Publications by authors named "Marti Jett"

97 Publications

"GrimAge," an epigenetic predictor of mortality, is accelerated in major depressive disorder.

Transl Psychiatry 2021 Apr 6;11(1):193. Epub 2021 Apr 6.

Weill Institute for Neurosciences and Department of Psychiatry and Behavioral Sciences, University of California San Francisco (UCSF) School of Medicine, San Francisco, CA, USA.

Major depressive disorder (MDD) is associated with premature mortality and is an independent risk factor for a broad range of diseases, especially those associated with aging, such as cardiovascular disease, diabetes, and Alzheimer's disease. However, the pathophysiology underlying increased rates of somatic disease in MDD remains unknown. It has been proposed that MDD represents a state of accelerated cellular aging, and several measures of cellular aging have been developed in recent years. Among such metrics, estimators of biological age based on predictable age-related patterns of DNA methylation (DNAm), so-called 'epigenetic clocks', have shown particular promise for their ability to capture accelerated aging in psychiatric disease. The recently developed DNAm metric known as 'GrimAge' is unique in that it was trained on time-to-death data and has outperformed its predecessors in predicting both morbidity and mortality. Yet, GrimAge has not been investigated in MDD. Here we measured GrimAge in 49 somatically healthy unmedicated individuals with MDD and 60 age-matched healthy controls. We found that individuals with MDD exhibited significantly greater GrimAge relative to their chronological age ('AgeAccelGrim') compared to healthy controls (p = 0.001), with a median of 2 years of excess cellular aging. This difference remained significant after controlling for sex, current smoking status, and body-mass index (p = 0.015). These findings are consistent with prior suggestions of accelerated cellular aging in MDD, but are the first to demonstrate this with an epigenetic metric predictive of premature mortality.
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http://dx.doi.org/10.1038/s41398-021-01302-0DOI Listing
April 2021

Microdissection of Mouse Brain into Functionally and Anatomically Different Regions.

J Vis Exp 2021 02 15(168). Epub 2021 Feb 15.

Walter Reed Army Institute of Research, Medical Readiness Systems Biology, Center for Military Psychiatry and Neuroscience;

The brain is the command center for the mammalian nervous system and an organ with enormous structural complexity. Protected within the skull, the brain consists of an outer covering of grey matter over the hemispheres known as the cerebral cortex. Underneath this layer reside many other specialized structures that are essential for multiple phenomenon important for existence. Acquiring samples of specific gross brain regions requires quick and precise dissection steps. It is understood that at the microscopic level, many sub-regions exist and likely cross the arbitrary regional boundaries that we impose for the purpose of this dissection. Mouse models are routinely used to study human brain functions and diseases. Changes in gene expression patterns may be confined to specific brain areas targeting a particular phenotype depending on the diseased state. Thus, it is of great importance to study regulation of transcription with respect to its well-defined structural organization. A complete understanding of the brain requires studying distinct brain regions, defining connections, and identifying key differences in the activities of each of these brain regions. A more comprehensive understanding of each of these distinct regions may pave the way for new and improved treatments in the field of neuroscience. Herein, we discuss a step-by-step methodology for dissecting the mouse brain into sixteen distinct regions. In this procedure, we have focused on male mouse C57Bl/6J (6-8 week old) brain removal and dissection into multiple regions using neuroanatomical landmarks to identify and sample discrete functionally-relevant and behaviorally-relevant brain regions. This work will help lay a strong foundation in the field of neuroscience, leading to more focused approaches in the deeper understanding of brain function.
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http://dx.doi.org/10.3791/61941DOI Listing
February 2021

Epigenetic biotypes of post-traumatic stress disorder in war-zone exposed veteran and active duty males.

Mol Psychiatry 2020 Dec 18. Epub 2020 Dec 18.

Medical Readiness Systems Biology, Walter Reed Army Institute for Research, Silver Spring, MD, USA.

Post-traumatic stress disorder (PTSD) is a heterogeneous condition evidenced by the absence of objective physiological measurements applicable to all who meet the criteria for the disorder as well as divergent responses to treatments. This study capitalized on biological diversity observed within the PTSD group observed following epigenome-wide analysis of a well-characterized Discovery cohort (N = 166) consisting of 83 male combat exposed veterans with PTSD, and 83 combat veterans without PTSD in order to identify patterns that might distinguish subtypes. Computational analysis of DNA methylation (DNAm) profiles identified two PTSD biotypes within the PTSD+ group, G1 and G2, associated with 34 clinical features that are associated with PTSD and PTSD comorbidities. The G2 biotype was associated with an increased PTSD risk and had higher polygenic risk scores and a greater methylation compared to the G1 biotype and healthy controls. The findings were validated at a 3-year follow-up (N = 59) of the same individuals as well as in two independent, veteran cohorts (N = 54 and N = 38), and an active duty cohort (N = 133). In some cases, for example Dopamine-PKA-CREB and GABA-PKC-CREB signaling pathways, the biotypes were oppositely dysregulated, suggesting that the biotypes were not simply a function of a dimensional relationship with symptom severity, but may represent distinct biological risk profiles underpinning PTSD. The identification of two novel distinct epigenetic biotypes for PTSD may have future utility in understanding biological and clinical heterogeneity in PTSD and potential applications in risk assessment for active duty military personnel under non-clinician-administered settings, and improvement of PTSD diagnostic markers.
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http://dx.doi.org/10.1038/s41380-020-00966-2DOI Listing
December 2020

TBI weight-drop model with variable impact heights differentially perturbs hippocampus-cerebellum specific transcriptomic profile.

Exp Neurol 2021 01 22;335:113516. Epub 2020 Oct 22.

Military Nutrition Division, US Army Research Institute of Environmental Medicine, 10 General Greene Ave, Bldg 42, Natick, MA 01760, United States of America.

The degree of brain injury is the governing factor for the magnitude of the patient's psycho- and physiological deficits post-injury, and the associated long-term consequences. The present scaling method used to segregate the patients among mild, moderate and severe phases of traumatic brain injury (TBI) has major limitations; however, a more continuous stratification of TBI is still elusive. With the anticipation that differentiating molecular markers could be the backbone of a robust method to triage TBI, we used a modified closed-head injury (CHI) Marmarou model with two impact heights (IH). By definition, IH directly correlates with the impact force causing TBI. In our modified CHI model, the rat skull was fitted with a helmet to permit a diffuse axonal injury. With the frontal cortex as the focal point of injury, the adjacent brain regions (hippocampus, HC and cerebellum, CB) were susceptible to diffuse secondary shock injury. At 8 days post injury (po.i.), rats impacted by 120 cm IH (IH) took a longer time to find an escape route in the Barnes maze as compared to those impacted by 100 cm IH (IH). Using a time-resolved interrogation of the transcriptomic landscape of HC and CB tissues, we mined those genes that altered their regulations in correlation with the variable IHs. At 14 days po.i., when all rats demonstrated nearly normal visuomotor performance, the bio-functional analysis suggested an advanced healing mechanism in the HC of IH group. In contrast, the HC of IH group displayed a delayed healing with evidence of active cell death networks. Combining whole genome rat microarrays with behavioral analysis provided the insight of neuroprotective signals that could be the foundation of the next generation triage for TBI patients.
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http://dx.doi.org/10.1016/j.expneurol.2020.113516DOI Listing
January 2021

PTSD is associated with increased DNA methylation across regions of HLA-DPB1 and SPATC1L.

Brain Behav Immun 2021 Jan 3;91:429-436. Epub 2020 Nov 3.

