Blunted Nocturnal Salivary Melatonin Secretion Profiles in Military-Related Posttraumatic Stress Disorder.

Background: Sleep disturbances are a hallmark of posttraumatic stress disorder (PTSD), yet few studies have evaluated the role of dysregulated endogenous melatonin secretion in this condition. Methods: This study compared the sleep quality and nocturnal salivary melatonin profiles of Canadian Armed Forces (CAF) personnel diagnosed with PTSD, using the Clinician Administered PTSD Scale (CAPS score ≥50), with two healthy CAF control groups; comprising, a "light control" (LC) group with standardized evening light exposure and "normal control" (NC) group without light restriction. Participants were monitored for 1-week using wrist actigraphy to assess sleep quality, and 24-h salivary melatonin levels were measured (every 2h) by immunoassay on the penultimate day in a dim-light (< 5 lux) laboratory environment. Results: A repeated measures design showed that mean nocturnal melatonin concentrations for LC were higher than both NC (p = .03) and PTSD (p = .003) with no difference between PTSD and NC. Relative to PTSD, NC had significantly higher melatonin levels over a 4-h period (01 to 05 h), whereas the LC group had higher melatonin levels over an 8-h period (23 to 07 h). Actigraphic sleep quality parameters were not different between healthy controls and PTSD patients, likely due to the use of prescription sleep medications in the PTSD group. Conclusions: These results indicate that PTSD is associated with blunted nocturnal melatonin secretion, which is consistent with previous findings showing lower melatonin after exposure to trauma and suggestive of severe chronodisruption. Future studies targeting the melatonergic system for therapeutic intervention may be beneficial for treatment-resistant PTSD.

Machine learning multivariate pattern analysis predicts classification of posttraumatic stress disorder and its dissociative subtype: a multimodal neuroimaging approach.

BACKGROUND: The field of psychiatry would benefit significantly from developing objective biomarkers that could facilitate the early identification of heterogeneous subtypes of illness. Critically, although machine learning pattern recognition methods have been applied recently to predict many psychiatric disorders, these techniques have not been utilized to predict subtypes of posttraumatic stress disorder (PTSD), including the dissociative subtype of PTSD (PTSD + DS). METHODS: Using Multiclass Gaussian Process Classification within PRoNTo, we examined the classification accuracy of: (i) the mean amplitude of low-frequency fluctuations (mALFF; reflecting spontaneous neural activity during rest); and (ii) seed-based amygdala complex functional connectivity within 181 participants [PTSD (n = 81); PTSD + DS (n = 49); and age-matched healthy trauma-unexposed controls (n = 51)]. We also computed mass-univariate analyses in order to observe regional group differences [false-discovery-rate (FDR)-cluster corrected p < 0.05, k = 20]. RESULTS: We found that extracted features could predict accurately the classification of PTSD, PTSD + DS, and healthy controls, using both resting-state mALFF (91.63% balanced accuracy, p < 0.001) and amygdala complex connectivity maps (85.00% balanced accuracy, p < 0.001). These results were replicated using independent machine learning algorithms/cross-validation procedures. Moreover, areas weighted as being most important for group classification also displayed significant group differences at the univariate level. Here, whereas the PTSD + DS group displayed increased activation within emotion regulation regions, the PTSD group showed increased activation within the amygdala, globus pallidus, and motor/somatosensory regions. CONCLUSION: The current study has significant implications for advancing machine learning applications within the field of psychiatry, as well as for developing objective biomarkers indicative of diagnostic heterogeneity.

A review of the relation between dissociation, memory, executive functioning and social cognition in military members and civilians with neuropsychiatric conditions.

