In 2019, a small study raised the tantalizing prospect that ageing could be reversed. Scientists in California gave 9 men aged 51 to 65 a growth hormone and two diabetes medications for a year1. The drugs seemed to rejuvenate the men’s thymus glands and immune function. They also shaved 2.5 years off the men’s biological age, as measured by one of the most talked-about technologies in ageing research: epigenetic clocks.
Biological age is an important concept, albeit a slippery one. Everyone’s physical and mental functioning gradually declines from early adulthood onwards, but this occurs at different rates in different people. A technique for measuring biological age detects a signal that is a better guide to a person’s functional capacity than their actual, chronological age.
As more and more scientists seek to slow, halt or rewind ageing, such methods will be needed to assess whether the new manipulations achieve these goals.
Epigenetic clocks use algorithms to calculate biological age on the basis of a read-out of the extent to which dozens or even hundreds of sites across an individual’s genome are bound by methyl groups — a form of epigenetic modification.
In 2017, the scientists behind the growth-hormone trial — based at Intervene Immune, an anti-ageing biotech company in Torrance, California — were excited by their observation of thymus and immune renewal. They contacted Steve Horvath, an anti-ageing researcher at the University of California, Los Angeles, to ask if he would use an epigenetic clock to analyse blood samples they had taken during the trial. Horvath agreed. “Anybody who has an exciting study,” he says, “I love to get involved.”
But critics have questioned the purported decrease in biological age, stressing that it was a small, unblinded study with no placebo control arm. “If you have nine people,” says Horvath, “and you get a statistically significant result, it means there’s a strong effect.” He and the company are now running a randomized and placebo-controlled phase II replication on a larger group of 85 people.
The study is one of many, in humans and in animals, that seek ways to reduce epigenetic-clock scores — and thereby develop new anti-ageing interventions.
But some experts are concerned by the unknowns that still surround this technology. Matt Kaeberlein, who studies ageing at the University of Washington in Seattle, says: “It’s become a sort of dogma in the field — and in the popular perception — that these things are really measuring biological ageing. We really need to understand how these things are working.”
Horvath acknowledges this. “That’s the weakness of these biomarkers,” he says. “They come out of a machine-learning algorithm. They work beautifully in a mathematical sense, but biologists want more.”
The US Food and Drug Administration does not currently recognize epigenetic-clock scores as surrogate end points for clinical trials. 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.
Molecular horology
The DNA methylation that underpins epigenetic clocks is a reversible process that is catalysed by enzymes. It involves the addition of a tag known as a methyl group to parts of the genome in which cytosine bases are bound to guanine bases through a phosphate group (CpG). When methylated, CpGs can act as binding sites for proteins that alter DNA’s 3D structure. At numerous CpGs, methylation has been shown to profoundly decrease gene expression, offering a clear mechanism by which it can affect biological function.
In the late 1990s, researchers at Johns Hopkins University in Baltimore, Maryland, discovered ageing- and cancer-related changes to DNA methylation in cells of the human colon2. Theories of ageing have long considered ways in which genomic integrity might be lost progressively, such as by mutations accumulating or the telomere caps of chromosomes shortening. This observation of shifting DNA methylation bolstered the nascent idea that epigenetic disruption might drive ageing by increasingly dysregulating gene expression.
But whereas early studies of methylation focused on genes selected for their known relevance to ageing, epigenetic clocks are the fruit of ‘big data’ science.
In the late 2000s, arrays emerged that take DNA from many cells and analyse thousands of CpGs to determine what fraction of them bear a methyl group. Combined with machine learning, these arrays were quickly used to seekepigenetic signatures for numerous traits.
But even if a signal is uncovered, much work typically remains. The effects of methylation have been characterized at only a tiny portion of the human genome’s roughly 28 million CpGs; many CpGs are not obviously associated with genes; and even statistically robust signals often represent only small percentage changes in methylation.
In 2011, Horvath was asked to prob
