ABSTRACT Emerging knowledge suggests that post-traumatic stress disorder (PTSD) pathophysiology is linked to the patients’ epigenetic changes, but comprehensive studies examining genome-wide

methylation have not been performed. In this study, we examined genome-wide DNA methylation in peripheral whole blood in combat veterans with and without PTSD to ascertain differentially

methylated probes. Discovery was initially made in a training sample comprising 48 male Operation Enduring Freedom (OEF)/Operation Iraqi Freedom (OIF) veterans with PTSD and 51

age/ethnicity/gender-matched combat-exposed PTSD-negative controls. Agilent whole-genome array detected ~5600 differentially methylated CpG islands (CpGI) annotated to ~2800 differently

used to confirm the methylation status of 20 DMGs shown to be highly perturbed in the training set. To improve the statistical power and mitigate the assay bias and batch effects, a union

set combining both training and test set was assayed using a different platform from Illumina. The pathways curated from this analysis confirmed 65% of the pool of pathways mined from

training and test sets. The results highlight the importance of assay methodology and use of independent samples for discovery and validation of differentially methylated genes mined from

whole blood. Nonetheless, the current study demonstrates that several important epigenetically altered networks may distinguish combat-exposed veterans with and without PTSD. SIMILAR CONTENT

BEING VIEWED BY OTHERS EPIGENETIC BIOTYPES OF POST-TRAUMATIC STRESS DISORDER IN WAR-ZONE EXPOSED VETERAN AND ACTIVE DUTY MALES Article Open access 18 December 2020 EPIGENOME-WIDE

ASSOCIATION STUDY OF POSTTRAUMATIC STRESS DISORDER IDENTIFIES NOVEL LOCI IN U.S. MILITARY VETERANS Article Open access 17 February 2022 EPIGENOME-WIDE META-ANALYSIS OF PTSD SYMPTOM SEVERITY

IN THREE MILITARY COHORTS IMPLICATES DNA METHYLATION CHANGES IN GENES INVOLVED IN IMMUNE SYSTEM AND OXIDATIVE STRESS Article 07 January 2022 INTRODUCTION Adverse life experiences alter the

epigenetic profile1, 2, 3 in a manner that is salient for pathophysiology of post-traumatic stress disorder (PTSD).4, 5, 6 Changes in methylation status of the glucocorticoid receptor gene

have been reported previously in combat veterans with PTSD.7 Methylation changes in these same genes were also observed in association with parental trauma, suggesting that such effects may

be related to heritable risk profiles.8 Consistent claims were presented by _in vivo_ studies.9, 10 Together, these discoveries drive a strong rationale for screening the epigenetic profiles

of patients’ blood to identify next-generation strategies for PTSD risk factors, diagnostics and experimental therapeutics. A growing body of cohort-based studies has linked the epigenetic

changes with PTSD development,11, 12, 13 mostly focusing on pre-determined targets such as immunity14, 15, 16 and neuroendocrinology.7, 8, 17, 18 For the present study, strict

inclusion–exclusion criteria were used19, 20 to identify a training set comprising 48 male veterans with PTSD (PTSD+) and 51 age-/ethnicity-/gender-matched controls (PTSD−). Control veterans

experienced war trauma but were negative for current and past PTSD (Supplementary Table S1). An independent test set comprising 31 PTSD+/29 PTSD− veterans was recruited using the same

screening protocol. Enriched by the differentially methylated genes (DMGs), the epigenetically altered networks are linked to nervous systems' development and function, PTSD-associated

somatic complications and endocrine signaling. All of these networks mined from the training set were validated by the test set (Table 1). Subsequently, we consolidated the test and training

sets to develop a union set and revaluated the methylation profile using the improved sample size. The result confirmed 65% of the pathways mined from the test and training sets. Going

forward, we will consider the methylation profile from this union set as the discovery set to be confirmed in a new validation set, for which subjects are currently being recruited.

