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.

Relationship between SLC6A2 gene polymorphisms and brain volume in Han Chinese adults who lost their sole child.

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.

Modulation of resting-state functional connectivity in default mode network is associated with the long-term treatment outcome in major depressive disorder.

BACKGROUND: Treatment non-response and recurrence are the main sources of disease burden in major depressive disorder (MDD). However, little is known about its neurobiological mechanism concerning the brain network changes accompanying pharmacotherapy. The present study investigated the changes in the intrinsic brain networks during 6-month antidepressant treatment phase associated with the treatment response and recurrence in MDD. METHODS: Resting-state functional magnetic resonance imaging was acquired from untreated patients with MDD and healthy controls at baseline. The patients' depressive symptoms were monitored by using the Hamilton Rating Scale for Depression (HAMD). After 6 months of antidepressant treatment, patients were re-scanned and followed up every 6 months over 2 years. Traditional statistical analysis as well as machine learning approaches were conducted to investigate the longitudinal changes in macro-scale resting-state functional network connectivity (rsFNC) strength and micro-scale resting-state functional connectivity (rsFC) associated with long-term treatment outcome in MDD. RESULTS: Repeated measures of the general linear model demonstrated a significant difference in the default mode network (DMN) rsFNC change before and after the 6-month antidepressant treatment between remitters and non-remitters. The difference in the rsFNC change over the 6-month antidepressant treatment between recurring and stable MDD was also specific to DMN. Machine learning analysis results revealed that only the DMN rsFC change successfully distinguished non-remitters from the remitters at 6 months and recurring from stable MDD during the 2-year follow-up. CONCLUSION: Our findings demonstrated that the intrinsic DMN connectivity could be a unique and important target for treatment and recurrence prevention in MDD.

Connectome gradient dysfunction in major depression and its association with gene expression profiles and treatment outcomes.

Patients with major depressive disorder (MDD) exhibit concurrent deficits in both sensory and higher-order cognitive processing. Connectome studies have suggested a principal primary-to-transmodal gradient in functional brain networks, supporting the spectrum from sensation to cognition. However, whether this gradient structure is disrupted in patients with MDD and how this disruption associates with gene expression profiles and treatment outcome remain unknown. Using a large cohort of resting-state fMRI data from 2227 participants (1148 MDD patients and 1079 healthy controls) recruited at nine sites, we investigated MDD-related alterations in the principal connectome gradient. We further used Neurosynth, postmortem gene expression, and an 8-week antidepressant treatment (20 MDD patients) data to assess the meta-analytic cognitive functions, transcriptional profiles, and treatment outcomes related to MDD gradient alterations, respectively. Relative to the controls, MDD patients exhibited global topographic alterations in the principal primary-to-transmodal gradient, including reduced explanation ratio, gradient range, and gradient variation (Cohen's d = 0.16-0.21), and focal alterations mainly in the primary and transmodal systems (d = 0.18-0.25). These gradient alterations were significantly correlated with meta-analytic terms involving sensory processing and higher-order cognition. The transcriptional profiles explained 53.9% variance of the altered gradient pattern, with the most correlated genes enriched in transsynaptic signaling and calcium ion binding. The baseline gradient maps of patients significantly predicted symptomatic improvement after treatment. These results highlight the connectome gradient dysfunction in MDD and its linkage with gene expression profiles and clinical management, providing insight into the neurobiological underpinnings and potential biomarkers for treatment evaluation in this disorder.

Aberrant temporal-spatial complexity of intrinsic fluctuations in major depression.

