Moaddel and C. Ubaida‐Mohien share first authorship.
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ISSN:1474-9718
1474-9726
1474-9726
DOI:10.1111/acel.13902