MATERIALS AND METHODS ETHICAL STATEMENT The Institutional Review Boards of the US Army Medical Research and Materiel Command, the New York University Langone Medical Center (New York, NY,

USA), the Icahn School of Medicine at Mt Sinai (New York, NY, USA) and the James J Peters Veterans Administration Medical Center (Bronx, NY, USA) approved this study. Study participants gave

written and informed consent to participate. The study was conducted in accordance with the provisions of the Helsinki Declaration. COHORT RECRUITMENT AND ANALYSIS The recruitment process

involved several steps detailed in the Supplementary Table S1 and in previous communications.19, 20 The training set of 48 PTSD+/51 PTSD− and the test set of 31 PTSD+/29 PTSD− veterans was

probed by whole-genome arrays (Agilent, Santa Clara, CA, USA) containing ~27k CpGIs. The outcome was normalized to minimize the confounding factors attributed to batch processing.21

Functional analysis was performed using those DMGs, which encoded CpGIs meeting the cutoff false discovery rate<0.1. Next, we merged the training and test sets to develop a union set

comprising 79 PTSD+/80 PTSD− veterans, which was probed by whole-genome arrays (Illumina, San Diego, CA, USA) containing 450 k probes. The outcome was corrected to minimize heterogeneous

cell populations22 and age effects, and was screened at _P_<0.05 to find DMGs. Available GEO databases are as follows: GSE76401 and GSE85399. ClueGo v2.1.2 and Ingenuity pathway analysis

were used for network construction, and pathways that we report met the cutoff of _P_<0.05. RESULTS The primary purpose of the present communication was to identify the functional

networks associated with combat-related PTSD, and thereby to provide a better understanding of PTSD pathophysiology. To meet this goal, we recruited 48 PTSD+/51 PTSD− veterans as a training

set and 31 PTSD+/29 PTSD− veterans as a test set. To increase the statistical power and to minimize any bias of the Agilent high-throughput array platform, we took two measures. First, we

constructed a union set by consolidating the training and test sets, following a recently published strategy.19, 20 Second, we retested the methylation profile, probing the union set using a

different array platform manufactured by Illumina. Furthermore, this union set retains sufficient statistical power. Taking a moderate estimate of 50% s.d.'s in probe signals and a

relatively conservative estimate for the mean difference (that is, top 1%), 76 people per group should give 95% power to detect an individual probe with a (Bonferroni-adjusted) genome-wide

significance of _P_<1.162931e−07. FUNCTIONAL ANALYSIS OF THE TRAINING SET FOUND A HOST OF PTSD-RELATED NETWORKS In the investigation of the 48 PTSD+/51 PTSD− training set, we identified

5578 differentially methylated CpGIs annotated to 3662 genes. We collectively defined the 1698 promoter-bound CpGIs and 157 additional divergent promoter regions as the _promoter_ regions

(Supplementary Figure S4A). Altogether, 4721 CpGIs annotated 2401 DMGs that displayed a log2 ratio >0.1 and were defined as hypermethylated. Conversely, 857 CpGIs (672 DMGs) displaying a

log2 ratio <0.1 were defined as hypomethylated. The remaining DMGs co-enriched by both hyper- and hypomethylated CpGIs were excluded from the subsequent functional analysis. For the

functional analysis, we used those DMGs, which encoded promoter-bound CpGIs, estimated as nearly 60% of total DMGs. Significantly enriched networks with similar functional purposes were

grouped together, resulting in four network clusters (Figure 1): nervous system functions (Figure 2a), PTSD-associated somatic complications (Figure 2b), PTSD-relevant endocrine signaling

networks (Supplementary Figure S6A) and nervous system development (Supplementary Figure S6B). TEST SET VALIDATED ALL THE NETWORKS IDENTIFIED BY THE TRAINING SET There was a significant

(_P_<0.001) overlap at the DMG level between the 48 PTSD+/51 PTSD− training set and the 31 PTSD+/29 PTSD− test set with 779 DMGs in common between the two sets assayed by the Agilent

whole-genome array. Furthermore, a significant agreement was noted at the functional level as all of the networks mined from the training set emerged significantly enriched by DMGs

identified from the test set (Table 1). UNION SET PROBED BY A DIFFERENT ARRAY PLATFORM VALIDATED A MAJORITY OF NETWORKS IDENTIFIED BY THE TRAINING AND TEST SETS The union set probed by the

Illumina array resulted in 3339 DMG, 74.4% of which encoded hypermethylated CpGIs (Supplementary Figures S4B and C). One hundred ninety-one DMGs were in common between the training set and

union set, and 107 DMGs were in common between the test set and union set (Supplementary Figure S5). There were 852 DMGs encoding promoter-bound CpGIs enriched in networks linked to

addiction, long-term impact on cerebral functions, social withdrawal, diabetes, aging, inflammation, circadian rhythm, dopamine-serotonin signaling, neurogenesis, cannabinoid signaling,

nerve impulse and synaptic plasticity. In addition, 407 DMGs in shelf and shore regions were enriched in networks associated with REM sleep, circadian rhythm, inflammation,

hypothalamic–pituitary–adrenal axis and axon guidance. Altogether, the union set confirmed 15 out of 23 networks mined from the training set and validated by test set. All of the networks

clustered under PTSD-associated somatic complications and nervous systems' development were confirmed by the training, test and union sets. METHYLATION STATUS OF SELECTED DMGS VALIDATED

