Stress-related cognitive style is related to volumetric change of the hippocampus and FK506 binding protein 5 polymorphism in post-traumatic stress disorder.

BACKGROUND: Patients with post-traumatic stress disorder (PTSD) show a different stress-related cognitive style compared with healthy controls (HC). The FK506 binding protein 5 gene (FKBP5), one of the PTSD known risk factors, is involved in the stress response through the hypothalamic-pituitary-adrenal axis and brain volumetric alterations. The present study aimed to uncover the neural correlates of stress-related cognitive styles through the analysis of the regional brain volumes and FKBP5 genotype in patients with PTSD compared with HC. METHODS: In this study, 51 patients with PTSD and 94 HC were assessed for stress-related cognitive styles, PTSD symptoms severity, and genotype of FKBP5 single nucleotide polymorphisms, and underwent T1-weighted structural magnetic resonance imaging. Diagnosis-by-genotype interaction for regional brain volumes was examined in 16 brain regions of interest. RESULTS: Patients with PTSD showed significantly higher levels of catastrophizing, ruminative response, and repression, and reduced distress aversion and positive reappraisal compared with HC (p < 0.001). Significant diagnosis-by-genotype interactions for regional brain volumes were observed for bilateral hippocampi and left frontal operculum. A significant positive correlation between the severity of the repression and left hippocampal volume was found in a subgroup of patients with PTSD with FKBP5 rs3800373 (AA genotype) or rs1360780 (CC genotype). CONCLUSIONS: The present study showed the influences of FKBP5 genotype on the distorted cognitive styles in PTSD by measuring the volumetric alteration of hippocampal regions, providing a possible role of the hippocampus and left frontal operculum as significant neurobiological correlates of PTSD.

Clinical Implication of Altered Inhibitory Response in Patients with Post-traumatic Stress Disorder: Electrophysiological Evidence from a Go/Nogo Task.

Inhibitory dysfunction is closely associated to post-traumatic stress disorder (PTSD). The present study investigated the neurophysiological evidence for and the brain regions related to inhibitory dysfunction in PTSD. Fifty patients with PTSD and 63 healthy controls (HCs) participated in a Go/Nogo task combined with electroencephalographic recordings. The N2-P3 complexes of event-related potentials (ERPs) elicited during the Nogo condition were compared between groups. Participants underwent structural magnetic resonance imaging to examine cortical volumes and completed questionnaires. Correlations between altered ERPs and cortical volumes of regions of interest as well as psychological symptoms were analysed. Nogo-N2 latencies at five electrode sites (Fz, FCz, Cz, CPz, and Pz) were significantly delayed in patients with PTSD compared to HCs. Nogo-N2 latency had a significant negative correlation with the volume of gyrus in the inferior frontal cortex, orbitofrontal cortex, amygdala, and medial prefrontal cortex. Nogo-N2 latency was significantly and positively correlated with catastrophizing, anxiety, and perceived threat. These findings show inhibitory dysfunction in patients with PTSD, reflected by the delay in Nogo-N2 latencies. They also indicate that Nogo-N2 latencies are associated with smaller cortical volumes responsible for inhibition as well as with major symptoms of PTSD.

The Importance of Low-frequency Alpha (8-10 Hz) Waves and Default Mode Network in Behavioral Inhibition.

Objective: : Alpha wave of electroencephalography (EEG) is known to be related to behavioral inhibition. Both the alpha wave and default mode network (DMN) are predominantly activated during resting-state. To study the mechanisms of the trait inhibition, this research investigating the relations among alpha wave, DMN and behavioral inhibition in resting-state. Methods: : We explored the relationship among behavioral inhibition, resting-state alpha power, and DMN. Resting-state EEG, behavioral inhibition/behavioral activation scale (BIS/BAS), Barratt impulsivity scale, and no-go accuracy were assessed in 104 healthy individuals. Three groups (i.e., participants with low/middle/high band power) were formed based on the relative power of each total-alpha, low-alpha (LA), and high-alpha band. Source-reconstructed EEG and functional network measures of 25 DMN regions were calculated. Results: : Significant differences and correlations were found based on LA band power alone. The high LA group had significantly greater BIS, clustering coefficient, efficiency, and strength, and significantly lower path length than low/middle LA group. BIS score showed a significant correlation with functional network measures of DMN. Conclusion: : Our study revealed that LA power is related to behavioral inhibition and functional network measures of DMN of LA band appear to represent significant inhibitory function.