Accumulating evidence suggests that the brain is highly dynamic; thus, investigation of brain dynamics especially in brain connectivity would provide crucial information that stationary functional connectivity could miss. This study investigated temporal expressions of spatial modes within the default mode network (DMN), salience network (SN) and cognitive control network (CCN) using a reliable data-driven co-activation pattern (CAP) analysis in two independent data sets. We found enhanced CAP-to-CAP transitions of the SN in patients with MDD. Results suggested enhanced flexibility of this network in the patients. By contrast, we also found reduced spatial consistency and persistence of the DMN in the patients, indicating reduced variability and stability in individuals with MDD. In addition, the patients were characterized by prominent activation of mPFC. Moreover, further correlation analysis revealed that persistence and transitions of RCCN were associated with the severity of depression. Our findings suggest that functional connectivity in the patients may not be simply attenuated or potentiated, but just alternating faster or slower among more complex patterns. The aberrant temporal-spatial complexity of intrinsic fluctuations reflects functional diaschisis of resting-state networks as characteristic of patients with MDD.

Relationship between childhood maltreatment and cognitive function in medication-free patients with major depressive disorder.

This study aimed to elucidate the contribution of childhood maltreatment (CM) and the disease of major depressive disorder (MDD) on cognitive function in medication-free patients in a current depressive episode, and to examine the effect of CM on the improvement of cognitive function after treatment with antidepressants. One hundred and fifty-three unmedicated patients with MDD and 142 healthy controls (HCs) underwent clinical interviews. CM assessment was performed using the Childhood Trauma Questionnaire (CTQ), and a battery of comprehensive neurocognitive tests was used to assess the participants' executive function, processing speed, attention, and memory. After 6 months of treatment with antidepressants, the neurocognitive tests were reperformed in patients with MDD and HCs. There was a significant main effect of MDD on all four cognitive domains, while the main effect of CM was only significant on memory. No significant interactive effect was found between MDD and CM on any of the cognitive domains. In the MDD group, higher CTQ total score was predictive of poorer memory performance. After treatment, significant main effects of treatment and MDD were found on all four cognitive domains in remitted patients with MDD. No significant main effect of CM or three-way interaction effect of treatment × MDD × CM was found on any of the cognitive domains. The disease of MDD contributed to impairments in all four cognitive domains. CM independently contributed to memory impairment in patients in a current depressive episode, with higher severity of CM predictive of poorer memory performance.

Prevalence and risk factors of anxious and depressive symptoms in first-trimester females and their partners: a study during the pandemic era of COVID-19 in China.

BACKGROUND: The pandemic of coronavirus disease 2019 lastingly affects public mental health. Many studies have described symptoms of anxiety and depression in pregnant women before the pandemic. However, the limited study focuses on the prevalence and risk factors of mood symptoms among first-trimester females and their partners during the pandemic in China, which was the aim of the study. METHODS: One hundred and sixty-nine first-trimester couples were enrolled. The Edinburgh Postnatal Depression Scale, Patient Health Questionnaire-9, Generalized Anxiety Disorder 7-Item, Family Assessment Device-General Functioning (FAD-GF), and Quality of Life Enjoyment and Satisfaction Questionnaire, Short Form (Q-LES-Q-SF) were applied. Data were mainly analyzed through logistic regression analysis. RESULTS: 17.75% and 5.92% of first-trimester females had depressive and anxious symptoms, respectively. Among partners, 11.83% and 9.47% had depressive and anxious symptoms, respectively. In females, higher scores of FAD-GF (OR = 5.46 and 13.09; P < 0.05) and lower scores of Q-LES-Q-SF (OR = 0.83 and 0.70; P < 0.01) were related to the risk of depressive and anxious symptoms. Higher scores of FAD-GF were associated with the risk of depressive and anxious symptoms in partners (OR = 3.95 and 6.89; P < 0.05). A history of smoking was also related to males' depressive symptoms (OR = 4.49; P < 0.05). CONCLUSION: This study prompted prominent mood symptoms during the pandemic. Family functioning, quality of life, and smoking history increased risks of mood symptoms among early pregnant families, which facilitated the updating of medical intervention. However, the current study did not explore interventions based on these findings.

Impact of childhood maltreatment on adult resilience.

