DNA methylation GrimAge strongly predicts lifespan and healthspan

Ake T. Lu(University of California, Los Angeles), Austin Quach(University of California, Los Angeles), James G. Wilson(University of Mississippi Medical Center), Alex P. Reiner(Fred Hutch Cancer Center), Abraham Aviv(Rutgers New Jersey Medical School), Kenneth Raj(Public Health England), Lifang Hou(Robert H. Lurie Comprehensive Cancer Center of Northwestern University), Andrea Baccarelli(Columbia University), Yun Li(University of North Carolina at Chapel Hill), James D. Stewart(University of North Carolina at Chapel Hill), Eric A. Whitsel(University of North Carolina at Chapel Hill), Themistocles L. Assimes(Stanford University), Luigi Ferrucci(National Institute on Aging), Steve Horvath(University of California, Los Angeles)
Aging
January 21, 2019
10.18632/aging.101684
Cited by 2,544Open Access
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Abstract

.Using large scale validation data from thousands of individuals, we demonstrate that DNAm GrimAge stands out among existing epigenetic clocks in terms of its predictive ability for time-to-death (Cox regression P=2.0E-75), time-to-coronary heart disease (Cox P=6.2E-24), time-to-cancer (P= 1.3E-12), its strong relationship with computed tomography data for fatty liver/excess visceral fat, and age-at-menopause (P=1.6E-12). AgeAccelGrim is strongly associated with a host of age-related conditions including comorbidity count (P=3.45E-17). Similarly, age-adjusted DNAm PAI-1 levels are associated with lifespan (P=5.4E-28), comorbidity count (P= 7.3E-56) and type 2 diabetes (P=2.0E-26). These DNAm-based biomarkers show the expected relationship with lifestyle factors including healthy diet and educational attainment.Overall, these epigenetic biomarkers are expected to find many applications including human anti-aging studies.

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