The associations between modifiable risk factors and nonalcoholic fatty liver disease: A comprehensive Mendelian randomization study.

BACKGROUND AND AIMS: Early identification of modifiable risk factors is essential for the prevention of nonalcoholic fatty liver disease (NAFLD). We aimed to systematically explore the relationships between genetically predicted modifiable risk factors and NAFLD. APPROACH AND RESULTS: We applied univariable and multivariable Mendelian randomization analyses to explore the relationships between 35 modifiable risk factors and NAFLD. We also evaluated the combined results in three independent large genome-wide association studies. Genetically predicted alcohol frequency, elevated serum levels of liver enzymes, triglycerides, C-reactive protein, and obesity traits, including body mass index, waist circumference, and body fat mass, were associated with increased risks of NAFLD (all with p < 0.05). Poor physical condition had a suggestive increased risk for NAFLD (odds ratio [OR] = 2.63, p  = 0.042). Genetically instrumented type 2 diabetes (T2DM), hypothyroidism, and hypertension all increased the risk for NAFLD, and the ORs (95% confidence interval) were 1.508 (1.20-1.90), 13.08 (1.53-111.65), and 3.11 (1.33-7.31) for a 1-U increase in log-transformed odds, respectively. The positive associations of T2DM and hypertension with NAFLD remained significant in multivariable analyses. The combined results from the discovery and two replication datasets further confirmed that alcohol frequency, elevated serum liver enzymes, poor physical condition, obesity traits, T2DM, and hypertension significantly increase the risk of NAFLD, whereas higher education and high-density lipoprotein cholesterol (HDL-cholesterol) could lower NAFLD risk. CONCLUSIONS: Genetically predicted alcohol frequency, elevated serum liver enzymes, poor physical condition, obesity traits, T2DM, and hypertension were associated with an increased risk of NAFLD, whereas higher education and HDL-cholesterol were associated with a decreased risk of NAFLD.

Common and distinct functional brain network abnormalities in adolescent, early-middle adult, and late adult major depressive disorders.

BACKGROUND: The age-related heterogeneity in major depressive disorder (MDD) has received significant attention. However, the neural mechanisms underlying such heterogeneity still need further investigation. This study aimed to explore the common and distinct functional brain abnormalities across different age groups of MDD patients from a large-sample, multicenter analysis. METHODS: The analyzed sample consisted of a total of 1238 individuals including 617 MDD patients (108 adolescents, 12-17 years old; 411 early-middle adults, 18-54 years old; and 98 late adults, > = 55 years old) and 621 demographically matched healthy controls (60 adolescents, 449 early-middle adults, and 112 late adults). MDD-related abnormalities in brain functional connectivity (FC) patterns were investigated in each age group separately and using the whole pooled sample, respectively. RESULTS: We found shared FC reductions among the sensorimotor, visual, and auditory networks across all three age groups of MDD patients. Furthermore, adolescent patients uniquely exhibited increased sensorimotor-subcortical FC; early-middle adult patients uniquely exhibited decreased visual-subcortical FC; and late adult patients uniquely exhibited wide FC reductions within the subcortical, default-mode, cingulo-opercular, and attention networks. Analysis of covariance models using the whole pooled sample further revealed: (1) significant main effects of age group on FCs within most brain networks, suggesting that they are decreased with aging; and (2) a significant age group × MDD diagnosis interaction on FC within the default-mode network, which may be reflective of an accelerated aging-related decline in default-mode FCs. CONCLUSIONS: To summarize, these findings may deepen our understanding of the age-related biological and clinical heterogeneity in MDD.

Long-term Use of Proton Pump Inhibitors is Associated With An Increased Risk of Nonalcoholic Fatty Liver Disease.

