Early posttraumatic autonomic and endocrine markers to predict posttraumatic stress symptoms after a preventive intervention with oxytocin

Background: Efficient prevention of posttraumatic stress disorder (PTSD) needs to target individuals with an increased risk for adverse outcome after trauma. Prognostic or prescriptive biological markers assessed early posttrauma may inform personalized treatment recommendations. Objective: To test prognostic and prescriptive effects of early (posttraumatic) autonomic and endocrine markers on PTSD symptom development. Method: Autonomic and endocrine markers were assessed within 12 days posttrauma and before treatment initiation within a randomized placebo-controlled trial investigating repeated oxytocin administration as preventive intervention for PTSD. Linear mixed effects models were used to test the effects of heart rate (variability), resting cortisol, morning cortisol and cortisol awakening response (CAR), cortisol suppression by dexamethasone and resting oxytocin on PTSD symptoms 1.5, 3 and 6 months posttrauma in men (n = 54), women using hormonal contraception (n = 27) and cycling women (n = 19). Results: We found significant prognostic effects of resting oxytocin and cortisol suppression. In women using hormonal contraception, higher oxytocin was associated with higher PTSD symptoms across follow-up. Stronger cortisol suppression by dexamethasone, reflecting increased glucocorticoid receptor feedback sensitivity, was associated with lower PTSD symptoms across follow-up in men, but with higher symptoms at 1.5 months in women using hormonal contraception. These effects were independent of treatment condition. No further significant prognostic or prescriptive effects were detected. Conclusion: Our exploratory study indicates that resting oxytocin and glucocorticoid receptor feedback sensitivity early posttrauma are associated with subsequent PTSD symptom severity. Notably, prognostic effects depended on sex and hormonal contraception use, emphasizing the necessity to consider these factors in biomedical PTSD research

Oxytocin promotes functional coupling between paraventricular nucleus and both sympathetic and parasympathetic cardioregulatory nuclei

The neuropeptide oxytocin (OXT) facilitates prosocial behavior and selective sociality. In the context of stress, OXT also can down-regulate hypothalamic–pituitary–adrenal (HPA) axis activity, leading to consideration of OXT as a potential treatment for many socioaffective disorders. However, the mechanisms through which administration of exogenous OXT modulates social behavior in stressful environmental contexts are not fully understood. Here, we investigate the hypothesis that autonomic pathways are components of the mechanisms through which OXT aids the recruitment of social resources in stressful contexts that may elicit mobilized behavioral responses. Female prairie voles (Microtus ochrogaster) underwent a stressor (walking in shallow water) following pretreatment with intraperitoneal OXT (0.25 mg/kg) or OXT antagonist (OXT-A, 20 mg/kg), and were allowed to recover with or without their sibling cagemate. Administration of OXT resulted in elevated OXT concentrations in plasma, but did not dampen the HPA axis response to a stressor. However, OXT, but not OXT-A, pretreatment prevented the functional coupling, usually seen in the absence of OXT, between paraventricular nucleus (PVN) activity as measured by c-Fos immunoreactivity and HPA output (i.e. corticosterone release). Furthermore, OXT pretreatment resulted in functional coupling between PVN activity and brain regions regulating both sympathetic (i.e. rostral ventrolateral medulla) and parasympathetic (i.e. dorsal vagal complex and nucleus ambiguous) branches of the autonomic nervous system. These findings suggest that OXT increases central neural control of autonomic activity, rather than strictly dampening HPA axis activity, and provides a potential mechanism through which OXT may facilitate adaptive and context-dependent behavioral and physiological responses to stressors

Views on primary prevention of cardiovascular disease - an interview study with Swedish GPs

Background: General practitioners (GPs) have gradually become more involved in the prevention of cardiovascular disease (CVD), both through more frequent prescribing of pharmaceuticals and by giving advice regarding lifestyle factors. Most general practitioners are now faced with decisions about pharmaceutical or non-pharmaceutical treatment for primary prevention every day. The aim of this study was to explore, structure and describe the views on primary prevention of cardiovascular disease in clinical practice among Swedish GPs. Methods: Individual interviews were conducted with 21 GPs in southern Sweden. The interview transcripts were analysed using a qualitative approach, inspired by phenomenography. Results: Two main categories of description emerged during the analysis. One was the degree of reliance on research data regarding the predictability of real risk and the opportunities for primary prevention of CVD. The other was the allocation of responsibility between the patient and the doctor. The GPs showed different views, from being convinced of an actual and predictable risk for the individual to strongly doubting it; from relying firmly on protection from disease by pharmaceutical treatment to strongly questioning its effectiveness in individual cases; and from reliance on prevention of disease by non-pharmaceutical interventions to a total lack of reliance on such measures. Conclusions: The GPs' different views, regarding the rationale for and practical management of primary prevention of CVD, can be interpreted as a reflection of the complexity of patient counselling in primary prevention in clinical practice. The findings have implications for development and implementation of standard treatment guidelines, regarding long-time primary preventive treatment