BACKGROUND: Previous studies suggested that childhood maltreatment is associated with poor health outcomes. While not everyone who experiences abuse as a child goes on to experience poor mental health, some traumatized people are grown to be more resilient than others. Few studies have examined the association between childhood maltreatment and adult resilience. This study aimed to determine different relationships between specific types and features of childhood maltreatment with adult resilience among Chinese with Major Depressive Disorder (MDD) and healthy controls (HCs). METHODS: A total of 101 patients with MDD and 116 participants in the healthy control (HC) group from Zhumadian Psychiatric Hospital and its nearby communities were included in this analysis. Childhood maltreatment was assessed retrospectively using Childhood Trauma Questionnaire (CTQ). Adults' resilience was assessed by the Connor-Davidson Resilience Scale (CD-RISC). Generalized linear models were applied between childhood maltreatment (specific types and features) and resilience adjusting for covariates. RESULTS: The total score of CD-RISC and factor scores of strength, optimism, and tenacity in the HC group were higher than those in the MDD group. CTQ total score had a negative association with optimism score among participants in MDD (ß=-0.087, P < 0.001) and HC (ß=-0.074, P = 0.023) groups. Higher emotional neglect (EN) score (ß=-0.169, P = 0.001) and physical neglect (PN) score (ß=-0.153, P = 0.043) were related to a worse optimism score in MDD group. Emotional abuse (EA) score was associated with a worse tenacity score (ß=-0.674, P = 0.031) in MDD group. For participants in HC group, higher EN and PN scores were related to worse resilience scores (tenacity, strength, and optimism). CONCLUSIONS: Patients with MDD showed lower optimism than HCs. Childhood maltreatment, especially childhood negect, independently contributed to optimism, with more severe childhood maltreatment predictive of worse performance of optimism. EA in childhood was also linked to worse tenacity in adult patients with MDD.

The relationship between personality traits and dysfunctional attitudes in individuals with or without major depressive disorder: a case control study.

BACKGROUND: Dysfunctional attitudes, which are characterized by distorted self-cognitions, were considered to be linked to personality traits. It was found that certain personality traits may predict dysfunctional attitudes in patients with major depressive disorder (MDD). Nonetheless, the relationship between personality traits and dysfunctional attitudes remains under-researched. AIMS: The aim of this study is to examine the relationship between specific domains of Sixteen Personality Factor (16PF) and dysfunctional attitudes in Chinese participants with or without MDD. In addition, the present study explores the associations between 16PF and eight subtypes of dysfunctional attitudes, based on the proposed eight-factor structure of the Chinese version of the Dysfunctional Attitude Scale-Form A (C-DAS-A). METHODS: One hundred and sixty-eight participants with MDD and 130 healthy participants were included in the study (Trial Registration Number: ChiCTR1800014591). Personality was assessed using the 16PF Questionnaire. Dysfunctional attitudes were measured through the C-DAS-A. RESULTS: The 16PF dimensions associated with dysfunctional attitudes and the eight subtypes were mainly concentrated in the four anxiety facets including factors C, L, O, and Q4, in both MDD and HC groups. There were significant differences in the 16 PF dimensions that would explain dysfunctional attitudes between the two groups, which were as follows: factors C, G, and O in the MDD group, and factors L and Q4 in the HC group. CONCLUSIONS: Personality traits, especially the anxiety-related personality traits, were distinctly associated with the development of dysfunctional attitudes in people with or without MDD.

Associations of adverse childhood experiences with common psychiatric disorder in later life: results from the China mental health survey.

