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Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up
Biological age measurements (BAs) assess aging-related physiological change and predict health risks among individuals of the same chronological age (CA). Multiple BAs have been proposed and are well studied individually but not jointly. We included 845 individuals and 3973 repeated measurements fro...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
eLife Sciences Publications, Ltd
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7012595/ https://www.ncbi.nlm.nih.gov/pubmed/32041686 http://dx.doi.org/10.7554/eLife.51507 |
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author | Li, Xia Ploner, Alexander Wang, Yunzhang Magnusson, Patrik KE Reynolds, Chandra Finkel, Deborah Pedersen, Nancy L Jylhävä, Juulia Hägg, Sara |
author_facet | Li, Xia Ploner, Alexander Wang, Yunzhang Magnusson, Patrik KE Reynolds, Chandra Finkel, Deborah Pedersen, Nancy L Jylhävä, Juulia Hägg, Sara |
author_sort | Li, Xia |
collection | PubMed |
description | Biological age measurements (BAs) assess aging-related physiological change and predict health risks among individuals of the same chronological age (CA). Multiple BAs have been proposed and are well studied individually but not jointly. We included 845 individuals and 3973 repeated measurements from a Swedish population-based cohort and examined longitudinal trajectories, correlations, and mortality associations of nine BAs across 20 years follow-up. We found the longitudinal growth of functional BAs accelerated around age 70; average levels of BA curves differed by sex across the age span (50–90 years). All BAs were correlated to varying degrees; correlations were mostly explained by CA. Individually, all BAs except for telomere length were associated with mortality risk independently of CA. The largest effects were seen for methylation age estimators (GrimAge) and the frailty index (FI). In joint models, two methylation age estimators (Horvath and GrimAge) and FI remained predictive, suggesting they are complementary in predicting mortality. |
format | Online Article Text |
id | pubmed-7012595 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | eLife Sciences Publications, Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-70125952020-02-12 Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up Li, Xia Ploner, Alexander Wang, Yunzhang Magnusson, Patrik KE Reynolds, Chandra Finkel, Deborah Pedersen, Nancy L Jylhävä, Juulia Hägg, Sara eLife Epidemiology and Global Health Biological age measurements (BAs) assess aging-related physiological change and predict health risks among individuals of the same chronological age (CA). Multiple BAs have been proposed and are well studied individually but not jointly. We included 845 individuals and 3973 repeated measurements from a Swedish population-based cohort and examined longitudinal trajectories, correlations, and mortality associations of nine BAs across 20 years follow-up. We found the longitudinal growth of functional BAs accelerated around age 70; average levels of BA curves differed by sex across the age span (50–90 years). All BAs were correlated to varying degrees; correlations were mostly explained by CA. Individually, all BAs except for telomere length were associated with mortality risk independently of CA. The largest effects were seen for methylation age estimators (GrimAge) and the frailty index (FI). In joint models, two methylation age estimators (Horvath and GrimAge) and FI remained predictive, suggesting they are complementary in predicting mortality. eLife Sciences Publications, Ltd 2020-02-11 /pmc/articles/PMC7012595/ /pubmed/32041686 http://dx.doi.org/10.7554/eLife.51507 Text en © 2020, Li et al http://creativecommons.org/licenses/by/4.0/ http://creativecommons.org/licenses/by/4.0/This article is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use and redistribution provided that the original author and source are credited. |
spellingShingle | Epidemiology and Global Health Li, Xia Ploner, Alexander Wang, Yunzhang Magnusson, Patrik KE Reynolds, Chandra Finkel, Deborah Pedersen, Nancy L Jylhävä, Juulia Hägg, Sara Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up |
title | Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up |
title_full | Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up |
title_fullStr | Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up |
title_full_unstemmed | Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up |
title_short | Longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up |
title_sort | longitudinal trajectories, correlations and mortality associations of nine biological ages across 20-years follow-up |
topic | Epidemiology and Global Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7012595/ https://www.ncbi.nlm.nih.gov/pubmed/32041686 http://dx.doi.org/10.7554/eLife.51507 |
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