The @RISK Study: Risk communication for patients with type 2 diabetes: design of a randomised controlled trial

<p>Abstract</p> <p>Background</p> <p>Patients with type 2 diabetes mellitus (T2DM) have an increased risk to develop severe diabetes related complications, especially cardiovascular disease (CVD). The risk to develop CVD can be estimated by means of risk formulas. However, patients have difficulties to understand the outcomes of these formulas. As a result, they may not recognize the importance of changing lifestyle and taking medication in time. Therefore, it is important to develop risk communication methods, that will improve the patients' understanding of risks associated with having diabetes, which enables them to make informed choices about their diabetes care.</p> <p>The aim of this study is to investigate the effects of an intervention focussed on the communication of the absolute 10-year risk to develop CVD on risk perception, attitude and intention to change lifestyle behaviour in patients with T2DM. The conceptual framework of the intervention is based on the Theory of Planned Behaviour and the Self-regulation Theory.</p> <p>Methods</p> <p>A randomised controlled trial will be performed in the Diabetes Care System West-Friesland (DCS), a managed care system. Newly referred T2DM patients of the DCS, younger than 75 years will be eligible for the study. The intervention group will be exposed to risk communication on CVD, on top of standard managed care of the DCS. This intervention consists of a simple explanation on the causes and consequences of CVD, and possibilities for prevention. The probabilities of CVD in 10 year will be explained in natural frequencies and visualised by a population diagram. The control group will receive standard managed care. The primary outcome is appropriateness of risk perception. Secondary outcomes are attitude and intention to change lifestyle behaviour and illness perception. Differences between baseline and follow-up (2 and 12 weeks) between groups will be analysed according to the intention-to-treat principle. The study was powered on 120 patients in each group.</p> <p>Discussion</p> <p>This innovative risk communication method based on two behavioural theories might improve patient's appropriateness of risk perception and attitude concerning lifestyle change. With a better understanding of their CVD risk, patients will be able to make informed choices concerning diabetes care.</p> <p>Trail registration</p> <p>The trial is registered as NTR1556 in the Dutch Trial Register.</p

Assessment of brain age in posttraumatic stress disorder: Findings from the ENIGMA PTSD and brain age working groups

Background: Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. Method: Adult subjects (N = 2229; 56.2% male) aged 18–69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age − chronological age) controlling for chronological age, sex, and scan site. Results: BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. Discussion: Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan

Neuroimaging-Based Classification of PTSD Using Data-Driven Computational Approaches:A Multisite Big Data Study from the ENIGMA-PGC PTSD Consortium

BACKGROUND: Recent advances in data-driven computational approaches have been helpful in devising tools to objectively diagnose psychiatric disorders. However, current machine learning studies limited to small homogeneous samples, different methodologies, and different imaging collection protocols, limit the ability to directly compare and generalize their results. Here we aimed to classify individuals with PTSD versus controls and assess the generalizability using a large heterogeneous brain datasets from the ENIGMA-PGC PTSD Working group.METHODS: We analyzed brain MRI data from 3,477 structural-MRI; 2,495 resting state-fMRI; and 1,952 diffusion-MRI. First, we identified the brain features that best distinguish individuals with PTSD from controls using traditional machine learning methods. Second, we assessed the utility of the denoising variational autoencoder (DVAE) and evaluated its classification performance. Third, we assessed the generalizability and reproducibility of both models using leave-one-site-out cross-validation procedure for each modality.RESULTS: We found lower performance in classifying PTSD vs. controls with data from over 20 sites (60% test AUC for s-MRI, 59% for rs-fMRI and 56% for d-MRI), as compared to other studies run on single-site data. The performance increased when classifying PTSD from HC without trauma history in each modality (75% AUC). The classification performance remained intact when applying the DVAE framework, which reduced the number of features. Finally, we found that the DVAE framework achieved better generalization to unseen datasets compared with the traditional machine learning frameworks, albeit performance was slightly above chance.CONCLUSION: These results have the potential to provide a baseline classification performance for PTSD when using large scale neuroimaging datasets. Our findings show that the control group used can heavily affect classification performance. The DVAE framework provided better generalizability for the multi-site data. This may be more significant in clinical practice since the neuroimaging-based diagnostic DVAE classification models are much less site-specific, rendering them more generalizable.</p

SRH and HrQOL: does social position impact differently on their link with health status?