BACKGROUNDS: The adverse effects of long-term use of proton pump inhibitors (PPIs) have led to growing concern. The association between PPIs use and the risks of nonalcoholic fatty liver disease (NAFLD) remains controversial. GOAL: The aim of this study was to investigate the association between PPIs use and the risks of NAFLD among the general adult population in the United States. STUDY: We performed a cross-sectional study by extracting data from the National Health and Nutrition Examination Survey of 2017 to 2018. The association between PPIs use and NAFLD risks was analyzed by weighted multivariate logistic regression. RESULTS: Among the 4238 participants included in this study, 2167 were diagnosed with NAFLD. In the multivariate logistic regression model, PPIs use was associated with increased risks of NAFLD [odds ratio (OR): 1.318, 95% CI: 1.044-1.663; P=0.020]. This association was nonsignificant in participants taking PPIs for ˂5 years (OR: 0.846, 95% CI: 0.579-1.238; P=0.390), whereas it remained significant in participants taking PPIs for more than 5 years (OR: 2.016, 95% CI: 1.366-2.975; P=0.031). Further analysis showed that the use of PPIs was positively associated with risks of severe hepatic steatosis (OR: 1.451, 95% CI: 1.034-2.036; P=0.031) but not with mild-to-moderate steatosis (OR: 1.242, 95% CI: 0.886-1.741; P=0.208). CONCLUSIONS: This study indicated that taking PPIs was associated with increased risks of NAFLD, especially severe hepatic steatosis. Awareness should be raised regarding the potential risks of NAFLD when prescribing PPIs.

Aberrant brain dynamics in major depressive disorder during working memory task.

Working memory (WM) is a distributed and dynamic process, and WM deficits are recognized as one of the top-ranked endophenotype candidates for major depressive disorders (MDD). However, there is a lack of knowledge of brain temporal-spatial profile of WM deficits in MDD. We used the dynamical degree centrality (dDC) to investigate the whole-brain temporal-spatial profile in 40 MDD and 40 controls during an n-back task with 2 conditions (i.e., '0back' and '2back'). We explored the dDC temporal variability and clustered meta-stable states in 2 groups during different WM conditions. Pearson's correlation analysis was used to evaluate the relationship between the altered dynamics with clinical symptoms and WM performance. Compared with controls, under '2back vs. 0back' contrast, patients showed an elevated dDC variability in wide range of brain regions, including the middle frontal gyrus, orbital part of inferior frontal gyrus (IFGorb), hippocampus, and middle temporal gyrus. Furthermore, the increased dDC variability in the hippocampus and IFGorb correlated with worse WM performance. However, there were no significant group-related differences in the meta-stable states were observed. This study demonstrated the increased WM-related instability (i.e., the elevated dDC variability) was represented in MDD, and enhancing stability may help patients achieve better WM performance.

Evaluating test-retest reliability and sex-/age-related effects on temporal clustering coefficient of dynamic functional brain networks.

The multilayer dynamic network model has been proposed as an effective method to understand the brain function. In particular, derived from the definition of clustering coefficient in static networks, the temporal clustering coefficient provides a direct measure of the topological stability of dynamic brain networks and shows potential in predicting altered brain functions. However, test-retest reliability and demographic-related effects on this measure remain to be evaluated. Using a data set from the Human Connectome Project (157 male and 180 female healthy adults; 22-37 years old), the present study investigated: (1) the test-retest reliability of temporal clustering coefficient across four repeated resting-state functional magnetic resonance imaging scans as measured by intraclass correlation coefficient (ICC); and (2) sex- and age-related effects on temporal clustering coefficient. The results showed that (1) the temporal clustering coefficient had overall moderate test-retest reliability (ICC > 0.40 over a wide range of densities) at both global and subnetwork levels, (2) female subjects showed significantly higher temporal clustering coefficient than males at both global and subnetwork levels, particularly within the default-mode and subcortical regions, and (3) temporal clustering coefficient of the subcortical subnetwork was positively correlated with age in young adults. The results of sex effects were robustly replicated in an independent REST-meta-MDD data set, while the results of age effects were not. Our findings suggest that the temporal clustering coefficient is a relatively reliable and reproducible approach for identifying individual differences in brain function, and provide evidence for demographically related effects on the human brain dynamic connectomes.

