Multi-domain potential biomarkers for post-traumatic stress disorder (PTSD) severity in recent trauma survivors.
Ontology highlight
ABSTRACT: Contemporary symptom-based diagnosis of post-traumatic stress disorder (PTSD) largely overlooks related neurobehavioral mechanisms and relies entirely on subjective interpersonal reporting. Previous studies associating biomarkers with PTSD have mostly used symptom-based diagnosis as the main outcome measure, disregarding the wide variability and richness of PTSD phenotypical features. Here, we aimed to computationally derive potential biomarkers that could efficiently differentiate PTSD subtypes among recent trauma survivors. A three-staged semi-unsupervised method ("3C") was used to firstly categorize individuals by current PTSD symptom severity, then derive clusters based on clinical features related to PTSD (e.g. anxiety and depression), and finally to classify participants' cluster membership using objective multi-domain features. A total of 256 features were extracted from psychometrics, cognitive functioning, and both structural and functional MRI data, obtained from 101 adult civilians (age = 34.80 ± 11.95; 51 females) evaluated within 1 month of trauma exposure. The features that best differentiated cluster membership were assessed by importance analysis, classification tree, and ANOVA. Results revealed that entorhinal and rostral anterior cingulate cortices volumes (structural MRI domain), in-task amygdala's functional connectivity with the insula and thalamus (functional MRI domain), executive function and cognitive flexibility (cognitive testing domain) best differentiated between two clusters associated with PTSD severity. Cross-validation established the results' robustness and consistency within this sample. The neural and cognitive potential biomarkers revealed by the 3C analytics offer objective classifiers of post-traumatic morbidity shortly following trauma. They also map onto previously documented neurobehavioral mechanisms associated with PTSD and demonstrate the usefulness of standardized and objective measurements as differentiating clinical sub-classes shortly after trauma.
Project description:Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder. It can be difficult to discern the symptoms of PTSD and obtain an accurate diagnosis. Different magnetic resonance imaging (MRI) modalities focus on different aspects, which may provide complementary information for PTSD discrimination. However, none of the published studies assessed the diagnostic potential of multimodal MRI in identifying individuals with and without PTSD. In the current study, we investigated whether the complementary information conveyed by multimodal MRI scans could be combined to improve PTSD classification performance. Structural and resting-state functional MRI (rs-fMRI) scans were conducted on 17 PTSD patients, 20 trauma-exposed controls without PTSD (TEC) and 20 non-traumatized healthy controls (HC). Gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and regional homogeneity were extracted as classification features, and in order to integrate the information of structural and functional MRI data, the extracted features were combined by a multi-kernel combination strategy. Then a support vector machine (SVM) classifier was trained to distinguish the subjects at individual level. The performance of the classifier was evaluated using the leave-one-out cross-validation (LOOCV) method. In the pairwise comparison of PTSD, TEC, and HC groups, classification accuracies obtained by the proposed approach were 2.70, 2.50, and 2.71% higher than the best single feature way, with the accuracies of 89.19, 90.00, and 67.57% for PTSD vs. HC, TEC vs. HC, and PTSD vs. TEC respectively. The proposed approach could improve PTSD identification at individual level. Additionally, it provides preliminary support to develop the multimodal MRI method as a clinical diagnostic aid.
Project description:Although functional impairment typically improves during evidence-based psychotherapies (EBPs) for borderline personality disorder (BPD), functional levels often remain suboptimal after treatment. The present pilot study evaluated whether and how integrating PTSD treatment into an EBP for BPD would improve functional outcomes. Participants were 26 women with BPD, PTSD, and recent suicidal and/or self-injurious behavior who were randomized to receive one year of Dialectical Behavior Therapy (DBT) or DBT with the DBT Prolonged Exposure (DBT PE) protocol for PTSD. Five domains of functioning were assessed at 4-month intervals during treatment and at 3-months post-treatment. DBT + DBT PE was superior to DBT in improving global social adjustment, health-related quality of life, and achieving good global functioning, but not interpersonal problems or quality of life. Results of time-lagged mixed effects models indicated that, across both treatments, reductions in PTSD severity significantly predicted subsequent improvement in global social adjustment, global functioning, and health-related quality of life, whereas reductions in post-traumatic cognitions significantly predicted later improvement in all functional outcomes except global social adjustment. These findings provide preliminary evidence supporting the role of change in PTSD severity and trauma-related cognitions as active mechanisms in improving functional outcomes among individuals with BPD and PTSD.
