BackgroundAn overlap of clinical symptoms between major depressive disorder (MDD) and social anxiety disorder (SAD) suggests that the two disorders exhibit similar brain mechanisms. However, few studies have directly compared the brain structures of the two disorders. The aim of this study was to assess the gray matter volume (GMV) and cortical thickness alterations between non-comorbid medication-naive MDD patients and SAD patients.MethodsHigh-resolution T1-weighted images were acquired from 37 non-comorbid MDD patients, 24 non-comorbid SAD patients and 41 healthy controls (HCs). Voxel-based morphometry analysis of the GMV (corrected with a false discovery rate of p < 0.001) and vertex-based analysis of cortical thickness (corrected with a clusterwise probability of p < 0.001) were performed, and group differences were compared by ANOVA followed by post hoc tests.OutcomesRelative to the HCs, both the MDD patients and SAD patients showed the following results: GMV reductions in the bilateral orbital frontal cortex (OFC), putamen, and thalamus; cortical thickening in the bilateral medial prefrontal cortex, posterior dorsolateral prefrontal cortex, insular cortex, left temporal pole, and right superior parietal cortex; and cortical thinning in the left lateral OFC and bilateral rostral middle frontal cortex. In addition, MDD patients specifically showed a greater thickness in the left fusiform gyrus and right lateral occipital cortex and a thinner thickness in the bilateral lingual and left cuneus. SAD patients specifically showed a thinner cortical thickness in the right precentral cortex.InterpretationOur results indicate that MDD and SAD share common patterns of gray matter abnormalities in the orbitofrontal-striatal-thalamic circuit, salience network and dorsal attention network. These consistent structural differences in the two patient groups may contribute to the broad spectrum of emotional, cognitive and behavioral disturbances observed in MDD patients and SAD patients. In addition, we found disorder-specific involvement of the visual processing regions in MDD and the precentral cortex in SAD. These findings provide new evidence regarding the shared and specific neuropathological mechanisms that underlie MDD and SAD.

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BackgroundSeveral task-based functional MRI (fMRI) studies have highlighted abnormal activation in specific regions involving the low-level perceptual (auditory, visual, and somato-motor) network in posttraumatic stress disorder (PTSD) patients. However, little is known about whether the functional connectivity of the low-level perceptual and higher-order cognitive (attention, central-execution, and default-mode) networks change in medication-naïve PTSD patients during the resting state.MethodsWe investigated the resting state networks (RSNs) using independent component analysis (ICA) in 18 chronic Wenchuan earthquake-related PTSD patients versus 20 healthy survivors (HSs).ResultsCompared to the HSs, PTSD patients displayed both increased and decreased functional connectivity within the salience network (SN), central executive network (CEN), default mode network (DMN), somato-motor network (SMN), auditory network (AN), and visual network (VN). Furthermore, strengthened connectivity involving the inferior temporal gyrus (ITG) and supplementary motor area (SMA) was negatively correlated with clinical severity in PTSD patients.LimitationsGiven the absence of a healthy control group that never experienced the earthquake, our results cannot be used to compare alterations between the PTSD patients, physically healthy trauma survivors, and healthy controls. In addition, the breathing and heart rates were not monitored in our small sample size of subjects. In future studies, specific task paradigms should be used to reveal perceptual impairments.ConclusionsThese findings suggest that PTSD patients have widespread deficits in both the low-level perceptual and higher-order cognitive networks. Decreased connectivity within the low-level perceptual networks was related to clinical symptoms, which may be associated with traumatic reminders causing attentional bias to negative emotion in response to threatening stimuli and resulting in emotional dysregulation.

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.