Associations of serum uric acid levels with liver disease-related morbidity and mortality: A prospective cohort study of the UK Biobank.

BACKGROUND AND AIMS: The association of serum uric acid (SUA) levels with liver-related morbidity and mortality remains undetermined. Therefore, we aimed to explore the association of SUA levels with liver-related morbidity and mortality. METHODS: The present cohort study included 459 619 adults from the UK Biobank. Multivariable Cox proportional hazards models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for the associations of SUA levels with morbidity and mortality of overall liver disease. Mendelian randomization (MR) analyses were conducted to explore the underlying causality. A polygenic risk score was generated to assess whether there was a gene-exposure interaction. RESULTS: During a median follow-up of 12.6 years, 14 302 nonfatal and 609 fatal cases of overall liver disease were identified. Compared to individuals in the lowest quartile, the HRs (95% CI) of incident overall liver disease were 1.08 (1.02-1.14), 1.13 (1.07-1.20) and 1.44 (1.36-1.53) for individuals with SUA levels in quartiles 2, 3 and 4 respectively. Similarly, the HRs (95% CI) of liver disease-associated mortality were 1.09 (0.78-1.52), 1.55 (1.14-2.13) and 1.96 (1.42-2.69) for individuals with SUA levels in quartiles 2, 3 and 4 respectively. The MR results did not support the causal association of SUA levels with liver disease. In addition, there was a significant modification effect of the polygenic risk score on the association of SUA levels with incident overall liver disease (pinteraction  = .003). CONCLUSIONS: Higher SUA levels were significantly associated with an increased risk of overall liver disease morbidity and mortality.

Association between ultra-processed foods consumption and risk of non-alcoholic fatty liver disease: a population-based analysis of NHANES 2011-2018.

An increasing number of studies have evaluated the association between ultra-processed foods (UPF) consumption and metabolic disorders. However, the association between UPF intake and non-alcoholic fatty liver disease (NAFLD) remains unclear. In this study, we analysed data from 6545 participants who were recruited in National Health and Nutrition Examination Surveys 2011-2018. UPF were defined in light of the NOVA food classification system and divided into quartiles based on its proportion of total weight intake. Complex logistic regression models were used to assess the association between UPF and NAFLD. Mediation analyses were conducted to reveal underlying mediators. We found that NAFLD patients consumed more UPF than controls (925·92 ± 18·08 v. 812·70 ± 14·32 g/d, P < 0·001). Dietary intake of UPF (% weight) was negatively related to the Healthy Eating Index-2015 score (Spearman r = -0·32, P < 0·001). In the multivariable model, the highest quartile compared with the lowest, the OR (95 % CI) were 1·83 (1·33, 2·53) for NAFLD (OR per 10 % increment: 1·15; 95 % CI: 1·09, 1·22; P for trend < 0·001) and 1·52 (1·12, 2·07) for insulin resistance (OR per 10 % increment: 1·11; 95 % CI: 1·05, 1·18; P for trend = 0·002). Mediation analyses revealed that poor diet quality, high saturated fat and refined grain intake partly mediated the association between UPF and NAFLD. In conclusion, high UPF intake was associated with an increased risk of NAFLD in US adults. Further prospective studies are needed to verify these findings.

Abnormal network properties and fiber connections of DMN across major mental disorders: a probability tracing and graph theory study.