BACKGROUND: Associations between adverse childhood experiences (ACEs) and common psychiatric disorders among older Chinese individuals have not been well reported. The objectives of this study are to examine the prevalence of ACEs and the associations of ACEs with common psychiatric disorders among older adults in China. METHODS: The study used data from the China Mental Health Survey (CMHS), a nationally representative epidemiological survey, which used computer-assisted personal interviewing (CAPI), logistic regression models were used to examine community-based adult psychiatric disorders and associated risk factors. Finally, 2,317 individuals aged 60 years or over were included in the CMHS. The national prevalence of ACEs in older adults were estimated and logistic regression were used to analyse the association between ACEs and past-year psychiatric disorders. RESULTS: Prevalence of ACEs among older adults in China was 18.1%. The three most common types of ACEs were neglect (11.6%), domestic violence (9.2%), and parental loss (9.1%). This study proved the association between ACEs and common past-year psychiatric disorders in older adults. ACEs increased the risk of past-year psychiatric disorders in older adults. After adjustment for age, sex, marital status, employment status, education, rural or urban residence, region, and physical diseases, the association between ACEs and past-year psychiatric disorders were still significant. CONCLUSIONS: ACEs are linked to an increased risk for past-year psychiatric disorders in older adults. ACEs may have long-term effects on older adults' mental well-being. Preventing ACEs may help reduce possible adverse health outcomes in later life.

Protocol of a prospective community-based study about the onset and course of depression in a nationally representative cohort of adults in China: the China Depression Cohort Study-I.

BACKGROUND: Depression is the second most important cause of disability worldwide. Reducing this major burden on global health requires a better understanding of the etiology, risk factors, and course of the disorder. With the goal of improving the prevention, recognition, and appropriate management of depressive disorders in China, the China Depression Cohort Study will establish a nationally representative sample of at least 85,000 adults (the China Depression Cohort Study-I) and 15,000 middle school students (the China Depression Cohort Study-II) and follow them over time to identify factors that influence the onset, characteristics, and course of depressive disorders. This protocol describes the China Depression Cohort Study-I. METHODS: A multistage stratified random sampling method will be used to identify a nationally representative community-based cohort of at least 85,000 adults (i.e., ≥ 18 years of age) from 34 communities in 17 of mainland China's 31 provincial-level administrative regions. Baseline data collection includes 1) demographic, social and clinical data, 2) diagnostic information, 3) biological samples (i.e., blood, urine, hair), 4) brain MRI scans, and 5) environmental data (e.g., community-level metrics of climate change, air pollution, and socio-economic characteristics). Baseline findings will identify participants with or without depressive disorders. Annual reassessments will monitor potential risk factors for depression and identify incident cases of depression. Cox Proportional-Hazards Regression, Network analysis, Disease trajectory modelling, and Machine learning prediction models will be used to analyze the collected data. The study's main outcomes are the occurrence of depressive disorders; secondary outcomes include adverse behaviors (e.g., self-harm, suicide), the recurrence of depression and the incidence other mental disorders. DISCUSSION: The China Depression Cohort Study-I will collect a comprehensive, nationally representative set of individual-level and community-level variables over time. The findings will reframe the understanding of depression from a 'biology-psychology-society' perspective. This perspective will improve psychiatrists' understanding of depression and, thus, promote the development of more effective subgroup-specific antidepressant drugs and other interventions based on the new biomarkers and relationships identified in the study. TRAIL REGISTRATION: The protocol has been registered on the Chinese Clinical Trial Registry (No. ChiCTR2200059016).

Spot Detection for Laser Sensors Based on Annular Convolution Filtering.

Spot detection has attracted continuous attention for laser sensors with applications in communication, measurement, etc. The existing methods often directly perform binarization processing on the original spot image. They suffer from the interference of the background light. To reduce this kind of interference, we propose a novel method called annular convolution filtering (ACF). In our method, the region of interest (ROI) in the spot image is first searched by using the statistical properties of pixels. Then, the annular convolution strip is constructed based on the energy attenuation property of the laser and the convolution operation is performed in the ROI of the spot image. Finally, a feature similarity index is designed to estimate the parameters of the laser spot. Experiments on three datasets with different kinds of background light show the advantages of our ACF method, with comparison to the theoretical method based on international standard, the practical method used in the market products, and the recent benchmark methods AAMED and ALS.

