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DNA methylation-based measures of biological age: meta-analysis predicting time to death
Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals LLC
2016
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5076441/ https://www.ncbi.nlm.nih.gov/pubmed/27690265 http://dx.doi.org/10.18632/aging.101020 |
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author | Chen, Brian H. Marioni, Riccardo E. Colicino, Elena Peters, Marjolein J. Ward-Caviness, Cavin K. Tsai, Pei-Chien Roetker, Nicholas S. Just, Allan C. Demerath, Ellen W. Guan, Weihua Bressler, Jan Fornage, Myriam Studenski, Stephanie Vandiver, Amy R. Moore, Ann Zenobia Tanaka, Toshiko Kiel, Douglas P. Liang, Liming Vokonas, Pantel Schwartz, Joel Lunetta, Kathryn L. Murabito, Joanne M. Bandinelli, Stefania Hernandez, Dena G. Melzer, David Nalls, Michael Pilling, Luke C. Price, Timothy R. Singleton, Andrew B. Gieger, Christian Holle, Rolf Kretschmer, Anja Kronenberg, Florian Kunze, Sonja Linseisen, Jakob Meisinger, Christine Rathmann, Wolfgang Waldenberger, Melanie Visscher, Peter M. Shah, Sonia Wray, Naomi R. McRae, Allan F. Franco, Oscar H. Hofman, Albert Uitterlinden, André G. Absher, Devin Assimes, Themistocles Levine, Morgan E. Lu, Ake T. Tsao, Philip S. Hou, Lifang Manson, JoAnn E. Carty, Cara L. LaCroix, Andrea Z. Reiner, Alexander P. Spector, Tim D. Feinberg, Andrew P. Levy, Daniel Baccarelli, Andrea van Meurs, Joyce Bell, Jordana T. Peters, Annette Deary, Ian J. Pankow, James S. Ferrucci, Luigi Horvath, Steve |
author_facet | Chen, Brian H. Marioni, Riccardo E. Colicino, Elena Peters, Marjolein J. Ward-Caviness, Cavin K. Tsai, Pei-Chien Roetker, Nicholas S. Just, Allan C. Demerath, Ellen W. Guan, Weihua Bressler, Jan Fornage, Myriam Studenski, Stephanie Vandiver, Amy R. Moore, Ann Zenobia Tanaka, Toshiko Kiel, Douglas P. Liang, Liming Vokonas, Pantel Schwartz, Joel Lunetta, Kathryn L. Murabito, Joanne M. Bandinelli, Stefania Hernandez, Dena G. Melzer, David Nalls, Michael Pilling, Luke C. Price, Timothy R. Singleton, Andrew B. Gieger, Christian Holle, Rolf Kretschmer, Anja Kronenberg, Florian Kunze, Sonja Linseisen, Jakob Meisinger, Christine Rathmann, Wolfgang Waldenberger, Melanie Visscher, Peter M. Shah, Sonia Wray, Naomi R. McRae, Allan F. Franco, Oscar H. Hofman, Albert Uitterlinden, André G. Absher, Devin Assimes, Themistocles Levine, Morgan E. Lu, Ake T. Tsao, Philip S. Hou, Lifang Manson, JoAnn E. Carty, Cara L. LaCroix, Andrea Z. Reiner, Alexander P. Spector, Tim D. Feinberg, Andrew P. Levy, Daniel Baccarelli, Andrea van Meurs, Joyce Bell, Jordana T. Peters, Annette Deary, Ian J. Pankow, James S. Ferrucci, Luigi Horvath, Steve |
author_sort | Chen, Brian H. |
collection | PubMed |
description | Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2×10(−9)), independent of chronological age, even after adjusting for additional risk factors (p<5.4×10(−4)), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5×10(−43)). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality. |
format | Online Article Text |
id | pubmed-5076441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2016 |
publisher | Impact Journals LLC |
record_format | MEDLINE/PubMed |
spelling | pubmed-50764412016-10-27 DNA methylation-based measures of biological age: meta-analysis predicting time to death Chen, Brian H. Marioni, Riccardo E. Colicino, Elena Peters, Marjolein J. Ward-Caviness, Cavin K. Tsai, Pei-Chien Roetker, Nicholas S. Just, Allan C. Demerath, Ellen W. Guan, Weihua Bressler, Jan Fornage, Myriam Studenski, Stephanie Vandiver, Amy R. Moore, Ann Zenobia Tanaka, Toshiko Kiel, Douglas P. Liang, Liming Vokonas, Pantel Schwartz, Joel Lunetta, Kathryn L. Murabito, Joanne M. Bandinelli, Stefania Hernandez, Dena G. Melzer, David Nalls, Michael Pilling, Luke C. Price, Timothy R. Singleton, Andrew B. Gieger, Christian Holle, Rolf Kretschmer, Anja Kronenberg, Florian Kunze, Sonja Linseisen, Jakob Meisinger, Christine Rathmann, Wolfgang