Dissociative experiences, involving altered states of consciousness, have long been understood as a consequence or response to traumatic experiences, where a reduced level of consciousness may aid in survival during and after a traumatic event. Indeed, the dissociative subtype of post-traumatic stress disorder (PTSD-DS) was added recently to the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5). Dissociative symptoms are present across a host of neuropsychiatric conditions, including PTSD, psychotic spectrum illnesses, anxiety and mood disorders. Transdiagnostically, the presence of dissociative symptoms is associated with a greater illness burden and reduced treatment outcomes. Critically, dissociative symptoms are related to impaired performance on measures of attention, executive functioning, memory, and social cognition and may contribute to the widespread cognitive dysfunction observed across psychiatric illnesses. Despite this knowledge, the relation between dissociative symptoms and reduced cognitive function remains poorly understood. Here, we review the evidence linking dissociative symptoms to cognitive dysfunction across neuropsychiatric disorders. In addition, we explore two potential neurobiological mechanisms that may underlie the relation between dissociative symptoms and cognitive dysfunction in trauma-related neuropsychiatric conditions. Specifically, we hypothesize that: 1) functional sensory deafferentation at the level of the thalamus, as observed in the defence cascade model of dissociation, may underlie reduced attention and arousal leading to progressive cognitive dysfunction and; 2) altered functional connectivity between key brain networks implicated in cognitive functioning may represent a critical neurobiological mechanism linking dissociative symptoms and cognitive dysfunction in patients with PTSD-DS and transdiagnostically.

Disturbed EEG sleep, paranoid cognition and somatic symptoms identify veterans with post-traumatic stress disorder.

BACKGROUND: Chronic post-traumatic stress disorder (PTSD) behavioural symptoms and medically unexplainable somatic symptoms are reported to occur following the stressful experience of military combatants in war zones. AIMS: To determine the contribution of disordered EEG sleep physiology in those military combatants who have unexplainable physical symptoms and PTSD behavioural difficulties following war-zone exposure. METHOD: This case-controlled study compared 59 veterans with chronic sleep disturbance with 39 veterans with DSM-IV and clinician-administered PTSD Scale diagnosed PTSD who were unresponsive to pharmacological and psychological treatments. All had standardised EEG polysomnography, computerised sleep EEG cyclical alternating pattern (CAP) as a measure of sleep stability, self-ratings of combat exposure, paranoid cognition and hostility subscales of Symptom Checklist-90, Beck Depression Inventory and the Wahler Physical Symptom Inventory. Statistical group comparisons employed linear models, logistic regression and chi-square automatic interaction detection (CHAID)-like decision trees. RESULTS: Veterans with PTSD were more likely than those without PTSD to show disturbances in non-rapid eye movement (REM) and REM sleep including delayed sleep onset, less efficient EEG sleep, less stage 4 (deep) non-REM sleep, reduced REM and delayed onset to REM. There were no group differences in the prevalence of obstructive sleep apnoeas/hypopnoeas and periodic leg movements, but sleep-disturbed, non-PTSD military had more EEG CAP sleep instability. Rank order determinants for the diagnosis of PTSD comprise paranoid thinking, onset to REM sleep, combat history and somatic symptoms. Decision-tree analysis showed that a specific military event (combat), delayed onset to REM sleep, paranoid thinking and medically unexplainable somatic pain and fatigue characterise chronic PTSD. More PTSD veterans reported domestic and social misbehaviour. CONCLUSIONS: Military combat, disturbed REM/non-REM EEG sleep, paranoid ideation and medically unexplained chronic musculoskeletal pain and fatigue are key factors in determining PTSD disability following war-zone exposure. DECLARATION OF INTEREST: None. COPYRIGHT AND USAGE: © The Royal College of Psychiatrists 2016. This is an open access article distributed under the terms of the Creative Commons Non-Commercial, No Derivatives (CC BY-NC-ND) license.

Predictors of posttraumatic stress disorder, depression, and suicidal ideation among Canadian Forces personnel in a National Canadian Military Health Survey.

Despite efforts to elucidate the relationship between traumatic event exposure and adverse mental health outcomes, our ability to understand why only some trauma-exposed individuals become emotionally affected remains challenged. The aim of the current study is to determine the relations between social support, religiosity, and number of lifetime traumatic events experienced on past-12 month posttraumatic stress disorder (PTSD), depression, and suicidal ideation (SI) in a nationally representative sample of Canadian Forces personnel. The current study used data from the Canadian Community Health Survey Cycle 1.2 - Canadian Forces Supplement. The impact of a number of predictive and mediating factors was assessed using structural equation modeling. Social support and number of lifetime traumatic events experienced were significant predictors of past-year PTSD, depression, and SI; however PTSD did not mediate the relationship between number of traumatic events and SI nor between social support and SI. Conversely, depression mediated the relationship between number of traumatic events and SI. Possible mechanisms for these findings and their implications are discussed.