Psychosocial crisis intervention for coronavirus disease 2019 patients and healthcare workers. / æ–°åž‹å† çŠ¶ç— æ¯’è‚ºç‚Žæ‚£è€ å’ŒåŒ»åŠ¡äººå‘˜çš„å¿ƒç†ç¤¾ä¼šå±æœºå¹²é¢„ï¼ˆè‹±æ–‡ï¼‰.

OBJECTIVES: Shelter hospital was an alternative way to provide large-scale medical isolation and treatment for people with mild coronavirus disease 2019 (COVID-19). Due to various reasons, patients admitted to the large shelter hospital was reported high level of psychological distress, so did the healthcare workers. This study aims to introduce a comprehensive and multifaceted psychosocial crisis intervention model. METHODS: The psychosocial crisis intervention model was provided to 200 patients and 240 healthcare workers in Wuhan Wuchang shelter hospital. Patient volunteers and organized peer support, client-centered culturally sensitive supportive care, timely delivery of scientific information about COVID-19 and its complications, mental health knowledge acquisition of non-psychiatric healthcare workers, group activities, counseling and education, virtualization of psychological intervention, consultation and liaison were exhibited respectively in the model. Pre-service survey was done in 38 patients and 49 healthcare workers using the Generalized Anxiety Disorder 7-item (GAD-7) scale, the Patient Health Questionnaire 2-item (PHQ-2) scale, and the Primary Care PTSD screen for the Diagnostic and Statistical Manual of Mental Disorders, 5th edition (PC-PTSD-5). Forty-eight healthcare workers gave feedback after the intervention. RESULTS: The psychosocial crisis intervention model was successfully implemented by 10 mental health professionals and was well-accepted by both patients and healthcare workers in the shelter hospital. In pre-service survey, 15.8% of 38 patients were with anxiety, 55.3% were with stress, and 15.8% were with depression; 16.3% of 49 healthcare workers were with anxiety, 26.5% were with stress, and 22.4% were with depression. In post-service survey, 62.5% of 48 healthcare workers thought it was very practical, 37.5% thought more practical; 37.5% of them thought it was very helpful to relief anxiety and insomnia, and 27.1% thought much helpful; 37.5% of them thought it was very helpful to recognize patients with anxiety and insomnia, and 29.2% thought much helpful; 35.4% of them thought it was very helpful to deal with patients' anxiety and insomnia, and 37.5% thought much helpful. CONCLUSIONS: Psychological crisis intervention is feasible, acceptable, and associated with positive outcomes. Future tastings of this model in larger population and different settings are warranted.

Psychoradiological abnormalities in treatment-naive noncomorbid patients with posttraumatic stress disorder.

BACKGROUND: Neuroimaging studies in posttraumatic stress disorder (PTSD) have identified various alterations in white matter (WM) microstructural organization. However, it remains unclear whether these are localized to specific regions of fiber tracts, and what diagnostic value they might have. This study set out to explore the spatial profile of WM abnormalities along defined fiber tracts in PTSD. METHODS: Diffusion tensor images were obtained from 77 treatment-naive noncomorbid patients with PTSD and 76 demographically matched trauma-exposed non-PTSD (TENP) controls. Using automated fiber quantification, tract profiles of fractional anisotropy, axial diffusivity, mean diffusivity, and radial diffusivity were calculated to evaluate WM microstructural organization. Results were analyzed by pointwise comparisons, by correlation with symptom severity, and for diagnosis-by-sex interactions. Support vector machine analyses assessed the ability of tract profiles to discriminate PTSD from TENP. RESULTS: Compared to TENP, PTSD showed lower fractional anisotropy accompanied by higher radial diffusivity and mean diffusivity in the left uncinate fasciculus, and lower fractional anisotropy accompanied by higher radial diffusivity in the right anterior thalamic radiation. Tract profile alterations were correlated with symptom severity, suggesting a pathophysiological relevance. There were no significant differences in diagnosis-by-sex interaction. Tract profiles allowed individual classification of PTSD versus TENP with significant accuracy, of potential diagnostic utility. CONCLUSIONS: These findings add to the knowledge of the neuropathological basis of PTSD. WM alterations based on a tract-profile quantification approach are a potential biomarker for PTSD.

