Faculty Bibliography
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346
An Electroencephalography Connectomic Profile of Posttraumatic Stress Disorder
OBJECTIVE/UNASSIGNED:The authors sought to identify brain regions whose frequency-specific, orthogonalized resting-state EEG power envelope connectivity differs between combat veterans with posttraumatic stress disorder (PTSD) and healthy combat-exposed veterans, and to determine the behavioral correlates of connectomic differences. METHODS/UNASSIGNED:The authors first conducted a connectivity method validation study in healthy control subjects (N=36). They then conducted a two-site case-control study of veterans with and without PTSD who were deployed to Iraq and/or Afghanistan. Healthy individuals (N=95) and those meeting full or subthreshold criteria for PTSD (N=106) underwent 64-channel resting EEG (eyes open and closed), which was then source-localized and orthogonalized to mitigate effects of volume conduction. Correlation coefficients between band-limited source-space power envelopes of different regions of interest were then calculated and corrected for multiple comparisons. Post hoc correlations of connectomic abnormalities with clinical features and performance on cognitive tasks were conducted to investigate the relevance of the dysconnectivity findings. RESULTS/UNASSIGNED:Seventy-four brain region connections were significantly reduced in PTSD (all in the eyes-open condition and predominantly using the theta carrier frequency). Underconnectivity of the orbital and anterior middle frontal gyri were most prominent. Performance differences in the digit span task mapped onto connectivity between 25 of the 74 brain region pairs, including within-network connections in the dorsal attention, frontoparietal control, and ventral attention networks. CONCLUSIONS/UNASSIGNED:Robust PTSD-related abnormalities were evident in theta-band source-space orthogonalized power envelope connectivity, which furthermore related to cognitive deficits in these patients. These findings establish a clinically relevant connectomic profile of PTSD using a tool that facilitates the lower-cost clinical translation of network connectivity research.
PMID: 31964161
ISSN: 1535-7228
CID: 4273872
Mending broken bonds in military couples using emotionally focused therapy for couples: Tips and discoveries [Case Report]
Military families face specific challenges related to military service, deployments, separations, and coming together. The process of reintegration back to civilian life can be challenged by posttraumatic stress and other readjustment difficulties that can affect not only the veteran but the family as a whole. Strengthening bonds and relationships is an important step in recovery. In this paper, the authors review the application of emotionally focused therapy to couples therapy with military couples and identify factors that can facilitate the therapeutic process with this unique population.
PMID: 31953952
ISSN: 1097-4679
CID: 4264692
Challenging the patient and therapist during evolving phases of a veteran's treatment within a strong public-private partnership [Case Report]
Veterans Health Administration (VA) Medical Centers provide excellent care for many veterans. However, there are a number of veterans who are ineligible or choose not to access mental health treatment at the VA. To meet the needs of those veterans and of military family members, private centers have emerged to fill in gaps where care is unavailable or scarce. This paper describes how one such center, the Steven A. Cohen Military Family Center at NYU Langone Health, partnered with the local VA hospital to give one veteran ineligible for free mental health services the care he desperately needed. The case demonstrates the transformative work that can take place when public-private partnerships are forged and evidence-based treatments can be provided in a flexible way. It also illustrates the complexity of many veterans' presentations, which in this case required the therapist to continually challenge her conceptualization as she and the patient navigated different phases of his treatment.
PMID: 31909832
ISSN: 1097-4679
CID: 4257182
Predeployment neurocognitive functioning predicts postdeployment posttraumatic stress in Army personnel
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/METHODS: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) 2019 APA, all rights reserved).
PMID: 31789568
ISSN: 1931-1559
CID: 4217962
Multi-omic biomarker identification and validation for diagnosing warzone-related post-traumatic stress disorder
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.
PMID: 31501510
ISSN: 1476-5578
CID: 4071472
Individual Patterns of Abnormality in Resting-State Functional Connectivity Reveal Two Data-Driven PTSD Subgroups
OBJECTIVE/UNASSIGNED:A major challenge in understanding and treating posttraumatic stress disorder (PTSD) is its clinical heterogeneity, which is likely determined by various neurobiological perturbations. This heterogeneity likely also reduces the effectiveness of standard group comparison approaches. The authors tested whether a statistical approach aimed at identifying individual-level neuroimaging abnormalities that are more prevalent in case subjects than in control subjects could reveal new clinically meaningful insights into the heterogeneity of PTSD. METHODS/UNASSIGNED:Resting-state functional MRI data were recorded from 87 unmedicated PTSD case subjects and 105 war zone-exposed healthy control subjects. Abnormalities were modeled using tolerance intervals, which referenced the distribution of healthy control subjects as the "normative population." Out-of-norm functional connectivity values were examined for enrichment in cases and then used in a clustering analysis to identify biologically defined PTSD subgroups based on their abnormality profiles. RESULTS/UNASSIGNED:The authors identified two subgroups among PTSD cases, each with a distinct pattern of functional connectivity abnormalities with respect to healthy control subjects. Subgroups differed clinically on levels of reexperiencing symptoms and improved case-control discriminability and were detectable using independently recorded resting-state EEG data. CONCLUSIONS/UNASSIGNED:The results provide proof of concept for the utility of abnormality-based approaches for studying heterogeneity within clinical populations. Such approaches, applied not only to neuroimaging data, may allow detection of subpopulations with distinct biological signatures so that further clinical and mechanistic investigations can be focused on more biologically homogeneous subgroups.