The Effect of Social Isolation, Loneliness, and Physical Activity on Depressive Symptoms of Older Adults during COVID-19: A Moderated Mediation Analysis.

Depressive symptoms have been commonly reported in older adults during the coronavirus disease (COVID-19) pandemic. Social isolation as a result of social distancing to prevent COVID-19 was reported to increase the level of depressive symptoms both directly and indirectly through the mediating effect of loneliness. Depressive symptoms in older adults can be regulated through health behaviors such as physical activity. Therefore, this study used a moderated mediation model to explain depressive symptoms. The English Longitudinal Study of Ageing COVID-19 wave 2 data were used. A total of 296 individuals were excluded due to missing values, leaving a final sample of 6499. Depressive symptoms, social isolation, loneliness, and physical activity were used in the moderated mediation analysis with various demographic and general health variables as covariates. Loneliness was found to significantly mediate the relationship between social isolation and depression. While moderate physical activity significantly moderated the effects of social isolation and loneliness on depressive symptoms, mild physical activity alone significantly moderated the effects of loneliness on depressive symptoms. This study revealed the impact of social isolation on depressive symptoms directly and indirectly mediated by loneliness, with a moderating effect of moderate and mild physical activity in the elderly during COVID-19 in a moderated mediation model.

Understanding a Mutually Destructive Relationship Between Individuals With Borderline Personality Disorder and Their Favorite Person.

OBJECTIVE: Individuals with borderline personality disorder (BPD) commonly have a favorite person (FP), whom they are heavily emotionally attached to and dependent on. This study aims to identify and illustrate the patterns of destructive FP relationships based on actual experiences described by those with BPD. METHODS: A data mining process was conducted using raw data collected from online communities, such as blogs and social networks. An in-depth review of the information to better understand the natural course of the FP relationship was also conducted. RESULTS: Individuals with BPD form an intense and insecure attachment toward their FP, from which they enormously suffer. FPs can be their friends, romantic or life partners, or family members. As their feelings go beyond their control, being increasingly obsessed with their FP, they make their FP gradually lose hope in continuing the relationship and want to quit trying to fulfill their needs. The relationship finally ends when the FP stops being responsible for meeting their expectations and eventually drifts away. CONCLUSION: This study suggests that certain FPs, distinctively named Teddy Bear Person, may behave in a particular manner to increase the likelihood of the FP relationship becoming more destructive. Moreover, the rejection sensitivity model should be discussed to understand their dysfunctional interaction.

Association between Dissociative Symptoms and Morning Cortisol Levels in Patients with Post-traumatic Stress Disorder.

Objective: Patients with post-traumatic stress disorder (PTSD) showed inconsistencies in their cortisol level, an index of the hypothalamic-pituitary-adrenal axis function. This study examined the relationship between dissociation, childhood trauma, and morning cortisol levels in PTSD patients. Methods: This study included 69 (23 males and 46 females) patients and 82 (22 males and 60 females) healthy controls (HCs). Clinical assessments, including the Childhood Trauma Questionnaire (CTQ) and Peri-traumatic Dissociative Experiences Questionnaire scores, and morning cortisol levels were evaluated. The morning cortisol levels were compared between PTSD with high dissociation and low dissociation (PTSD-LD) groups. The effect of CTQ subtype on morning cortisol levels was analyzed. Results: The PTSD with high dissociation group showed significantly lower cortisol levels than that of the PTSD-LD and HC groups. A significant inverse correlation was found between cortisol levels and dissociation. A significant positive correlation was found between dissociation and physical abuse and sexual abuse scores. Morning cortisol levels showed a significant positive correlation with emotional abuse, emotional neglect, and physical neglect, respectively. There was no moderating or mediating effect of CTQ on the relationship between cortisol level and dissociation. Conclusion: These findings suggest that dissociation is a significant factor related to hypocortisolism in PTSD patients. Additionally, basal morning cortisol levels and dissociation scores were closely associated with childhood trauma.