BY TARGETED BISULFITE SEQUENCING Forty-two DMGs were selected from the training set based on their methylation status and their relevance to PTSD. Their methylation status was verified by

targeted bisulfite sequencing (Zymo Research, Irvine, CA, USA; Table 2).23, 24 Twenty genes out of forty-two DMGs were confirmed with the Agilent array data. Table 2 lists these genes and

their relevance to PTSD and associated comorbidities. DISCUSSION CLINICAL MEASURES WERE IN AGREEMENT WITH THE EPIGENETICALLY ALTERED NETWORKS AND DMGS Self-reported clinical measures

indicated that veterans with PTSD were concurrently experiencing higher levels of fear, social withdrawal, anxiety, hostility, depression and anger than were controls. Epigenetic

investigation of DNA extracted from whole blood revealed networks relevant to these PTSD-associated negative emotions. Greater waist size, waist-to-hip ratio and body mass index19 were found

in PTSD cases as compared with controls and are consistent with the observed pathways associated with cardiac diseases, diabetes and metabolic syndrome. PTSD-associated immune dysregulation

has been previously reported in epigenetic studies.14, 15, 19 Consistent with previous findings,14 our results found a host of innate immunity-associated genes, consisting of 60% of the

entire set of DMGs found altered in PTSD patients. In extending this knowledge, we functionally linked a majority of these genes to mobilization of phagocytic macrophages and leukocytes. In

addition, we identified epigenetically altered networks linked to learning and memory that are relevant for PTSD-associated neurocognitive impairment. Previous epidemiology studies suggested

that there was an increased risk of premature aging in PTSD.34, 35, 36 We identified two epigenetically altered networks relevant to aging. The first network is telomere management and

interaction with pathways of two mediators, wnt/β-catenin37 and p53.38 The epigenetic profile of these aging markers35 was altered in PTSD. The second network is mitochondrial dysfunction,

also epigenetically altered in PTSD veterans. Consistent with these markers of premature aging, we found evidence recently for decreased mitochondrial DNA copy numbers in PTSD veterans from

this cohort, suggesting a role for energy deprivation in PTSD that escalates the aging process.39 Premature aging40, 41 and other PTSD-associated somatic complications, such as dysregulation

of immunity,42 are known to be associated with circadian rhythm. Veterans with PTSD showed epigenetic regulation of some of the key molecular nodes responsible for setting the circadian

clock. We identified DMGs encoding CREB3 and GRIN2A, which control photoreception,43 and that are involved in signaling to entrain the circadian clock regulation by _CLOCK_ and _PER1_

genes.44 Epigenetic changes in neurogenic functional pathways were captured by the differential methylation of members of the neural helix–loop–helix family, including NEUROG1 and HES1 and

their regulators ATOH-1, Pax6 and NKX2-2.45, 46 Epigenetic perturbations of networks related to the hypothalamic–pituitary–adrenal axis functions and the synthesis of key feedback

regulators, such as corticotrophin and glucocorticoid, as well as epigenetic changes in the serotonergic and dopaminergic networks, may serve as targets for novel therapeutics for PTSD.47

STRENGTHS, LIMITATIONS AND FUTURE WORK The Diagnostic and Statistical Manual of Mental Disorders-IV diagnostic criteria48 were used to determine the PTSD status, an approach to clinical

phenotyping, which has limitations. We attempted to maximize signal detection by employing stringent selection criteria including a requirement of Clinician-Administered PTSD scale scores of

40 or greater for PTSD cases and scores less than 20 for controls.19, 20 Our array-based approach selected two platforms that ensured extensive coverage of the genome and instilled higher

confidence in the outcome. We also focused primarily on the promoter regions, as the methylation shifts near transcription start site are most likely to be associated with long-term gene

silencing.49 Given the biological heterogeneity of PTSD, our findings are limited by the sizes of our discovery, test and union sets.50 The selection of the Illumina platform was driven by

the following three factors: (i) this platform offered nearly twice the number of CpGIs to test in comparison to the Agilent platform; (ii) the significantly lower amount of input DNA

required for the Illumina assay (500 ng DNA versus 5 μg for the Agilent, assay) satisfied our need to conserve gradually decreasing DNA stocks; and (iii) the growing preference for the