Emory University, Department of Gynecology and Obstetrics, Atlanta, GA, USA; Emory University School of Medicine, Department of Psychiatry and Behavioral Sciences, Atlanta, GA, USA. Electronic address:

Posttraumatic stress disorder (PTSD) is characterized by intrusive thoughts, avoidance, negative alterations in cognitions and mood, and arousal symptoms that adversely affect mental and physical health. Recent evidence links changes in DNA methylation of CpG cites to PTSD. Since clusters of proximal CpGs share similar methylation signatures, identification of PTSD-associated differentially methylated regions (DMRs) may elucidate the pathways defining differential risk and resilience of PTSD. Here we aimed to identify epigenetic differences associated with PTSD. DNA methylation data profiled from blood samples using the MethylationEPIC BeadChip were used to perform a DMR analysis in 187 PTSD cases and 367 trauma-exposed controls from the Grady Trauma Project (GTP). DMRs were assessed with R package bumphunter. We identified two regions that associate with PTSD after multiple test correction. These regions were in the gene body of HLA-DPB1 and in the promoter of SPATC1L. The DMR in HLA-DPB1 was associated with PTSD in an independent cohort. Both DMRs included CpGs whose methylation associated with nearby sequence variation (meQTL) and that associated with expression of their respective genes (eQTM). This study supports an emerging literature linking PTSD risk to genetic and epigenetic variation in the HLA region.
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http://dx.doi.org/10.1016/j.bbi.2020.10.023DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7749859PMC
January 2021

Correction: A DNA methylation clock associated with age-related illnesses and mortality is accelerated in men with combat PTSD.

Mol Psychiatry 2020 Jul 10. Epub 2020 Jul 10.

Weill Institute for Neurosciences and Department of Psychiatry, University of California San Francisco (UCSF) School of Medicine, San Francisco, CA, USA.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.
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http://dx.doi.org/10.1038/s41380-020-0837-yDOI Listing
July 2020

Pre-deployment risk factors for PTSD in active-duty personnel deployed to Afghanistan: a machine-learning approach for analyzing multivariate predictors.

Mol Psychiatry 2020 Jun 2. Epub 2020 Jun 2.

Department of Psychiatry, Center for Alcohol Use Disorder and PTSD, New York University Grossman School of Medicine, New York, NY, USA.

Active-duty Army personnel can be exposed to traumatic warzone events and are at increased risk for developing post-traumatic stress disorder (PTSD) compared with the general population. PTSD is associated with high individual and societal costs, but identification of predictive markers to determine deployment readiness and risk mitigation strategies is not well understood. This prospective longitudinal naturalistic cohort study-the Fort Campbell Cohort study-examined the value of using a large multidimensional dataset collected from soldiers prior to deployment to Afghanistan for predicting post-deployment PTSD status. The dataset consisted of polygenic, epigenetic, metabolomic, endocrine, inflammatory and routine clinical lab markers, computerized neurocognitive testing, and symptom self-reports. The analysis was computed on active-duty Army personnel (N = 473) of the 101st Airborne at Fort Campbell, Kentucky. Machine-learning models predicted provisional PTSD diagnosis 90-180 days post deployment (random forest: AUC = 0.78, 95% CI = 0.67-0.89, sensitivity = 0.78, specificity = 0.71; SVM: AUC = 0.88, 95% CI = 0.78-0.98, sensitivity = 0.89, specificity = 0.79) and longitudinal PTSD symptom trajectories identified with latent growth mixture modeling (random forest: AUC = 0.85, 95% CI = 0.75-0.96, sensitivity = 0.88, specificity = 0.69; SVM: AUC = 0.87, 95% CI = 0.79-0.96, sensitivity = 0.80, specificity = 0.85). Among the highest-ranked predictive features were pre-deployment sleep quality, anxiety, depression, sustained attention, and cognitive flexibility. Blood-based biomarkers including metabolites, epigenomic, immune, inflammatory, and liver function markers complemented the most important predictors. The clinical prediction of post-deployment symptom trajectories and provisional PTSD diagnosis based on pre-deployment data achieved high discriminatory power. The predictive models may be used to determine deployment readiness and to determine novel pre-deployment interventions to mitigate the risk for deployment-related PTSD.
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http://dx.doi.org/10.1038/s41380-020-0789-2DOI Listing
June 2020

Effect of Combat Exposure and Posttraumatic Stress Disorder on Telomere Length and Amygdala Volume.

Biol Psychiatry Cogn Neurosci Neuroimaging 2020 07 31;5(7):678-687. Epub 2020 Mar 31.

Department of Psychiatry, University of California, San Francisco School of Medicine, San Francisco, California.

Background: Traumatic stress can adversely affect physical and mental health through neurobiological stress response systems. We examined the effects of trauma exposure and posttraumatic stress disorder (PTSD) on telomere length, a biomarker of cellular aging, and volume of the amygdala, a key structure of stress regulation, in combat-exposed veterans. In addition, the relationships of psychopathological symptoms and autonomic function with telomere length and amygdala volume were examined.

Methods: Male combat veterans were categorized as having PTSD diagnosis (n = 102) or no lifetime PTSD diagnosis (n = 111) based on the Clinician-Administered PTSD Scale. Subjects were assessed for stress-related psychopathology, trauma severity, autonomic function, and amygdala volumes by magnetic resonance imaging.

Results: A significant interaction was found between trauma severity and PTSD status for telomere length and amygdala volume after adjusting for multiple confounders. Subjects with PTSD showed shorter telomere length and larger amygdala volume than those without PTSD among veterans exposed to high trauma, while there was no significant group difference in these parameters among those exposed to low trauma. Among veterans exposed to high trauma, greater telomere shortening was significantly correlated with greater norepinephrine, and larger amygdala volume was correlated with more severe psychological symptoms and higher heart rates.

Conclusions: These data suggest that the intensity of the index trauma event plays an important role in interacting with PTSD symptomatology and autonomic activity in predicting telomere length and amygdala volume. These results highlight the importance of trauma severity and PTSD status in predicting certain biological outcomes.
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http://dx.doi.org/10.1016/j.bpsc.2020.03.007DOI Listing
July 2020

A DNA methylation clock associated with age-related illnesses and mortality is accelerated in men with combat PTSD.

Mol Psychiatry 2020 May 7. Epub 2020 May 7.

Weill Institute for Neurosciences and Department of Psychiatry, University of California San Francisco (UCSF) School of Medicine, San Francisco, CA, USA.

DNA methylation patterns at specific cytosine-phosphate-guanine (CpG) sites predictably change with age and can be used to derive "epigenetic age", an indicator of biological age, as opposed to merely chronological age. A relatively new estimator, called "DNAm GrimAge", is notable for its superior predictive ability in older populations regarding numerous age-related metrics like time-to-death, time-to-coronary heart disease, and time-to-cancer. PTSD is associated with premature mortality and frequently has comorbid physical illnesses suggestive of accelerated biological aging. This is the first study to assess DNAm GrimAge in PTSD patients. We investigated the acceleration of GrimAge relative to chronological age, denoted "AgeAccelGrim" in combat trauma-exposed male veterans with and without PTSD using cross-sectional and longitudinal data from two independent well-characterized veteran cohorts. In both cohorts, AgeAccelGrim was significantly higher in the PTSD group compared to the control group (N = 162, 1.26 vs -0.57, p = 0.001 and N = 53, 0.93 vs -1.60 Years, p = 0.008), suggesting accelerated biological aging in both cohorts with PTSD. In 3-year follow-up study of individuals initially diagnosed with PTSD (N = 26), changes in PTSD symptom severity were correlated with AgeAccelGrim changes (r = 0.39, p = 0.049). In addition, the loss of CD28 cell surface markers on CD8 + T cells, an indicator of T-cell senescence/exhaustion that is associated with biological aging, was positively correlated with AgeAccelGrim, suggesting an immunological contribution to the accelerated biological aging. Overall, our findings delineate cellular correlates of biological aging in combat-related PTSD, which may help explain the increased medical morbidity and mortality seen in this disease.
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http://dx.doi.org/10.1038/s41380-020-0755-zDOI Listing
May 2020

Evaluating the impact of trauma and PTSD on epigenetic prediction of lifespan and neural integrity.

