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There is increasing evidence that major trauma can adversely affect the brain and cognition. In some cases, trauma may lead to deficits in executive function (EF). The anterior insula may be a causal outflow hub acting to coordinate EF-related brain networks. To clarify the neural underpinnings of EF deficits (EFD) after trauma, we performed a resting-state functional magnetic resonance imaging (rs-fMRI) study of anterior insular subnetworks in adults who have lost their only child. A total of 167 participants completed various psychological and cognitive assessments to assess EF-related deficits. Correlations were computed between abnormal connectivity and cognitive/post-traumatic stress symptoms. The results showed abnormal anterior insular subregion connectivity in the default mode network (DMN), prefrontal lobe, and cerebellum lobe in participants with EFD. No correlation was found between abnormal connectivity and cognitive/post-traumatic stress symptoms in participants with EFD. These results suggest that excessive connections between the insula and DMN could contribute to EFD after trauma. Overall, this study provides novel references into the neural mechanisms of EF status after trauma exposure., (Copyright © 2023 IBRO. Published by Elsevier Inc. All rights reserved.)

Background: Post-traumatic stress disorder (PTSD) is associated with disruption of the brain network topology; however, little is known about the topological changes and sex effects in PTSD patients following a unique trauma, the loss of an only child, in China., Methods: Fifty-one lost-only-child parents with PTSD, 93 lost-only-child non-PTSD parents (NPTSD), and 50 healthy subjects underwent resting-state functional MRI. The whole-brain functional network was constructed by thresholding partial correlation matrices of 90 brain regions. Group differences in the topological properties, the diagnosis-by-sex interaction, and the relationships between topological metrics and clinical variables were investigated., Results: Compared with healthy subjects, PTSD and NPTSD groups exhibited significantly shorter path lengths and higher nodal centralities in many brain regions across sexes; however, no significant difference was found between the PTSD and NPTSD groups. Additionally, the global topological metrics did not show any sex difference, whereas the nodal centralities in the left insula, right inferior frontal gyrus, and right posterior cingulate cortex differed significantly only in women, and the nodal centralities in the bilateral anterior cingulate cortices and left hippocampus were significantly different only in men. Furthermore, the nodal centralities of the right parahippocampus demonstrated significant diagnosis-by-sex interaction., Limitation: Cross-sectional design of this study could not demonstrate the causality., Conclusions: The parents who lost their only child exhibited a shift toward randomization and significant nodal topological alterations independent of PTSD effects. Additionally, sex differences were observed primarily in the topological properties at the nodal level, which may indicate a neurobiological contribution to the greater incidence of PTSD in females., (Copyright © 2019. Published by Elsevier B.V.)

Background: Disturbance of the triple network model was recently proposed to be associated with the occurrence of posttraumatic stress disorder (PTSD) symptoms. Based on resting-state dynamic causal modeling (rs-DCM) analysis, we investigated the neurobiological model at a neuronal level along with potential neuroimaging biomarkers for identifying individuals with PTSD., Methods: We recruited survivors of a devastating typhoon including 27 PTSD patients, 33 trauma-exposed controls (TECs), and 30 healthy controls without trauma exposure. All subjects underwent resting-state functional magnetic resonance imaging. Independent components analysis was used to identify triple networks. Detailed effective connectivity patterns were estimated by rs-DCM analysis. Spearman correlation analysis was performed on aberrant DCM parameters with clinical assessment results relevant to PTSD diagnosis. We also carried out step-wise binary logistic regression and receiver operating characteristic curve (ROC) analysis to confirm the capacity of altered effective connectivity parameters to distinguish PTSD patients., Results: Within the executive control network, enhanced positive connectivity from the left posterior parietal cortex to the left dorsolateral prefrontal cortex was correlated with intrusion symptoms and showed good performance (area under the receiver operating characteristic curve = 0.879) in detecting PTSD patients. In the salience network, we observed a decreased causal flow from the right amygdala to the right insula and a lower transit value for the right amygdala in PTSD patients relative to TECs., Conclusion: Altered effective connectivity patterns in the triple network may reflect the occurrence of PTSD symptoms, providing a potential biomarker for detecting patients. Our findings shed new insight into the neural pathophysiology of PTSD.

Background: The volumetry of the hippocampal subregion may provide additional information in the early investigation of amnestic mild cognitive impairment (aMCI) and the T2 signal intensity (T2-SI) of the hippocampal subregion has not been well studied quantitatively by magnetic resonance imaging (MRI) in aMCI., Methods: Using combined MRI-based hippocampal volumetry and T2-SI at the levels of the whole hippocampus and hippocampal subregion, 18 patients with aMCI and 18 age-matched controls were investigated., Results: Significantly lower left whole hippocampal and hippocampal head volumes and higher T2-SI in the bilateral whole hippocampus and hippocampal head were shown, whereas atrophy of the right whole hippocampus and hippocampal subregion was not significant in aMCI. Additionally, correlations were found among the hippocampal volume, T2-SI and Mini-Mental State Examination (MMSE) scores for aMCI in the whole hippocampus and some hippocampal subregions and an almost perfect correlation was found between T2-SI of the left hippocampal head and MMSE scores regarding aMCI (r = -0.831, P = 0.000)., Conclusion: Abnormalities of the hippocampal volume and T2-SI were documented in aMCI, whereas T2-SI was implied to be more susceptible than the volume in the pathohistological progression in aMCI. Additionally, T2-SI in the left hippocampal head may be a potential biomarker to facilitate the early diagnosis of aMCI.

