Research Paper Volume 14, Issue 23 pp 9484—9549
DNA methylation GrimAge version 2
- 1 Dept. of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA 90095, USA
- 2 San Diego Institute of Science, Altos Labs, San Diego, CA 92121, USA
- 3 Population Sciences in the Pacific Program (Cancer Epidemiology), University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI 96813, USA
- 4 Department of Epidemiology, UCLA Fielding School of Public Health, Los Angeles, CA 90095, USA
- 5 Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
- 6 Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, Scotland, UK
- 7 Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD 21224, USA
- 8 Geriatric Unit, Local Health Unit Tuscany Centre, Firenze, Tuscany 40125, Italy
- 9 Dept. of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC 27516-8050, USA
- 10 Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- 11 Department of Psychiatry and Behavioral Sciences, University of California, San Francisco, CA 94143-0848, USA
- 12 Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- 13 Dept. of Medicine, School of Medicine, University of North Carolina, Chapel Hill, NC 27599, USA
- 14 Departments of Medicine and Population Health Science, Jackson Heart Study, University of Mississippi Medical Center, Jackson, MS 39216, USA
- 15 Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, Scotland, UK
- 16 Dept. of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA 90095, USA
Received: September 22, 2022 Accepted: November 21, 2022 Published: December 14, 2022
https://doi.org/10.18632/aging.204434How to Cite
Copyright: © 2022 Lu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
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.