Neuropsychopharmacology 2020 09 7;45(10):1609-1616. Epub 2020 May 7.

Department of Gynecology and Obstetrics, Emory University, Atlanta, GA, USA.

Post-traumatic stress disorder (PTSD) is a debilitating disorder that develops in some people following trauma exposure. Trauma and PTSD have been associated with accelerated cellular aging. This study evaluated the effect of trauma and PTSD on accelerated GrimAge, an epigenetic predictor of lifespan, in traumatized civilians. This study included 218 individuals with current PTSD, 427 trauma-exposed controls without any history of PTSD and 209 subjects with lifetime PTSD history who are not categorized as current PTSD cases. The Traumatic Events Inventory (TEI) and Clinician-Administered PTSD Scale (CAPS) were used to measure lifetime trauma burden and PTSD, respectively. DNA from whole blood was interrogated using the MethylationEPIC or HumanMethylation450 BeadChips. GrimAge estimates were calculated using the methylation age calculator. Cortical thickness of 69 female subjects was assessed by using T1-weighted structural MRI images. Associations between trauma exposure, PTSD, cortical thickness, and GrimAge acceleration were tested with multiple regression models. Lifetime trauma burden (p = 0.03), current PTSD (p = 0.02) and lifetime PTSD (p = 0.005) were associated with GrimAge acceleration, indicative of a shorter predicted lifespan. The association with lifetime PTSD was replicated in an independent cohort (p = 0.04). In the MRI sub sample, GrimAge acceleration also associated with cortical atrophy in the right lateral orbitofrontal cortex (p = 0.03) and right posterior cingulate (p = 0.04), brain areas associated with emotion-regulation and threat-regulation. Our findings suggest that lifetime trauma and PTSD may contribute to a higher epigenetic-based mortality risk. We also demonstrate a relationship between cortical atrophy in PTSD-relevant brain regions and shorter predicted lifespan.
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http://dx.doi.org/10.1038/s41386-020-0700-5DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7421899PMC
September 2020

Role of enhanced glucocorticoid receptor sensitivity in inflammation in PTSD: insights from computational model for circadian-neuroendocrine-immune interactions.

Am J Physiol Endocrinol Metab 2020 07 21;319(1):E48-E66. Epub 2020 Apr 21.

Harvard John Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts.

Although glucocorticoid resistance contributes to increased inflammation, individuals with posttraumatic stress disorder (PTSD) exhibit increased glucocorticoid receptor (GR) sensitivity along with increased inflammation. It is not clear how inflammation coexists with a hyperresponsive hypothalamic-pituitary-adrenal (HPA) axis. To understand this better, we developed and analyzed an integrated mathematical model for the HPA axis and the immune system. We performed mathematical simulations for a dexamethasone (DEX) suppression test and IC-dexamethasone for cytokine suppression by varying model parameters. The model analysis suggests that increasing the steepness of the dose-response curve for GR activity may reduce anti-inflammatory effects of GRs at the ambient glucocorticoid levels, thereby increasing proinflammatory response. The adaptive response of proinflammatory cytokine-mediated stimulatory effects on the HPA axis is reduced due to dominance of the GR-mediated negative feedback on the HPA axis. To verify these hypotheses, we analyzed the clinical data on neuroendocrine variables and cytokines obtained from war-zone veterans with and without PTSD. We observed significant group differences for cortisol and ACTH suppression tests, proinflammatory cytokines TNFα and IL6, high-sensitivity C-reactive protein, promoter methylation of GR gene, and IC for lysozyme suppression. Causal inference modeling revealed significant associations between cortisol suppression and post-DEX cortisol decline, promoter methylation of human GR gene exon 1F (), IC, and proinflammatory cytokines. We noted significant mediation effects of promoter methylation on inflammatory cytokines through changes in GR sensitivity. Our findings suggest that increased GR sensitivity may contribute to increased inflammation; therefore, interventions to restore GR sensitivity may normalize inflammation in PTSD.
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http://dx.doi.org/10.1152/ajpendo.00398.2019DOI Listing
July 2020

Novel Pharmacological Targets for Combat PTSD-Metabolism, Inflammation, The Gut Microbiome, and Mitochondrial Dysfunction.

Mil Med 2020 01;185(Suppl 1):311-318

Department of Psychiatry, University of California, San Francisco (UCSF), School of Medicine, 401 Parnassus Ave, San Francisco, CA 94143.

Introduction: Current pharmacological treatments of post-traumatic stress disorder (PTSD) have limited efficacy. Although the diagnosis is based on psychopathological criteria, it is frequently accompanied by somatic comorbidities and perhaps "accelerated biological aging," suggesting widespread physical concomitants. Such physiological comorbidities may affect core PTSD symptoms but are rarely the focus of therapeutic trials.

Methods: To elucidate the potential involvement of metabolism, inflammation, and mitochondrial function in PTSD, we integrate findings and mechanistic models from the DOD-sponsored "Systems Biology of PTSD Study" with previous data on these topics.

Results: Data implicate inter-linked dysregulations in metabolism, inflammation, mitochondrial function, and perhaps the gut microbiome in PTSD. Several inadequately tested targets of pharmacological intervention are proposed, including insulin sensitizers, lipid regulators, anti-inflammatories, and mitochondrial biogenesis modulators.

Conclusions: Systemic pathologies that are intricately involved in brain functioning and behavior may not only contribute to somatic comorbidities in PTSD, but may represent novel targets for treating core psychiatric symptoms.
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http://dx.doi.org/10.1093/milmed/usz260DOI Listing
January 2020

Genomic influences on self-reported childhood maltreatment.

Transl Psychiatry 2020 01 27;10(1):38. Epub 2020 Jan 27.

Department of Psychiatry, University of California San Diego, La Jolla, CA, USA.

Childhood maltreatment is highly prevalent and serves as a risk factor for mental and physical disorders. Self-reported childhood maltreatment appears heritable, but the specific genetic influences on this phenotype are largely unknown. The aims of this study were to (1) identify genetic variation associated with self-reported childhood maltreatment, (2) estimate SNP-based heritability (h), (3) assess predictive value of polygenic risk scores (PRS) for childhood maltreatment, and (4) quantify genetic overlap of childhood maltreatment with mental and physical health-related phenotypes, and condition the top hits from our analyses when such overlap is present. Genome-wide association analysis for childhood maltreatment was undertaken, using a discovery sample from the UK Biobank (UKBB) (n = 124,000) and a replication sample from the Psychiatric Genomics Consortium-posttraumatic stress disorder group (PGC-PTSD) (n = 26,290). h for childhood maltreatment and genetic correlations with mental/physical health traits were calculated using linkage disequilibrium score regression. PRS was calculated using PRSice and mtCOJO was used to perform conditional analysis. Two genome-wide significant loci associated with childhood maltreatment (rs142346759, p = 4.35 × 10, FOXP1; rs10262462, p = 3.24 × 10, FOXP2) were identified in the discovery dataset but were not replicated in PGC-PTSD. h for childhood maltreatment was ~6% and the PRS derived from the UKBB was significantly predictive of childhood maltreatment in PGC-PTSD (r = 0.0025; p = 1.8 × 10). The most significant genetic correlation of childhood maltreatment was with depressive symptoms (r = 0.70, p = 4.65 × 10), although we show evidence that our top hits may be specific to childhood maltreatment. This is the first large-scale genetic study to identify specific variants associated with self-reported childhood maltreatment. Speculatively, FOXP genes might influence externalizing traits and so be relevant to childhood maltreatment. Alternatively, these variants may be associated with a greater likelihood of reporting maltreatment. A clearer understanding of the genetic relationships of childhood maltreatment, including particular abuse subtypes, with a range of phenotypes, may ultimately be useful in in developing targeted treatment and prevention strategies.
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http://dx.doi.org/10.1038/s41398-020-0706-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7026037PMC
January 2020

Temporal analysis of mRNA expression profiles in Orientia infected C3HeB/FeJ mouse.

