Microstructural Abnormalities in Children with Post-traumatic Stress Disorder: A Diffusion Tensor Imaging Study at 3.0T

Posttraumatic stress disorder (PTSD) is a severe anxiety disorder characterized by re-experiencing, avoidance and hyperarousal. Brain microstructure abnormalities in PTSD, especially in children, are not yet well characterized. The aim of this study was to use MR diffusion tensor imaging (DTI) to identify brain microstructure alterations in children with PTSD compared to non-PTSD controls who experienced the same time-limited trauma. We studied 27 children with PTSD and 24 age- and gender-matched traumatized controls without PTSD, who all experienced the 2008 Sichuan major earthquake. DTI data were acquired and analyzed in terms of fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD) and axial diffusivity (AD). Children with PTSD showed an abnormal pattern, not only of FA, but also of the diffusivity measures MD, AD and RD. Most of the abnormal brain regions belonged to two important networks: the default-mode network, including precuneus and angular gyrus and the salience network, including insula, putamen and thalamus. This DTI study identifies microstructural abnormalities of children with PTSD after a major earthquake, our results are consistent with the suggestion that pediatric PTSD is accompanied by a connectivity disequilibrium between the salience and default-mode networks, a finding of potential pathophysiological significance

White Matter Abnormalities in Post-traumatic Stress Disorder Following a Specific Traumatic Event

Studies of posttraumatic stress disorder (PTSD) are complicated by wide variability in the intensity and duration of prior stressors in patient participants, secondary effects of chronic psychiatric illness, and a variable history of treatment with psychiatric medications. In magnetic resonance imaging (MRI) studies, patient samples have often been small, and they were not often compared to similarly stressed patients without PTSD in order to control for general stress effects. Findings from these studies have been inconsistent. The present study investigated whole-brain microstructural alterations of white matter in a large drug-naive population who survived a specific, severe traumatic event (a major 8.0-magnitude earthquake). Using diffusion tensor imaging (DTI), we explored group differences between 88 PTSD patients and 91 matched traumatized non-PTSD controls in fractional anisotropy (FA), as well as its component elements axial diffusivity (AD) and radial diffusivity (RD), and examined these findings in relation to findings from deterministic DTI tractography. Relations between white matter alterations and psychiatric symptom severity were examined. PTSD patients, relative to similarly stressed controls, showed an FA increase as well as AD and RD changes in the white matter beneath left dorsolateral prefrontal cortex and forceps major. The observation of increased FA in the PTSD group suggests that the pathophysiology of PTSD after a specific acute traumatic event is distinct from what has been reported in patients with several years duration of illness. Alterations in dorsolateral prefrontal cortex may be an important aspect of illness pathophysiology, possibly via the region's established role in fear extinction circuitry. Use-dependent myelination or other secondary compensatory changes in response to heightened demands for threat appraisal and emotion regulation may be involved

COVID-19 vicarious traumatization links functional connectome to general distress.

As characterized by repeated exposure of others' trauma, vicarious traumatization is a common negative psychological reaction during the COVID-19 pandemic and plays a crucial role in the development of general mental distress. This study aims to identify functional connectome that encodes individual variations of pandemic-related vicarious traumatization and reveal the underlying brain-vicarious traumatization mechanism in predicting general distress. The eligible subjects were 105 general university students (60 females, aged from 19 to 27 years) undergoing brain MRI scanning and baseline behavioral tests (October 2019 to January 2020), whom were re-contacted for COVID-related vicarious traumatization measurement (February to April 2020) and follow-up general distress evaluation (March to April 2021). We applied a connectome-based predictive modeling (CPM) approach to identify the functional connectome supporting vicarious traumatization based on a 268-region-parcellation assigned to network memberships. The CPM analyses showed that only the negative network model stably predicted individuals' vicarious traumatization scores (q2 = -0.18, MSE = 617, r [predicted, actual] = 0.18, p = 0.024), with the contributing functional connectivity primarily distributed in the fronto-parietal, default mode, medial frontal, salience, and motor network. Furthermore, mediation analysis revealed that vicarious traumatization mediated the influence of brain functional connectome on general distress. Importantly, our results were independent of baseline family socioeconomic status, other stressful life events and general mental health as well as age, sex and head motion. Our study is the first to provide evidence for the functional neural markers of vicarious traumatization and reveal an underlying neuropsychological pathway to predict distress symptoms in which brain functional connectome affects general distress via vicarious traumatization

