Accelerated DNA methylation age: Associations with PTSD and neural integrity
Introduction
Chronic psychological stress may accelerate cellular aging and lead to early onset of age-related disease, neurodegeneration, and pre-mature mortality (Epel, 2009, Epel et al., 2004, Lindqvist et al., 2015). Posttraumatic stress disorder (PTSD) has been identified as a chronic stress-related condition that may accelerate cellular aging, increasing risk for neuronal cell death via oxidative stress, inflammatory, and other pathophysiological pathways (Lohr et al., 2015, Miller and Sadeh, 2014, Moreno-Villanueva et al., 2013, Williamson et al., 2015). Repeated activation of the hypothalamic–pituitary–adrenal (HPA) axis system, chronic sleep deprivation, and other PTSD-related disturbances are hypothesized to increase reactive oxygen species and decrease the capacity of antioxidants to protect neurons from the toxic effects of oxidative stress (Miller and Sadeh, 2014). Chronic PTSD may also lead to glucocorticoid-mediated increases in peripheral and central nervous system inflammation, and dysregulated autonomic and metabolic processes (Epel, 2009, Lohr et al., 2015, Williamson et al., 2015) thereby degrading cellular integrity and ultimately leading to cell death.
Within the past two years, important advances have been made in the use of DNA methylation (DNAm) data to index chronological age. Hannum et al. (2013) developed a model of cellular age (DNAm age) based on methylation levels measured in whole blood at 71 DNA loci and found this metric of DNAm age to be highly correlated with chronological age (r = .96). The majority of the loci in this algorithm were located in or near genes important for the development of age-related disease, DNA damage and repair, and/or oxidative stress (Hannum et al., 2013). In the same year, Horvath (2013) independently developed a multi-tissue DNAm age algorithm using 353 loci and found this metric to also correlate highly with chronological age at r = .96. Despite these impressive associations, the biological mechanism(s) linking epigenetic variation to chronological age remain unclear.
Preliminary cross-sectional evidence suggests that exposure to pathogenic environmental factors may influence DNAm age, yielding higher estimates than would be expected based on chronological age. For example, Horvath et al. (2014) showed that obesity was associated with accelerated DNAm age in human liver tissue. Accelerated DNAm age relative to chronological age has also been linked to indices of disease, including cross-sectional associations with worse performance on measures of fluid intelligence, grip strength, and lung function (Marioni et al., 2015b). Likewise, a meta-analysis of over 4600 older-aged adults found that for every five year-increase in DNAm age relative to chronological age using the Hannum et al. (2013) and Horvath (2013) algorithms, there were 21% and 11% increases, respectively, in all-cause mortality (Marioni et al., 2015a).
To our knowledge, only one published study (Boks et al., 2015) has examined associations between trauma and/or PTSD and DNAm age. In that study of 96 male soldiers, trauma exposure was positively related to DNAm age per the Horvath (2013) algorithm, while self-reported PTSD symptoms unexpectedly predicted decreased DNAm age estimates over the course of approximately one year (Boks et al., 2015). However, chronological age was not included in this analysis so it remains unclear how these findings relate to discrepancies between DNAm age and chronological age. In this study, we aimed to address this limitation by examining the association between the cumulative lifetime burden of PTSD and DNAm age, controlling for chronological age.
We also tested the hypothesis that accelerated DNAm age is correlated with indices of neural integrity in regions known to degrade with normal aging. Gray matter volume and cortical thickness decrease globally with advancing age (Good et al., 2001, Resnick et al., 2003) with these effects most evident in prefrontal regions (Resnick et al., 2003, Salat et al., 2004, Salat et al., 2005b). Studies of white matter microstructural integrity (i.e., diffusion tensor imaging; DTI) have found the most consistent effects using measures of fractional anisotropy (FA) in the prefrontal cortex (Bennett et al., 2010, Burgmans et al., 2010, Pfefferbaum et al., 2000, Salat et al., 2005a) and the genu of the corpus callosum (Bennett et al., 2010, Burgmans et al., 2010, Kochunov et al., 2012, Pfefferbaum et al., 2000, Salat et al., 2005a, Voineskos et al., 2012, Zahr et al., 2009), which connects the right and left prefrontal cortices (Hofer and Frahm, 2006). These regions are involved in higher-order executive functions, such as working memory and response inhibition (Zahr et al., 2009), which also show age-related declines (Park et al., 2002). Based on this, a final aim of this study was to examine possible links between accelerated DNAm age and performance on executive function tasks that depend on these regions of interest (ROIs).
We hypothesized that lifetime PTSD severity (as indexed by a latent variable capturing PTSD severity across three time intervals), would be associated with accelerated DNAm age estimates relative to chronological age. We also expected that advanced DNAm age would be negatively related to microstructural integrity (FA values) in areas of the brain previously linked to age-related degeneration (the frontal cortex and genu) and to performance on executive function tasks mediated by our ROIs.
Section snippets
Participants
Horvath (2013) and Hannum et al. (2013) DNAm age estimates were available for 289 veterans of the conflicts in Iraq and Afghanistan assessed at the Translational Research Center for TBI and Stress Disorders, a VA RR&D Traumatic Brain Injury Center of Excellence at VA Boston Healthcare System. Exclusion criteria included history of seizures (unrelated to head injury), neurological illness, current bipolar or psychotic disorder, severe depression or anxiety, active homicidal and/or suicidal
DNAm age associations with chronological age
The Hannum DNAm age estimates were highly correlated with self-reported chronological age (r = .88, p < .001) and the Horvath DNAm age algorithm yielded a virtually identical estimate (r = .87, p < .001). The two DNAm age estimates correlated with each other at r = .88, p < .001, but the residual variables (with chronological age regressed out) were only moderately associated with each other (r = .49, p < .001). Neither the Hannum nor Horvath DNAm age residuals were associated with chronological age (rs = .002
Discussion
Advancing the understanding of mechanisms linking PTSD to pre-mature morbidity and mortality is important given the prevalence of chronic PTSD and the high individual and societal costs associated with it (Bruffaerts et al., 2012). Emerging evidence suggests that PTSD may be associated with accelerated cellular aging and, at least partially through this, linked to various adverse health outcomes (Lohr et al., 2015, Miller and Sadeh, 2014) but, until recently, research on accelerated aging has
Disclosures
Authors Wolf, Logue, Hayes, Sadeh, Schichman, Stone, Salat, Milberg, McGlinchey, and Miller reported no biomedical financial interests or potential conflicts of interest.
Contributions
Authors Wolf, Logue, Hayes, Sadeh, and Miller contributed to the conception and design of the study. Authors Wolf, Logue, Schichman, Stone, Salat, Milberg, McGlinchey, and Miller contributed to the acquisition of data and the interpretation of data. Authors Wolf, Logue, and Miller contributed to the data analyses. All authors contributed to the drafting and/or critical revision of this manuscript for important intellectual content. All authors provided final approval of the submitted manuscript.
Acknowledgements
This research was supported in part by NIMH grant R21MH102834 “Neuroimaging Genetics of PTSD” and the Translational Research Center for TBI and Stress Disorders (TRACTS), a VA Rehabilitation Research and Development Traumatic Brain Injury Center of Excellence (B9254-C), and the Cooperative Studies Program, Department of Veterans Affairs. This research is the result of work supported with resources and the use of facilities at the Pharmacogenomics Analysis Laboratory, Research and Development
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