BMC Microbiol 2020 01 6;20(1). Epub 2020 Jan 6.

Viral and Rickettsial Diseases Department, Infectious Diseases Directorate, Naval Medical Research Center, 503 Robert Grant Ave, RM3N71, Silver Spring, MD, 20910, USA.

Background: Scrub typhus causes up to 35% mortality if left untreated. One billion people living in the endemic regions are at risk. In spite of its heavy disease burden in some of the most populated areas in the world, there is no vaccine available. Although the disease can be effectively treated by proper antibiotics, timely and accurate diagnosis remains a challenge. Orientia tsutsugamushi infects a variety of mammalian cells in vitro and replicates in the cytoplasm of the infected cells. Microarray analysis has been used extensively to study host-pathogen interactions in in vitro models to understand pathogenesis. However there is a lack of in vivo studies.

Results: In this study, C3HeB/FeJ (C3H) mice were infected by O. tsutsugamushi via the intraperitoneal route and monitored gene expression at 10 different time points post infection. We observed two distinct types of expression profiles in the genes that we analyzed. There are two valleys (4-18 h and 2-4 days) with low number of differentially expressed genes (DEG) with three peaks with high number of DEG at 2 h, 1-day and 7-day post infection. Further analysis revealed that pathways like complement and coagulation cascade, and blood clotting cascade pathways showed significant global changes throughout entire time course. Real time quantitative Polymerase Chain Reaction (RT-qPCR) confirmed the change of expression for genes involved in complement and coagulation cascade. These results suggested dynamic regulation of the complement and coagulation cascades throughout most of the time post infection while some other specific pathways, such as fatty acid metabolism and tryptophan metabolism, are turned on or off at certain times post infection.

Conclusions: The findings highlight the complex interconnection among all different biological pathways. It is conceivable that specific pathways such as cell growth control and cell development in the host are affected by Orientia in the initial phase of infection for Orientia to grow intracellularly. Once Orientia is replicating successfully inside the host as infection progresses, the infection could activate pathways involved in cellular immune responses to defend for host cell survival and try to eliminate the pathogen.
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http://dx.doi.org/10.1186/s12866-019-1684-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6945539PMC
January 2020

Investigating gene expression profiles of whole blood and peripheral blood mononuclear cells using multiple collection and processing methods.

PLoS One 2019 6;14(12):e0225137. Epub 2019 Dec 6.

US Army Center for Environmental Health Research, Fort Detrick, MD, United States of America.

Gene expression profiling using blood samples is a valuable tool for biomarker discovery in clinical studies. Different whole blood RNA collection and processing methods are highly variable and might confound comparisons of results across studies. The main aim of the current study is to compare how blood storage, extraction methodologies, and the blood components themselves may influence gene expression profiling. Whole blood and peripheral blood mononuclear cell (PBMC) samples were collected in triplicate from five healthy donors. Whole blood was collected in RNAgard® and PAXgene® Blood RNA Tubes, as well as in collection tubes with anticoagulants such as dipotassium ethylenediaminetetraacetic acid (K2EDTA) and Acid Citrate Dextrose Solution A (ACD-A). PBMCs were separated using sodium citrate Cell Preparation Tubes (CPT™), FICOLL™, magnetic separation, and the LeukoLOCK™ methods. After blood collection, the LeukoLOCK™, K2EDTA and ACD-A blood tubes were shipped overnight using cold conditions and samples from the rest of the collection were immediately frozen with or without pre-processing. The RNA was isolated from whole blood and PBMCs using a total of 10 different experimental conditions employing several widely utilized RNA isolation methods. The RNA quality was assessed by RNA Integrity Number (RIN), which showed that all PBMC procedures had the highest RIN values when blood was stabilized in TRIzol® Reagent before RNA extraction. Initial data analysis showed that human blood stored and shipped at 4°C overnight performed equally well when checked for quality using RNA integrity number when compared to frozen stabilized blood. Comparisons within and across donor/method replicates showed signal-to-noise patterns which were not captured by RIN value alone. Pathway analysis using the top 1000 false discovery rate (FDR) corrected differentially expressed genes (DEGs) showed frozen vs. cold shipping conditions greatly impacted gene expression patterns in whole blood. However, the top 1000 FDR corrected DEGs from PBMCs preserved after frozen vs. cold shipping conditions (LeukoLOCK™ preserved in RNAlater®) revealed no significantly affected pathways. Our results provide novel insight into how RNA isolation, various storage, handling, and processing methodologies can influence RNA quality and apparent gene expression using blood samples. Careful consideration is necessary to avoid bias resulting from downstream processing. Better characterization of the effects of collection method idiosyncrasies will facilitate further research in understanding the effect of gene expression variability in human sample types.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0225137PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6897427PMC
March 2020

Trauma Management Therapy and Prolonged Exposure Therapy for PTSD in an active duty sample: Design and methodology of a randomized clinical trial.

Contemp Clin Trials Commun 2020 Mar 15;17:100491. Epub 2019 Nov 15.

US Army Center for Environmental Health Research, Fort Detrick, MD, USA.

Posttraumatic stress disorder (PTSD) resulting from military service is a common, yet often chronic condition. Treatment outcome often is attenuated by programs that are (a) lengthy in nature and (b) constricted in their target outcomes. These limitations leave much of the emotional and behavioral impairment that accompanies PTSD unaddressed and/or unassessed. Typical PTSD treatment programs are 3-4 months in length, which is challenging for the pace of the nation's military. In this investigation, we will compare two treatments, Trauma Management Therapy (TMT) and Prolonged Exposure (PE), both redesigned to address the needs of active duty personnel (300 participants at 3 military installations). Specifically, we will compare the TMT Intensive Outpatient Program (IOP; 3 weeks) to PE's compressed (2 week) format. Both interventions will be compared to a standard course of PE (12 weeks). In addition to PTSD symptomatology, outcome measurement includes other aspects of psychopathology as well as changes in social, occupational, and familial impairment. Potential negative outcomes of massed treatment, such as increased suicidal ideation or increased alcohol use, will be assessed, as will genetic predictors of PTSD subtype and treatment outcome. This study will inform the delivery of care for military-related PTSD and particularly the use of intensive or compressed treatments for active duty personnel.
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http://dx.doi.org/10.1016/j.conctc.2019.100491DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6881668PMC
March 2020

Predeployment neurocognitive functioning predicts postdeployment posttraumatic stress in Army personnel.

Neuropsychology 2020 Mar 2;34(3):276-287. Epub 2019 Dec 2.