Impact of Interpersonal Relationships and Acquired Capability for Suicide on Suicide Attempts: A Cross-Sectional Study.

OBJECTIVE: This study examined the path model predicting suicide attempts (SA) by interpersonal need for suicide desire, acquired capability for suicide, the emotion dysregulation, and depression symptoms in people admitted to hospitals for medical treatment. METHODS: A total of 344 participants (200 depressed patients with attempted suicide, 144 depressed patients with suicidal ideation) were enrolled for this study. Depression, anxiety, emotion regulation, interpersonal needs, and acquired capability for suicide were evaluated. A model with pathways from emotion regulation difficulties and interpersonal needs to SA was proposed. Participants were divided into two groups according to the presence of SA or suicidal ideation. RESULTS: Acquired capability for suicide mediated the path from depression to SA. In the path model, difficulties in emotion regulation and interpersonal needs predicted depression significantly. Although depression itself was not significantly related to acquired capability for suicide, depression was significantly related to acquired capability for suicide in suicide attempter group. CONCLUSION: Interventions with two factors affecting SA will clarify the suicide risk and contribute to finding risk factors.

A knowledge-based multivariate statistical method for examining gene-brain-behavioral/cognitive relationships: Imaging genetics generalized structured component analysis.

With advances in neuroimaging and genetics, imaging genetics is a naturally emerging field that combines genetic and neuroimaging data with behavioral or cognitive outcomes to examine genetic influence on altered brain functions associated with behavioral or cognitive variation. We propose a statistical approach, termed imaging genetics generalized structured component analysis (IG-GSCA), which allows researchers to investigate such gene-brain-behavior/cognitive associations, taking into account well-documented biological characteristics (e.g., genetic pathways, gene-environment interactions, etc.) and methodological complexities (e.g., multicollinearity) in imaging genetic studies. We begin by describing the conceptual and technical underpinnings of IG-GSCA. We then apply the approach for investigating how nine depression-related genes and their interactions with an environmental variable (experience of potentially traumatic events) influence the thickness variations of 53 brain regions, which in turn affect depression severity in a sample of Korean participants. Our analysis shows that a dopamine receptor gene and an interaction between a serotonin transporter gene and the environment variable have statistically significant effects on a few brain regions' variations that have statistically significant negative impacts on depression severity. These relationships are largely supported by previous studies. We also conduct a simulation study to safeguard whether IG-GSCA can recover parameters as expected in a similar situation.

A Dimensional Understanding of Borderline Personality Disorder Using MMPI-2 PSY-5 Scales in Clinical Samples.

OBJECTIVE: This study aims to understand borderline personality disorder (BPD) features by employing the Personality Psychopathology Five (PSY-5) scales from the Minnesota Multiphasic Personality Inventory-2 (MMPI-2). METHODS: A total of 156 psychiatric patients completed PSY-5 scales of MMPI-2 and Personality Assessment Inventory-Borderline Subscale (PAI-BOR). Pearson's partial correlation analysis was conducted to control the impact of age and gender and to determine the relationship between PSY-5 scales and BOR. A hierarchical multiple regression analysis was implemented to examine whether PSY-5 scales predicted the BOR-total, and a path analysis was performed to determine whether PSY-5 scales predicted each PAI-BOR subscale. RESULTS: The BOR-total score had a significant correlation with all PSY-5 scores, even after controlling for age and gender. However, only aggressiveness (AGGR), disconstraint (DISC), negative emotionality/neuroticism (NEGE), and introversion/low positive emotionality (INTR), excluding psychoticism (PSYC), significantly predicted BOR-total. The path analysis indicates that PSYC did not predict any BOR subscale, while NEGE predicted all BOR subscales. CONCLUSION: The study findings indicate that NEGE best reflects BPD features, while PSYC is far from the core domain that describes BPD. In addition, the influence of age should be considered when understanding BPD, since age predicted the BOR-total and two BOR subscales.

An approach to structural equation modeling with both factors and components: Integrated generalized structured component analysis.

