Background: Adverse Childhood Experiences (ACEs), which include traumatic injury, are
associated with poor health outcomes in later life, yet the biological mechanisms mediating this association
are unknown. Neurocircuitry, immune system and hormone regulation differ from normal in
adults reporting ACEs. These systems could be affected by epigenetic changes, including methylation
of cytosine (5mC) in genomic DNA, activated by ACEs. Since 5mC levels influence gene expression
and can be long lasting, altered 5mC status at specific sites or throughout the genome is hypothesized
to influence mental and physical outcomes after ACE(s). Human and animal studies support this, with
animal models allowing experiments for attributing causality. Here we provide a lengthy introduction
and background on 5mC and the impact of early life adversity.
Objective: Next we address the issue of a mixture of cell types in saliva, the most accessible biospecimen
for 5mC analysis. Typical human bio-specimens for 5mC analysis include saliva or buccal
swabs, whole blood or types of blood cells, tumors and post-mortem brain. In children saliva is the
most accessible bio-specimen, but contains a mixture of keratinocytes and white blood cells, as do
buccal swabs. Even in saliva from the same individual at different time points, cell composition may
differ widely. Similar issues affect analysis in blood, where nucleated cells represent a wide array of
white blood cell types. Unless variations in ratios of these cells between each sample are included in
the analysis, results can be unreliable.
Methods: Several different biochemical assays are available to test for site-specific methylation levels genome-
wide, each producing different information, with high-density arrays being the easiest to use, and bisulfite
whole genome sequencing the most comprehensive. We compare results from different assays and
use high-throughput computational processing to deconvolve cell composition in saliva samples.
Results: Here we present examples demonsrating the critical importance of determining the relative contribution
of blood cells versus keratinocytes to the 5mC profile found in saliva. We further describe a
strategy to perform a reference-based computational correction for cell composition, and therefore to
identify differential methylation patterns due to experience, or for the diagnosis of phenotypes that correlate
between traits, such as hormone levels, trauma status and various mental health outcomes.
Conclusion: Specific sites that respond to adversity with altered methylation levels in either blood
cells, keratinocytes or both can be identified by this rigorous approach, which will then be used as diagnostic
biomarkers and therapeutic targets.