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

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

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.

Feasibility and Efficacy of a Resiliency Intervention for the Prevention of Chronic Emotional Distress Among Survivor-Caregiver Dyads Admitted to the Neuroscience Intensive Care Unit: A Randomized Clinical Trial

IMPORTANCE

To our knowledge, there are no evidence-based interventions to prevent chronic emotional distress (ie, depression, anxiety, and posttraumatic stress [PTS]) in critical care survivors and their informal caregivers.

OBJECTIVE

To determine the feasibility and preliminary effect of the novel dyadic resiliency intervention Recovering Together (RT) on reducing symptoms of depression, anxiety, and PTS among hospitalized patients and their informal caregivers.

DESIGN, SETTING, AND PARTICIPANTS

This single-blind, pilot randomized clinical trial of RT vs an educational control was conducted among 58 dyads in which either the survivor or caregiver endorsed clinically significant symptoms of depression, anxiety, or PTS. The study was conducted in the neuroscience intensive care unit at Massachusetts General Hospital. Data were collected from September 2019 to March 2020.

INTERVENTIONS

Both RT and control programs had 6 sessions (2 at bedside and 4 via live video after discharge), and both survivor and caregiver participated together.

MAIN OUTCOMES AND MEASURES

The primary outcomes were feasibility of recruitment and intervention delivery, credibility, and satisfaction. The secondary outcomes included depression and anxiety (measured by the Hospital Depression and Anxiety Scale), PTS (measured by the PTSD Checklist-Civilian Version), and intervention targets (ie, mindfulness, measured by the Cognitive and Affective Mindfulness Scale-Revised; coping, measured by the Measure of Current Status-Part A; and dyadic interpersonal interactions, measured by the Dyadic Relationship Scale). Main outcomes and targets were assessed at baseline, 6 weeks, and 12 weeks.

RESULTS

The 58 dyads were randomized to RT (29 dyads [50.0%]; survivors: mean [SD] age, 49.3 [16.7] years; 9 [31.0%] women; caregivers: mean [SD] age, 52.4 [14.3] years; 22 [75.9%] women) or control (29 dyads [50.0%]; survivors: mean [SD] age, 50.3 [16.4] years; 12 [41.3%] women; caregivers, mean [SD] age, 52.1 [14.9], 17 [58.6%] women). Feasibility (recruitment [76%], randomization [100%], and data collection [83%-100%]), adherence (86%), fidelity (100%; κ = 0.98), satisfaction (RT: 57 of 58 [98%] with scores >6; control: 58 of 58 [100%] with scores >6), credibility (RT: 47 of 58 [81%] with scores >6; control: 46 of 58 [80%] with scores >6), and expectancy (RT: 49 of 58 [85%] with scores >13.5; 51 of 58 [87%] with scores >13.5) exceeded benchmarks set a priori. Participation in RT was associated with statistically and clinically significant improvement between baseline and postintervention in symptoms of depression (among survivors: -4.0 vs -0.6; difference, -3.4; 95% CI, -5.6 to -1.3; P = .002; among caregivers: -3.8 vs 0.6; difference, -4.5; 95% CI, -6.7 to -2.3; P < .001), anxiety (among survivors: -6.0 vs 0.3; difference, -6.3; 95% CI, -8.8 to -3.8; P < .001; among caregivers: -5.0 vs -0.9; difference, -4.1; 95% CI, -6.7 to -1.5, P = .002), and PTS (among survivors: -11.3 vs 1.0; difference, -12.3; 95% CI, -18.1 to -6.5, P < .001; among caregivers, -11.4 vs 5.0; difference, -16.4, 95% CI, -21.8 to -10.9; P < .001). Improvements sustained through the 12-week follow-up visit. We also observed RT-dependent improvement in dyadic interpersonal interactions for survivors (0.2 vs -0.2; difference, 0.4; 95% CI, 0.0 to 0.8; P = .04).

CONCLUSIONS AND RELEVANCE

In this pilot randomized clinical trial, RT was feasible and potentially efficacious in preventing chronic emotional distress in dyads of survivors of the neuroscience intensive care unit and their informal caregivers.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT03694678.