Illumina assay in the epigenetics literature11, 51 was convincing for its selection. The present study recruited the largest cohort size used to date to study the PTSD pathophysiology. The

statistical analysis has moderate statistical power attributed to the sample size, which was further enhanced by the strict regulations applied by the pathway enrichment analysis. The

epigenetic contributions of many of those genes discovered have been reported as linked to PTSD via transcriptomic variations. In addition, many novel epigenetic markers linked to PTSD were

presented here. Together, this study revealed some of the key aspects of PTSD, such as its long-term health implications, which could be best explained by the epigenetic model. However, it

is challenging to draw robust mechanistic conclusions due to the non-longitudinal nature of the study; hence, there is a limited scope for making inferences about whether these epigenetic

alterations are causes of or consequences of PTSD. This study is also lacking in prospective design, gender balance and systems-wide integration. The findings are compromised further by the

fact that the array platforms are potentially unable to provide the extensive coverage typical of deep sequencing. On the basis of these findings, future work should focus on those

epigenetically altered networks presented herein, which showed clinical relevance to PTSD pathophysiology. Our study presented a knowledge-driven data-mining architecture particularly useful

to identify potential biomarkers for a multifactorial disease such as PTSD. In particular, we demonstrated how to use the clinical and physical dimensions as the successful guiding cue to

mine the molecular markers linked to disease pathophysiology. This data-mining approach will be practised further in our future study that will recruit a new validation set to confirm the

results obtained from the union set serving as the better-powered discovery set. We will also recruit a cohort of female veterans to minimize gender bias. Additional data from blood counts

and magnetic resonance imaging will be included. System-wide knowledge integration will be performed to identify PTSD biomarkers with the highest efficacy.52, 53, 54, 55, 56 REFERENCES *

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by the USAMRMC Military Operational Medicine Research Program (MOMRP)/Defense Health Agency (DHA)/Congressional Special Interests (CSI) and MOMRP 190040. DISCLAIMER The views, opinions

and/or findings contained in this report are those of the authors and should not be construed as an official Department of the Army position, policy or decision, unless so designated by

other official documentation. AUTHOR INFORMATION Author notes * R Hammamieh, N Chakraborty, A Gautam, S Muhie and R Yang: These authors contributed equally to this work. AUTHORS AND

AFFILIATIONS * Integrative Systems Biology, US Army Center for Environmental Health Research, Frederick, MD, USA R Hammamieh, A Gautam & M Jett * USACEHR, The Geneva Foundation,

Frederick, MD, USA N Chakraborty, S Muhie, D Donohue, S-A Miller & S Srinivasan * Advanced Biomedical Computing Center, Frederick National Laboratory for Cancer Research, Frederick, MD,

USA R Yang & R Kumar * Departments of Biological Sciences and Computer Science, The University of Memphis, Memphis, TN, USA B J Daigle Jr * School of Engineering and Applied Sciences,

Harvard University, Cambridge, MA, USA Y Zhang, L Petzold & F J Doyle III * Department of Psychiatry, Steven and Alexandra Cohen Veterans Center for the Study of Posttraumatic Stress and

Traumatic Brain Injury, NYU School of Medicine, New York, NY, USA D A Amara & C Marmar * Department of Psychiatry, Mount Sinai School of Medicine, James J Peters Veterans Administration

Medical Center, Bronx, NY, USA J Flory & R Yehuda * Department of Psychiatry, University of California San Francisco, San Francisco, CA, USA O M Wolkowitz * Department of Ob/Gyn,

Reproductive Sciences, University of California, San Francisco, San Francisco, CA, USA S H Mellon * Institute for Systems Biology, Seattle, WA, USA L Hood Authors * R Hammamieh View author

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ETHICS DECLARATIONS COMPETING INTERESTS The authors declare no conflict of interest. ADDITIONAL INFORMATION Supplementary Information accompanies the paper on the Translational Psychiatry

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Chakraborty, N., Gautam, A. _et al._ Whole-genome DNA methylation status associated with clinical PTSD measures of OIF/OEF veterans. _Transl Psychiatry_ 7, e1169 (2017).

https://doi.org/10.1038/tp.2017.129 Download citation * Received: 03 May 2017 * Accepted: 04 May 2017 * Published: 11 July 2017 * Issue Date: July 2017 * DOI:

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