Steven and Alexandra Cohen Veterans Center for the Study of Posttraumatic Stress and Traumatic Brain Injury, Department of Psychiatry, New York University School of Medicine.

Objective: The Fort Campbell Cohort study was designed to assess predeployment biological and behavioral markers and build predictive models to identify risk and resilience for posttraumatic stress disorder (PTSD) following deployment. This article addresses neurocognitive functioning variables as potential prospective predictors.

Method: In a sample of 403 soldiers, we examined whether PTSD symptom severity (using the PTSD Checklist) as well as posttraumatic stress trajectories could be prospectively predicted by measures of executive functioning (using two web-based tasks from WebNeuro) assessed predeployment.

Results: Controlling for age, gender, education, prior number of deployments, childhood trauma exposure, and PTSD symptom severity at Phase 1, linear regression models revealed that predeployment sustained attention and inhibitory control performance were significantly associated with postdeployment PTSD symptom severity. We also identified two posttraumatic stress trajectories utilizing latent growth mixture models. The "resilient" group consisted of 90.9% of the soldiers who exhibited stable low levels of PTSD symptoms from pre- to postdeployment. The "increasing" group consisted of 9.1% of the soldiers, who exhibited an increase in PTSD symptoms following deployment, crossing a threshold for diagnosis based on PTSD Checklist scores. Logistic regression models predicting trajectory revealed a similar pattern of findings as the linear regression models, in which predeployment sustained attention (95% CI of odds ratio: 1.0109, 1.0558) and inhibitory control (95% CI: 1.0011, 1.0074) performance were significantly associated with postdeployment PTSD trajectory.

Conclusions: These findings have clinical implications for understanding the pathogenesis of PTSD and building preventative programs for military personnel. (PsycINFO Database Record (c) 2020 APA, all rights reserved).
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http://dx.doi.org/10.1037/neu0000603DOI Listing
March 2020

Gene expression profiling of whole blood: A comparative assessment of RNA-stabilizing collection methods.

PLoS One 2019 10;14(10):e0223065. Epub 2019 Oct 10.

Integrative Systems Biology Program, U.S. Army Center for Environmental Health Research, Fort Detrick, MD, United States of America.

Peripheral Blood gene expression is widely used in the discovery of biomarkers and development of therapeutics. Recently, a spate of commercial blood collection and preservation systems have been introduced with proprietary variations that may differentially impact the transcriptomic profiles. Comparative analysis of these collection platforms will help optimize protocols to detect, identify, and reproducibly validate true biological variance among subjects. In the current study, we tested two recently introduced whole blood collection methods, RNAgard® and PAXgene® RNA, in addition to the traditional method of peripheral blood mononuclear cells (PBMCs) separated from whole blood and preserved in Trizol reagent. Study results revealed striking differences in the transcriptomic profiles from the three different methods that imply ex vivo changes in gene expression occurred during the blood collection, preservation, and mRNA extraction processes. When comparing the ability of the three preservation methods to accurately capture individuals' expression differences, RNAgard® outperformed PAXgene® RNA, and both showed better individual separation of transcriptomic profiles than PBMCs. Hence, our study recommends using a single blood collection platform, and strongly cautions against combining methods during the course of a defined study.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223065PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6786555PMC
March 2020

International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci.

Authors:
Caroline M Nievergelt Adam X Maihofer Torsten Klengel Elizabeth G Atkinson Chia-Yen Chen Karmel W Choi Jonathan R I Coleman Shareefa Dalvie Laramie E Duncan Joel Gelernter Daniel F Levey Mark W Logue Renato Polimanti Allison C Provost Andrew Ratanatharathorn Murray B Stein Katy Torres Allison E Aiello Lynn M Almli Ananda B Amstadter Søren B Andersen Ole A Andreassen Paul A Arbisi Allison E Ashley-Koch S Bryn Austin Esmina Avdibegovic Dragan Babić Marie Bækvad-Hansen Dewleen G Baker Jean C Beckham Laura J Bierut Jonathan I Bisson Marco P Boks Elizabeth A Bolger Anders D Børglum Bekh Bradley Megan Brashear Gerome Breen Richard A Bryant Angela C Bustamante Jonas Bybjerg-Grauholm Joseph R Calabrese José M Caldas-de-Almeida Anders M Dale Mark J Daly Nikolaos P Daskalakis Jürgen Deckert Douglas L Delahanty Michelle F Dennis Seth G Disner Katharina Domschke Alma Dzubur-Kulenovic Christopher R Erbes Alexandra Evans Lindsay A Farrer Norah C Feeny Janine D Flory David Forbes Carol E Franz Sandro Galea Melanie E Garrett Bizu Gelaye Elbert Geuze Charles Gillespie Aferdita Goci Uka Scott D Gordon Guia Guffanti Rasha Hammamieh Supriya Harnal Michael A Hauser Andrew C Heath Sian M J Hemmings David Michael Hougaard Miro Jakovljevic Marti Jett Eric Otto Johnson Ian Jones Tanja Jovanovic Xue-Jun Qin Angela G Junglen Karen-Inge Karstoft Milissa L Kaufman Ronald C Kessler Alaptagin Khan Nathan A Kimbrel Anthony P King Nastassja Koen Henry R Kranzler William S Kremen Bruce R Lawford Lauren A M Lebois Catrin E Lewis Sarah D Linnstaedt Adriana Lori Bozo Lugonja Jurjen J Luykx Michael J Lyons Jessica Maples-Keller Charles Marmar Alicia R Martin Nicholas G Martin Douglas Maurer Matig R Mavissakalian Alexander McFarlane Regina E McGlinchey Katie A McLaughlin Samuel A McLean Sarah McLeay Divya Mehta William P Milberg Mark W Miller Rajendra A Morey Charles Phillip Morris Ole Mors Preben B Mortensen Benjamin M Neale Elliot C Nelson Merete Nordentoft Sonya B Norman Meaghan O'Donnell Holly K Orcutt Matthew S Panizzon Edward S Peters Alan L Peterson Matthew Peverill Robert H Pietrzak Melissa A Polusny John P Rice Stephan Ripke Victoria B Risbrough Andrea L Roberts Alex O Rothbaum Barbara O Rothbaum Peter Roy-Byrne Ken Ruggiero Ariane Rung Bart P F Rutten Nancy L Saccone Sixto E Sanchez Dick Schijven Soraya Seedat Antonia V Seligowski Julia S Seng Christina M Sheerin Derrick Silove Alicia K Smith Jordan W Smoller Scott R Sponheim Dan J Stein Jennifer S Stevens Jennifer A Sumner Martin H Teicher Wesley K Thompson Edward Trapido Monica Uddin Robert J Ursano Leigh Luella van den Heuvel Miranda Van Hooff Eric Vermetten Christiaan H Vinkers Joanne Voisey Yunpeng Wang Zhewu Wang Thomas Werge Michelle A Williams Douglas E Williamson Sherry Winternitz Christiane Wolf Erika J Wolf Jonathan D Wolff Rachel Yehuda Ross McD Young Keith A Young Hongyu Zhao Lori A Zoellner Israel Liberzon Kerry J Ressler Magali Haas Karestan C Koenen

Nat Commun 2019 10 8;10(1):4558. Epub 2019 Oct 8.

Broad Institute of MIT and Harvard, Stanley Center for Psychiatric Research, Cambridge, MA, USA.