In this article, we propose integrated generalized structured component analysis (IGSCA), which is a general statistical approach for analyzing data with both components and factors in the same model, simultaneously. This approach combines generalized structured component analysis (GSCA) and generalized structured component analysis with measurement errors incorporated (GSCAM) in a unified manner and can estimate both factor- and component-model parameters, including component and factor loadings, component and factor path coefficients, and path coefficients connecting factors and components. We conduct 2 simulation studies to investigate the performance of IGSCA under models with both factors and components. The first simulation study assesses how existing approaches for structural equation modeling and IGSCA recover parameters. This study shows that only consistent partial least squares (PLSc) and IGSCA yield unbiased estimates of all parameters, whereas the other approaches always provided biased estimates of several parameters. As such, we conduct a second, extensive simulation study to evaluate the relative performance of the 2 competitors (PLSc and IGSCA), considering a variety of experimental factors (model specification, sample size, the number of indicators per factor/component, and exogenous factor/component correlation). IGSCA exhibits better performance than PLSc under most conditions. We also present a real data application of IGSCA to the study of genes and their influence on depression. Finally, we discuss the implications and limitations of this approach, and recommendations for future research. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Correction: Improving the quality of sexual history disclosure on sex offenders: Emphasis on a polygraph examination.

[This corrects the article DOI: 10.1371/journal.pone.0239046.].

Interaction between catechol-O-methyltransferase polymorphism and childhood trauma in suicidal ideation of patients with post-traumatic stress disorder.

INTRODUCTION: Suicidal behavior of post-traumatic stress disorder (PTSD) patients is influenced by genetic and environmental factors. The catechol-O-methyltransferase (COMT) gene has been known to be associated with suicidal ideation. The present study aimed to explore the relationship of COMT polymorphism, childhood trauma, and suicidal ideation in patients with PTSD. METHODS: Fifty patients with PTSD and 62 healthy controls (HCs) were recruited, and COMT variants rs4680 and rs4633 were genotyped through peripheral blood. Psychological assessments such as the childhood trauma questionnaire (CTQ), the scale for suicidal ideation, the clinician-administered PTSD scale for DSM-5, and a PTSD checklist were administered. A regression analysis, the Johnson-Neyman technique, and a two-way analysis of covariance were conducted. RESULTS: Interaction of COMT polymorphism (rs4680, rs4633) and childhood emotional abuse (subscale of CTQ) predicted suicidal ideation in patients with PTSD. Patients with the rs4680 Val/Val genotype, compared to Met carriers genotype, showed higher suicidal ideation when childhood emotional abuse was high. Patients with the rs4633 CC genotype, compared to T carriers genotype, showed higher suicidal ideation when childhood emotional abuse was high. CONCLUSION: Our results suggest that vulnerability to suicide could be increased in the Val/Val genotype of COMT rs4680 and the CC genotype of rs4633 in patients with PTSD. Moreover, PTSD group with high childhood emotional abuse demonstrated a significantly higher suicidal ideation than did those with low childhood emotional abuse.

Altered Cortical Functional Networks in Patients With Schizophrenia and Bipolar Disorder: A Resting-State Electroencephalographic Study.

BACKGROUND: Pathologies of schizophrenia and bipolar disorder have been poorly understood. Brain network analysis could help understand brain mechanisms of schizophrenia and bipolar disorder. This study investigates the source-level brain cortical networks using resting-state electroencephalography (EEG) in patients with schizophrenia and bipolar disorder. METHODS: Resting-state EEG was measured in 38 patients with schizophrenia, 34 patients with bipolar disorder type I, and 30 healthy controls. Graph theory based source-level weighted functional networks were evaluated: strength, clustering coefficient (CC), path length (PL), and efficiency in six frequency bands. RESULTS: At the global level, patients with schizophrenia or bipolar disorder showed higher strength, CC, and efficiency, and lower PL in the theta band, compared to healthy controls. At the nodal level, patients with schizophrenia or bipolar disorder showed higher CCs, mostly in the frontal lobe for the theta band. Particularly, patients with schizophrenia showed higher nodal CCs in the left inferior frontal cortex and the left ascending ramus of the lateral sulcus compared to patients with bipolar disorder. In addition, the nodal-level theta band CC of the superior frontal gyrus and sulcus (cognition-related region) correlated with positive symptoms and social and occupational functioning scale (SOFAS) scores in the schizophrenia group, while that of the middle frontal gyrus (emotion-related region) correlated with SOFAS scores in the bipolar disorder group. CONCLUSIONS: Altered cortical networks were revealed and these alterations were significantly correlated with core pathological symptoms of schizophrenia and bipolar disorder. These source-level cortical network indices could be promising biomarkers to evaluate patients with schizophrenia and bipolar disorder.

