We don’t all age at the same rate. But while some supercentenarians may age exceptionally slowly because they hit the genetic jackpot, many of them Behavioral and lifestyle factors accelerate agingincluding stress, lack of sleep, poor diet, smoking and alcohol.
Since these environmental effects are imprinted in our genome in the form of epigenetic marks, it is possible to quantify molecular aging characterizing the epigenome in prognostic genomic sites, according to a new article in “Frontiers in Aging.”
Over the past decade, scientists have developed several “epigenetic clocks,” calibrated based on the chronological age and various lifestyle factors of large numbers of people.. Most of them have focused on DNA methylation in blood cells, making sample collection tedious and stressful for the patient.
But earlier this year, American scientists developed a second-generation watch, called CheekAge, which It is based on methylation data in easily collected cells from inside the cheeks. Today, the team demonstrated for the first time that CheekAge can accurately predict mortality riskeven if epigenetic data from another tissue is used as input.
“We also show that specific methylation sites are particularly important for this correlation, revealing potential links between specific genes and processes and human mortality captured by our clock,” said Maxim Shokhirev, first author of the study and director of Computational Biology and Science. from Tally Health in New York (United States). CheekAge was developed or “trained” by correlating the methylation fraction across approximately 200,000 sites with an overall health and lifestyle score, which reflects presumed differences in physiological aging.
In the present study, Shokhirev and colleagues used the statistical programming to see how much predicted all-cause mortality in 1,513 women and men, born in 1921 and 1936 and followed throughout their lives by the Lothian Birth Cohorts (LBC) program at the University of Edinburgh (UK). One goal of the LBC was to link differences in cognitive aging to lifestyle and psychosocial factors as well as biomedical, genetic, epigenetic, and brain imaging data.
Every three years, the volunteers’ methylome was measured in their blood cells at around 450,000 DNA methylation sites. The last available methylation time point was used with the mortality status to calculate CheekAge and its association with mortality risk. Mortality data were obtained from the Scottish National Health Service Central Register.
The results show that CheekAge is significantly associated with mortality in a longitudinal dataset and outperforms first-generation clocks trained on datasets containing blood data, according to the authors. Specifically, for each standard deviation increase in CheekAge, the hazard ratio for all-cause mortality increased by 21%. This means that CheekAge is strongly associated with mortality risk in the elderly.
“The fact that our epigenetic clock driven in cheek cells predicting mortality by measuring the methylome in blood cells suggests that there are common mortality signals in all tissues,” says Shokhirev. “This implies that a simple non-invasive mouth swab can be an effective way to predict mortality by measuring the methylome in blood cells. valuable alternative for studying and monitoring the biology of aging.
The researchers looked in more detail at the methylation sites most strongly associated with mortality. Genes located around or near these sites are potential candidates for affect life expectancy or the risk of age-related diseases. For example, the PDZRN4 gene, a possible tumor suppressor, and ALPK2, a gene implicated in cancer and heart health in animal models. Other notable genes had previously been implicated in the development of cancer, osteoporosis, inflammation and metabolic syndrome.
