Metabolic and Genetic Markers of Biological Age

Abstract

Biological age is a concept that takes into account the heterogeneity of the aging process in different individuals that results in differences in survival and variations in relative health. Any measure of biological age must be better than chronological age at predicting mortality. Several quantitative measures of biological age have been developed. Among them are frailty indices, one of which called FI₃₄ is discussed here in greater detail. FI₃₄ increases exponentially with age reflecting decline in health and function ability. It readily depicts different patterns and trajectories of aging, and it is moderately heritable. Thus, it has been used to identify a genomic region on chromosome 12 associated with healthy aging. FI₃₄ has also been useful in describing the metabolic characteristics of this phenotype, revealing both sex and genetic differences. These differences give rise to specific, testable models regarding healthy aging, which involve cell and tissue damage and mitochondrial metabolism. FI₃₄ has been directly compared to various metrics based on DNA methylation as a predictor of mortality, demonstrating that it outperforms them uniformly. This and other frailty indices take a top-down, systems based view of aging that is cognizant of the integrated function of the complex aging system.

Keywords: DNA methylation; energy metabolism; frailty index; genes; healthy aging.

FIGURE 1

Body composition and creatine kinase levels are associated with FI₃₄ in females and males, respectively. (A) Female and (B) male nonagenarians were compared. FI₃₄ is the outcome variable presented as a standardized coefficient in multiple linear regressions. The explanatory variables are CK, FFM, FM, and RMR. The sample size (N) and the coefficient of determination (R²) with p-value are shown. ^∗p < 0.05; ^∗∗p < 0.01; ^∗∗∗p < 0.001, for the standardized coefficients for each variable. Based on data from Kim et al. (2014).

FIGURE 2

Comparison of effect sizes for hazards of death. Cox proportional hazards regressions were applied to the survival data of 262 subjects ages 60–103 and are presented as Z scores. Age, FI₃₄, DNA methylation age (DNAm Age), Age Acceleration Difference (Age Diff), and Age Acceleration Residual (Age Resid) are the covariates. (A) All subjects, (B) nonagenarians (N = 161). ^∗p < 0.05; ^∗∗p < 0.01; ^∗∗∗p < 0.001. This figure has been adapted from Kim et al. (2017) under the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).