Project description:Six hundred and one patients, who sustained injuries in militant activities, admitted during a 7 month period to a zonal referral hospital were studied. The majority, 54.6% from the Armed Forces and 38.8% from the para-military forces, were in the age group of 22-53 years. There were 40 (6.7%) civilian casualties. These were in the age group of 20-45 years. A large number (75.7%) of the casualties manifested with post-traumatic stress symptoms. 24.3% of them were rated as post-traumatic stress disorder. Six months follow-up revealed persistence of post-traumatic stress disorder in 17.1% of the cases. By one year, 42.1% who responded to the follow-up letters had persistence of post-traumatic stress disorder in 4.95%. Early recognition of this psychic trauma and preventive strategies are discussed.
Project description:Early intervention following exposure to a traumatic life event could change the clinical path from the development of post traumatic stress disorder (PTSD) to recovery, hence the interest in early detection and underlying biological mechanisms involved in the development of post traumatic sequelae. We introduce a novel end-to-end neural network that employs resting-state and task-based functional MRI (fMRI) datasets, obtained one month after trauma exposure, to predict PTSD symptoms at one-, six- and fourteen-months after the exposure. FMRI data, as well as PTSD status and symptoms, were collected from adults at risk for PTSD development, after admission to emergency room following a traumatic event. Our computational method utilized a per-region encoder to extract brain regions embedding, which were subsequently updated by applying the algorithmic technique of pairwise attention. The affinities obtained between each pair of regions were combined to create a pairwise co-activation map used to perform multi-label classification. The results demonstrate that the novel method's performance in predicting PTSD symptoms, in a prospective manner, outperforms previous analytical techniques reported in the fMRI literature, all trained on the same dataset. We further show a high predictive ability for predicting PTSD symptom clusters and PTSD persistence. To the best of our knowledge, this is the first deep learning method applied on fMRI data with respect to prospective clinical outcomes, to predict PTSD status, severity and symptom clusters. Future work could further delineate the mechanisms that underlie such a prediction, and potentially improve single patient characterization.
Project description:Post-traumatic stress disorder (PTSD) can become a chronic and severely disabling condition resulting in a reduced quality of life and increased economic burden. The disorder is directly related to exposure to a traumatic event, e.g., a real or threatened injury, death, or sexual assault. Extensive research has been done on the neurobiological alterations underlying the disorder and its related phenotypes, revealing brain circuit disruption, neurotransmitter dysregulation, and hypothalamic-pituitary-adrenal (HPA) axis dysfunction. Psychotherapy remains the first-line treatment option for PTSD given its good efficacy, although pharmacotherapy can also be used as a stand-alone or in combination with psychotherapy. In order to reduce the prevalence and burden of the disorder, multilevel models of prevention have been developed to detect the disorder as early as possible and to reduce morbidity in those with established diseases. Despite the clinical grounds of diagnosis, attention is increasing to the discovery of reliable biomarkers that can predict susceptibility, aid diagnosis, or monitor treatment. Several potential biomarkers have been linked with pathophysiological changes related to PTSD, encouraging further research to identify actionable targets. This review highlights the current literature regarding the pathophysiology, disease development models, treatment modalities, and preventive models from a public health perspective, and discusses the current state of biomarker research.
Project description:Traumatic birth experiences may lead to serious psychological impairment. Recent studies show that a considerable number of women can develop post-traumatic stress disorder (PTSD), in some cases in a subsyndromal form. Until now, the possibility that postpartum psychological symptoms might be a continuum of a pre-existing disorder in pregnancy has rarely been considered. This study therefore aimed to evaluate the proportion of women who develop post-traumatic stress disorder as a result of childbirth. Materials and Methods: 56 multiparous women were recruited for the study. The diagnosis of PTSD was made according to the criteria for psychological disorders in the DSM-IV (Diagnostics and Statistical Manual of Mental Disorders). The data were collected in structured interviews in the 30th to 38th week of gestation and in the 6th week post partum. Results: Of the 56 women participating, 52 (93?%) completed the survey. Uncontrolled results showed that 21.15?% of the multiparous women met the full diagnostic PTSD criteria in the 6th week post partum. After the exclusion of all cases already characterised by all criteria or a subsyndromal form of PTSD caused by previous traumatisation, the PTSD rate was below 8?% at 6 weeks postpartum (=?incidence rate of PTSD post partum). Conclusions: The present study is the first prospective longitudinal study to demonstrate the occurrence of full criteria PTSD in multiparous women as a result of childbirth after having excluded pre-existing PTSD. The results of our study show a high prevalence rate of PTSD during pregnancy. A number of women report all aspects of post-traumatic stress disorder as a result of childbirth.