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.

Background: Norepinephrine transporter (NET) is encoded by the SLC6A2 gene and is a potential target for studying the pathogenesis of PTSD. To the best of our knowledge, no prior investigations have examined SLC6A2 polymorphism-related neuroimaging abnormalities in PTSD patients. Methods: In 218 Han Chinese adults who had lost their sole child, we investigated the association between the T-182 C SLC6A2 genotype and gray matter volume (GMV). Participants included 57 PTSD sufferers and 161 non-PTSD sufferers, and each group was further separated into three subgroups based on each participant's SLC6A2 genotype (TT, CT, and CC). All participants received magnetic resonance imaging (MRI) and clinical evaluation. To assess the effects of PTSD diagnosis, genotype, and genotype × diagnosis interaction on GMV, 2 × 3 full factorial designs were used. Pearson's correlations were used to examine the association between GMV and CAPS, HAMD, and HAMA. Results: The SLC6A2 genotype showed significant main effects on GMV of the left superior parietal gyrus (SPG) and the bilateral middle cingulate gyrus (MCG). Additionally, impacts of the SLC6A2 genotype-diagnosis interaction were discovered in the left superior frontal gyrus (SFG). The CAPS, HAMA, and HAMD scores, as well as the genotype main effect and diagnostic SLC6A2 interaction, did not significantly correlate with each other. Conclusion: These findings indicate a modulatory effect that the SLC6A2 polymorphism exerts on the SPG and MCG, irrespective of PTSD diagnosis. We found evidence to suggest that the SLC6A2 genotype-diagnosis interaction on SFG may potentially contribute to PTSD pathogenesis in adults who lost their sole child. [ABSTRACT FROM AUTHOR]

Background: Losing one's only child is a major traumatic life event that may lead to post-traumatic stress disorder (PTSD); however, the underlying mechanisms of its psychological consequences remain poorly understood. Here, we investigated subregional hippocampal functional connectivity (FC) networks based on resting-state functional magnetic resonance imaging and the deoxyribonucleic acid methylation of the human glucocorticoid receptor gene (NR3C1) in adults who had lost their only child. Methods: A total of 144 Han Chinese adults who had lost their only child (51 adults with PTSD and 93 non-PTSD adults [trauma-exposed controls]) and 50 controls without trauma exposure were included in this fMRI study (age: 40–67 years). FCs between hippocampal subdivisions (four regions in each hemisphere: cornu ammonis1 [CA1], CA2, CA3, and dentate gyrus [DG]) and methylation levels of the NR3C1 gene were compared among the three groups. Results: Trauma-exposed adults, regardless of PTSD diagnosis, had weaker positive FC between the left hippocampal CA1, left DG, and the posterior cingulate cortex, and weaker negative FC between the right CA1, right DG, and several frontal gyri, relative to healthy controls. Compared to non-PTSD adults, PTSD adults showed decreased negative FC between the right CA1 region and the right middle/inferior frontal gyri (MFG/IFG), and decreased negative FC between the right DG and the right superior frontal gyrus and left MFG. Both trauma-exposed groups showed lower methylation levels of the NR3C1 gene. Conclusions: Adults who had lost their only child may experience disrupted hippocampal network connectivity and NR3C1 methylation status, regardless of whether they have developed PTSD. [ABSTRACT FROM AUTHOR]

Background: Limbic structural changes have been found in people with post-traumatic stress disorder (PTSD). However, the results were controversial, and no study has examined the hippocampal and amygdala volume changes in parents with or without PTSD who had lost their only child and could no longer conceive in China.Methods: Hippocampal and amygdala volumes of 57 parents with PTSD (PTSD+), 11 trauma-exposed parents without PTSD (PTSD-) and 39 non-traumatized controls were examined using magnetic resonance imaging. Correlations of the volumes with the time since trauma, Clinician-Administered PTSD Scale (CAPS) scores, age, gender and intracranial volume (ICV) were investigated in the PTSD+ group.Results: left hippocampal volumes were significantly smaller in the PTSD+ and PTSD- groups than in the controls, but there were no significant differences between the PTSD+ and PTSD- groups. Furthermore, there was no significant difference in the right hippocampus or bilateral amygdala volumes. Additionally, the hippocampal and amygdala volumes showed no correlation with the time since trauma, CAPS score and gender, whereas the left hippocampal volumes were correlated with ICV, and the bilateral amygdala volumes were correlated with ICV and age in the PTSD+ group.Limitations: The PTSD- group included only 11 participants.Conclusions: left hippocampal volumes decreased in parents who lost their only child, with or without PTSD. Our results suggest a potentially unique role of the trauma of losing an only child, which is extremely painful and may induce a decrease in the left hippocampal volume independent of PTSD effects. [ABSTRACT FROM AUTHOR]