The default mode network (DMN) is related to brain functions and its abnormalities were associated with mental disorders' pathophysiology. To further understand the common and distinct DMN alterations across disorders, we capitalized on the probability tracing method and graph theory to analyze the role of DMN across three major mental disorders. A total of 399 participants (156 schizophrenia [SCZ], 90 bipolar disorder [BP], 58 major depression disorder [MDD], and 95 healthy controls [HC]) completed magnetic resonance imaging (MRI)-scanning, clinical, and cognitive assessment. The MRI preprocessing of diffusion-tensor-imaging was conducted in FMRIB Software Library and probabilistic fiber tracking was applied by PANDA. This study had three main findings. First, patient groups showed significantly lower cluster coefficient in whole-brain compared with HC. SCZ showed significantly longer characteristic path compared with HC. Second, patient groups showed inter-group specificity in abnormalities of DMN connections. Third, SCZ was sensitive to left_medial_superior_frontal_gyrus (L_SFGmed)-right_anterior_cingulate_gyrus (R_ACG) connection relating to positive symptoms; left_ACG-right_ACG connection was the mania's antagonistic factor in BP. This trans-diagnostic study found disorder-specific structural abnormalities in the fiber connection of R_SFGmed-L_SFGmed-R_ACG_L_ACG within DMN, where SCZ showed more disconnections compared with other disorders. And these connections are diagnosis-specifically correlated to phenotypes. The current study may provide further evidence of shared and distinct endo-phenotypes across psychopathology.

Different dietary carbohydrate component intakes and long-term outcomes in patients with NAFLD: results of longitudinal analysis from the UK Biobank.

BACKGROUND: This study aimed to investigate the association between the intake of different dietary carbohydrate components and the long-term outcomes of non-alcoholic fatty liver disease (NAFLD). METHODS: We used prospective data from 26,729 NAFLD participants from the UK Biobank cohort study. Dietary information was recorded by online 24-hour questionnaires (Oxford WebQ). Consumption of different carbohydrate components was calculated by the UK Nutrient Databank Food Composition Table. Cox proportional hazards models were used to estimate the adjusted hazard ratio (HR) and 95% confidence interval (CI). A substitution model was used to estimate the associations of hypothetical substitution for free sugars. RESULTS: During a median of 10.5 (IQR: 10.2-11.2) years and a total of 280,135 person-years of follow-up, 310 incident end-stage liver disease (ESLD) and 1750 deaths were recorded. Compared with the lowest quartile, the multi-adjusted HRs (95% CI) of incident ESLD in the highest quartile were 1.65 (1.14-2.39) for free sugars, 0.51 (0.35-0.74) for non-free sugars, and 0.55 (0.36-0.83) for fiber. For overall mortality, the multi-adjusted HRs (95% CI) in the highest quartile were 1.21 (1.04-1.39) for free sugars, 0.79 (0.68-0.92) for non-free sugars, and 0.79 (0.67-0.94) for fiber. Substituting free sugars with equal amounts of non-free sugars, starch or fiber was associated with a lower risk of incident ESLD and overall mortality. CONCLUSIONS: A lower intake of free sugars and a higher intake of fiber are associated with a lower incidence of ESLD and overall mortality in NAFLD patients. These findings support the important role of the quality of dietary carbohydrates in preventing ESLD and overall mortality in NAFLD patients.

The centrality of working memory networks in differentiating bipolar type I depression from unipolar depression: A task-fMRI study.

OBJECTIVES: Up to 70%-80% of patients with bipolar disorder are misdiagnosed as having major depressive disorder (MDD), leading to both delayed intervention and worsening disability. Differences in the cognitive neurophysiology may serve to distinguish between the depressive phase of type 1 bipolar disorder (BDD-I) from MDD, though this remains to be demonstrated. To this end, we investigate the discriminatory signal in the topological organization of the functional connectome during a working memory (WM) task in BDD-I and MDD, as a candidate identification approach. METHODS: We calculated and compared the degree centrality (DC) at the whole-brain voxel-wise level in 31 patients with BDD-I, 35 patients with MDD, and 80 healthy controls (HCs) during an n-back task. We further extracted the distinct DC patterns in the two patient groups under different WM loads and used machine learning approaches to determine the distinguishing ability of the DC map. RESULTS: Patients with BDD-I had lower accuracy and longer reaction time (RT) than HCs at high WM loads. BDD-I is characterized by decreased DC in the default mode network (DMN) and the sensorimotor network (SMN) when facing high WM load. In contrast, MDD is characterized by increased DC in the DMN during high WM load. Higher WM load resulted in better classification performance, with the distinct aberrant DC maps under 2-back load discriminating the two disorders with 90.91% accuracy. CONCLUSIONS: The distributed brain connectivity during high WM load provides novel insights into the neurophysiological mechanisms underlying cognitive impairment of depression. This could potentially distinguish BDD-I from MDD if replicated in future large-scale evaluations of first-episode depression with longitudinal confirmation of diagnostic transition.

