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DNA methylation GrimAge version 2
We previously described a DNA methylation (DNAm) based biomarker of human mortality risk DNAm GrimAge. Here we describe version 2 of GrimAge (trained on individuals aged between 40 and 92) which leverages two new DNAm based estimators of (log transformed) plasma proteins: high sensitivity C-reactive...
Autores principales: | , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Impact Journals
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9792204/ https://www.ncbi.nlm.nih.gov/pubmed/36516495 http://dx.doi.org/10.18632/aging.204434 |
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author | Lu, Ake T. Binder, Alexandra M. Zhang, Joshua Yan, Qi Reiner, Alex P. Cox, Simon R. Corley, Janie Harris, Sarah E. Kuo, Pei-Lun Moore, Ann Z. Bandinelli, Stefania Stewart, James D. Wang, Cuicui Hamlat, Elissa J. Epel, Elissa S. Schwartz, Joel D. Whitsel, Eric A. Correa, Adolfo Ferrucci, Luigi Marioni, Riccardo E. Horvath, Steve |
author_facet | Lu, Ake T. Binder, Alexandra M. Zhang, Joshua Yan, Qi Reiner, Alex P. Cox, Simon R. Corley, Janie Harris, Sarah E. Kuo, Pei-Lun Moore, Ann Z. Bandinelli, Stefania Stewart, James D. Wang, Cuicui Hamlat, Elissa J. Epel, Elissa S. Schwartz, Joel D. Whitsel, Eric A. Correa, Adolfo Ferrucci, Luigi Marioni, Riccardo E. Horvath, Steve |
author_sort | Lu, Ake T. |
collection | PubMed |
description | We previously described a DNA methylation (DNAm) based biomarker of human mortality risk DNAm GrimAge. Here we describe version 2 of GrimAge (trained on individuals aged between 40 and 92) which leverages two new DNAm based estimators of (log transformed) plasma proteins: high sensitivity C-reactive protein (logCRP) and hemoglobin A1C (logA1C). We evaluate GrimAge2 in 13,399 blood samples across nine study cohorts. After adjustment for age and sex, GrimAge2 outperforms GrimAge in predicting mortality across multiple racial/ethnic groups (meta P=3.6x10(-167) versus P=2.6x10(-144)) and in terms of associations with age related conditions such as coronary heart disease, lung function measurement FEV1 (correlation= -0.31, P=1.1x10(-136)), computed tomography based measurements of fatty liver disease. We present evidence that GrimAge version 2 also applies to younger individuals and to saliva samples where it tracks markers of metabolic syndrome. DNAm logCRP is positively correlated with morbidity count (P=1.3x10(-54)). DNAm logA1C is highly associated with type 2 diabetes (P=5.8x10(-155)). DNAm PAI-1 outperforms the other age-adjusted DNAm biomarkers including GrimAge2 in correlating with triglyceride (cor=0.34, P=9.6x10(-267)) and visceral fat (cor=0.41, P=4.7x10(-41)). Overall, we demonstrate that GrimAge version 2 is an attractive epigenetic biomarker of human mortality and morbidity risk. |
format | Online Article Text |
id | pubmed-9792204 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Impact Journals |
record_format | MEDLINE/PubMed |
spelling | pubmed-97922042022-12-27 DNA methylation GrimAge version 2 Lu, Ake T. Binder, Alexandra M. Zhang, Joshua Yan, Qi Reiner, Alex P. Cox, Simon R. Corley, Janie Harris, Sarah E. Kuo, Pei-Lun Moore, Ann Z. Bandinelli, Stefania Stewart, James D. Wang, Cuicui Hamlat, Elissa J. Epel, Elissa S. Schwartz, Joel D. Whitsel, Eric A. Correa, Adolfo Ferrucci, Luigi Marioni, Riccardo E. Horvath, Steve Aging (Albany NY) Research Paper We previously described a DNA methylation (DNAm) based biomarker of human mortality risk DNAm GrimAge. Here we describe version 2 of GrimAge (trained on individuals aged between 40 and 92) which leverages two new DNAm based estimators of (log transformed) plasma proteins: high sensitivity C-reactive protein (logCRP) and hemoglobin A1C (logA1C). We evaluate GrimAge2 in 13,399 blood samples across nine study cohorts. After adjustment for age and sex, GrimAge2 outperforms GrimAge in predicting mortality across multiple racial/ethnic groups (meta P=3.6x10(-167) versus P=2.6x10(-144)) and in terms of associations with age related conditions such as coronary heart disease, lung function measurement FEV1 (correlation= -0.31, P=1.1x10(-136)), computed tomography based measurements of fatty liver disease. We present evidence that GrimAge version 2 also applies to younger individuals and to saliva samples where it tracks markers of metabolic syndrome. DNAm logCRP is positively correlated with morbidity count (P=1.3x10(-54)). DNAm logA1C is highly associated with type 2 diabetes (P=5.8x10(-155)). DNAm PAI-1 outperforms the other age-adjusted DNAm biomarkers including GrimAge2 in correlating with triglyceride (cor=0.34, P=9.6x10(-267)) and visceral fat (cor=0.41, P=4.7x10(-41)). Overall, we demonstrate that GrimAge version 2 is an attractive epigenetic biomarker of human mortality and morbidity risk. Impact Journals 2022-12-14 /pmc/articles/PMC9792204/ /pubmed/36516495 http://dx.doi.org/10.18632/aging.204434 Text en Copyright: © 2022 Lu et al. https://creativecommons.org/licenses/by/3.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/3.0/) (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Paper Lu, Ake T. Binder, Alexandra M. Zhang, Joshua Yan, Qi Reiner, Alex P. Cox, Simon R. Corley, Janie Harris, Sarah E. Kuo, Pei-Lun Moore, Ann Z. Bandinelli, Stefania Stewart, James D. Wang, Cuicui Hamlat, Elissa J. Epel, Elissa S. Schwartz, Joel D. Whitsel, Eric A. Correa, Adolfo Ferrucci, Luigi Marioni, Riccardo E. Horvath, Steve DNA methylation GrimAge version 2 |
title | DNA methylation GrimAge version 2 |
title_full | DNA methylation GrimAge version 2 |
title_fullStr | DNA methylation GrimAge version 2 |
title_full_unstemmed | DNA methylation GrimAge version 2 |
title_short | DNA methylation GrimAge version 2 |
title_sort | dna methylation grimage version 2 |
topic | Research Paper |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9792204/ https://www.ncbi.nlm.nih.gov/pubmed/36516495 http://dx.doi.org/10.18632/aging.204434 |
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