The risk of posttraumatic stress disorder (PTSD) following trauma is heritable, but robust common variants have yet to be identified. In a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls we conduct a genome-wide association study of PTSD. We demonstrate SNP-based heritability estimates of 5-20%, varying by sex. Three genome-wide significant loci are identified, 2 in European and 1 in African-ancestry analyses. Analyses stratified by sex implicate 3 additional loci in men. Along with other novel genes and non-coding RNAs, a Parkinson's disease gene involved in dopamine regulation, PARK2, is associated with PTSD. Finally, we demonstrate that polygenic risk for PTSD is significantly predictive of re-experiencing symptoms in the Million Veteran Program dataset, although specific loci did not replicate. These results demonstrate the role of genetic variation in the biology of risk for PTSD and highlight the necessity of conducting sex-stratified analyses and expanding GWAS beyond European ancestry populations.
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http://dx.doi.org/10.1038/s41467-019-12576-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6783435PMC
October 2019

Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder.

Mol Psychiatry 2020 12 10;25(12):3337-3349. Epub 2019 Sep 10.

Department of Psychiatry, New York Langone Medical School, New York, NY, USA.

Post-traumatic stress disorder (PTSD) impacts many veterans and active duty soldiers, but diagnosis can be problematic due to biases in self-disclosure of symptoms, stigma within military populations, and limitations identifying those at risk. Prior studies suggest that PTSD may be a systemic illness, affecting not just the brain, but the entire body. Therefore, disease signals likely span multiple biological domains, including genes, proteins, cells, tissues, and organism-level physiological changes. Identification of these signals could aid in diagnostics, treatment decision-making, and risk evaluation. In the search for PTSD diagnostic biomarkers, we ascertained over one million molecular, cellular, physiological, and clinical features from three cohorts of male veterans. In a discovery cohort of 83 warzone-related PTSD cases and 82 warzone-exposed controls, we identified a set of 343 candidate biomarkers. These candidate biomarkers were selected from an integrated approach using (1) data-driven methods, including Support Vector Machine with Recursive Feature Elimination and other standard or published methodologies, and (2) hypothesis-driven approaches, using previous genetic studies for polygenic risk, or other PTSD-related literature. After reassessment of ~30% of these participants, we refined this set of markers from 343 to 28, based on their performance and ability to track changes in phenotype over time. The final diagnostic panel of 28 features was validated in an independent cohort (26 cases, 26 controls) with good performance (AUC = 0.80, 81% accuracy, 85% sensitivity, and 77% specificity). The identification and validation of this diverse diagnostic panel represents a powerful and novel approach to improve accuracy and reduce bias in diagnosing combat-related PTSD.
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http://dx.doi.org/10.1038/s41380-019-0496-zDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7714692PMC
December 2020

Mechanistic inferences on metabolic dysfunction in posttraumatic stress disorder from an integrated model and multiomic analysis: role of glucocorticoid receptor sensitivity.

Am J Physiol Endocrinol Metab 2019 11 19;317(5):E879-E898. Epub 2019 Jul 19.

Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, Massachusetts.

Posttraumatic stress disorder (PTSD) is associated with neuroendocrine alterations and metabolic abnormalities; however, how metabolism is affected by neuroendocrine disturbances is unclear. The data from combat-exposed veterans with PTSD show increased glycolysis to lactate flux, reduced TCA cycle flux, impaired amino acid and lipid metabolism, insulin resistance, inflammation, and hypersensitive hypothalamic-pituitary-adrenal (HPA) axis. To analyze whether the co-occurrence of multiple metabolic abnormalities is independent or arises from an underlying regulatory defect, we employed a systems biological approach using an integrated mathematical model and multiomic analysis. The models for hepatic metabolism, HPA axis, inflammation, and regulatory signaling were integrated to perform metabolic control analysis (MCA) with respect to the observations from our clinical data. We combined the metabolomics, neuroendocrine, clinical laboratory, and cytokine data from combat-exposed veterans with and without PTSD to characterize the differences in regulatory effects. MCA revealed mechanistic association of the HPA axis and inflammation with metabolic dysfunction consistent with PTSD. This was supported by the data using correlational and causal analysis that revealed significant associations between cortisol suppression, high-sensitivity C-reactive protein, homeostatic model assessment of insulin resistance, γ-glutamyltransferase, hypoxanthine, and several metabolites. Causal mediation analysis indicates that the effects of enhanced glucocorticoid receptor sensitivity (GRS) on glycolytic pathway, gluconeogenic and branched-chain amino acids, triglycerides, and hepatic function are jointly mediated by inflammation, insulin resistance, oxidative stress, and energy deficit. Our analysis suggests that the interventions to normalize GRS and inflammation may help to manage features of metabolic dysfunction in PTSD.
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http://dx.doi.org/10.1152/ajpendo.00065.2019DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6879860PMC
November 2019

Distinct Profiles of Cell-Free MicroRNAs in Plasma of Veterans with Post-Traumatic Stress Disorder.

J Clin Med 2019 Jul 3;8(7). Epub 2019 Jul 3.

Institute for Systems Biology, Seattle, WA 98109, USA.

Dysregulation of circulating microRNAs (miRNAs) in body fluids has been reported in psychiatric disorders such as schizophrenia, bipolar disorder, major depressive disorder, and post-traumatic stress disorder (PTSD). Recent studies of various diseases showed that extracellular vesicles (EV) in body fluids can provide different spectra of circulating miRNAs and disease-associated signatures from whole fluid or EV-depleted fraction. However, the association of miRNAs in EVs to PTSD has not been studied. In this study, we performed a comprehensive profiling of miRNAs in whole plasma, extracellular vesicles (EV) and EV-depleted plasma (EVD) samples collected from combat veterans with PTSD and matched controls by utilizing a next-generation sequencing (NGS) platform. In total, 520 circulating miRNAs were quantified from 24 male Iraq and Afghanistan combat veterans with ( 12) and without ( 12) PTSD. The overall miRNA profiles in whole plasma, EV and EVD fractions were different and miRNAs affected by PTSD were also distinct in each sample type. The concentration changes of miR-203a-3p in EV and miR-339-5p in EVD were confirmed in an independent validation cohort that consisted of 20 veterans (10 with and 10 without PTSD) using qPCR. The target genes of these two miRNAs were involved in signaling pathways and comorbid conditions associated with PTSD (e.g., neurotransmitter systems such as dopaminergic and serotonergic signaling, inflammatory response, and cardiovascular diseases). Our findings suggest that PTSD may have different impacts on miRNAs encapsulated in vesicles and outside of vesicles. Further studies using larger samples are needed to evaluate the utility of these miRNAs as diagnostic biomarkers for PTSD.
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http://dx.doi.org/10.3390/jcm8070963DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6678393PMC
July 2019

Polygenic risk associated with post-traumatic stress disorder onset and severity.

Transl Psychiatry 2019 06 7;9(1):165. Epub 2019 Jun 7.

Harvard John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA.

Post-traumatic stress disorder (PTSD) is a psychiatric illness with a highly polygenic architecture without large effect-size common single-nucleotide polymorphisms (SNPs). Thus, to capture a substantial portion of the genetic contribution, effects from many variants need to be aggregated. We investigated various aspects of one such approach that has been successfully applied to many traits, polygenic risk score (PRS) for PTSD. Theoretical analyses indicate the potential prediction ability of PRS. We used the latest summary statistics from the largest published genome-wide association study (GWAS) conducted by Psychiatric Genomics Consortium for PTSD (PGC-PTSD). We found that the PRS constructed for a cohort comprising veterans of recent wars (n = 244) explains a considerable proportion of PTSD onset (Nagelkerke R = 4.68%, P = 0.003) and severity (R = 4.35%, P = 0.0008) variances. However, the performance on an African ancestry sub-cohort was minimal. A PRS constructed with schizophrenia GWAS also explained a significant fraction of PTSD diagnosis variance (Nagelkerke R = 2.96%, P = 0.0175), confirming previously reported genetic correlation between the two psychiatric ailments. Overall, these findings demonstrate the important role polygenic analyses of PTSD will play in risk prediction models as well as in elucidating the biology of the disorder.
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http://dx.doi.org/10.1038/s41398-019-0497-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6555815PMC
June 2019

Molecular alterations induced by Yersinia pestis, dengue virus and Staphylococcal enterotoxin B under severe stress.

