One of the most remarkable findings in aging over the past decade is that it’s possible to track the rate of aging based on stereotyped DNA methylation changes across a diverse set of tissues. These are known as epigenetic clocks.
But as anyone in the gene expression field knows, changes in the levels of epigenetic markers between groups (like young vs older) is confounded by cell type proportion differences between those groups.
This cell type proportion confound makes it harder to tell whether the changes in DNA methylation are truly a marker of aging or whether they are due to cell type proportion variations that may be already known to occur during aging, like naive T cell depletion due to thymus atrophy.
Single cell epigenetics has the potential to address this problem. By measuring DNA methylation patterns within individual cells, you can compare the epigenetic patterns within the same cell type between groups, and don’t have to worry (as much) about overall changes in cell type proportion .
I was interested to see whether anyone has used single cell epigenetic profiling, which was just come out within the past couple of years, to measure whether changes in epigenetic marks can be seen within single cells during aging.
First, let’s back up a second and talk about epigenetics. Two of the major factors that defines a cell’s epigenome are its DNA methylation patterns and its histone post-translational modifications.
DNA methylation has been studied a bit in single cells. One study looked at DNA methylation in hepatocytes and didn’t find many differences between old and young cells.
However, as a recent review points out, single cell DNA methylation data are currently limited because of sample quantity within each cell, and can’t easily compare methylation patterns between different cells in the same region of the genome.
On the histone modification front, I found a nice article by Cheung et al 2018, who measured histone post-translational modifications (PTMs) in single cells derived from blood samples. They found that in aging, there was increased variability histone PTMs both between individuals and between cells.
So, in summary, here are some future directions for this research field that it would be prudent to keep an eye one:
- How much of the changes in DNA methylation seen in aging are due to changes in relative cell type proportions as opposed to changes within single cells? If we assume that age-related changes in DNA methylation will be similar to age-related changes in histone PTMs, then Cheung et al.’s results suggest that the changes in DNA methylation are probably due to true changes within single cells during aging.
- Is there a way to slow or reverse age-related changes in DNA methylation or histone PTMs, perhaps targeted to stem cell populations? It’s not clear that this can be done in a practical way, especially if age-related changes are driven primarily by an increase in variability/entropy.
- If it is possible to slow or reverse DNA methylation or histone PTMs, would that help to slow aging and thus “square the curve” of age-related disease? Aging might be too multifactorial for a single intervention like this to make a major difference, though.
: I add “as much” here because differential expression analysis in single cell data is far from straightforward, and e.g. has the potential to be biased by subtle differences in the distribution of sub-cell type spectrum between groups.