PMID: 31838870
ISSN: 1535-7228
CID: 4243432
Microstate Features Predict Severity of PTSD and Depression Symptoms [Meeting Abstract]
Background: Electroencephalography (EEG) signals consist of topographically defined, stable, and short-lived microstates (Poulsen et al., 2018). Microstates underlie functionally defined networks described in the fMRI literature and play an important role in human cognition. Differences in duration, frequency of occurrence, and transition probabilities of microstates have been found between clinical populations and healthy controls (e.g., Abell et al., 2013).
Method(s): With 504 subjects, the present study is one of the largest investigations of EEG microstates in the literature, and the largest that investigates EEG microstates in clinical populations. The current study includes participants in each of the following populations: Posttraumatic Stress Disorder, Traumatic Brain Injury, Major Depression, and healthy controls. Resting eyes closed EEG recordings were analyzed using the microstate MATLAB toolbox (Poulsen et al., 2018) and custom scripts. Seven discrete microstate classes were identified using a hold-out sample of 40 healthy controls, and the resulting microstate maps were back-fitted to the other participants. Microstate statistics were extracted for each participant and entered into regression analyses with PTSD severity and depression severity as dependent variables.
Result(s): The occurrence, duration, and transition probabilities of multiple microstates significantly predicted PTSD severity (multiple R2 =.19, p =.01), but only certain microstate transition probabilities predicted depression severity (multiple R2 =.18, p =.10). The neural generators of these microstates were determined to provide further insight into these findings.
Conclusion(s): This and future studies can provide promising targets for interventions in an effort to reduce symptom burden in these clinical populations. Supported By: Cohen Veterans Bioscience Keywords: EEG Microstate Analysis, PT
Method(s): With 504 subjects, the present study is one of the largest investigations of EEG microstates in the literature, and the largest that investigates EEG microstates in clinical populations. The current study includes participants in each of the following populations: Posttraumatic Stress Disorder, Traumatic Brain Injury, Major Depression, and healthy controls. Resting eyes closed EEG recordings were analyzed using the microstate MATLAB toolbox (Poulsen et al., 2018) and custom scripts. Seven discrete microstate classes were identified using a hold-out sample of 40 healthy controls, and the resulting microstate maps were back-fitted to the other participants. Microstate statistics were extracted for each participant and entered into regression analyses with PTSD severity and depression severity as dependent variables.
Result(s): The occurrence, duration, and transition probabilities of multiple microstates significantly predicted PTSD severity (multiple R2 =.19, p =.01), but only certain microstate transition probabilities predicted depression severity (multiple R2 =.18, p =.10). The neural generators of these microstates were determined to provide further insight into these findings.
Conclusion(s): This and future studies can provide promising targets for interventions in an effort to reduce symptom burden in these clinical populations. Supported By: Cohen Veterans Bioscience Keywords: EEG Microstate Analysis, PT
EMBASE:2001857639
ISSN: 1873-2402
CID: 4131852
Gene expression profiling of whole blood: A comparative assessment of RNA-stabilizing collection methods
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.
PMID: 31600258
ISSN: 1932-6203
CID: 4129952
International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci
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.
PMID: 31594949
ISSN: 2041-1723
CID: 4130622
American journal of physiology. Endocrinology & metabolism. 2019:317(5):E879-E898.DOI: 10.1152/ajpendo.00065.2019
Mechanistic inferences on metabolic dysfunction in PTSD from an integrated model and multi-omic analysis: Role of glucocorticoid receptor sensitivity
Post-traumatic stress disorder 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 shows increased glycolysis to lactate flux, reduced TCA cycle flux, impaired amino acid and lipid metabolism, insulin resistance, inflammation and hypersensitive HPA-axis. To analyze whether the co-occurrence of multiple metabolic abnormalities are independent, or arises from an underlying regulatory defect, we employed a systems biological approach using an integrated mathematical model and multi-omic 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 data. We combined the metabolomics, neuroendocrine, clinical lab 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, hs-CRP, HOMAIR, GGT, 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.
PMID: 31322414
ISSN: 1522-1555
CID: 4071462