Brain Behav Immun 2019 08 15;80:725-741. Epub 2019 May 15.

Systems Biology Enterprise, U.S. Army Center for Environmental Health Research, Fort Detrick, MD 21702, USA. Electronic address:

Background: Severe stress can have drastic and systemic effects with dire implications on the health and wellbeing of exposed individuals. Particularly, the effect of stress on the immune response to infection is of interest to public health because of its implications for vaccine efficacy and treatment strategies during stressful scenarios. Severe stress has previously been shown to cause an anergic state in the immune system that persists following exposure to a potent mitogen.

Methods: Transcriptome and microRNA changes were characterized using blood samples collected from U.S. Army Ranger candidates immediately before and after training, followed by exposure to representative pathogenic agents: Yersinia pestis, dengue virus 2, and Staphylococcal enterotoxin B (SEB). We employed experimental and computational approaches to characterize altered gene expression, processes, pathways, and regulatory networks mediating the host's response towards severe stress; to assess the protective immunity status of the stressed host towards infection; and to identify pathogen-induced biomarkers under severe stress conditions.

Results: We observed predicted inhibition of pathways significantly associated with lymphopoiesis, wound healing, inflammatory response, lymphocyte activation, apoptosis, and predicted activation of oxidative stress. Using weighted correlation network analyses, we demonstrated preservation of these pathways across infection and stress combinations. Regulatory networks comprising a common set of upstream regulators: transcription factors, microRNAs and post-translational regulators (kinases and phosphatases) may be drivers of molecular alterations leading to compromised protective immunity. Other sets of transcripts were persistently altered in both the pre- and post-stress conditions due to the host's response to each pathogenic agent, forming specific molecular signatures with the potential to distinguish infection from that of severe stress.

Conclusions: Our results suggest that severe stress alters molecules implicated in the development of leukopoietic stem cells, thereby leading to depletion of cellular and molecular repertoires of protective immunity. Suppressed molecules mediating membrane trafficking of recycling endosomes, membrane translocation and localization of the antigen processing mechanisms and cell adhesions indicate suboptimal antigen presentation, impaired formation of productive immunological synapses, and inhibited T-cell activations. These factors may collectively be responsible for compromised protective immunity (infection susceptibility, delayed wound healing, and poor vaccine response) observed in people under severe stress.
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http://dx.doi.org/10.1016/j.bbi.2019.05.022DOI Listing
August 2019

Metabolomic analysis of male combat veterans with post traumatic stress disorder.

PLoS One 2019 18;14(3):e0213839. Epub 2019 Mar 18.

Department of Psychiatry and UCSF Weill Institute for Neurosciences, University of California, San Francisco, CA, United States of America.

Posttraumatic stress disorder (PTSD) is associated with impaired major domains of psychology and behavior. Individuals with PTSD also have increased co-morbidity with several serious medical conditions, including autoimmune diseases, cardiovascular disease, and diabetes, raising the possibility that systemic pathology associated with PTSD might be identified by metabolomic analysis of blood. We sought to identify metabolites that are altered in male combat veterans with PTSD. In this case-control study, we compared metabolomic profiles from age-matched male combat trauma-exposed veterans from the Iraq and Afghanistan conflicts with PTSD (n = 52) and without PTSD (n = 51) ('Discovery group'). An additional group of 31 PTSD-positive and 31 PTSD-negative male combat-exposed veterans was used for validation of these findings ('Test group'). Plasma metabolite profiles were measured in all subjects using ultrahigh performance liquid chromatography/tandem mass spectrometry and gas chromatography/mass spectrometry. We identified key differences between PTSD subjects and controls in pathways related to glycolysis and fatty acid uptake and metabolism in the initial 'Discovery group', consistent with mitochondrial alterations or dysfunction, which were also confirmed in the 'Test group'. Other pathways related to urea cycle and amino acid metabolism were different between PTSD subjects and controls in the 'Discovery' but not in the smaller 'Test' group. These metabolic differences were not explained by comorbid major depression, body mass index, blood glucose, hemoglobin A1c, smoking, or use of analgesics, antidepressants, statins, or anti-inflammatories. These data show replicable, wide-ranging changes in the metabolic profile of combat-exposed males with PTSD, with a suggestion of mitochondrial alterations or dysfunction, that may contribute to the behavioral and somatic phenotypes associated with this disease.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0213839PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6422302PMC
December 2019

Dyspigmented hypertrophic scars: Beyond skin color.

Pigment Cell Melanoma Res 2019 09 5;32(5):643-656. Epub 2019 Apr 5.

Firefighters' Burn and Surgical Research Laboratory, MedStar Health Research Institute, Washington, District of Columbia.

Although pigment synthesis is well understood, relevant mechanisms of psychologically debilitating dyspigmentation in nascent tissue after cutaneous injuries are still unknown. Here, differences in genomic transcription of hyper- and hypopigmented tissue relative to uninjured skin were investigated using a red Duroc swine scar model. Transcription profiles differed based on pigmentation phenotypes with a trend of more upregulation or downregulation in hyper- or hypopigmented scars, respectively. Ingenuity Pathway Analysis of significantly modulated genes in both pigmentation phenotypes showed pathways related to redox, metabolic, and inflammatory responses were more present in hypopigmented samples, while those related to stem cell development differentiation were found mainly in hyperpigmented samples. Cell-cell and cell-extracellular matrix interactions and inflammation responses were predicted (z-score) active in hyperpigmented and inactive in hypopigmented. The proinflammatory high-mobility group box 1 pathway showed the opposite trend. Analysis of differentially regulated mutually exclusive genes showed an extensive presence of metabolic, proinflammatory, and oxidative stress pathways in hypopigmented scars, while melanin synthesis, glycosaminoglycans biosynthesis, and cell differentiation pathways were predominant in hyperpigmented scar. Several potential therapeutic gene targets have been identified.
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http://dx.doi.org/10.1111/pcmr.12780DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6697599PMC
September 2019

Metabolomic analyses reveal lipid abnormalities and hepatic dysfunction in non-human primate model for Yersinia pestis.

Metabolomics 2018 12 29;15(1). Epub 2018 Dec 29.

US Army Center for Environmental Health Research, 568 Doughten Drive, Fort Detrick, MD, 21702, USA.

Introduction: Pneumonic plague is caused by the aerosolized form of Yersinia pestis and is a highly virulent infection with complex clinical consequences, and without treatment, the fatality rate approaches 100%. The exact mechanisms of disease progression are unclear, with limited work done using metabolite profiling to study disease progression.

Objective: The aim of this pilot study was to profile the plasma metabolomics in an animal model of Y. pestis infection.

Methods: In this study, African Green monkeys were challenged with the highly virulent, aerosolized Y. pestis strain CO92, and untargeted metabolomics profiling of plasma was performed using liquid and gas chromatography with mass spectrometry.