Distinct pre-COVID brain structural signatures in COVID-19-related post-traumatic stress symptoms and post-traumatic growth

Post-traumatic stress symptoms and post-traumatic growth are common co-occurring psychological responses following exposure to traumatic events (such as COVID-19 pandemic), their mutual relationship remains unclear. To explore this relationship, structural magnetic resonance imaging data were acquired from 115 general college students before the COVID-19 pandemic, and follow-up post-traumatic stress symptoms and post-traumatic growth measurements were collected during the pandemic. Voxel-based morphometry was conducted and individual structural covariance networks based on gray matter volume were further analyzed using graph theory and partial least squares correlation. Behavioral correlation found no significant relationship between post-traumatic stress symptoms and post-traumatic growth. Voxel-based morphometry analyses showed that post-traumatic stress symptoms were positively correlated with gray matter volume in medial prefrontal cortex/dorsal anterior cingulate cortex, and post-traumatic growth was negatively correlated with gray matter volume in left dorsolateral prefrontal cortex. Structural covariance network analyses found that post-traumatic stress symptoms were negatively correlated with the local efficiency and clustering coefficient of the network. Moreover, partial least squares correlation showed that post-traumatic stress symptoms were correlated with pronounced nodal properties patterns in default mode, sensory and motor regions, and a marginal correlation of post-traumatic growth with a nodal property pattern in emotion regulation-related regions. This study advances our understanding of the neurobiological substrates of post-traumatic stress symptoms and post-traumatic growth, and suggests that they may have different neuroanatomical features

Disrupted morphological grey matter networks in early-stage Parkinson’s disease

AbstractWhile previous structural-covariance studies have an advanced understanding of brain alterations in Parkinson's disease (PD), brain–behavior relationships have not been examined at the individual level. This study investigated the topological organization of grey matter (GM) networks, their relation to disease severity, and their potential imaging diagnostic value in PD. Fifty-four early-stage PD patients and 54 healthy controls (HC) underwent structural T1-weighted magnetic resonance imaging. GM networks were constructed by estimating interregional similarity in the distributions of regional GM volume using the Kullback–Leibler divergence measure. Results were analyzed using graph theory and network-based statistics (NBS), and the relationship to disease severity was assessed. Exploratory support vector machine analyses were conducted to discriminate PD patients from HC and different motor subtypes. Compared with HC, GM networks in PD showed a higher clustering coefficient (P = 0.014) and local efficiency (P = 0.014). Locally, nodal centralities in PD were lower in postcentral gyrus and temporal-occipital regions, and higher in right superior frontal gyrus and left putamen. NBS analysis revealed decreased morphological connections in the sensorimotor and default mode networks and increased connections in the salience and frontoparietal networks in PD. Connection matrices and graph-based metrics allowed single-subject classification of PD and HC with significant accuracy of 73.1 and 72.7%, respectively, while graph-based metrics allowed single-subject classification of tremor-dominant and akinetic–rigid motor subtypes with significant accuracy of 67.0%. The topological organization of GM networks was disrupted in early-stage PD in a way that suggests greater segregation of information processing. There is potential for application to early imaging diagnosis.</jats:p

Multilayer analysis of dynamic network reconfiguration in pediatric posttraumatic stress disorder.