Association between night shift work and NAFLD: a prospective analysis of 281,280 UK Biobank participants.

CONTEXT: This study aimed to investigate the association between night shift work and the risk of nonalcoholic fatty liver disease (NAFLD). METHODS: We conducted a prospective analysis of 281,280 UK Biobank participants. Cox proportional hazards models were used to estimate the association of night shift work with incident NAFLD. Polygenic risk score analyses were performed to assess whether a genetic predisposition to NAFLD modified the association. RESULTS: During a median follow-up of 12.1 years (3,373,964 person-years), 2,555 incident NAFLD cases were identified. Compared with workers who never/rarely worked night shifts, those who worked some night shifts or usual/permanent night shifts were 1.12 (95% CI: 0.96-1.31) and 1.27 (95% CI: 1.08-1.48) times more likely to develop NAFLD, respectively. Among the 75,059 participants who had reports on lifetime experience of night shift work, those with a longer duration, a higher frequency, more consecutive night shifts and a longer length per shift all showed higher risks of incident NAFLD. Further analyses showed that the association between night shift work and incident NAFLD was not modified by a genetic predisposition to NAFLD. CONCLUSIONS: Night shift work was associated with increased risks of incident NAFLD.

Profiles of depressive symptoms and influential factors among people living with HIV in China.

BACKGROUND: Depressive symptoms are highly prevalent among people living with HIV (PLWH). We leveraged Latent Profile Analysis (LPA) to identify profiles of depressive symptoms among PLWHs. We also investigated differences in psychological factors of interest, demographic characteristics, and HIV-related factors across patients' profiles. METHODS: A cross-sectional study was conducted at one hospital and two designated prison facilities in Hunan province, China. A total sample of 533 PLWHs (320 recruited from the hospital, 213 recruited from prisons) completed the survey. Depressive symptoms were assessed using the 9-item Patient Health Questionnaire (PHQ-9). Family function, resilience, childhood trauma, demographic characteristics, and HIV-related factors were also evaluated. We conducted LPA and multinomial logistic regression analyses to: 1) identify distinct profiles for depressive symptoms; 2) identify demographic characteristics, and HIV-related, and psychological factors predicting PLWHs' likelihood to express a specific profile. RESULTS: We identified three distinct profiles of depressive symptoms among PLWHs: severe symptoms (11.8%), moderate symptoms (40.5%), and low/no symptoms (47.7%). Moderate/ severe family dysfunction, low resilience, experiencing emotional abuse and neglect were more likely to fall in the "severe symptoms" rather than the "low/no symptoms" profile. In addition, severe family dysfunction, low resilience, and experiencing emotional neglect indicated a higher likelihood of being classified in the "moderate symptoms" profile, compared to the "low/no symptoms" profile. CONCLUSION: Identifying profiles of depressive symptoms among PLWHs using the PHQ-9 items allows for understanding of the distinct paths of development of depressive symptoms and for developing tailored prevention and intervention programs for PLWHs.

Attention-Guided Huber Loss for Head Pose Estimation Based on Improved Capsule Network.

