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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Vydáno v:Aging cell Ročník 23; číslo 1; s. e13902 - n/a
Hlavní autoři: 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
Médium: Journal Article
Jazyk:angličtina
Vydáno: England John Wiley & Sons, Inc 01.01.2024
John Wiley and Sons Inc
Témata:
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
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Abstract 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.
AbstractList 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.
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.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.
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.
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.
Author Tanaka, Toshiko
Tian, Qu
Kaileh, Mary
Ubaida‐Mohien, Ceereena
Lovett, Jacqueline
Moore, Ann Zenobia
Collingham, Victoria
Fantoni, Giovanna
Sen, Ranjan
Turek, Lisa
Chia, Chee W.
Moaddel, Ruin
Candia, Julián
Shehadeh, Nader
Ferrucci, Luigi
Egan, Josephine M.
AuthorAffiliation 1 Biomedical Research Centre National Institute on Aging, NIH Baltimore Maryland USA
AuthorAffiliation_xml – name: 1 Biomedical Research Centre National Institute on Aging, NIH Baltimore Maryland USA
Author_xml – sequence: 1
  givenname: Ruin
  orcidid: 0000-0002-6812-0127
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  surname: Ferrucci
  fullname: Ferrucci, Luigi
  email: ferruccilu@grc.nia.nih.gov
  organization: National Institute on Aging, NIH
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Copyright Published 2023. This article is a U.S. Government work and is in the public domain in the USA. published by Anatomical Society and John Wiley & Sons Ltd.
Published 2023. This article is a U.S. Government work and is in the public domain in the USA. Aging Cell published by Anatomical Society and John Wiley & Sons Ltd.
2024. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: Published 2023. This article is a U.S. Government work and is in the public domain in the USA. published by Anatomical Society and John Wiley & Sons Ltd.
– notice: Published 2023. This article is a U.S. Government work and is in the public domain in the USA. Aging Cell published by Anatomical Society and John Wiley & Sons Ltd.
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Issue 1
Keywords senescence
kidney function
inflammation
mitochondrial health
muscle metabolomics
plasma metabolomics
aging
urine metabolomics
Language English
License Attribution
Published 2023. This article is a U.S. Government work and is in the public domain in the USA. Aging Cell published by Anatomical Society and John Wiley & Sons Ltd.
This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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SSID ssj0017903
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Snippet The study of age‐related biomarkers from different biofluids and tissues within the same individual might provide a more comprehensive understanding of...
The study of age-related biomarkers from different biofluids and tissues within the same individual might provide a more comprehensive understanding of...
SourceID pubmedcentral
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pubmed
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SourceType Open Access Repository
Aggregation Database
Index Database
Enrichment Source
Publisher
StartPage e13902
SubjectTerms 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
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Title Cross‐sectional analysis of healthy individuals across decades: Aging signatures across multiple physiological compartments
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Volume 23
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