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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...

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Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Impact Journals 2022
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.
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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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