Summary: Researchers have developed a second-generation epigenetic clock called CheekAge that uses cheek cell samples to accurately predict mortality risk. Unlike previous clocks based on blood samples, CheekAge is non-invasive and captures methylation patterns associated with aging and longevity.
In a recent study of more than 1,500 people, CheekAge showed that the risk of death increased by 21% for every standard deviation increase in the clock’s age prediction. This new tool provides an easy and effective way to monitor aging and may help track age-related diseases.
Important facts:
CheekAge uses cheek cells to predict mortality risk with a 21% increased hazard ratio. This provides a non-invasive alternative to blood-based epigenetic clocks. CheekAge identifies important genes associated with longevity and age-related diseases.
Source: Frontier
We don’t all age at the same rate. But while some supercentenarians may age very slowly because they hit the genetics jackpot, a variety of behavioral and lifestyle factors can slow down aging, including stress, lack of sleep, malnutrition, smoking, and alcohol. It is known to accelerate
Because such environmental influences are imprinted on our genome in the form of epigenetic marks, it is possible to quantify molecular aging by characterizing the epigenome at prognostic genomic sites.
Over the past decade, scientists have developed several such “epigenetic clocks” that are adjusted for the chronological age and various lifestyle factors of large numbers of people.
Most of these focused on DNA methylation in blood cells, making sample collection cumbersome and stressful for patients. But earlier this year, scientists in the United States developed a second-generation clock called CheekAge, based on methylation data from easily collected cells from the inside of the cheek.
Now, in Frontiers in Aging, the research team shows for the first time that CheekAge can accurately predict mortality risk, even when epigenetic data from another tissue is used as input.
“We also demonstrate that specific methylation sites are particularly important for this correlation, revealing potential links between specific genes and processes and human mortality captured by our clocks. ” said Dr. Maxim Shokhirev, lead author of the study and head of computational biology and data science. A company called Tully Health in New York.
CheekAge was developed or “trained” by correlating the percentage of methylation at approximately 200,000 sites with an overall health and lifestyle score, reflecting estimated differences in physiological aging.
The body clock is ticking
In the current study, Shokhirev et al. used statistical programming to estimate all-cause mortality in 1,513 men and women born in 1921 and 1936 and followed throughout their lives by the Lothian Birth Cohort (LBC) program at the University of Edinburgh. We investigated how accurately the prediction was made. .
One of the goals 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 had their blood cell methylomes measured at approximately 450,000 DNA methylation sites.
The last available methylation time point was used along with mortality status to calculate the association between CheekAge and mortality risk. Data on mortality were obtained from the Scottish National Health Service Central Register.
“[Our results]show that CheekAge is significantly associated with mortality in longitudinal datasets and outperforms first-generation clocks trained on datasets containing blood data,” the authors wrote. concluded.
Specifically, for every one standard deviation increase in CheekAge, the hazard ratio for all-cause mortality increased by 21%. This means that CheekAge is strongly associated with the risk of death in older adults.
“The fact that our epigenetic clock trained in cheek cells predicts mortality when measuring the methylome within blood cells suggests that there is a common mortality signal across tissues.” said Shokhirev.
“This means that a simple, non-invasive cheek swab could be a valuable alternative for studying and tracking the biology of aging.”
strongest predictor
The researchers looked more closely at the methylation sites most strongly associated with mortality. Genes located around or near these sites are candidates that may influence lifespan and risk of age-related diseases.
Examples include the gene PDZRN4, which is a potential tumor suppressor, and ALPK2, a gene implicated in cancer and heart health in animal models. Other notable genes have previously been implicated in the development of cancer, osteoporosis, inflammation, and metabolic syndrome.
“It will be interesting to determine whether genes like ALPK2 influence longevity and health in animal models,” said the study’s final author and director of scientific affairs and education at Tully Health. said one Dr. Adib Johnson.
“Future research is also needed to determine what associations there are with CheekAge beyond all-cause mortality.
“For example, other associations may include the incidence of various age-related diseases and the length of ‘healthy life expectancy’, which is the period of healthy life free from age-related chronic diseases and disabilities. Masu.”
About this epigenetics and aging research news
Author: Misha Dijkstra
Source: Frontier
Contact: Mischa Dijkstra – Frontiers
Image: Image credited to Neuroscience News
Original research: Open access.
“CheekAge, the next generation epigenetic oral clock, predicts mortality in human blood.” (Maxim Shokhirev et al) Frontiers of Aging
abstract
CheekAge, the next generation epigenetic oral clock, predicts mortality in human blood
While early first-generation epigenetic aging clocks were trained to estimate chronological age as accurately as possible, more recent next-generation clocks have been trained to estimate chronological age as accurately as possible, while more recent next-generation clocks have been trained to estimate chronological age as accurately as possible. Contains DNA methylation information.
We recently created a non-invasive, next-generation epigenetic clock trained using Infinium MethylationEPIC data from over 8,000 diverse adult oral samples.
Although the clock was correlated with a variety of health, lifestyle, and disease factors, its ability to capture mortality rates was not evaluated.
To address this gap, we applied CheekAge to the 1921 and 1936 longitudinal Lothian birth cohorts. Despite missing nearly half of the CpG inputs, CheekAge was significantly associated with mortality in this longitudinal blood dataset.
Specifically, a 1 standard deviation change corresponds to a hazard ratio (HR) of 1.21 (FDR q = 1.66e-6). CheekAge outperformed all first-generation clocks tested and showed comparable HR (HR = 1.23, q = 2.45e-9) to the blood-trained next-generation DNAm PhenoAge clock.
To better understand the relative importance of each CheekAge input in blood, we repeatedly removed each clock CpG and recalculated the overall mortality association.
The most significant effect was due to omitting CpG cg14386193, which is annotated in the gene ALPK2. Excluding this DNA methylation site increased the FDR value nearly 3-fold (4.92e-06).
Furthermore, to better understand the associated biology, we performed enrichment analysis of the top annotated CpGs that influence mortality.
In summary, we provide critical validation of CheekAge and highlight novel CpGs underlying newly identified mortality associations.