Correcting Brain Tissue Heterogeneity with DNA Methylation

A few weeks ago, we highlighted some great work that has been very useful in helping correct for heterogeneous cell populations in blood. Now, we’ve just got wind of a clever new bioinformatics tool to correct for heterogeneity in the brain.

Researchers have studied DNA methylation in brain tissue to see if there’s an association between that modification and psychiatric disease for some time now. But the results haven’t been all that eye-popping.


A hard-working crew from Johns Hopkins and Harvard explain that those studies used brain preparations that contained bulk brain, which includes a buffet of different types of cells, many of which exhibit different ratios in the various parts of the brain.  This can really put a damper on DNA methylation analyses since the methylation marks can vary dramatically in different cell types, regardless of whether someone has a disease. And in some psychiatric diseases, certain brain regions containing various cell types can become larger or smaller, skewing DNA methylation results.

The scientists figured if they could correct for that heterogeneity, they might find some real, honest-to-goodness DNA methylation differences that they could pin to disease. Here’s a little of what they did:

  • Identified DNA methylation markers called “cell epigenotype specific” (CETS) markers. They distinguish neuronal from non-neuronal cells.
  • Developed a model that used the top CETS markers as surrogates to quantify neuronal and non-neuronal cells.
  • Developed an algorithm that can turn DNA methylation profiles obtained from heterogeneous brain tissue preps into useful neuronal and non-neuronal profiles.

They used these tools to study DNA methylation patterns in different brain regions, in subjects with depression, and in brains of people at different ages.

An R package called “CETS” is publicly available and will work with data from a variety of platforms.

You can read the open access article  at Landes Biosciences’ Epigenetics, March 2013.