Association between childhood trauma and medication adherence among patients with major depressive disorder: the moderating role of resilience.

BACKGROUND: Suboptimal medication adherence is a major reason for failure in the management of major depressive disorder (MDD), childhood trauma might be an essential risk factor of suboptimal medication adherence. This study aimed to comprehensively explore the associations between different types of childhood trauma and medication adherence among patients with MDD, and to test whether resilience has moderating effects on the foregoing associations. METHODS: Participants were from the Depression Cohort in China (ChiCTR registry number 1900022145), 282 MDD patients with completed both baseline and 12-weeks follow-up investigations were included in this study. The diagnosis of MDD was assessed by trained psychiatrists using the Mini-International Neuropsychiatric Interview (M.I.N.I.). Childhood trauma was evaluated using the Childhood Trauma Questionnaire-28 item Short Form (CTQ-SF), and resilience was evaluated using the Connor-Davidson Resilience Scale (CD-RISC). Demographic characteristics, depression symptoms, anxiety symptoms, suicidal ideation, suicidal attempt, insomnia symptoms, and painful somatic symptoms were also investigated. Participants were divided into groups of optimal and suboptimal adherence based on their Medication Adherence Rating Scale scores. Logistic regression and stratified analyses were performed. RESULTS: A total of 234 participants (83%) reported suboptimal medication adherence. After adjusting for covariates, CTQ total scores (AOR = 1.03, 95%CI = 1.01-1.06), CTQ measures of sexual abuse (AOR = 1.17, 95%CI = 1.01-1.37), and CTQ measures of physical neglect (AOR = 1.12, 95%CI = 1.02-1.23) were all associated with an increased likelihood of suboptimal adherence. There were significant moderating effects of resilience on the associations of childhood trauma (P = 0.039) and physical neglect (P = 0.034) with medication adherence. The stratification analyses showed that CTQ total scores and CTQ measures of physical neglect were independently associated with an increased risk of suboptimal adherence among patients with MDD with low-resilience or moderate-resilience, while not significantly associated with suboptimal adherence in those with high-resilience. CONCLUSION: Childhood trauma was a significant risk factor of suboptimal adherence among patients with MDD, and resilience moderated the foregoing association. Obtaining a history of childhood trauma and assessing resilience may help identify patients with suboptimal adherence when providing MDD pharmacotherapy. Psychiatrists may consider enhancing resilience to cope with the adverse effects of childhood trauma on medication adherence.

Screening Depressive Symptoms and Incident Major Depressive Disorder Among Chinese Community Residents Using a Mobile App-Based Integrated Mental Health Care Model: Cohort Study.