Riemannian classifier enhances the accuracy of machine-learning-based diagnosis of PTSD using resting EEG.

Recently, objective and automated methods for the diagnosis of post-traumatic stress disorder (PTSD) have attracted increasing attention. However, previous studies on machine-learning-based diagnosis of PTSD with resting-state electroencephalogram (EEG) have reported poor accuracies of as low as 60%. Here, a Riemannian geometry-based classifier, the Fisher geodesic minimum distance to the mean (FgMDM), was employed for PTSD classification for the first time. Eyes-closed resting-state EEG data of 39 healthy individuals and 42 PTSD patients were used for the analysis. EEG source activities in 148 cortical regions were parcellated based on the Destrieux atlas, and their covariances were evaluated for each individual. Thirty epochs of preprocessed EEG were employed to calculate source activities. In addition, the FgMDM approach was applied to each EEG source covariance to construct the classifier. For a comparison, linear discriminant analysis (LDA), support vector machine (SVM), and random forest (RF) classifiers employing source band powers and network features as feature candidates were also tested. The FgMDM classifier showed an average classification accuracy of 75.240.80%. In contrast, the maximum accuracies of LDA, SVM, and RF classifiers were 66.54 ± 2.99%, 61.11 ± 2.98%, and 60.99 ± 2.19%, respectively. Our study demonstrated that the diagnostic accuracy of PTSD with resting-state EEG could be significantly improved by employing the FgMDM framework, which is a type of Riemannian geometry-based classifier.

The Impact of Emotional Exhaustion on Psychological Factors in Workers with Secondary Traumatic Experiences: A Multi-Group Path Analysis.

OBJECTIVE: The objective of the present study was to explore causal pathways to understand how second traumatic experiences could affect the development of emotional exhaustion and psychiatric problems. METHODS: A total of 582 workers who had jobs vulnerable to secondary traumatic experiences were enrolled for this study. Emotional exhaustion, secondary trauma, resilience, perceived stress, depression, anxiety, and sleep problems were evaluated. A model with pathways from secondary traumatic experience score to depression and anxiety was proposed. The participants were divided into three groups according to the resilience: the low, middle and high resilience group. RESULTS: Resilience was a meaningful moderator between secondary traumatic experiences and psychiatric problems. In the path model, the secondary trauma and perceived stress directly and indirectly predicted perceived stress, emotional exhaustion, depression, anxiety, and sleep problems in all three groups. Direct effects of perceived stress on depression and anxiety were the largest in the low resilience group. However, direct effects of secondary trauma on perceived stress and emotional exhaustion were the largest in the high resilience group. CONCLUSION: Understanding the needs of focusing for distinct psychological factors offers a valuable direction for the development of intervention programs to prevent emotional exhaustion among workers with secondary traumatic experiences.

Improving the quality of sexual history disclosure on sex offenders: Emphasis on a polygraph examination.

The increasing recidivism rate of sex offenders indicates potential problems in existing recidivism programs. The present study was conducted to determine whether the polygraph examination is a useful technique to obtain a sex offender's concealed past sexual history. We collected fifty-two sex offenders' data and analyzed it. Among the 52 participants, the court ordered 26 sex offenders to take the psychiatric evaluation and the polygraph test. The other half were prisoners at the hospital who were currently undergoing treatment. The participants in the polygraph group disclosed more deviant sexual behaviors and paraphilia interests/behaviors than the comparison group. Thus, the polygraph examination is a powerful tool that can encourage sex offenders to disclose hidden information to help create suitable psychological therapy programs for preventing recidivism in the future.

Influence of childhood trauma and brain-derived neurotrophic factor Val66Met polymorphism on posttraumatic stress symptoms and cortical thickness.

