Reviewing the Present State of Aging Clocks
This open access paper could serve as an introduction to aging clocks for someone who has previously given little attention to the ongoing attempts to build ways to quickly and cost-effectively measure biological age. Near every complex set of biological data obtained from an individual can be used to build clocks that estimate age. The present major challenge is the inability to trust the results of any specific clock for any specific scenario involving the use of therapies to treat aging. There is next to no understanding of how in detail the clock data is driven by mechanisms and dysfunctions of aging, and thus no ability to predict ahead of time whether a clock will give useful answers for any given therapy targeting a mechanism of aging. Clocks must be calibrated to their uses, and this is a slow and expensive process.
Aging research has delineated the aging process by classifying two separate but interconnected mechanisms: intrinsic and extrinsic aging. Intrinsic aging describes changes in biological hallmarks including cellular and molecular changes, genetics, and hormonal changes that have been described to occur naturally over time. Extrinsic aging, however, is regulated by exposure to environmental stressors, dietary habits, oxidative stress, and other factors that accelerate physiologic aging. Traditionally, aging has been quantified by chronological age, which is the exact number of years an individual has lived. However, chronological age does not fully capture the heterogeneity of the aging process, excluding many extrinsic factors that contribute to aging.
Subsequently, the calculation of biological age, which aims to account for interindividual variations in aging rate, has become a topic of interest in aging research. Aging clock models are tools that utilize various modeling approaches to estimate chronological or biological age. Moreover, aging clock models can estimate the rate of aging (ΔAge), otherwise known as the difference between model-predicted biological age and chronological age. Positive differences between model-predicted biological age and chronological age indicate accelerated aging whereas a negative difference indicates decelerated aging. If the calculated ΔAge exceeds the mean absolute error (MAE) of the aging rate estimation, these individuals can be determined to be fast or slow agers.
Aging clocks models may utilize any hallmark changes that occur because of aging, and these may include epigenetic changes, telomere length, genomic stability, altered intercellular communication, chronic inflammation, and gut microbiome dysbiosis, among others. Notably, some of the first aging clock models include the Horvath clock (2013) and Hannum clock (2013), which are both epigenetic clocks modeled after changes in DNA methylation patterns and varying cytosine phosphate guanine (CpG) sites across the genome. Several aging clock models have emerged since then, varying from microbiome-based clocks to proteomic clocks.
This bio-clock review paper omitted what is probably the most important biological clock of all: the amount of point- and deletion-mutation damage that has been accumulated with age by the mitochondrial DNA. Because of proximity to ROS-generating ATP production and poor DNA repair mechanisms, the mtDNA damage rate is 100-1000 times larger than that for nuclear DNA. The cell world has many energy-dependent repair mechanisms that could fix most of the problems in the paper's clock list, but those repair mechanisms get shut down with age as mitochondrial ATP production drops due to mtDNA damage and a severe cellular energy shortage sets in.
Of course, the level of mtDNA damage currently can be assessed only with elaborate and expensive mechanisms, usually involving DNA sequencing. We need a better mito-clock.
@John G. Cramer
Your comment prompted me to search "(pure) dna clock (non-methylation)", to no avail. Which leads me to file the hypothesis that the METHYLATION 'clock bubble' is [largely] fueled by the LONG-STANDING bans in some ;) SPECIFIC but VERY phrarma-PROFITABLE countries on consumer dna sequencing :) .
( facebook. com / groups / hbrhs. human. blgcl. rjvntn. hospital. setting. paris )
@benoît (paris, france)
I didn't realize that DNA sequencing was banned anywhere. Modern nanopore sequencing makes it relatively cheap and easy. I calculated that for around $7k I could put together a setup in my basement that would sequence mtDNA.
I find it interesting that the epigenetic programming of nuclear DNA works by methylating CpG sites to encourage genes to turn off and spool onto histones, but mitochondrial DNA has no histones. Methylation of mtDNA does not seem to do anything. If there is any epigenetic programming at all for mitochondria, it is done on the nuclear DNA genes that make mitochondrial proteins.
I am entertaining the causal hypothesis that age-related damage to mtDNA diminishes ATP production, thereby creating an energy shortage that stimulates epigenetic-programming methylation to shut down selected genes that are big energy consumers.