Project description:Mitochondrial metabolism is increasingly implicated in psychopathologies and mood disorders, including post-traumatic stress disorder (PTSD). We recently reported that mice exposed to a novel paradigm for the induction of PTSD-like behavior displayed reduced mitochondrial electron transport chain (mtETC) complex activity as well as decreased multi-system fatty acid oxidation (FAO) flux. Based on these results, we hypothesized that stressed and PTSD-like animals would display evidence of metabolic reprogramming in both cerebellum and plasma consistent with increased energetic demand, mitochondrial metabolic reprogramming, and increased oxidative stress. We performed targeted metabolomics in both cerebellar tissue and plasma, as well as untargeted nuclear magnetic resonance (NMR) spectroscopy in the cerebellum of 6 PTSD-like and 7 resilient male mice as well as 7 trauma-naïve controls. We identified numerous differences in amino acids and tricarboxylic acid (TCA) cycle metabolite concentrations in the cerebellum and plasma consistent with altered mitochondrial energy metabolism in trauma exposed and PTSD-like animals. Pathway analysis identified metabolic pathways with significant metabolic pathway shifts associated with trauma exposure, including the tricarboxylic acid cycle, pyruvate, and branched-chain amino acid metabolism in both cerebellar tissue and plasma. Altered glutamine and glutamate metabolism, and arginine biosynthesis was evident uniquely in cerebellar tissue, while ketone body levels were modified in plasma. Importantly, we also identified several cerebellar metabolites (e.g. choline, adenosine diphosphate, beta-alanine, taurine, and myo-inositol) that were sufficient to discriminate PTSD-like from resilient animals. This multilevel analysis provides a comprehensive understanding of local and systemic metabolite fingerprints associated with PTSD-like behavior, and subsequently altered brain bioenergetics. Notably, several transformed metabolic pathways observed in the cerebellum were also reflected in plasma, connecting central and peripheral biosignatures of PTSD-like behavior. These preliminary findings could direct further mechanistic studies and offer insights into potential metabolic interventions, either pharmacological or dietary, to improve PTSD resilience.
Project description:BackgroundAt present there are no objective, biological markers that can be used to reliably identify individuals with post-traumatic stress disorder (PTSD). This study assessed the diagnostic potential of structural magnetic resonance imaging (sMRI) for identifying trauma-exposed individuals with and without PTSD.MethodsMRI scans were acquired from 50 survivors of the Sichuan earthquake of 2008 who had developed PTSD, 50 survivors who had not developed PTSD and 40 healthy controls who had not been exposed to the earthquake. Support vector machine (SVM), a multivariate pattern recognition technique, was used to develop an algorithm that distinguished between the three groups at an individual level. The accuracy of the algorithm and its statistical significance were estimated using leave-one-out cross-validation and permutation testing.ResultsWhen survivors with PTSD were compared against healthy controls, both grey and white matter allowed discrimination with an accuracy of 91% (p < 0.001). When survivors without PTSD were compared against healthy controls, the two groups could be discriminated with accuracies of 76% (p < 0.001) and 85% (p < 0.001) based on grey and white matter, respectively. Finally, when survivors with and without PTSD were compared directly, grey matter allowed discrimination with an accuracy of 67% (p < 0.001); in contrast the two groups could not be distinguished based on white matter.ConclusionsThese results reveal patterns of neuroanatomical alterations that could be used to inform the identification of trauma survivors with and without PTSD at the individual level, and provide preliminary support to the development of SVM as a clinically useful diagnostic aid.
Project description:BackgroundLow hippocampal volume could serve as an early risk factor for posttraumatic stress disorder (PTSD) in interaction with other brain anomalies of developmental origin. One such anomaly may well be the presence of a large cavum septum pellucidum (CSP), which has been loosely associated with PTSD. We performed a longitudinal prospective study of recent trauma survivors. We hypothesized that at 1 month after trauma exposure the relation between hippocampal volume and PTSD symptom severity will be moderated by CSP volume, and that this early interaction will account for persistent PTSD symptoms at subsequent time points.MethodsOne hundred seventy-one adults (87 women, average age 34.22 years [range, 18-65 years of age]) who were admitted to a general hospital's emergency department after a traumatic event underwent clinical assessment and structural magnetic resonance imaging within 1 month after trauma. Follow-up clinical evaluations were conducted at 6 (n = 97) and 14 (n = 78) months after trauma. Hippocampal and CSP volumes were measured automatically by FreeSurfer software and verified manually by a neuroradiologist (D.N.).ResultsAt 1 month after trauma, CSP volume significantly moderated the relation between hippocampal volume and PTSD severity (p = .026), and this interaction further predicted symptom severity at 14 months posttrauma (p = .018). Specifically, individuals with a smaller hippocampus and larger CSP at 1 month posttrauma showed more severe symptoms at 1 and 14 months after trauma exposure.ConclusionsOur study provides evidence for an early neuroanatomical risk factors for PTSD, which could also predict the progression of the disorder in the year after trauma exposure. Such a simple-to-acquire neuroanatomical signature for PTSD could guide early management as well as long-term monitoring.