Results: At early time points post-exposure, we found significant increases in polyunsaturated, long chain fatty acid metabolites with p values ranging from as low as 0.000001 (ratio = 1.94) for the metabolite eicosapentaenoate to 0.04 (ratio = 1.36) for the metabolite adrenate when compared to time-matched controls. Multiple acyl carnitines metabolites were increased at earlier time points and could be a result of fatty acid oxidation defects with p values ranging from as low as 0.00001 (ratio = 2.95) for the metabolite octanoylcarnitine to 0.04 (ratio = 1.33) for metabolite deoxycarnitine when compared to time-matched controls. Dicarboxylic acids are important metabolic products of fatty acids oxidation, and when compared to time matched controls, were higher at earlier time points where metabolite tetradecanedioate has a ratio of 4.09 with significant p value of 0.000002 and adipate with a ratio of 1.12 and p value of 0.004. The metabolites from lysolipids (with significant p values ranging from 0.00006 for 1-oleoylglycerophosphoethanolamine to 0.04 for 1-stearoylglycerophosphoethanolamine and a ratio of 0.47 and 0.78, respectively) and bile acid metabolism (with significant p values ranging from 0.02 for cholate to 0.04 for deoxycholate and a ratio of 0.39 and 0.66, respectively) pathways were significantly lower compared to their time-matched controls during the entire course of infection. Metabolite levels from amino acid pathways were disrupted, and a few from the leucine, isoleucine and valine pathway were significantly higher (p values ranging from 0.002 to 0.04 and ratios ranging from 1.3 to 1.5, respectively), whereas metabolites from the urea cycle, arginine and proline pathways were significantly lower (p values ranging from 0.00008 to 0.02 and ratios ranging from 0.5 to 0.7, respectively) during the course of infection.

Conclusions: The involvement of several lipid pathways post-infection suggested activation of pathways linked to inflammation and oxidative stress. Metabolite data further showed increased energy demand, and multiple metabolites indicated potential hepatic dysfunction. Integration of blood metabolomics and transcriptomics data identified linoleate as a core metabolite with cross-talk with multiple genes from various time points. Collectively, the data from this study provided new insights into the mechanisms of Y. pestis pathogenesis that may aid in development of therapeutics.
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http://dx.doi.org/10.1007/s11306-018-1457-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6311182PMC
December 2018

The responses of lungs and adjacent lymph nodes in responding to Yersinia pestis infection: A transcriptomic study using a non-human primate model.

PLoS One 2019 21;14(2):e0209592. Epub 2019 Feb 21.

US Army Center for Environmental Health Research, Fort Detrick, MD, United States of America.

Initiation of treatment during the pre-symptomatic phase of Yersinia pestis (Y. pestis) infection is particularly critical. The rapid proliferation of Y. pestis typically couples with the manifestation of common flu-like early symptoms that often misguides the medical intervention. Our study used African green monkeys (AGM) that did not exhibit clear clinical symptoms for nearly two days after intranasal challenge with Y. pestis and succumbed within a day after showing the first signs of clinical symptoms. The lung, and mediastinal and submandibular lymph nodes (LN) accumulated significant Y. pestis colonization immediately after the intranasal challenge. Hence, organ-specific molecular investigations are deemed to be the key to elucidating mechanisms of the initial host response. Our previous study focused on the whole blood of AGM, and we found early perturbations in the ubiquitin-microtubule-mediated host defense. Altered expression of the genes present in ubiquitin and microtubule networks indicated an early suppression of these networks in the submandibular lymph nodes. In concert, the upstream toll-like receptor signaling and downstream NFκB signaling were inhibited at the multi-omics level. The inflammatory response was suppressed in the lungs, submandibular lymph nodes and mediastinal lymph nodes. We posited a causal chain of molecular mechanisms that indicated Y. pestis was probably able to impair host-mediated proteolysis activities and evade autophagosome capture by dysregulating both ubiquitin and microtubule networks in submandibular lymph nodes. Targeting these networks in a submandibular LN-specific and time-resolved fashion could be essential for development of the next generation therapeutics for pneumonic plague.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0209592PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6383991PMC
October 2019

Functional Heatmap: an automated and interactive pattern recognition tool to integrate time with multi-omics assays.

BMC Bioinformatics 2019 Feb 15;20(1):81. Epub 2019 Feb 15.

Integrative Systems Biology Program, US Army Center for Environmental Health Research, Fort Detrick, Frederick, MD, 21702-5010, USA.

Background: Life science research is moving quickly towards large-scale experimental designs that are comprised of multiple tissues, time points, and samples. Omic time-series experiments offer answers to three big questions: what collective patterns do most analytes follow, which analytes follow an identical pattern or synchronize across multiple cohorts, and how do biological functions evolve over time. Existing tools fall short of robustly answering and visualizing all three questions in a unified interface.

Results: Functional Heatmap offers time-series data visualization through a Master Panel page, and Combined page to answer each of the three time-series questions. It dissects the complex multi-omics time-series readouts into patterned clusters with associated biological functions. It allows users to identify a cascade of functional changes over a time variable. Inversely, Functional Heatmap can compare a pattern with specific biology respond to multiple experimental conditions. All analyses are interactive, searchable, and exportable in a form of heatmap, line-chart, or text, and the results are easy to share, maintain, and reproduce on the web platform.

Conclusions: Functional Heatmap is an automated and interactive tool that enables pattern recognition in time-series multi-omics assays. It significantly reduces the manual labour of pattern discovery and comparison by transferring statistical models into visual clues. The new pattern recognition feature will help researchers identify hidden trends driven by functional changes using multi-tissues/conditions on a time-series fashion from omic assays.
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http://dx.doi.org/10.1186/s12859-019-2657-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377781PMC
February 2019

PanoromiX: a time-course network medicine platform integrating molecular assays and pathophenotypic data.

BMC Bioinformatics 2018 Nov 29;19(1):458. Epub 2018 Nov 29.

Integrative Systems Biology Program, US Army Center for Environmental Health Research, 568 Doughten Drive, Fort Detrick, MD, 21702-5010, USA.

Background: Network medicine aims to map molecular perturbations of any given diseases onto complex networks with functional interdependencies that underlie a pathological phenotype. Furthermore, investigating the time dimension of disease progression from a network perspective is key to gaining key insights to the disease process and to identify diagnostic or therapeutic targets. Existing platforms are ineffective to modularize the large complex systems into subgroups and consolidate heterogeneous data to web-based interactive animation.

Results: We have developed PanoromiX platform, a data-agnostic dynamic interactive visualization web application, enables the visualization of outputs from genome based molecular assays onto modular and interactive networks that are correlated with any pathophenotypic data (MRI, Xray, behavioral, etc.) over a time course all in one pane. As a result, PanoromiX reveals the complex organizing principles that orchestrate a disease-pathology from a gene regulatory network (nodes, edges, hubs, etc.) perspective instead of snap shots of assays. Without extensive programming experience, users can design, share, and interpret their dynamic networks through the PanoromiX platform with rich built-in functionalities.

Conclusions: This emergent tool of network medicine is the first to visualize the interconnectedness of tailored genome assays to pathological networks and phenotypes for cells or organisms in a data-agnostic manner. As an advanced network medicine tool, PanoromiX allows monitoring of panel of biomarker perturbations over the progression of diseases, disease classification based on changing network modules that corresponds to specific patho-phenotype as opposed to clinical symptoms, systematic exploration of complex molecular interactions and distinct disease states via regulatory network changes, and the discovery of novel diagnostic and therapeutic targets.
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http://dx.doi.org/10.1186/s12859-018-2494-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6267067PMC
November 2018