As a whole people do not age at the same rate, nor do we die at the same ages. Some people die very young and others hit the genetic lottery and age exceptionally slowly to become supercentenarians seemingly defying mortality with the help of healthy lifestyle factors. On the other hand, some people live life day to day without caring about factors that are known to speed up aging such as stress, poor nutrition, smoking, alcohol, and bad sleep hygiene.
Environmental effects get imprinted on our genomes in the form of epigenetic markers that make it possible to quantify molecular aging by characterizing the epigenome at prognostic sites. Scientists have developed several epigenetic clocks against chronological age and various lifestyle factors, most focused on DNA methylation in blood cells. Recently scientists developed a second-generation epigenetic clock called CheekAge which is based on methylation data that is collected from inside our mouth on the cheeks.
Predicting Mortality with CheekAge
The paper published in the Frontiers in Aging shows for the first time that CheekAge is able to accurately predict the risk of mortality, even if epigenetic data from another tissue is used as input. The technology was trained by correlating the fraction of methylation at close to 200,000 sites with an overall score for lifestyle and health reflecting presumed differences in physiological aging.
“We also demonstrate that specific methylation sites are especially important for this correlation, revealing potential links between specific genes and processes and human mortality captured by our clock,” said Dr. Maxim Shokhirev, the study’s first author and Head of Computational Biology and Data Science at Tally Health, New York.
Training the Clock
Statistical programming was used to see how CheekAge predicted mortality from any cause among 1,513 people born between 1921 and 1936 who were followed throughout life by the Lothian Birth Cohorts (LBC) program of the University of Edinburgh. Every 3 years, the participants had their methylome in blood cells measured at approximately 450,000 DNA methylation sites. The scientists utilized the last available methylation time point along with the mortality status (obtained from the Scottish National Health Service Central Register) to calculate CheekAge and its association with mortality risk.
The Clock is Ticking
According to scientists from the University of Edinburgh and the New York-based company Tally Health, for every increase by a single standard deviation in CheekAge, the hazard ratio of all-cause mortality increased by 21%, which means that CheekAge is strongly associated with mortality risk in older adults.
“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,” concluded the authors.
“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,” said Shokhirev. “This implies that a simple, non-invasive cheek swab can be a valuable alternative for studying and tracking the biology of aging.”
Other Cheeky Discoveries
When looking at those methylation sites that were most strongly associated with mortality in greater detail genes located around these sites are potential candidates for impacting lifespan or the risk of age-related disease.
For example, the gene PDZRN4, a possible tumor suppressor, and ALPK2, a gene implicated in cancer and heart health in animal models. Other genes that stood out had previously been implicated in the development of cancer, osteoporosis, inflammation, and metabolic syndrome.
“It would be intriguing to determine if genes like ALPK2 impact lifespan or health in animal models,” said Dr Adiv Johnson, the study’s last author and the Head of Scientific Affairs and Education at Tally Health.
“Future studies are also needed to identify what other associations besides all-cause mortality can be captured with CheekAge. 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.”
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