In Search of Specific Epigenetic Predictors of Longevity

Just as the research community is sifting the world for correlations between variations in the human genome and variations in human longevity, so too are scientists beginning to pay greater attention to the role of the epigenome. The DNA in every one of our cells is better thought of as a whirling, dynamic machine rather than a static blueprint. It is in motion, a blur, a thousand thousand feedback loops involving the production of proteins that selectively alter the process of producing proteins. The amount of any one specific protein in a given cell produced from its DNA blueprint rises and falls dynamically, in response to environmental conditions, time of day, status of the cell's internal machinery, and a million other variations tuned by evolution. The epigenome is this dynamic partner to the static genome, a catalog of how genes become tagged and the changes that result from those tags. Epigenetics is the study of how DNA interacts with the machinery of protein construction to selectively modify the output in response to circumstances - and what that then means for cells, organs, and the operation of the body as a whole.

Just as there are genetic variations that subtly contribute to human longevity, we should expect there to be equally subtle epigenetic variations - though more complex, and harder to uncover. Research here contributes to the grand debate over the degree to which aging is programmed: is the epigenetic contribution to aging a matter of growing disarray in the processes of tagging and correcting levels of protein production, arising due to damage, or are there signs of programmed changes in levels of protein production that cause damage and dysfunction?

A paper from earlier this year claims epigenetic biomarkers of longevity in nematode worms, a much simpler animal to study than we mammals:

Why do some individuals live longer than others? ... Inter-individual variation in human longevity has not been found to be under substantial genetic control, with heritability generally between 15% and 30% ... The situation is thrown into relief in studies of C. elegans, in which genetically identical siblings reared in identical environments usually experience different lifespans. In this work, we show that physiological differences between identical animals begin to appear relatively early in life and that markers of ill health in young adulthood presage shorter lifespans.

Using fluorescent markers to examine the level of activation of several genes, we found three regulatory microRNA genes [in] which early-adulthood expression patterns individually predict up to 47% of lifespan differences. Though expression of each increases throughout this time, mir-71 and mir-246 correlate with lifespan, while mir-239 anti-correlates. Two of these three microRNA "biomarkers of aging" act upstream in insulin/IGF-1-like signaling (IIS) and other known longevity pathways, thus we infer that these microRNAs not only report on but also likely determine longevity. Thus, fluctuations in early-life IIS, due to variation in these microRNAs and from other causes, may determine individual lifespan.

The educated guess at this point is that the way in which natural, unmodified life span emerges depends a little on the DNA blueprint, a lot on the environment, but just as much on chains of chaotic happenstance in the enormously complex operations of metabolism. We might consider that last line item a form of stochastic accumulation of molecular damage to cells: even with all other things being equal, individuals will age at somewhat different rates because initially small, localized differences in biological damage snowball over time into widely diverging system-wide outcomes.

Interestingly, it looks like there are good signposts on that road; we shall no doubt see how good or useful epigenetic biomarkers turn out to be in humans. Certainly a large community of researchers are hotly engaged in trying to uncover truly reliable biomarkers that measure aging or predict longevity, so if there is something to be found in the epigenome they will eventually find it.

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