Head pose estimation is an important technology for analyzing human behavior and has been widely researched and applied in areas such as human-computer interaction and fatigue detection. However, traditional head pose estimation networks suffer from the problem of easily losing spatial structure information, particularly in complex scenarios where occlusions and multiple object detections are common, resulting in low accuracy. To address the above issues, we propose a head pose estimation model based on the residual network and capsule network. Firstly, a deep residual network is used to extract features from three stages, capturing spatial structure information at different levels, and a global attention block is employed to enhance the spatial weight of feature extraction. To effectively avoid the loss of spatial structure information, the features are encoded and transmitted to the output using an improved capsule network, which is enhanced in its generalization ability through self-attention routing mechanisms. To enhance the robustness of the model, we optimize Huber loss, which is first used in head pose estimation. Finally, experiments are conducted on three popular public datasets, 300W-LP, AFLW2000, and BIWI. The results demonstrate that the proposed method achieves state-of-the-art results, particularly in scenarios with occlusions.

Disrupted intrinsic functional brain topology in patients with major depressive disorder.

Aberrant topological organization of whole-brain networks has been inconsistently reported in studies of patients with major depressive disorder (MDD), reflecting limited sample sizes. To address this issue, we utilized a big data sample of MDD patients from the REST-meta-MDD Project, including 821 MDD patients and 765 normal controls (NCs) from 16 sites. Using the Dosenbach 160 node atlas, we examined whole-brain functional networks and extracted topological features (e.g., global and local efficiency, nodal efficiency, and degree) using graph theory-based methods. Linear mixed-effect models were used for group comparisons to control for site variability; robustness of results was confirmed (e.g., multiple topological parameters, different node definitions, and several head motion control strategies were applied). We found decreased global and local efficiency in patients with MDD compared to NCs. At the nodal level, patients with MDD were characterized by decreased nodal degrees in the somatomotor network (SMN), dorsal attention network (DAN) and visual network (VN) and decreased nodal efficiency in the default mode network (DMN), SMN, DAN, and VN. These topological differences were mostly driven by recurrent MDD patients, rather than first-episode drug naive (FEDN) patients with MDD. In this highly powered multisite study, we observed disrupted topological architecture of functional brain networks in MDD, suggesting both locally and globally decreased efficiency in brain networks.

Impaired robust interhemispheric function integration of depressive brain from REST-meta-MDD database in China.

BACKGROUND: Recently, functional homotopy (FH) architecture, defined as robust functional connectivity (FC) between homotopic regions, has been frequently reported to be altered in MDD patients (MDDs) but with divergent locations. METHODS: In this study, we obtained resting-state functional magnetic resonance imaging (R-fMRI) data from 1004 MDDs (mean age, 33.88 years; age range, 18-60 years) and 898 matched healthy controls (HCs) from an aggregated dataset from 20 centers in China. We focused on interhemispheric function integration in MDDs and its correlation with clinical characteristics using voxel-mirrored homotopic connectivity (VMHC) devised to inquire about FH patterns. RESULTS: As compared with HCs, MDDs showed decreased VMHC in visual, motor, somatosensory, limbic, angular gyrus, and cerebellum, particularly in posterior cingulate gyrus/precuneus (PCC/PCu) (false discovery rate [FDR] q < 0.002, z = -7.07). Further analysis observed that the reduction in SMG and insula was more prominent with age, of which SMG reflected such age-related change in males instead of females. Besides, the reduction in MTG was found to be a male-special abnormal pattern in MDDs. VMHC alterations were markedly related to episode type and illness severity. The higher Hamilton Depression Rating Scale score, the more apparent VMHC reduction in the primary visual cortex. First-episode MDDs revealed stronger VMHC reduction in PCu relative to recurrent MDDs. CONCLUSIONS: We confirmed a significant VMHC reduction in MDDs in broad areas, especially in PCC/PCu. This reduction was affected by gender, age, episode type, and illness severity. These findings suggest that the depressive brain tends to disconnect information exchange across hemispheres.

Load-dependent inverted U-shaped connectivity of the default mode network in schizophrenia during a working-memory task: evidence from a replication functional MRI study.

