The Time of Your Life
The French romantic poet Charles Baudelaire famously had a clock on his desk with a somber warning on the dial: It is later than you think.
Well, is it?
Aging can be defined by sequential or progressive changes in an organism that lead to an increased risk of debility, disease, and death. It is actually the major risk factor for most pathological conditions that limit health span and promote chronic disorders including immuno-senescence, cardio-metabolic disorders, osteoporosis, sarcopenia, arthritis, cataracts, neurodegenerative diseases, and most cancers. Because of such importance, a set of identifiable genetic and environmental markers able to tell if one’s biological age is on par with one’s chronological age have been much sought after. Pushed by new discoveries in basic biological processes, perhaps as well as the desire for immortality, new markers of aging are being discovered regularly. But, how reliable are they and how much should they affect lifestyle choices?
It has been clear for a long time that aging rates between individuals sharing the same birth year can vary significantly. While chronological age is a somewhat poor predictor of comparative biological age, a number of other methods to assess biological age have been developed that span from functional tests measuring grip strength, walking speed, and standing balance to more “objective” molecular methods like measuring genome instability, p16INK4a expression levels, cellular senescence, proteostasis, structures of IgG glycans and mitochondrial function (c.f., a good review from the Lancet on biological age predictors).
The American Federation of Aging Research has promulgated a set of criteria to evaluate biomarkers of aging. They must:
(1) predict remaining life expectancy better than chronological age,
(2) monitor mechanisms underlying the aging process but not a specific disease,
(3) be subject to repeated tests without harming the individual, and
(4) be testable in both laboratory animals and humans.
No single method as of yet fulfills all the criteria above, but various markers can help in specific applications. Here are two examples of markers that were developed to give a better estimate of your risk of disease and death:
– Telomere Length (TL): In the early 1970s, Soviet theorist Alexei Olovnikov first recognized that chromosomes could not completely replicate their ends, coining the now-famous "end replication problem.” He then suggested that DNA sequences are lost every time a cell replicates until the loss reaches a critical level at which point cell division ends. An inverse correlation between TL and human chronological age has since then been well-documented in the literature and a significant negative correlation of about -0.3 between mean chronological age and mean TL was found across 124 cross-sectional studies. To complement these findings, numerous epidemiological studies indicated that short telomeres were associated with higher morbidity and all-cause mortality and TL appeared to be a better predictor for survival than chronological age.
An important caveat to this wealth of data is that a large inconsistency was observed among studies. The discrepancy, attributable to differences in the methods of TL measurement and statistical modeling, was so great that some authors even questioned whether the link between TL and aging-associated processes really exists and it has led to hot debates about whether TL is a reliable tool to evaluate the rate of aging in human populations. Nevertheless, despite this uncertainty, TL currently remains one of the most widely used biomarkers of aging in epidemiological and clinical studies. In recent years, TL is also being increasingly used as a potential biomarker in personalized medicine.
– Epigenetic Clock: In the late 1990s, researchers at Johns Hopkins University discovered aging- and cancer-related changes to DNA methylation in cells of the human colon. DNA methylation levels measure the accumulation of methyl groups in DNA molecules. Methylation is an important mechanism to control gene expression. The observation of changing DNA methylation with age and diseases allowed the development of the idea that epigenetic disruption could be a marker of biological age.
In 2011, Steve Horvath, an anti-aging researcher at the University of California, Los Angeles, created the first of these clocks based on the methylation profile of a few chosen genes. The number of genes to follow quickly increased to 71 for better prediction, and Horvath produced a multi-organ clock. Today, data from 353 genes has been used to predict human age from the embryo to old age. Perhaps not surprisingly, embryonic stem cells have an epigenetic age of nearly zero, whereas cancer cells show accelerated aging.
While the first studies focused on the methylation of genes relevant to aging, the modern epigenetic clocks are derived from big data science with thousands of genes screened. By increasing the number of relevant gene candidates, the goal was to trade mechanistic understanding for accuracy. The US Food and Drug Administration does not, however, currently recognize epigenetic-clock scores as surrogate endpoints for clinical trials because it wants their mechanistic basis to be better defined. And it wants an answer to the crucial question of whether a short-term decrease in someone’s epigenetic-clock score definitively lowers their chances of developing age-related ill health.
We all seem to feel the effects of aging too fast, but in the case of Baudelaire who died in 1867 at just 46 years old after two years in a semi-paralyzed state from a stroke, most likely due to his consumption of opium and alcohol, his clock had a particularly cruel relevance. Searching for new ways of understanding health and the aging process could help achieve older ages with grace and at one’s own pace.