Neuroimage studies have reported functional connectome abnormalities in posttraumatic stress disorder (PTSD), especially in adults. However, these studies often treated the brain as a static network, and time-variance of connectome topology in pediatric posttraumatic stress disorder remain unclear. To explore case-control differences in dynamic connectome topology, resting-state functional magnetic resonance imaging data were acquired from 24 treatment-naïve non-comorbid pediatric posttraumatic stress disorder patients and 24 demographically matched trauma-exposed non-posttraumatic stress disorder controls. A graph-theoretic analysis was applied to construct time-varying modular structure of whole-brain networks by maximizing the multilayer modularity. Network switching rate at the global, subnetwork, and nodal levels were calculated and compared between posttraumatic stress disorder and trauma-exposed non-posttraumatic stress disorder groups, and their associations with posttraumatic stress disorder symptom severity and sex interactions were explored. At the global level, individuals with posttraumatic stress disorder exhibited significantly lower network switching rates compared to trauma-exposed non-posttraumatic stress disorder controls. This difference was mainly involved in default-mode and dorsal attention subnetworks, as well as in inferior temporal and parietal brain nodes. Posttraumatic stress disorder symptom severity was negatively correlated with switching rate in the global network and default mode network. No significant differences were observed in the interaction between diagnosis and sex/age. Pediatric posttraumatic stress disorder is associated with dynamic reconfiguration of brain networks, which may provide insights into the biological basis of this disorder

Disrupted Functional Network Topology in Children and Adolescents With Post-traumatic Stress Disorder

Neuroimaging studies in children and adolescents with post-traumatic stress disorder (PTSD) have focused on abnormal structures and the functionality of a few individual brain regions. However, little is known about alterations to the topological organization of whole-brain functional networks in children and adolescents with PTSD. To this end, we investigated the topological properties of brain functional networks derived from resting-state functional magnetic resonance imaging (r-fMRI) in patients suffering from PTSD. The r-fMRI data were obtained from 10 PTSD patients and 16 trauma-exposed non-PTSD subjects. Graph theory analysis was used to investigate the topological properties of the two groups, and group comparisons of topological metrics were performed using nonparametric permutation tests. Both the PTSD and non-PTSD groups showed the functional brain network to have a small-world architecture. However, the PTSD group exhibited alterations in global properties characterized by higher global efficiency, lower clustering coefficient, and characteristic path length, implying a shift toward randomization of the networks. The PTSD group also showed increased nodal centralities, predominately in the left middle frontal gyrus, caudate nucleus, and hippocampus, and decreased nodal centralities in the left anterior cingulate cortex, left paracentral lobule, and bilateral thalami. In addition, the clustering coefficient and nodal betweenness of the left paracentral lobule were found to be negatively and positively correlated with the re-experiencing and hyper-arousal symptoms of PTSD respectively. The findings of disrupted topological properties of functional brain networks may help to better understand the pathophysiological mechanism of PTSD in children and adolescents

Topologically convergent and divergent morphological gray matter networks in early-stage Parkinson's disease with and without mild cognitive impairment

Patients with Parkinson's disease with mild cognitive impairment (PD‐M) progress to dementia more frequently than those with normal cognition (PD‐N), but the underlying neurobiology remains unclear. This study aimed to define the specific morphological brain network alterations in PD‐M, and explore their potential diagnostic value. Twenty‐four PD‐M patients, 17 PD‐N patients, and 29 healthy controls (HC) underwent a structural MRI scan. Similarity between interregional gray matter volume distributions was used to construct individual morphological brain networks. These were analyzed using graph theory and network‐based statistics (NBS), and their relationship to neuropsychological tests was assessed. Support vector machine (SVM) was used to perform individual classification. Globally, compared with HC, PD‐M showed increased local efficiency (p = .001) in their morphological networks, while PD‐N showed decreased normalized path length (p = .008). Locally, similar nodal deficits were found in the rectus and lingual gyrus, and cerebellum of both PD groups relative to HC; additionally in PD‐M nodal deficits involved several frontal and parietal regions, correlated with cognitive scores. NBS found that similar connections were involved in the default mode and cerebellar networks of both PD groups (to a greater extent in PD‐M), while PD‐M, but not PD‐N, showed altered connections involving the frontoparietal network. Using connections identified by NBS, SVM allowed discrimination with high accuracy between PD‐N and HC (90%), PD‐M and HC (85%), and between the two PD groups (65%). These results suggest that default mode and cerebellar disruption characterizes PD, more so in PD‐M, whereas frontoparietal disruption has diagnostic potential