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Post-Partum Depression (PPD) is the most common health issue impacting emotional well being in women and is often comorbid with anxiety (PPD-A). Previous studies have shown that adequate social support can protect against PPD and PPD-A. However, how the brain connectome is disrupted in PPD and PPD-A and the neural basis underlying the role of social support in PPD and PPD-A remains unclear. The present study aims to explore these issues in patients with PPD and PPD-A. Well-established questionnaires and resting-state functional Magnetic Resonance Imaging (rsfMRI) were performed in 45 PPD, 31 PDD-A patients and 62 Healthy Postnatal Women (HPW). Brain functional integration was measured by analysis of Functional Connectivity Strength (FCS). Association and mediation analyses were performed to investigate relationships between FCS, PPD and PPD-A symptoms and social support. PPD patients showed specifically higher FCS in right parahippocampus, whereas PPD-A patients showed specifically higher FCS in left ventrolateral prefrontal cortex. In all postpartum women, depression symptoms positively correlated with FCS in left paracentral lobule; depression and anxiety symptoms were negatively correlated with FCS in right cerebellem posterior lobe (CPL), a brain region implicated in supporting social cognition and regulation of emotion. Subsequent mediation analysis revealed that perceived social support mediated the association between right CPL FCS and PPD and PPD-A symptoms. Measurement of FCS in disorder-specific neural circuits offers a potential biomarker to study and measure the efficacy of social support for PPD and PPD-A.

The relationship between depression and severe non-alcoholic fatty liver disease (NAFLD) has not been clearly defined. We conducted a longitudinal cohort study and a two-sample Mendelian randomization (MR) analysis to assess the association of depression with severe NAFLD risk. We used individual data from the UK Biobank study with 481,181 participants, and summary data from published genome-wide association studies. The association between depression and severe NAFLD was assessed using Cox proportional hazards regression analysis. Two-sample MR for depression with NAFLD was conducted, the principal analysis employed the inverse variance weighted (IVW) approach. In the observational study, after a median follow-up of 13.46 years, 4,563 participants had severe NAFLD. In multivariable-adjusted model, participants with depression had an increased risk of severe NAFLD (hazards ratio:1.21, 95% confidence interval (CI):1.09–1.34), as compared to those without depression. In subgroup analyses, the association between depression and severe NAFLD risk was generally observed across different subgroups. For the MR, result also showed that genetically predicted depression was causally associated with a higher risk of NAFLD (odds ratio:1.55, 95%CI:1.10–2.19) in IVW. Our study revealed a prospective association of depression with severe NAFLD, thus potentially necessitating clinical monitoring of individuals with depression for severe NAFLD.

Social anxiety disorder (SAD) is a common and disabling condition characterized by excessive fear and avoidance of public scrutiny. Psychoradiology studies have suggested that the emotional and behavior deficits in SAD are associated with abnormalities in regional brain function and functional connectivity. However, little is known about whether intrinsic functional brain networks in patients with SAD are topologically disrupted. Here, we collected resting-state fMRI data from 33 drug-naive patients with SAD and 32 healthy controls (HC), constructed functional networks with 34 predefined regions based on previous meta-analytic research with task-based fMRI in SAD, and performed network-based statistic and graph-theory analyses. The network-based statistic analysis revealed a single connected abnormal circuitry including the frontolimbic circuit (termed the “fear circuit”, including the dorsolateral prefrontal cortex, ventral medial prefrontal cortex and insula) and posterior cingulate/occipital areas supporting perceptual processing. In this single altered network, patients with SAD had higher functional connectivity than HC. At the global level, graph-theory analysis revealed that the patients exhibited a lower normalized characteristic path length than HC, which suggests a disorder-related shift of network topology toward randomized configurations. SAD-related deficits in nodal degree, efficiency and participation coefficient were detected in the parahippocampal gyrus, posterior cingulate cortex, dorsolateral prefrontal cortex, insula and the calcarine sulcus. Aspects of abnormal connectivity were associated with anxiety symptoms. These findings highlight the aberrant topological organization of functional brain network organization in SAD, which provides insights into the neural mechanisms underlying excessive fear and avoidance of social interactions in patients with debilitating social anxiety. •We defined 34 network nodes based on task-based SAD fMRI meta-analytic studies.•SAD had higher functional connectivity in a single connected component.•SAD had a shift of brain network topology toward randomized configurations.•Abnormal connectivity in SAD was significantly associated with anxiety symptoms.