<p>Abstract</p> <p>Background</p> <p>Self-rated Health (SRH) and health-related quality of life (HRQoL) are used to evaluate health disparities. Like all subjective measures of health, they are dependent on health expectations that are associated with socioeconomic characteristics. It is thus needed to analyse the influence played by socioeconomic position (SEP) on the relationship between these two indicators and health conditions if we aim to use them to study health disparities. Our objective is to assess the influence of SEP on the relationship between physical health status and subjective health status, measured by SRH and HRQoL using the SF-36 scale.</p> <p>Methods</p> <p>We used data from the French National Health Survey. SEP was assessed by years of education and household annual income. Physical health status was measured by functional limitations and chronic low back pain.</p> <p>Results</p> <p>Regardless of their health status, people with lower SEP were more likely than their more socially advantaged counterparts to report poor SRH and poorer HRQoL, using any of the indicators of SEP. The negative impact of chronic low back pain on SRH was relatively greater in people with a high SEP than in those with a low SEP. In contrast, chronic low back pain and functional limitations had less impact on physical and mental component scores of quality of life for socially advantaged men and women.</p> <p>Conclusions</p> <p>Both SRH and HRQoL were lower among those reporting functional limitations or chronic low back pain. However, the change varied according SEP and the measure. In relative term, the negative impact of a given health condition seems to be greater on SRH and lower on HRQoL for people with higher SEP in comparison with people with low SEP. Using SRH could thus decrease socioeconomic differences. In contrast using HRQoL could increase these differences, suggesting being cautious when using these indicators for analyzing health disparities.</p

Intrusive Traumatic Re-Experiencing Domain (ITRED) – Functional Connectivity Feature Classification by the ENIGMA PTSD Consortium

Background Intrusive Traumatic Re-Experiencing Domain (ITRED) was recently introduced as a novel perspective on posttraumatic psychopathology, proposing to focus research of posttraumatic stress disorder (PTSD) on the unique symptoms of intrusive and involuntary re-experiencing of the trauma, namely, intrusive memories, nightmares, and flashbacks. The aim of the present study was to explore ITRED from a neural network connectivity perspective. Methods Data was collected from nine sites taking part in the ENIGMA-PTSD Consortium (n=584) and included itemized PTSD symptoms scores and resting-state functional connectivity (rsFC) data. We assessed the utility of rsFC in classifying PTSD, ITRED-only (no PTSD diagnosis), and Trauma-exposed (TE)-only (no PTSD or ITRED) groups using a machine learning approach, examining well-known networks implicated in PTSD. Random forest classification model was built on a training set using cross-validation (CV), and the averaged CV model performance for classification was evaluated using area-under-the-curve (AUC). The model was tested using a fully independent portion of the data (test dataset), and the test AUC was evaluated. Results RsFC signatures differentiated TE-only participants from PTSD and from ITRED-only participants at about 60% accuracy. Conversely, rsFC signatures did not differentiate PTSD from ITRED-only individuals (45% accuracy). Common features differentiating TE-only participants from PTSD and from ITRED-only participants mainly involved default mode network-related pathways. Some unique features, such as connectivity within the frontal-parietal network, differentiated TE-only participants from one group (PTSD or ITRED-only), but to a lesser extent from the other. Conclusion Neural network connectivity supports ITRED as a novel neurobiologically-based approach to classifying post-trauma psychopathology

Assessment of brain age in posttraumatic stress disorder: Findings from the ENIGMA PTSD and brain age working groups

BACKGROUND: Posttraumatic stress disorder (PTSD) is associated with markers of accelerated aging. Estimates of brain age, compared to chronological age, may clarify the effects of PTSD on the brain and may inform treatment approaches targeting the neurobiology of aging in the context of PTSD. METHOD: Adult subjects (N = 2229; 56.2% male) aged 18-69 years (mean = 35.6, SD = 11.0) from 21 ENIGMA-PGC PTSD sites underwent T1-weighted brain structural magnetic resonance imaging, and PTSD assessment (PTSD+, n = 884). Previously trained voxel-wise (brainageR) and region-of-interest (BARACUS and PHOTON) machine learning pipelines were compared in a subset of control subjects (n = 386). Linear mixed effects models were conducted in the full sample (those with and without PTSD) to examine the effect of PTSD on brain predicted age difference (brain PAD; brain age - chronological age) controlling for chronological age, sex, and scan site. RESULTS: BrainageR most accurately predicted brain age in a subset (n = 386) of controls (brainageR: ICC = 0.71, R = 0.72, MAE = 5.68; PHOTON: ICC = 0.61, R = 0.62, MAE = 6.37; BARACUS: ICC = 0.47, R = 0.64, MAE = 8.80). Using brainageR, a three-way interaction revealed that young males with PTSD exhibited higher brain PAD relative to male controls in young and old age groups; old males with PTSD exhibited lower brain PAD compared to male controls of all ages. DISCUSSION: Differential impact of PTSD on brain PAD in younger versus older males may indicate a critical window when PTSD impacts brain aging, followed by age-related brain changes that are consonant with individuals without PTSD. Future longitudinal research is warranted to understand how PTSD impacts brain aging across the lifespan