BACKGROUND: Depression is associated with significant morbidity and human capital costs globally. Early screening for depressive symptoms and timely depressive disorder case identification and intervention may improve health outcomes and cost-effectiveness among affected individuals. China's public and academic communities have reached a consensus on the need to improve access to early screening, diagnosis, and treatment of depression. OBJECTIVE: This study aims to estimate the screening prevalence and associated factors of subthreshold depressive symptoms among Chinese residents enrolled in the cohort study using a mobile app-based integrated mental health care model and investigate the 12-month incidence rate and related factors of major depressive disorder (MDD) among those with subthreshold depressive symptoms. METHODS: Data were drawn from the Depression Cohort in China (DCC) study. A total of 4243 community residents aged 18 to 64 years living in Nanshan district, Shenzhen city, in Guangdong province, China, were encouraged to participate in the DCC study when visiting the participating primary health care centers, and 4066 (95.83%) residents who met the DCC study criteria were screened for subthreshold depressive symptoms using the Patient Health Questionnaire-9 at baseline. Of the 4066 screened residents, 3168 (77.91%) with subthreshold depressive symptoms were referred to hospitals to receive a psychiatric diagnosis of MDD within 12 months. Sleep duration, anxiety symptoms, well-being, insomnia symptoms, and resilience were also investigated. The diagnosis of MDD was provided by trained psychiatrists using the Mini-International Neuropsychiatric Interview. Univariate and multivariate logistic regression models were performed to explore the potential factors related to subthreshold depressive symptoms at baseline, and Cox proportional hazards models were performed to explore the potential factors related to incident MDD. RESULTS: Anxiety symptoms (adjusted odds ratio [AOR] 1.63, 95% CI 1.42-1.87) and insomnia symptoms (AOR 1.13, 95% CI 1.05-1.22) were associated with an increased risk of subthreshold depressive symptoms, whereas well-being (AOR 0.93, 95% CI 0.87-0.99) was negatively associated with depressive symptoms. During the follow-up period, the 12-month incidence rate of MDD among participants with subthreshold depressive symptoms was 5.97% (189/3168). After incorporating all significant variables from the univariate analyses, the multivariate Cox proportional hazards model reported that a history of comorbidities (adjusted hazard ratio [AHR] 1.49, 95% CI 1.04-2.14) and anxiety symptoms (AHR 1.13, 95% CI 1.09-1.17) were independently associated with an increased risk of incident MDD. The 5-item World Health Organization Well-Being Index was associated with a decreased risk of incident MDD (AHR 0.90, 95% CI 0.86-0.94). CONCLUSIONS: Elevated anxiety symptoms and unfavorable general well-being were significantly associated with subthreshold depressive symptoms and incident MDD among Chinese residents in Shenzhen. Early screening for subthreshold depressive symptoms and related factors may be helpful for identifying populations at high risk of incident MDD.

Mental health conditions among the general population, healthcare workers and quarantined population during the coronavirus disease 2019 (COVID-19) pandemic.

This study sought to assess the differences in mental health conditions among the general population, quarantined population and healthcare workers during the COVID-19 outbreak in China. An online rapid assessment captured depressive and anxiety symptoms, and sleep quality data. A total of 2689 participants (n=374 general population, n=403 healthcare workers, n=1912 quarantined population) were included in the final statistical analysis. The proportion of individuals with mild and/or serious depression and anxiety were higher in the general population when compared to the quarantined population and healthcare workers (58.6% vs. 25.1%vs. 48.6%, P<0.001; 41.2% vs. 18.5% vs. 35.7%, P<0.001). The prevalence of sleep disturbance was higher among healthcare workers than the general population and quarantined population (29.8% vs. 24.1% vs. 22.7%, P=0.013). Logistic regression analysis showed that, perceived effect on daily life was associated with depression, anxiety and sleep disturbance in the general population, quarantined population and the healthcare workers. The general population had a greater risk of developing psychological problems. The healthcare workers suffered the poorest sleep quality. Future research must further explorethe targeted measures for the general population and healthcare workers while combating COVID-19.

