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Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging

To define metrics of phenotypic aging, it is essential to identify biological and environmental factors that influence the pace of aging. Previous attempts to develop aging metrics were hampered by cross-sectional designs and/or focused on younger populations. In the Baltimore Longitudinal Study of...

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Autores principales: Kuo, Pei-Lun, Schrack, Jennifer A., Levine, Morgan E., Shardell, Michelle D., Simonsick, Eleanor M., Chia, Chee W., Moore, Ann Zenobia, Tanaka, Toshiko, An, Yang, Karikkineth, Ajoy, AlGhatrif, Majd, Elango, Palchamy, Zukley, Linda M., Egan, Josephine M., de Cabo, Rafael, Resnick, Susan M., Ferrucci, Luigi
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group US 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9997119/
https://www.ncbi.nlm.nih.gov/pubmed/36910594
http://dx.doi.org/10.1038/s43587-022-00243-7
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author Kuo, Pei-Lun
Schrack, Jennifer A.
Levine, Morgan E.
Shardell, Michelle D.
Simonsick, Eleanor M.
Chia, Chee W.
Moore, Ann Zenobia
Tanaka, Toshiko
An, Yang
Karikkineth, Ajoy
AlGhatrif, Majd
Elango, Palchamy
Zukley, Linda M.
Egan, Josephine M.
de Cabo, Rafael
Resnick, Susan M.
Ferrucci, Luigi
author_facet Kuo, Pei-Lun
Schrack, Jennifer A.
Levine, Morgan E.
Shardell, Michelle D.
Simonsick, Eleanor M.
Chia, Chee W.
Moore, Ann Zenobia
Tanaka, Toshiko
An, Yang
Karikkineth, Ajoy
AlGhatrif, Majd
Elango, Palchamy
Zukley, Linda M.
Egan, Josephine M.
de Cabo, Rafael
Resnick, Susan M.
Ferrucci, Luigi
author_sort Kuo, Pei-Lun
collection PubMed
description To define metrics of phenotypic aging, it is essential to identify biological and environmental factors that influence the pace of aging. Previous attempts to develop aging metrics were hampered by cross-sectional designs and/or focused on younger populations. In the Baltimore Longitudinal Study of Aging (BLSA), we collected longitudinally across the adult age range a comprehensive list of phenotypes within four domains (body composition, energetics, homeostatic mechanisms and neurodegeneration/neuroplasticity) and functional outcomes. We integrated individual deviations from population trajectories into a global longitudinal phenotypic metric of aging and demonstrate that accelerated longitudinal phenotypic aging is associated with faster physical and cognitive decline, faster accumulation of multimorbidity and shorter survival. These associations are more robust compared with the use of phenotypic and epigenetic measurements at a single time point. Estimation of these metrics required repeated measures of multiple phenotypes over time but may uniquely facilitate the identification of mechanisms driving phenotypic aging and subsequent age-related functional decline.
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spelling pubmed-99971192023-03-09 Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging Kuo, Pei-Lun Schrack, Jennifer A. Levine, Morgan E. Shardell, Michelle D. Simonsick, Eleanor M. Chia, Chee W. Moore, Ann Zenobia Tanaka, Toshiko An, Yang Karikkineth, Ajoy AlGhatrif, Majd Elango, Palchamy Zukley, Linda M. Egan, Josephine M. de Cabo, Rafael Resnick, Susan M. Ferrucci, Luigi Nat Aging Article To define metrics of phenotypic aging, it is essential to identify biological and environmental factors that influence the pace of aging. Previous attempts to develop aging metrics were hampered by cross-sectional designs and/or focused on younger populations. In the Baltimore Longitudinal Study of Aging (BLSA), we collected longitudinally across the adult age range a comprehensive list of phenotypes within four domains (body composition, energetics, homeostatic mechanisms and neurodegeneration/neuroplasticity) and functional outcomes. We integrated individual deviations from population trajectories into a global longitudinal phenotypic metric of aging and demonstrate that accelerated longitudinal phenotypic aging is associated with faster physical and cognitive decline, faster accumulation of multimorbidity and shorter survival. These associations are more robust compared with the use of phenotypic and epigenetic measurements at a single time point. Estimation of these metrics required repeated measures of multiple phenotypes over time but may uniquely facilitate the identification of mechanisms driving phenotypic aging and subsequent age-related functional decline. Nature Publishing Group US 2022-07-18 2022 /pmc/articles/PMC9997119/ /pubmed/36910594 http://dx.doi.org/10.1038/s43587-022-00243-7 Text en © This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2022, corrected publication 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Kuo, Pei-Lun
Schrack, Jennifer A.
Levine, Morgan E.
Shardell, Michelle D.
Simonsick, Eleanor M.
Chia, Chee W.
Moore, Ann Zenobia
Tanaka, Toshiko
An, Yang
Karikkineth, Ajoy
AlGhatrif, Majd
Elango, Palchamy
Zukley, Linda M.
Egan, Josephine M.
de Cabo, Rafael
Resnick, Susan M.
Ferrucci, Luigi
Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging
title Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging
title_full Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging
title_fullStr Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging
title_full_unstemmed Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging
title_short Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging
title_sort longitudinal phenotypic aging metrics in the baltimore longitudinal study of aging
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9997119/
https://www.ncbi.nlm.nih.gov/pubmed/36910594
http://dx.doi.org/10.1038/s43587-022-00243-7
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