BACKGROUND: Working-memory deficit is associated with aberrant degree distribution of the brain connectome in schizophrenia. However, the brain neural mechanism underlying the degree redistribution pattern in schizophrenia is still uncertain. METHODS: We examined the functional degree distribution of the connectome in 81 patients with schizophrenia and 77 healthy controls across different working-memory loads during an n-back task. We tested the associations between altered degree distribution and clinical symptoms, and we conducted functional connectivity analyses to investigate the neural mechanism underlying altered degree distribution. We repeated these analyses in a second independent data set of 96 participants. In the second data set, we employed machine-learning analysis to study whether the degree distribution pattern of one data set could be used to discriminate between patients with schizophrenia and controls in the other data set. RESULTS: Patients with schizophrenia showed decreased centrality in the dorsal posterior cingulate cortex (dPCC) for the "2-back versus 0-back" contrast compared to healthy controls. The dPCC centrality pattern across all working-memory loads was an inverted U shape, with a left shift of this pattern in patients with schizophrenia. This reduced centrality was correlated with the severity of delusions and related to reduced functional connectivity between the dPCC and the dorsal precuneus. We replicated these results with the second data set, and the machine-learning analyses achieved an accuracy level of 71%. LIMITATIONS: We used a limited n-back paradigm that precluded the examination of higher working-memory loads. CONCLUSION: Schizophrenia is characterized by a load-dependent reduction of centrality in the dPCC, related to the severity of delusions. We suggest that restoring dPCC centrality in the presence of cognitive demands might have a therapeutic effect on persistent delusions in people with schizophrenia.

Multimetric structural covariance in first-episode major depressive disorder: a graph theoretical analysis.

BACKGROUND: Abnormalities of cortical morphology have been consistently reported in major depressive disorder (MDD), with widespread focal alterations in cortical thickness, surface area and gyrification. However, it is unclear whether these distributed focal changes disrupt the system-level architecture (topology) of brain morphology in MDD. If present, such a topological disruption might explain the mechanisms that underlie altered cortical morphology in MDD. METHODS: Seventy-six patients with first-episode MDD (33 male, 43 female) and 66 healthy controls (32 male, 34 female) underwent structural MRI scans. We calculated cortical indices, including cortical thickness, surface area and local gyrification index, using FreeSurfer. We constructed morphological covariance networks using the 3 cortical indices separately, and we analyzed the topological properties of these group-level morphological covariance networks using graph theoretical approaches. RESULTS: Topological differences between patients with first-episode MDD and healthy controls were restricted to the thickness-based network. We found a significant decrease in global efficiency but an increase in local efficiency of the left superior frontal gyrus and the right paracentral lobule in patients with first-episode MDD. When we simulated targeted lesions affecting the most highly connected nodes, the thickness-based networks in patients with first-episode MDD disintegrated more rapidly than those in healthy controls. LIMITATIONS: Our sample of patients with first-episode MDD has limited generalizability to patients with chronic and recurrent MDD. CONCLUSION: A systems-level disruption in cortical thickness (but not surface area or gyrification) occurs in patients with first-episode MDD.

Factors influencing medication adherence among patients with severe mental disorders from the perspective of mental health professionals.

BACKGROUND: Medication adherence is a common issue influenced by various factors among patients with severe mental disorders worldwide. However, most literature to date has been primarily quantitative and has focused on medication adherence issue from the perspective of patients or their caregivers. Moreover, research focused on medication adherence issue in China is scarce. Present study aims to explore the influential factors of medication adherence among patients with severe mental disorders form the perspective of mental health professionals in Hunan Province, China. METHODS: A qualitative study was performed in Hunan Province, China with 31 mental health professionals recruited from October to November 2017. And semi-structured interviews or focus group interviews were conducted along with audio recordings of all interviews. Interview transcripts were then coded and analyzed in Nvivo software with standard qualitative approaches. RESULTS: Three major themes influencing medication adherence among patients with severe mental disorders were identified as: (1) attitudes towards mental disorder/treatment; (2) inadequate aftercare; (3) resource shortages. CONCLUSIONS: This qualitative study identified the factors influencing medication adherence among patients with severe mental disorders in China. As a locally driven research study, it provides practical advice on medication adherence promotion for mental health workers and suggests culturally tailored models that improve the management of patients with severe mental disorders in order to reduce economic burden on individual and societal level.

