Some people like to say that age is just a number. Many scientists increasingly agree, arguing that DNA, protein, or other molecular measurements can tell a truer story about a person’s “biological” age than what’s on their birth certificate. Hundreds of so-called aging clocks developed in recent years reflect this idea, and clinical trials have started to use them to assess patients’ responses to putative antiaging treatments. Numerous wellness clinics now claim they can—for a steep price—deduce a person’s actual age, and multiple companies offer biological age testing for worried patients—and even for their dogs.
But scientists don’t agree on which aging clocks work best or how to verify their results. “We need to systematically evaluate them,” says bioinformatician Mahdi Moqri of Harvard Medical School. That’s the motivation for an unprecedented contest, funded by nonprofits and philanthropies and run by an organization called the Biomarkers of Aging Consortium, that is pitting hundreds of the clocks against one another for scientific honors—and some $300,000 in prize money.
Drawing on anonymized data and health information for 500 people, the competitors are vying to produce the most accurate predictions of chronological age, age at death, and “health span”—the time until onset of multiple age-related diseases. “The competition is put up or shut up” for clockmakers, says biogerontologist Steve Horvath of the cell rejuvenation firm Altos Labs, who developed a DNA-based aging assay that kick-started the field more than a decade ago.
This summer, the consortium released the results of the challenge’s first round, in which competitors had to estimate subjects’ chronological ages. Thirty-seven teams submitted more than 550 clocks; the competitors included veteran clockmakers, a company already marketing a test, and rank newcomers. “I thought of it more as a fun project,” says Jakob Träuble, a biotechnology Ph.D. student at the University of Cambridge. He and Stefan Jokiel, a physics master’s degree student at the Ludwig Maximilian University of Munich, came in third, winning a share of the $30,000 purse.
On 1 November, the consortium will announce the results of the $70,000 second round. It entails predicting the ages at death for the 15% to 20% of the subjects who have already died. Contestants in a final round, scheduled to wrap up next year, will face an even tougher challenge: predicting when people in the data set developed multiple age-related diseases.
More accurate, validated clocks could be a boon to clinical trials of potential antiaging treatments. And they could aid a much bigger contest: the XPRIZE Healthspan competition, launched last year, which will parcel out $101 million among scientists who by 2030 come up with strategies that can reverse age-related deterioration in muscles, the brain, and the immune system.
Over the years researchers have hailed a variety of candidate aging measures. Some use just a single marker, such as the length of telomeres, protective caps at tips of chromosomes. These individual measurements don’t capture the complexity of aging, says life scientist Vadim Gladyshev of Harvard Medical School, a member of the Biomarkers of Aging Consortium. More promising, he says, are clocks that aggregate data, such as the abundances of different proteins in the blood or the patterns of chemical changes to DNA called methylation.
Methylation clocks have raced ahead. Roughly 30 million locations, known as CpG sites, in the human genome can be methylated. The modifications often turn genes on or off, and their distribution across the genome changes as people grow older.
Horvath, who is also part of the consortium, began to use DNA methylation as an aging clock by chance. In 2010, he and his gay brother gave saliva samples for a study that aimed to identify markers of sexual orientation in identical twins. Horvath also lent the study his statistical expertise and became a co-author. The researchers gauged the methylation status of more than 27,000 sites, but the data revealed nothing about sexual orientation. However, Horvath and colleagues realized that measuring methylation for just 88 CpG sites predicted the participants’ ages to within about 5 years, a result they published in 2011.
In 2013, he showed that by expanding the methylation survey to 353 CpG sites in DNA from a variety of tissues, including blood, he could estimate age more precisely, thus launching the eponymous Horvath clock. In 2019, a team led by Horvath and computational scientist Ake Lu, now also at Altos Labs, described an even more powerful clock. The aptly named GrimAge can make forecasts of when people will develop heart disease or cancer, or die.
Researchers have debuted a slew of other methylation-based clocks, including the Hannum clock, PhenoAge, DunedinPACE, and DNAm Age, that can predict chronological age, mortality, and aging rate. “The field has exploded,” Gladyshev says.
Most methylation clocks rely on the variety of artificial intelligence (AI) known as machine learning, which can tease out patterns in huge data sets. To predict chronological age, researchers first train the algorithm by feeding it methylation data from people whose ages are known. Once the clock has learned which methylation sites correlate with age, it can turn an individual’s methylation pattern into an estimate of their biological age—an indication of whether they are aging faster or slower than their peers. By training the AI on data about health and mortality, researchers can also predict time to death or onset of disease.
More: https://www.science.org/content/article/scientific-showdown-seeks-biological-clock-best-tracks-aging
