The analysis of epigenetic changes—modifications that alter gene function without altering DNA sequence—could provide a more detailed description of how the human body ages than scientists have been able to devise in the past. New research has unveiled the potential for developing a “clock” that can be designed to successfully assign relative time to certain body tissues.
“Numerous other epigenetic changes in nuclear architecture and gene expression have been associated with aging,” wrote Dr. Philipp Oberdoerffer, investigator at the Center for Cancer Research, and Dr. David A. Sinclair from Harvard Medical School in Nature Reviews Molecular Cell Biology.
One of the most common of these epigenetic changes is DNA methylation, according to the Genetic Home Reference. DNA methylation is the addition of methyl groups to the nucleobases of DNA. DNA has four nucleobases (adenine, guanine, cytosine, and thymine), and methyl groups consist of three hydrogen atoms bonded to a single carbon (-CH3). When a methyl group bonds to a nucleobase, it can essentially turn the associated genes off, ending their functions.
Steve Horvath, Ph.D, from University of California, Los Angeles, focused on this type of epigenetic control. In an article in Genome Biology, Horvath stated that he was able to devise a “novel epigenetic clock” that could accurately tell the age of a host of tissues.
According to Genetics Home Reference, epigenetic changes can determine whether genes remain active or inactive. For example, when referring to methylation, the addition of those methyl groups to DNA can turn genes off. Ultimately, when errors occur in the epigenetic controls, the fate of genes can be drastically altered, leading to genetic disorders like cancers, Alzheimer’s disease, and so on.
Horvath analyzed a collection of cancerous and non-cancerous samples from Illumina DNA methylation datasets to device this epigenetic clock. Of the 8,000 samples he analyzed, most of them were non-cancerous, but in total these samples represented 51 human tissues and cell types, including blood cells, brain cells, and breast tissue.
Whereas some recent studies have focused only on a specific tissue types to describe DNA methylation age predictors, Horvath’s analysis of an unprecedented number of samples allowed him to develop a multi-tissue age predictor with incredible accuracy.
“Its astonishing accuracy across most tissues and cell types justifies its designation as a multi-stage age predictor,” wrote Horvath.
This age prediction is what Horvath refers to as DNA methylation age or, for short, DNAm age. For example, embryonic stem cells would get a DNAm age of zero, while another tissue would get a higher or lower age that corresponds to the number of cell passages it has gone through.
However, some of the tissues he tested did provide readings with high error; breast tissue, uterine endometrium, dermal fibroblasts, skeletal muscle tissue, and heart tissue samples all proved problematic. Horvath speculated about some of the reasons for such a high error, mentioning that some of them might have to do with hormonal changes or the recruitment of stem cells to aid in the formation of the heart’s cardiac muscle; this recruitment probably provided DNAm age readings of lower value, Horvath explained.
While conducting his research Horvath found out that the multi-tissue age predictor (or epigenetic clock) also works on chimpanzees’ tissues. According to Horvath, this would open up the possibility of identifying “model organisms for rejuvenating interventions.”
Horvath stated the DNAm age can have beneficial effects in the studies of “human development, aging, and cancer.” For instance, some forms of cancer affecting tissues exhibit high age acceleration, so his epigenetic clock would help compare the age of different tissues from a patient and, based on the abnormal discrepancies in age, determine whether further analysis is required.
Additionally, there is the potential that easily accessible tissues like skin or fluids like saliva and blood could be used as markers for inaccessible tissues like the brain, kidney, or liver.
Although his multi-tissue age predictor has given accurate DNAm age values across a variety of healthy or cancerous tissues, Horvath warns against overstating the usefulness of his findings.
“Future research will need to clarify whether DNAm age is only a marker of aging or relates to an effector of aging,” Horvath said.
Despite this, Horvath believes that his epigenetic clock will be a valuable addition to the field, because “DNAm age is arguably a promising marker for studying human development, aging, and cancer.”