Current methods for stress marker detection in saliva

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Introduction of relevant biomarkers in stress conditions.

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Reference ranges of biomarkers in normal conditions.

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Saliva as easy-accessible specimen.

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Review of analytical methods for biomarker determination in saliva.

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Possibilities for design of point-of-care devices.

Stress and stress-related diseases are leading to drastic consequences in private and professional life. Therefore, the need for stress prevention strategies is of personal and economic interest. Especially during the recent period related to covid-19 outbreak and lock-down, an ongoing discussion of increasing stress etiology is reported. Biomarker analysis may help to assist diagnosis and classification of stress-related diseases and therefore support therapeutical decisions. Due to its non-invasive sampling, the analysis of saliva has become highly attractive compared to the detection methods in other specimen. This review article summarizes the status of research, innovative approaches, and trends. Scientific literature published since 2011 was excerpted with concentration on the detection of up to seven promising marker substances. Most often reported cortisol represents the currently best evaluated stress marker, while norepinephrine (noradrenaline) or its metabolite 3-methoxy-4-hydroxyphenylglycol is also a quite commonly considered stress marker. Other complementary stress marker candidates are testosterone, dehydroepiandrosterone (DHEA) and its sulfonated analogue DHEA-S, alpha-amylase, secretory immunoglobulin A, and chromogranin A. Several working groups are researching in the field of stress marker detection to develop reliable, fast, and affordable methods. Analytical methods reported mainly focused on immunological and electrochemical as well as chromatographic methods hyphenated to mass spectrometric detection to yield the required detection limits.

Application of Systems Engineering Principles and Techniques in Biological Big Data Analytics: A Review

In the past few decades, we have witnessed tremendous advancements in biology, life sciences and healthcare. These advancements are due in no small part to the big data made available by various high-throughput technologies, the ever-advancing computing power, and the algorithmic advancements in machine learning. Specifically, big data analytics such as statistical and machine learning has become an essential tool in these rapidly developing fields. As a result, the subject has drawn increased attention and many review papers have been published in just the past few years on the subject. Different from all existing reviews, this work focuses on the application of systems, engineering principles and techniques in addressing some of the common challenges in big data analytics for biological, biomedical and healthcare applications. Specifically, this review focuses on the following three key areas in biological big data analytics where systems engineering principles and techniques have been playing important roles: the principle of parsimony in addressing overfitting, the dynamic analysis of biological data, and the role of domain knowledge in biological data analytics.

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

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 IC₅₀-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_50-DEX 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 (NR3C1-1F), IC_50-DEX, and proinflammatory cytokines. We noted significant mediation effects of NR3C1-1F 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.

Alterations in Plasma microRNA and Protein Levels in War Veterans with Chronic Mild Traumatic Brain Injury

Blast-related mild traumatic brain injury (mTBI) is considered the "signature" injury of the wars in Iraq and Afghanistan. Identifying biomarkers that could aid in diagnosis and assessment of chronic mTBI are urgently needed, as little progress has been made toward identifying blood-based biomarkers of repetitive mTBI in the chronic state. Addressing this knowledge gap is especially important in the population of military veterans who are receiving assessment and care often years after their last exposure. Circulating microRNAs (miRNAs), especially those encapsulated in extracellular vesicles (EVs), have gained interest as a source of biomarkers for neurological conditions. To identify biomarkers for chronic mTBI, we used next generation sequencing (NGS) to analyze miRNAs in plasma and plasma-derived EVs from 27 Iraq and Afghanistan war veterans with blast-related chronic mTBI, 11 deployed veteran non-TBI controls, and 31 civilian controls. We identified 32 miRNAs in plasma and 45 miRNAs in EVs that significantly changed in the chronic mTBI cohort compared with control groups. These miRNAs were predominantly associated with pathways involved in neuronal function, vascular remodeling, blood-brain barrier integrity, and neuroinflammation. In addition, the plasma proteome was analyzed and showed that the concentrations of C-reactive protein (CRP) and membrane metalloendopeptidase (MME) were elevated in chronic mTBI samples. These plasma miRNAs and proteins could potentially be used as biomarkers and provide insights into the molecular processes associated with the long-term health outcomes associated with blast-related chronic mTBI.

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

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.