​​Aging-US: DNA methylation-based measures of biological age

01-03-2022

Aging-US published "DNA methylation-based measures of biological age: meta-analysis predicting time to death" which reported that estimates of biological age based on DNA methylation patterns, often referred to as "epigenetic age", "DNAm age", have been shown to be robust biomarkers of age in humans.

These authors previously demonstrated that independent of chronological age, epigenetic age assessed in blood predicted all-cause mortality in four human cohorts. Here, they expanded their original observation to 13 different cohorts for a total sample size of 13,089 individuals, including three racial/ethnic groups. In addition, they examined whether incorporating information on blood cell composition into the epigenetic age metrics improves their predictive power for mortality.

All considered measures of epigenetic age acceleration were predictive of mortality, independent of chronological age, even after adjusting for additional risk factors.

The authors said, "DNA methylation-based biomarkers, often referred to as ‘epigenetic age’ or ‘epigenetic clock’, are robust estimators of chronological age of an individual."

DNA methylation-based biomarkers, often referred to as ‘epigenetic age’ or ‘epigenetic clock’, are robust estimators of chronological age of an individual

This estimate is consistent across most types of biological specimens, including whole blood, brain, breast, kidney, liver, lung, and saliva and cell types, including CD4 T cells, monocytes, B cells, glial cells, and neurons.

It is well known that blood cell composition changes with age and some of these changes might be independent predictors of mortality. Thus, it is of interest to understand whether considering information on blood cell composition in measures of epigenetic age improves their predictive power for mortality.

Here, the authors evaluated the ability to predict time to death for blood-based epigenetic age measures, both published and novel measures that incorporate information on blood cell composition.

Figure 4. Hazard ratio of death versus cohort characteristics. Each circle corresponds to a cohort (data set). Circle sizes correspond to the square root of the number of observed deaths, because the statistical power of a Cox model is determined by the number of observed deaths. A-C) The y-axis of each panel corresponds to the natural log of the hazard ratio (ln HR) of a univariate Cox regression model for all-cause mortality. Each panel corresponds to a different measure of epigenetic age acceleration A) universal age acceleration, B) intrinsic age acceleration, C) extrinsic age acceleration. Panels D-F are analogous to those in A-C but the x-axis corresponds to the median age of the subjects at baseline (Table 1). The title of each panel reports the Wald test statistic (T) and corresponding p-value resulting from a weighted linear regression model (y regressed on x) where each point (data set) is weighted by the square root of the number of observed deaths. The dotted red line represents the regression line. The black solid line represents the line of identify (i.e., no association).

Due to the well documented age-related changes in blood cell composition, they were able to distinguish epigenetic measures of age that were independent of changes in blood cell composition, and measures that incorporated age-related changes in blood cell composition.

The Research Team concluded in their Aging-US Research Output, "our results inform the ongoing debate about whether epigenetic biomarkers of age capture an aspect of biological age. While epigenetic processes are unlikely to be the only mediators of chronological age on mortality—in fact, multiple risk factors have stronger effects on mortality—our results suggest that at least one of the mediating processes relates to the epigenetic age of blood tissue and that this process is independent of age-dependent changes in blood cell composition. Future studies will be useful for gaining a mechanistic understanding of this intrinsic epigenetic aging process."

Full Text - https://www.aging-us.com/article/101020/text/

Correspondence to: Steve Horvath email: shorvath@mednet.ucla.edu

all-cause mortality lifespan epigenetics epigenetic clock DNA methylation mortality

Keywords: all-cause mortality, lifespan, epigenetics, epigenetic clock, DNA+methylation, mortality

About Aging-US:

Aging publishes research papers in all fields of aging research including but not limited, aging from yeast to mammals, cellular senescence, age-related diseases such as cancer and Alzheimer’s diseases and their prevention and treatment, anti-aging strategies and drug development and especially the role of signal transduction pathways such as mTOR in aging and potential approaches to modulate these signaling pathways to extend lifespan. The journal aims to promote treatment of age-related diseases by slowing down aging, validation of anti-aging drugs by treating age-related diseases, prevention of cancer by inhibiting aging. Cancer and COVID-19 are age-related diseases.

Aging is indexed by PubMed/Medline (abbreviated as “Aging (Albany NY)”), PubMed CentralWeb of Science: Science Citation Index Expanded (abbreviated as “Aging‐US” and listed in the Cell Biology and Geriatrics & Gerontology categories), Scopus (abbreviated as “Aging” and listed in the Cell Biology and Aging categories), Biological Abstracts, BIOSIS Previews, EMBASE, META (Chan Zuckerberg Initiative) (2018-2022), and Dimensions (Digital Science).

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