‘Cheeky’ new epigenetic clock predicts mortality from simple test

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CheekAge uses easy-to-collect cheek cells to accurately predict mortality, providing a non-invasive alternative to blood-based methods.

Over the last decade, the field of epigenetic clocks has rapidly expanded as scientists seek to unravel the biological mechanisms behind aging. Based on changes in DNA methylation, which can be caused by environmental or genetic factors as well as disease and aging itself, epigenetic clocks offer insights into how fast a person is aging biologically – a pace that may differ significantly from chronological age. They can serve as important tools for predicting not only an individual’s biological age but also the likelihood of age-related diseases and mortality.

CheekAge, the latest innovation in this field, enhances the current landscape by using cheek cells instead of blood samples, offering a less invasive method of data collection while maintaining predictive accuracy [1].

Longevity.Technology: CheekAge represents a significant addition to epigenetic research; it addresses several limitations posed by earlier clocks, which typically required blood samples – an approach both time-consuming and often stressful for individuals. This new method, which relies on methylation data from cheek cells, brings the possibility of a simpler, yet highly effective, measure of biological aging to a broader population. And being able to harvest more data is, of course, a Good Thing – having access to more data is highly beneficial in scientific research, as it allows for greater accuracy, validation and refinement of findings, leading to more robust and reliable conclusions.

In a recent study published in Frontiers in Aging, the research team, led by Dr Maxim Shokhirev from Tally Health, demonstrated that CheekAge could predict mortality with a level of accuracy that surpasses earlier models based on blood methylation data. The study examined the methylation data of over 1,500 men and women from the Lothian Birth Cohorts, a long-term Scottish research program, and found that CheekAge was significantly associated with all-cause mortality [1].

“Our results show that CheekAge is significantly associated with mortality in a longitudinal dataset and outcompetes first-generation clocks trained in datasets containing blood data,” said Shokhirev, who is the Head of Computational Biology and Data Science at Tally Health. The research highlights a crucial finding: the hazard ratio of all-cause mortality increased by 21% for every increase of one standard deviation in CheekAge [1]. This finding suggests that the clock is a powerful indicator of mortality risk in older adults.

One of the key advantages of CheekAge is its ability to capture mortality signals across tissues, not just from the cheek cells in which it was trained. “The fact that our epigenetic clock trained on cheek cells predicts mortality when measuring the methylome in blood cells suggests there are common mortality signals across tissues,” noted Shokhirev. This flexibility not only makes CheekAge a versatile tool but also emphasizes its potential for broader applications in aging research.

Epigenetic clocks work by analyzing the methylation patterns – chemical modifications to DNA – that accumulate with age. These patterns are influenced by a range of factors, including lifestyle, environment, and genetics. The ability to measure these changes offers a window into the biological processes of aging, providing an opportunity to predict health outcomes such as disease risk or lifespan. CheekAge takes this one step further by making the process easier for patients and researchers alike, using cells collected via a simple cheek swab rather than more invasive blood draws.

The study also explored the genes located near the most significant methylation sites associated with mortality. These genes offer clues into the biological pathways that could influence aging and lifespan. Among the candidates were PDZRN4, a potential tumor suppressor, and ALPK2, a gene that has shown connections to cancer and cardiovascular health in animal models. “It would be intriguing to determine if genes like ALPK2 impact lifespan or health in animal models,” said Dr Adiv Johnson, Head of Scientific Affairs and Education at Tally Health.

The implications of this study stretch beyond just predicting mortality. CheekAge could be adapted to predict other aging-related outcomes, such as the likelihood of developing chronic diseases or the length of one’s healthspan. According to Johnson: “Future studies are also needed to identify what other associations besides all-cause mortality can be captured with CheekAge.”

This flexibility highlights one of the most compelling aspects of CheekAge: its potential for future research. The ability to draw connections between specific genes, methylation patterns and age-related diseases could inform strategies for promoting healthier aging. In time, this clock could become a key tool for both clinicians and individuals looking to make informed decisions about their health and lifestyle as they age.

Moreover, the study’s findings reinforce the growing evidence that methylation patterns in different tissues – whether from blood, cheek cells, or other sources – may contain common signals related to mortality and health risks. As researchers continue to refine and expand these clocks, CheekAge may serve as a non-invasive, reliable alternative to blood-based methods for monitoring biological age and predicting health outcomes, both for individuals and as part of large-scale studies on human aging.