Faculty Bibliography

Background: Adverse childhood experiences (ACE) are associated with an increased risk of major depressive disorder (MDD) and hypothalamic-pituitary-adrenal (HPA) axis dysregulation. Within the HPA axis, corticotropin-releasing hormone and vasopressin (AVP) synergistically stimulate the release of adrenocorticotropic hormone, which promotes cortisol release. The cleavage product copeptin is produced during AVP synthesis and is a surrogate marker of AVP release. Children with ACE and young adults with depressive symptoms have higher levels of copeptin than healthy controls. Objective: To uncover the effects of MDD and ACE on copeptin levels in adult females. Methods: We recruited 94 women (mean age: 34.0 ± 3.6 years): 23 with MDD and ACE, 24 with MDD without ACE, 22 with ACE without MDD, and 25 healthy controls. ACE was defined as repeated sexual or physical abuse at least once a month over at least one year before the age of 18 years. MDD was defined by the DSM-IV criteria. Copeptin plasma levels were measured with an immunoluminometric assay. Results: The four groups did not differ in demographic variables. We found a significant negative correlation between body mass index (BMI) and copeptin plasma levels (r = -.21; p = .045). Copeptin plasma levels did not differ between the four groups after controlling for BMI. Conclusion: Neither MDD nor ACE was associated with altered plasma copeptin levels. Thus, copeptin does not seem to play a major role in MDD and ACE in adult females.

BACKGROUND:Visual and auditory signs of patient functioning have long been used for clinical diagnosis, treatment selection, and prognosis. Direct measurement and quantification of these signals can aim to improve the consistency, sensitivity, and scalability of clinical assessment. Currently, we investigate if machine learning-based computer vision (CV), semantic, and acoustic analysis can capture clinical features from free speech responses to a brief interview 1 month post-trauma that accurately classify major depressive disorder (MDD) and posttraumatic stress disorder (PTSD). METHODS:N = 81 patients admitted to an emergency department (ED) of a Level-1 Trauma Unit following a life-threatening traumatic event participated in an open-ended qualitative interview with a para-professional about their experience 1 month following admission. A deep neural network was utilized to extract facial features of emotion and their intensity, movement parameters, speech prosody, and natural language content. These features were utilized as inputs to classify PTSD and MDD cross-sectionally. RESULTS:Both video- and audio-based markers contributed to good discriminatory classification accuracy. The algorithm discriminates PTSD status at 1 month after ED admission with an AUC of 0.90 (weighted average precision = 0.83, recall = 0.84, and f1-score = 0.83) as well as depression status at 1 month after ED admission with an AUC of 0.86 (weighted average precision = 0.83, recall = 0.82, and f1-score = 0.82). CONCLUSIONS:Direct clinical observation during post-trauma free speech using deep learning identifies digital markers that can be utilized to classify MDD and PTSD status.

A better understanding of suicidal behavior is important to detect suicidality in at-risk populations such as patients with borderline personality disorder (BPD), posttraumatic stress disorder (PTSD), and major depressive disorder (MDD). Suicidal tendencies are clinically assessed by verbal thoughts rather than by specifically asking about mental images. This study examines whether imagery and verbal thoughts about suicide occur and differ between patients with BPD with and without comorbid PTSD compared to patients with MDD (clinical controls). All patient groups experienced suicide-related images. Patients with BPD with comorbid PTSD reported significantly more vivid images than patients with MDD. Severity of suicidal ideation, number of previous suicide attempts, and childhood traumata were significantly associated with suicidal imagery across all patient groups. The authors demonstrate for the first time that suicide-related mental imagery occurs in BPD and is associated with suicidal ideation. This finding highlights the importance of assessing mental imagery related to suicide in clinical practice.

Impaired cognitive functioning constitutes an important symptom of major depressive disorder (MDD), potentially associated with elevated cortisol levels. Adverse childhood experiences (ACE) enhance the risk for MDD and can contribute to disturbances in the stress systems, including cortisol and cognitive functions. In healthy participants, cortisol administration as well as acute stress can affect cognitive performance. In the current study, we tested cognitive performance in MDD patients with (N = 32) and without (N = 52) ACE and healthy participants with (N = 22) and without (N = 37) ACE after psychosocial stress induction (Trier Social Stress Test, TSST) and a control condition (Placebo-TSST). MDD predicted lower performance in verbal learning and both selective and sustained attention, while ACE predicted lower performance in psychomotoric speed and working memory. There were no interaction effects of MDD and ACE. After stress, MDD patients were more likely to show lower performance in working memory as well as in selective and sustained attention compared with participants without MDD. Individuals with ACE were more likely to show lower performance in verbal memory after stress compared with individuals without ACE. Our results indicate negative effects of MDD and ACE on distinct cognitive domains. Furthermore, MDD and/or ACE seem to enhance susceptibility for stress-related cognitive impairments.