Waldenberger, Melanie Visscher, Peter M. Shah, Sonia Wray, Naomi R. McRae, Allan F. Franco, Oscar H. Hofman, Albert Uitterlinden, André G. Absher, Devin Assimes, Themistocles Levine, Morgan E. Lu, Ake T. Tsao, Philip S. Hou, Lifang Manson, JoAnn E. Carty, Cara L. LaCroix, Andrea Z. Reiner, Alexander P. Spector, Tim D. Feinberg, Andrew P. Levy, Daniel Baccarelli, Andrea van Meurs, Joyce Bell, Jordana T. Peters, Annette Deary, Ian J. Pankow, James S. Ferrucci, Luigi Horvath, Steve Aging (Albany NY) Priority Research Paper Estimates of biological age based on DNA methylation patterns, often referred to as “epigenetic age”, “DNAm age”, have been shown to be robust biomarkers of age in humans. We previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, we expanded our original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, we examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality. All considered measures of epigenetic age acceleration were predictive of mortality (p≤8.2×10(−9)), independent of chronological age, even after adjusting for additional risk factors (p<5.4×10(−4)), and within the racial/ethnic groups that we examined (non-Hispanic whites, Hispanics, African Americans). Epigenetic age estimates that incorporated information on blood cell composition led to the smallest p-values for time to death (p=7.5×10(−43)). Overall, this study a) strengthens the evidence that epigenetic age predicts all-cause mortality above and beyond chronological age and traditional risk factors, and b) demonstrates that epigenetic age estimates that incorporate information on blood cell counts lead to highly significant associations with all-cause mortality. Impact Journals LLC 2016-09-28 /pmc/articles/PMC5076441/ /pubmed/27690265 http://dx.doi.org/10.18632/aging.101020 Text en Copyright: © 2016 Chen et al. http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Priority Research Paper Chen, Brian H. Marioni, Riccardo E. Colicino, Elena Peters, Marjolein J. Ward-Caviness, Cavin K. Tsai, Pei-Chien Roetker, Nicholas S. Just, Allan C. Demerath, Ellen W. Guan, Weihua Bressler, Jan Fornage, Myriam Studenski, Stephanie Vandiver, Amy R. Moore, Ann Zenobia Tanaka, Toshiko Kiel, Douglas P. Liang, Liming Vokonas, Pantel Schwartz, Joel Lunetta, Kathryn L. Murabito, Joanne M. Bandinelli, Stefania Hernandez, Dena G. Melzer, David Nalls, Michael Pilling, Luke C. Price, Timothy R. Singleton, Andrew B. Gieger, Christian Holle, Rolf Kretschmer, Anja Kronenberg, Florian Kunze, Sonja Linseisen, Jakob Meisinger, Christine Rathmann, Wolfgang Waldenberger, Melanie Visscher, Peter M. Shah, Sonia Wray, Naomi R. McRae, Allan F. Franco, Oscar H. Hofman, Albert Uitterlinden, André G. Absher, Devin Assimes, Themistocles Levine, Morgan E. Lu, Ake T. Tsao, Philip S. Hou, Lifang Manson, JoAnn E. Carty, Cara L. LaCroix, Andrea Z. Reiner, Alexander P. Spector, Tim D. Feinberg, Andrew P. Levy, Daniel Baccarelli, Andrea van Meurs, Joyce Bell, Jordana T. Peters, Annette Deary, Ian J. Pankow, James S. Ferrucci, Luigi Horvath, Steve DNA methylation-based measures of biological age: meta-analysis predicting time to death |
title | DNA methylation-based measures of biological age: meta-analysis predicting time to death |
title_full | DNA methylation-based measures of biological age: meta-analysis predicting time to death |
title_fullStr | DNA methylation-based measures of biological age: meta-analysis predicting time to death |
title_full_unstemmed | DNA methylation-based measures of biological age: meta-analysis predicting time to death |
title_short | DNA methylation-based measures of biological age: meta-analysis predicting time to death |
title_sort | dna methylation-based measures of biological age: meta-analysis predicting time to death |
topic | Priority Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5076441/ https://www.ncbi.nlm.nih.gov/pubmed/27690265 http://dx.doi.org/10.18632/aging.101020 |
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