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Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging
Pei‐Lun Kuo, Jennifer A. Schrack, Morgan E. Levine, Michelle Shardell, Eleanor M. Simonsick, Chee W. Chia, Ann Zenobia Moore, Toshiko Tanaka, Yang An, Ajoy Karikkineth, Majd AlGhatrif, Palchamy Elango, Linda Zukley, Josephine M. Egan, Rafael de Cabo
Nature Aging · 2022 · ▲ 93 citations
Abstract
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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- 10.1038/s43587-022-00243-7
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- 2026-07-22 MST
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APA
Kuo, P., Schrack, J.A., Levine, M.E., Shardell, M., Simonsick, E.M., Chia, C.W., Moore, A.Z., Tanaka, T., An, Y., Karikkineth, A., AlGhatrif, M., Elango, P., Zukley, L., Egan, J.M., Cabo, R.D., Resnick, S.M., & Ferrucci, L. (2022). Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging. <em>Nature Aging</em>. https://doi.org/10.1038/s43587-022-00243-7
Vancouver
Kuo P, Schrack JA, Levine ME, Shardell M, Simonsick EM, Chia CW, et al. Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging. Nature Aging. 2022. doi:10.1038/s43587-022-00243-7.
BibTeX
@article{peilun2022Longit,
title = {Longitudinal phenotypic aging metrics in the Baltimore Longitudinal Study of Aging},
author = {Pei‐Lun Kuo and Jennifer A. Schrack and Morgan E. Levine and Michelle Shardell and Eleanor M. Simonsick and Chee W. Chia and Ann Zenobia Moore and Toshiko Tanaka and Yang An and Ajoy Karikkineth and Majd AlGhatrif and Palchamy Elango and Linda Zukley and Josephine M. Egan and Rafael de Cabo and Susan M. Resnick and Luigi Ferrucci},
journal = {Nature Aging},
year = {2022},
doi = {10.1038/s43587-022-00243-7},
}
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