Interaction between childhood trauma and genetic factors influences the pathophysiology of posttraumatic stress disorder (PTSD). This study examined the interaction effect of childhood trauma and brain-derived neurotrophic factor (BDNF) Val66Met polymorphism on PTSD symptoms and brain cortical thickness. A total of 216 participants (133 healthy volunteers and 83 PTSD patients) were recruited. T1-weighted structural magnetic resonance imaging, BDNF rs6265 genotyping through blood sampling, and clinical assessments including the childhood trauma questionnaire (CTQ) and posttraumatic stress disorder Checklist (PCL) were performed. A moderated regression analysis, two-way multivariate analysis of covariance, and correlation analysis were conducted. An interaction between the CTQ and the BDNF polymorphism significantly influenced PTSD symptom severity. In fact, people with rs6265 Val/Val genotype and higher CTQ scores showed higher PCL scores. Additionally, this interaction was significant on both left fusiform and transverse temporal gyri thickness. Furthermore, the thickness of both brain regions was significantly correlated with psychological symptoms including depression, anxiety, rumination, and cognitive emotion regulation methods; yet this was mainly observed in people with the Val/Val genotype. The interaction between childhood trauma and BDNF polymorphism significantly influences both PTSD symptoms and cortical thickness and the Val/Val genotype may increase the risk in Korean population.

Neurophysiological and Psychological Predictors of Social Functioning in Patients with Schizophrenia and Bipolar Disorder.

OBJECTIVE: The aim of this study is to examine social functioning in patients with schizophrenia and bipolar disorder and explore the psychological and neurophysiological predictors of social functioning. METHODS: Twenty-seven patients with schizophrenia and thirty patients with bipolar disorder, as well as twenty-five healthy controls, completed measures of social functioning (questionnaire of social functioning), neurocognition (Verbal fluency, Korean-Auditory Verbal Learning Test), and social cognition (basic empathy scale and Social Attribution Task-Multiple Choice), and the childhood trauma questionnaire (CTQ). For neurophysiological measurements, mismatch negativity and heart rate variability (HRV) were recorded from all participants. Multiple hierarchical regression was performed to explore the impact of factors on social functioning. RESULTS: The results showed that CTQ-emotional neglect significantly predicted social functioning in schizophrenia group, while HRV-high frequency significantly predicted social functioning in bipolar disorder patients. Furthermore, emotional neglect and HRV-HF still predicted social functioning in all of the subjects after controlling for the diagnostic criteria. CONCLUSION: Our results implicated that even though each group has different predictors of social functioning, early traumatic events and HRV could be important indicators of functional outcome irrespective of what group they are.

Machine-learning-based classification between post-traumatic stress disorder and major depressive disorder using P300 features.

BACKGROUND: The development of optimal classification criteria for specific mental disorders which share similar symptoms is an important issue for precise diagnosis. We investigated whether P300 features in both sensor-level and source-level could be effectively used to classify post-traumatic stress disorder (PTSD) and major depressive disorder (MDD). METHOD: EEG signals were recorded from fifty-one PTSD patients, 67 MDD patients, and 39 healthy controls (HCs) while performing an auditory oddball task. Amplitude and latency of P300 were evaluated, and the current source analysis of P300 components was conducted using sLORETA. Finally, we classified two groups using machine-learning methods with both sensor- and source-level features. Moreover, we checked the comorbidity effects using the same approaches (PTSD-mono diagnosis (PTSDm, n = 28) and PTSD-comorbid diagnosis (PTSDc, n = 23)). RESULTS: PTSD showed significantly reduced P300 amplitudes and prolonged latency compared to HCs and MDD. Moreover, PTSD showed significantly reduced source activities, and the source activities were significantly correlated with symptoms of depression and anxiety. Also, the best classification accuracy at each pair was as follows: 80.00% (PTSD-HCs), 67.92% (MDD-HCs), 70.34% (PTSD-MDD), 82.09% (PTSDm-HCs), 71.58% (PTSDm-MDD), 82.56% (PTSDc-HCs), and 76.67% (PTSDc- MDD). CONCLUSION: Since abnormal P300 reflects pathophysiological characteristics of PTSD, PTSD patients were well-discriminated from MDD and HCs when using P300 features. Thus, altered P300 characteristics in both sensor- and source-level may be useful biomarkers to diagnosis PTSD.