Annually, approximately 30 million patients are discharged from the emergency department (ED) after a traumatic event¹. These patients are at substantial psychiatric risk, with approximately 10-20% developing one or more disorders, including anxiety, depression or post-traumatic stress disorder (PTSD)^2-4. At present, no accurate method exists to predict the development of PTSD symptoms upon ED admission after trauma⁵. Accurate risk identification at the point of treatment by ED services is necessary to inform the targeted deployment of existing treatment^6-9 to mitigate subsequent psychopathology in high-risk populations^10,11. This work reports the development and validation of an algorithm for prediction of post-traumatic stress course over 12 months using two independently collected prospective cohorts of trauma survivors from two level 1 emergency trauma centers, which uses routinely collectible data from electronic medical records, along with brief clinical assessments of the patient's immediate stress reaction. Results demonstrate externally validated accuracy to discriminate PTSD risk with high precision. While the predictive algorithm yields useful reproducible results on two independent prospective cohorts of ED patients, future research should extend the generalizability to the broad, clinically heterogeneous ED population under conditions of routine medical care.

Diagnosing autism spectrum disorders (ASD) is a complicated, time-consuming process which is particularly challenging in older individuals. One of the most widely used behavioral diagnostic tools is the Autism Diagnostic Observation Schedule (ADOS). Previous work using machine learning techniques suggested that ASD detection in children can be achieved with substantially fewer items than the original ADOS. Here, we expand on this work with a specific focus on adolescents and adults as assessed with the ADOS Module 4. We used a machine learning algorithm (support vector machine) to examine whether ASD detection can be improved by identifying a subset of behavioral features from the ADOS Module 4 in a routine clinical sample of N = 673 high-functioning adolescents and adults with ASD (n = 385) and individuals with suspected ASD but other best-estimate or no psychiatric diagnoses (n = 288). We identified reduced subsets of 5 behavioral features for the whole sample as well as age subgroups (adolescents vs. adults) that showed good specificity and sensitivity and reached performance close to that of the existing ADOS algorithm and the full ADOS, with no significant differences in overall performance. These results may help to improve the complicated diagnostic process of ASD by encouraging future efforts to develop novel diagnostic instruments for ASD detection based on the identified constructs as well as aiding clinicians in the difficult question of differential diagnosis.

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).

OBJECTIVES:Survivors of acute cardiovascular disease (CVD) events, such as acute coronary syndrome (ACS) and stroke, may experience significant psychological distress during and following the acute event. Long-term adverse effects may follow, including the development of posttraumatic stress disorder (PTSD), increased overall all-cause mortality, and recurrent cardiac events. The goal of this concepts paper is to describe and summarize the rates of adverse psychological outcomes, such as PTSD, following cardiovascular emergencies, to review how these psychological factors are associated with increased risk of future events and long-term health and to provide a theoretical framework for future work. METHODS:A panel of two board-certified emergency physicians, one with a doctorate in experimental psychology, along with one PhD clinical psychologist with expertise in psychoneuroendocrinology were co-authors involved in the paper. Each author used various search strategies (e.g., PubMed, Psycinfo, Cochrane, and Google Scholar) for primary research and reviewed articles related to their section. The references were reviewed and evaluated for relevancy and included based on review by the lead authors RESULTS: A meta-analysis of 24 studies (N > 2,300) found the prevalence of ACS-induced PTSD at nearly 12%, while a meta-analysis of nine studies (N = 1,138) found that 25% of survivors of transient ischemic attack and stroke report PTSD symptoms. The presence of PTSD doubles 3-year risk of CVD/mortality risk in ACS survivors. Cardiac patients treated during periods of ED overcrowding, hallway care, and perceived poor clinician-patient communication appear at greater risk for subsequent PTSD. CONCLUSIONS:Psychological stress is often present in patients undergoing evaluation for acute CVD events. Understanding such associations provides a foundation to appreciate the potential contribution of psychological variables on acute and long-term cardiovascular recovery, while also stimulating future areas of research and discovery.

Background/UNASSIGNED:United Nations (UN) personnel address a diverse range of political, social, and cultural crises throughout the world. Compared with other occupations routinely exposed to traumatic stress, there remains a paucity of research on mental health disorders and access to mental healthcare in this population. To fill this gap, personnel from UN agencies were surveyed for mental health disorders and mental healthcare utilization. Methods/UNASSIGNED:= 17 363) from 11 UN entities completed online measures of generalized anxiety disorder (GAD), major depressive disorder (MDD), posttraumatic stress disorder (PTSD), trauma exposure, mental healthcare usage, and socio-demographic information. Results/UNASSIGNED:Exposure to one or more traumatic events was reported by 36.2% of survey responders. Additionally, 17.9% screened positive for GAD, 22.8% for MDD, and 19.9% for PTSD. Employing multivariable logistic regressions, low job satisfaction, younger age (<35 years of age), greater length of employment, and trauma exposure on or off-duty was significantly associated with all the three disorders. Among individuals screening positive for a mental health disorder, 2.05% sought mental health treatment within and 10.01% outside the UN in the past year. Conclusions/UNASSIGNED:UN personnel appear to be at high risk for trauma exposure and screening positive for a mental health disorder, yet a small percentage screening positive for mental health disorders sought treatment. Despite the mental health gaps observed in this study, additional research is needed, as these data reflect a large sample of convenience and it cannot be determined if the findings are representative of the UN.