The chromatin remodeler CHD8 , which belongs to the ATP-dependent chromatin remodelers CHD family, is one of the most high-risk mutated genes in autism spectrum disorders. However, the role of CHD8 in neural differentiation and the mechanism of CHD8 in autism remains unclear, despite there are a few studies based on the CHD8 haploinsufficient models. Here, we generate the CHD8 knockout human ESCs by CRISPR/Cas9 technology and characterize the effect of loss-of-function of CHD8 on pluripotency maintenance and lineage determination by utilizing efficient directed differentiation protocols. The results show loss-of-function of CHD8 does not affect human ESC maintenance although having slight effect on proliferation and cell cycle. Interestingly, CHD8 depletion results in defective neuroectoderm differentiation, along with severe cell death in neural progenitor stage. Transcriptome analysis also indicates CHD8 does not alter the expression of pluripotent genes in ESC stage, but in neural progenitor cells depletion of CHD8 induces the abnormal expression of the apoptosis genes and suppresses neuroectoderm-related genes. These results provide the evidence that CHD8 plays an essential role in the pluripotency exit and neuroectoderm differentiation as well as the regulation of apoptosis during neurogenesis.

Schizophrenia is a complex disorder associated with aberrant brain functional connectivity. This study aims to demonstrate the relation of heterogeneous symptomatology in this disorder to distinct brain connectivity patterns within the triple-network model. The study sample comprised 300 first-episode antipsychotic-naive patients with schizophrenia (FES) and 301 healthy controls (HCs). At baseline, resting-state functional magnetic resonance imaging data were captured for each participant, and concomitant neurocognitive functions were evaluated outside the scanner. Clinical information of 49 FES in the discovery dataset were reevaluated at a 6-week follow-up. Differential features between FES and HCs were selected from triple-network connectivity profiles. Cutting-edge unsupervised machine learning algorithms were used to define patient subtypes. Clinical and cognitive variables were compared between patient subgroups. Two FES subgroups with differing triple-network connectivity profiles were identified in the discovery dataset and confirmed in an independent hold-out cohort. One patient subgroup appearing to have more severe clinical symptoms was distinguished by salience network (SN)-centered hypoconnectivity, which was associated with greater impairments in sustained attention. The other subgroup exhibited hyperconnectivity and manifested greater deficits in cognitive flexibility. The SN-centered hypoconnectivity subgroup had more persistent negative symptoms at the 6-week follow-up than the hyperconnectivity subgroup. The present study illustrates that clinically relevant cognitive subtypes of schizophrenia may be associated with distinct differences in connectivity in the triple-network model. This categorization may foster further analysis of the effects of therapy on these network connectivity patterns, which may help to guide therapeutic choices to effectively reach personalized treatment goals.

Neuroimaging findings suggest that social anxiety disorder (SAD) may be correlated with changes in regional- or network-level brain function. However, few studies have explored alterations in intrinsic resting cerebral function in patients with SAD at both the regional and network levels, particularly focusing on the theory of mind (ToM)-related regions. This study was performed to investigate changes in neural activity and functional connectivity (FC) in ToM-related regions during the resting state in SAD patients and to determine how these alterations are correlated with the clinical symptoms of SAD. Forty-three SAD patients and 43 matched healthy controls underwent resting-state functional magnetic resonance imaging (rsfMRI) scans. First, the amplitude of low-frequency fluctuation (ALFF) approach was used to explore regional activity. Then, the ToM-related region, i.e., the left precuneus, which showed altered ALFF values, was adopted as a seed for further FC analyses to assess network-level alterations in SAD. Between-group differences were compared using voxel-based two-sample t-tests (P<0.05, with Gaussian random field correction). Pearson's correlation analyses were performed to examine relationships between alterations in ALFF and FC and clinical symptoms. Compared with the healthy controls, SAD patients showed decreased ALFF in the bilateral putamen (PUT) and left supplementary motor area (SMA) and increased ALFF in the right inferior parietal lobule (IPL), left precuneus and right cerebellar posterior lobe. Moreover, SAD patients exhibited lower connectivity between the left precuneus and the cerebellar posterior lobe, right inferior temporal gyrus (ITG), right parahippocampal gyrus (PHG) and left medial prefrontal cortex (mPFC). The altered ALFF values in the left precuneus and the hypoconnectivity between the left precuneus and left cerebellar posterior lobe were correlated with the patients' clinical symptoms (P<0.05). The precuneus, a ToM-related region, was altered at both the regional and network level in patients with SAD. Pathological fear and avoidance in SAD were correlated with abnormal regional function in the precuneus, whereas depression and anxiety were primarily correlated with functional deficits in the precuneus-related network. The altered FC within the precuneus-cerebellar region may reflect an imbalance in the neuromodulation of anxiety and depressive symptoms in SAD. These findings may facilitate a greater understanding of potential SAD neural substrates and could be used to identify potential targets for further treatment. •Theory of mind (ToM) related region had both regional- and network-level alterations in patients with SAD.•Pathological fear and avoidance in SAD were correlated to abnormal regional functions in the precuneus.•Depression and anxiety were primarily correlated to functional deficits in the precuneus-related network.•The cerebellar dysfunctions may play an important role in the neuromodulation of clinical symptoms in SAD patients.

