(Credit: Andrey_Popov/Shutterstock)

NEW YORK — A quick swab of your cheek might one day reveal how long you have left to live. Researchers have discovered that a DNA test originally designed to measure biological aging from cells inside the cheek can accurately predict mortality risk, even when applied to blood samples. The findings suggest that common biological markers of aging exist across different tissues in the body, potentially opening new avenues for assessing health risks and developing anti-aging interventions.

The study centers on a tool called CheekAge, a next-generation “epigenetic clock” developed earlier this year. Our genes contain the instructions for building and maintaining our bodies, but how these genes are read and expressed can change over time. One way this happens is through a process called DNA methylation, where small chemical tags attach to our DNA. These tags act like switches, turning genes on or off.

Most previous epigenetic clocks relied on blood samples, making them less practical for widespread use. CheekAge, as its name implies, was designed to work with easily collected cheek cells. What makes this new study particularly intriguing is that CheekAge proved effective at predicting mortality risk even when applied to blood sample data.

To test this, they turned to a unique dataset from Scotland called the Lothian Birth Cohorts. This long-running study has been following two groups of people born in 1921 and 1936, collecting detailed health information and biological samples over many years.

Using blood samples from 1,513 participants (712 men and 801 women) between the ages of 67 and 90, the team applied their CheekAge algorithm. Even though CheekAge was designed for cheek samples and nearly half of its DNA markers weren’t present in the blood data, it still showed a strong ability to predict mortality risk.

Specifically, for each standard deviation increase in the difference between a person’s CheekAge and their actual age, their risk of death increased by 21%. To put this in perspective, the researchers divided participants into three groups based on their CheekAge results. The group with the “oldest” biological age reached 50% mortality about 7.8 years earlier than the group with the “youngest” biological age.

3D rendering capturing the double helix structure of DNA against a blue backdrop, highlighting the intricate beauty of life's genetic code
3D rendering capturing the double helix structure of DNA. Even though CheekAge was designed for cheek samples and nearly half of its DNA markers weren’t present in blood data, it still showed a strong ability to predict mortality risk. (Credit: Unsplash/THAVIS 3D)

What’s particularly impressive is that CheekAge performed better at predicting mortality than several other established epigenetic clocks. It even rivaled a specialized clock called DNAm PhenoAge, which was specifically designed to predict mortality using blood samples.

“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,” explains Dr. Maxim Shokhirev, the study’s first author and Head of Computational Biology and Data Science at Tally Health, in a statement. “This implies that a simple, non-invasive cheek swab can be a valuable alternative for studying and tracking the biology of aging.”

The study, published in the journal Frontiers in Aging, also identified specific DNA markers that seemed especially important for mortality prediction. One standout was a marker associated with a gene called ALPK2. When this marker was removed from the analysis, the ability to predict mortality dropped significantly. Interestingly, ALPK2 has been linked to heart development in animal studies and may play a role in certain cancers.

“It would be intriguing to determine if genes like ALPK2 impact lifespan or health in animal models. Future studies are also needed to identify what other associations besides all-cause mortality can be captured with CheekAge,” says Dr. Adiv Johnson, the study’s last author and Head of Scientific Affairs and Education at Tally Health. “For example, other possible associations might include the incidence of various age-related diseases or the duration of ‘healthspan’, the period of healthy life free of age-related chronic disease and disability.”

Other important markers were connected to genes involved in bone health, metabolism, and cellular processes related to aging. This suggests that CheekAge is capturing a variety of biological factors that contribute to overall health and longevity.

While more research is necessary to fully understand how CheekAge works and to confirm its predictive power in larger, more diverse populations, this study opens up exciting possibilities. Imagine being able to assess your health risks with a simple cheek swab, potentially allowing for earlier interventions and personalized health strategies.

Of course, it’s important to remember that these tools provide probabilities, not certainties. A high CheekAge doesn’t mean you’re destined for an early grave, just as a low CheekAge doesn’t guarantee a long life. However, as our understanding of the aging process grows, tools like CheekAge could become valuable assets in our quest for healthier, longer lives.

Paper Summary

Methodology

The researchers used DNA methylation data from blood samples collected as part of the Lothian Birth Cohorts study. They applied their CheekAge algorithm, which was originally designed for cheek swab samples, to this blood data. Despite missing some DNA markers, the algorithm still worked effectively. They then used statistical models to analyze how well CheekAge predicted mortality risk, taking into account factors like age, sex, and cell type composition in the blood samples.

Key Results

CheekAge showed a significant association with mortality risk. For each standard deviation increase in the difference between CheekAge and chronological age, the risk of death increased by 21%. The researchers also identified specific DNA markers that were particularly important for this prediction, with markers related to genes like ALPK2, B4GALNT3, and SAT1 standing out.

Study Limitations

The study used blood samples instead of cheek swabs, which CheekAge was originally designed for. The blood data also lacked about half of the DNA markers used in the full CheekAge model. The study population was limited to older adults from Scotland, so the results may not apply equally to other age groups or populations. Additionally, while CheekAge predicts mortality risk, it doesn’t explain the underlying causes of this risk.

Discussion & Takeaways

This study suggests that epigenetic changes measurable in easily accessible tissues like cheek cells could provide valuable information about overall health and mortality risk. The performance of CheekAge, even when applied to blood samples with missing data, indicates it’s capturing fundamental aging processes. The identification of specific DNA markers associated with mortality risk opens up new avenues for understanding the biology of aging and age-related diseases.

Funding & Disclosures

The study received funding from Tally Health, a company that some of the authors are affiliated with. It also received support from various research councils and charities, including the Wellcome Trust, the Biotechnology and Biological Sciences Research Council, the Economic and Social Research Council, and Age UK. These connections between the researchers and a company with potential commercial interests in the findings should be considered when interpreting the results.