Search

Objective This study aimed to explore the relationship between childhood physical abuse and suicidal ideation considering the effects of genetic and environmental factors in patients with post-traumatic stress disorder (PTSD) by focusing on brain-derived neurotrophic factor (BDNF) polymorphism and social support, respectively.Methods One-hundred fourteen patients with PTSD and 94 healthy controls (HCs) were genotyped with respect to BDNF Val66Met polymorphism. All participants underwent psychological assessments. The hierarchical regression analysis and the simple slope analysis were conducted.Results As for patients with PTSD, the moderation effect of BDNF polymorphism was significant but not for social support. Specifically, the BDNF Val/Val genotype worked as a risk factor and strengthens the relationship between childhood physical abuse and suicidal ideation. As for the HCs, the significant moderation effect was found only in social support, but not for BDNF polymorphism. The relationship between childhood physical abuse and suicidal ideation was weakened for the HCs with high social support.Conclusion This study demonstrated a significant BDNF genetic vulnerability for suicide in patients with PTSD who experienced childhood physical abuse. Our results suggested that social support provided a mitigating effect on the relationship between childhood physical abuse and suicidal ideation only in the HCs.

Transcranial direct current stimulation (tDCS) is an emerging therapeutic tool for treating posttraumatic stress disorder (PTSD). Prior studies have shown that tDCS responses are highly individualized, thus necessitating the individualized optimization of treatment configurations. To date, an effective tool for predicting tDCS treatment outcomes in patients with PTSD has not yet been proposed. Therefore, we aimed to build and validate a tool for predicting tDCS treatment outcomes in patients with PTSD. Forty-eight patients with PTSD received 20 min of 2 mA tDCS stimulation in position of the anode over the F3 and cathode over the F4 region. Non-responders were defined as those with less than 50% improvement after reviewing clinical symptoms based on the Clinician-Administered DSM-5 PTSD Scale (before and after stimulation). Resting-state electroencephalograms were recorded for 3 min before and after stimulation. We extracted power spectral densities (PSDs) for five frequency bands. A support vector machine (SVM) model was used to predict responders and non-responders using PSDs obtained before stimulation. We investigated statistical differences in PSDs before and after stimulation and found statistically significant differences in the F8 channel in the theta band (p = 0.01). The SVM model had an area under the ROC curve (AUC) of 0.93 for predicting responders and non-responders using PSDs. To our knowledge, this study provides the first empirical evidence that PSDs can be useful biomarkers for predicting the tDCS treatment response, and that a machine learning model can provide robust prediction performance. Machine learning models based on PSDs can be useful for informing treatment decisions in tDCS treatment for patients with PTSD.

Although transcranial direct stimulation (tDCS) has been proposed as an alternative treatment option for various psychiatric disorders, there is inconsistent information regarding the treatment effects of tDCS for patients with post-traumatic stress disorder (PTSD). This study aimed to investigate the tDCS efficacy and identify predictors of treatment response to tDCS in patients with PTSD.Fifty-one patients received 10 sessions of tDCS involving the position of the anode over the F3 area and cathode over the F4 as a condition of 2.0 mA and 20 min duration. Digit span test and 10 questionnaires (Clinician-Administered PTSD Scale (CAPS), Cognitive Emotion Regulation Questionnaire (CERQ), Multidimensional Experiential Avoidance Questionnaire (MEAQ), etc.) were used to measure tDCS effects on PTSD symptoms and identify predictors of response to tDCS.1) 50.9 % of patients had a significant reduction in the frequency and severity of PTSD symptoms, 2) PTSD-related symptoms such as depression, anxiety, rumination, and quality of life were significantly improved, 3) baseline scores on rumination and digit span test significantly predicted treatment response to tDCS.This study was open design without a sham control group. Also, the patients' medications were not controlled.This study highlighted the efficacy of frontal tDCS for the treatment of patients with PTSD and identified rumination and digit span as favorable predictive factors for the outcomes of tDCS.