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OBJECTIVES: Major depressive disorder (MDD) patients with anhedonia tend to have a poor prognosis. The underlying imaging basis for anhedonia in MDD remains largely unknown. The relationship between nodal properties and anhedonia in MDD patients need to be further investigated. Herein, this study aims to explore differences of cerebral functional node characteristics in MDD patients with severe anhedonia (MDD-SA) and MDD patients with mild anhedonia (MDD-MA) before and after the antidepressant treatment. METHODS: Ninety participants with current MDD were recruited in this study. 24-Item Hamilton Depression Scale (HAMD-24) and Snaith-Hamilton Pleasure Scale (SHAPS) were used to assess the severity of depression and anhedonia at baseline and the end of 6-months treatment. The MDD patients who scored above the 25th percentile on the SHAPS were assigned to an MDD-SA group (n=19), while those who scored below the 25th percentile were assigned to an MDD-MA group (n=18). All patients in the 2 groups received antidepressant treatment. Functional magnetic resonance imaging (fMRI) images of all the patients were collected at baseline and the end of 6-months treatment. Graph theory was applied to analyze the patients' cerebral functional nodal characteristics, which were measured by efficiency (ei) and degree (ki). RESULTS: Repeated measures 2-factor ANCOVA showed significant main effects on group on the ei and ki values of left superior frontal gyrus (LSFG) (P=0.003 and P=0.008, respectively), and on the ei and ki values of left medial orbital-frontal gyrus (LMOFG) (P=0.004 and P=0.008, respectively). Compared with the MDD-MA group, the significantly higher ei and ki values of the LSFG (P=0.015 and P=0.021, respectively), and the significantly higher ei and ki values of the LMOFG (P=0.015 and P=0.037, respectively) were observed in the MDD-SA group at baseline. Meanwhile, higher SHAPS scores could result in higher ei and ki values of LSFG (P=0.019 and P=0.026, respectively), and higher ei value of LMOFG (P=0.040) at baseline; higher SHAPS scores could result in higher ei values of LSFG (P=0.049) at the end of 6-months treatment. The multiple linear regression analysis revealed that sex were negatively correlated with the ei and ki values of LSFG (r= -0.014, P=0.004; r=-1.153, P=0.001, respectively). The onset age of MDD was negatively correlated with the ki value of LSFG (r=-0.420, P=0.034) at the end of 6-months treatment. We also found that SHAPS scores at baseline were positively correlated with the HAMD-24 scores (r=0.387, P=0.022) at the end of 6-months treatment. CONCLUSIONS: There are obvious differences in nodal properties between the MDD-SA and the MDD-MA patients, such as the high ei of LSFG in the MDD-SA patients, which may be associated with the severity of anhedonia. These nodal properties could be potential biomarkers for the prognosis of MDD. The increased ei and ki values in the LSFG of MDD-SA patients may underlie a compensatory mechanism or protective mechanism. The mechanism may be an important component of the pathological mechanism of MDD-SA. The poor prognosis in the MDD-SA patients suggests that anhedonia may predict a worse prognosis in MDD patients. Sex and onset age of MDD may affect the nodal properties of LSFG at baseline and the end of 6-months treatment.

Decreased functional connectivity of hippocampal subregions and methylation of the NR3C1 gene in Han Chinese adults who lost their only child.

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.

Using deep learning to classify pediatric posttraumatic stress disorder at the individual level.

BACKGROUND: Children exposed to natural disasters are vulnerable to developing posttraumatic stress disorder (PTSD). Previous studies using resting-state functional neuroimaging have revealed alterations in graph-based brain topological network metrics in pediatric PTSD patients relative to healthy controls (HC). Here we aimed to apply deep learning (DL) models to neuroimaging markers of classification which may be of assistance in diagnosis of pediatric PTSD. METHODS: We studied 33 pediatric PTSD and 53 matched HC. Functional connectivity between 90 brain regions from the automated anatomical labeling atlas was established using partial correlation coefficients, and the whole-brain functional connectome was constructed by applying a threshold to the resultant 90 * 90 partial correlation matrix. Graph theory analysis was used to examine the topological properties of the functional connectome. A DL algorithm then used this measure to classify pediatric PTSD vs HC. RESULTS: Graphic topological measures using DL provide a potentially clinically useful classifier for differentiating pediatric PTSD and HC (overall accuracy 71.2%). Frontoparietal areas (central executive network), cingulate cortex, and amygdala contributed the most to the DL model's performance. CONCLUSIONS: Graphic topological measures based on fMRI data could contribute to imaging models of clinical utility in distinguishing pediatric PTSD from HC. DL model may be a useful tool in the identification of brain mechanisms PTSD participants.