Several 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. We investigated the resting state networks (RSNs) using independent component analysis (ICA) in 18 chronic Wenchuan earthquake-related PTSD patients versus 20 healthy survivors (HSs). Compared 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. Given 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. These 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.

Abstract Recent neuroanatomical pattern recognition studies have shown some promises for developing an objective neuroimaging-based classification related to schizophrenia. This study explored the feasibility of reliably identifying schizophrenia using single and multimodal multivariate neuroimaging features. Multiple brain measures including regional gray matter (GM) volume, cortical thickness, gyrification, fractional anisotropy (FA), and mean diffusivity (MD) were extracted using fully automated procedures. We used Gradient Boosting Decision Tree to identify the most frequently selected features of each set of neuroanatomical metric and fused multimodal measures. The current classification model was trained and validated based on 98 patients with first-episode schizophrenia (FES) and 106 matched healthy controls (HCs). The classification model was trained and tested in an independent dataset of 54 patients with FES and 48 HCs using imaging data acquired on a different magnetic resonance imaging scanner. Using the most frequently selected features from fused structural and diffusion tensor imaging metrics, a classification accuracy of 75.05% was achieved, which was higher than accuracy derived from a single imaging metric. Most prominent discriminative features included cortical thickness of left transverse temporal gyrus and right parahippocampal gyrus, the FA of left corticospinal tract and right external capsule. In the independent cohort, average accuracy was 76.54%, derived from combined features selected from cortical thickness, gyrification, FA, and MD. These features characterized by GM abnormalities and white matter disruptions have discriminative power with respect to the underlying pathological changes in the brain of individuals having schizophrenia. Our results further highlight the potential advantage of multimodal data fusion for identifying schizophrenia.

This study was to explore the sex differences in clinical characteristics and brain gray matter volume (GMV) alterations in 29 male patients with major depressive disorder (MDDm), 53 female patients with MDD (MDDf), and in 29 male and 53 female matched healthy controls. Maps of GMV were constructed using magnetic resonance imaging data and compared between groups. We evaluated clinical symptoms using the Hamilton Rating Scale for Depression and obtained a total score and five syndrome scores. A two-factor ANCOVA model was specified using SPM8, with sex and diagnosis as the between-subject factors. We found that: (1) significant GMV increase in the left cerebellum and GMV reduction in the bilateral middle temporal gyrus and left ventral medial prefrontal gyrus occurred selectively in male patients, while the GMV reduction in the left lingual gyrus and dorsal medial prefrontal gyrus occurred selectively in female patients; (2) MDDf may have experienced more severe sleep disturbance than MDDm; and (3) the severity of sleep symptom could be predicted by the sex specific brain structural alterations in depressions. These findings suggest that sex specific anatomical alterations existed in MDD, and these alterations were associated with the clinical symptoms.

Chronic cough in adults is commonly caused by respiratory disorders (e.g., cough variant asthma, CVA), ear, nose and throat (ENT) disorders (e.g., postnasal drip), digestive disorders (e.g., gastroesophageal reflux disease, GERD), as well as anaphylaxis and allergy. Tic cough is infrequent in adults but warrants consideration in individuals who have excluded these somatic disorders and exhibit inadequate response to diagnostic treatments, especially those with a history of tic disorder or ongoing tic symptoms. In these cases, a multi-disciplinary treatment (MDT) for chronic cough that includes psychiatrists is recommended as the optimal management approach.