Mental health characteristics and their associations with childhood trauma among subgroups of people living with HIV in China.

BACKGROUND: People living with HIV (PLWH) carry a high risk for mental health problems, which has been extensively reported in the literature. However, an understanding of mental health characteristics in different subgroups of PLWH is still limited. In the present study, we conducted a cross-sectional survey to explore mental health characteristics and their associations with childhood trauma in two major subgroups of PLWH in China. METHODS: A total of 533 PLWH (213 prisoners in the prison system, and 320 outpatients) were assessed using the 8-item Positive Subscale of the Community Assessment of Psychic Experiences (CAPE-P8), Generalized Anxiety Disorder scale (GAD-7), Patient Health Questionnaire (PHQ-9), and Childhood Trauma Questionnaire (CTQ). RESULTS: From the total sample, 22.0% PLWH frequently experienced psychotic-like experiences (PLEs), 21.8% had clinically significant anxiety syndrome, 34.0% had clinically significant depressive syndrome, and 63.6% experienced at least one type of traumatic exposure during their childhood, with physical neglect being the most common. Compared to outpatients with HIV, prisoners living with HIV reported more severe mental health problems and a higher frequency of childhood trauma, with childhood trauma in turn predicting higher risk for mental health problems. Similarly, among outpatients living with HIV, both childhood emotional and sexual abuse had predictive effects on all the three mental health problems. CONCLUSIONS: The study suggests that PLWH have higher risk of anxiety, depression and PLEs, and childhood trauma could serve as predicting factors for such risks. In addition, childhood trauma may play distinct roles in predicting the risk for the mental health problems, depending on different subgroup of PLWH.

Mediating role of impaired wisdom in the relation between childhood trauma and psychotic-like experiences in Chinese college students: a nationwide cross-sectional study.

BACKGROUND: The association between childhood trauma (CT) and psychotic-like experiences (PLEs) is well-established. Many previous studies have recognized wisdom as a protective factor for mental health, but its role in the relation between CT and PLEs remains unknown. We aimed to investigate the mediating effect of wisdom in the above association among Chinese college students. METHODS: We conducted a nationwide survey covering 9 colleges across China and recruited a total of 5873 students using online questionnaires between September 14 and October 18, 2021. Convenience sampling was adopted. We employed the San Diego Wisdom Scale (SD-WISE), the Childhood Trauma Questionnaire (CTQ-28), and the 15-item Positive Subscale of the Community Assessment of Psychic Experiences (CAPE-15) to measure the wisdom, CT and PLEs, respectively. Descriptive, correlation, and mediation analysis were utilized. RESULTS: The positive correlation between CT and PLEs was well-replicated among college students (Pearson's r = 0.30, p < 0.001). Wisdom was negatively associated with CT (Pearson's r = - 0.46, p < 0.001) and frequency of PLEs (Pearson's r = - 0.25, p < 0.001). Total wisdom scores partially mediated the relationship between cumulative childhood trauma, neglect, abuse and PLEs, separately. The mediated model respectively explained 21.9%, 42.54% and 18.27% of the effect of CT on PLEs. Our model further suggested that childhood trauma could be related to PLEs through decreasing the following wisdom components: decisiveness, emotional regulation and prosocial behavior. CONCLUSION: For the first time, our results suggested that impaired wisdom played a role in the translation from childhood adversity to subclinical psychotic symptoms, implicating wisdom as a possible target for early intervention for psychosis among young individuals. Longitudinal work is warranted to verify the clinical implications.