Gender differences in alcohol drinking among adolescents: a school-based survey in China.

BACKGROUND: Alcohol drinking among adolescents is associated with their health development. However, the prevalence of alcohol drinking among adolescents in Southwestern China remains largely unexplored. This study aimed to investigate the prevalence of alcohol drinking, with a particular focus on gender differences, among primary and middle school students in Zigong, a city in Southwestern China. Additionally, we examined the association between alcohol consumption and demographic and family factors. METHODS: A school-based cross-sectional survey was conducted in a city in Southwestern China, encompassing a total of 89 360 students from 132 different ordinary schools, including both primary and middle schools. Participants were recruited through cluster sampling. The Alcohol Use Disorders Identification Test Consumption was employed to assess alcohol consumption. Gender differences in the prevalence of alcohol drinkers across various schools and grades were analysed. Multivariable logistic regression analysis was used to investigate factors associated with hazardous drinking. RESULTS: Out of the 89 360 participants, 19.0% reported alcohol drinking, with 2.1% classified as hazardous drinkers. There was a higher prevalence of alcohol drinking among boys compared with girls, as well as hazardous drinking. There were significant gender disparities in alcohol drinking observed across various schools and grade levels. A notable divergence between boys and girls was observed starting from grade 10, with a rising prevalence of hazardous drinking among boys and a decline among girls. Additionally, older age, male gender and being left-behind children were identified as risk factors for hazardous drinking, while belonging to a nuclear family and having parents who do not drink were protective factors against hazardous drinking. CONCLUSIONS: Alcohol consumption is prevalent among Chinese adolescents, with some even classified as hazardous drinkers. These findings may offer valuable insights for policymakers and caregivers, guiding them in formulating appropriate interventions and support strategies.

Mechanism of electroconvulsive therapy in schizophrenia: a bioinformatics analysis study of RNA-seq data.

OBJECTIVE: The molecular mechanism of electroconvulsive therapy (ECT) for schizophrenia remains unclear. The aim of this study was to uncover the underlying biological mechanisms of ECT in the treatment of schizophrenia using a transcriptional dataset. METHODS: The peripheral blood mRNA sequencing data of eight patients (before and after ECT) and eight healthy controls were analyzed by integrated co-expression network analysis and the differentially expressed genes were analyzed by cluster analysis. Gene set overlap analysis was performed using the hypergeometric distribution of phypfunction in R. Associations of these gene sets with psychiatric disorders were explored. Tissue-specific enrichment analysis, gene ontology enrichment analysis, and protein-protein interaction enrichment analysis were used for gene set organization localization and pathway analysis. RESULTS: We found the genes of the green-yellow module were significantly associated with the effect of ECT treatment and the common gene variants of schizophrenia ( P  = 0.0061; family-wise error correction). The genes of the green-yellow module are mainly enriched in brain tissue and mainly involved in the pathways of neurotrophin, mitogen-activated protein kinase and long-term potentiation. CONCLUSION: Genes associated with the efficacy of ECT were predominantly enriched in neurotrophin, mitogen-activated protein kinase and long-term potentiation signaling pathways.

School bullying results in poor psychological conditions: evidence from a survey of 95,545 subjects.

To investigate whether bullying and psychological conditions are correlated, this study analyzed a survey of primary and secondary school students from Zigong City, Sichuan Province. A total of 95,545 students completed a personal information questionnaire, the Multidimensional Peer-Victimization Scale (MPVS), and eight other scales pertaining to various psychological problems. The data showed that 68,315 (71.5%) participants experienced school bullying at varying degrees, indicating the prevalence of bullying among adolescents. The chi-square tests revealed a strong correlation between school bullying and psychological conditions. This correlation was further explored through multivariate logistic regression, showing that students who experienced mild bullying had a 3.10 times higher probability of emotional and behavioral problems, 4.06 times higher probability of experiencing prodromal symptoms of mental illness, 4.72 times higher probability of anxiety, 3.28 times higher probability of developing post-traumatic stress disorder (PTSD), 4.07 times higher probability of poor sleep quality, 3.13 times higher probability of internet addiction, 2.18 times higher probability of poor mental health, and 3.64 times higher probability of depression than students who did not experience bullying. The corresponding probabilities for students who experienced severe bullying were 11.35, 17.35, 18.52, 12.59, 11.67, 12.03, 4.64, and 5.34 times higher, respectively. In conclusion, school bullying and psychological conditions are significantly correlated among primary and secondary school students, and the more severe the bullying, the higher the probability to suffer from psychological problems.

Determination of the cutoff point for Smartphone Application-Based Addiction Scale for adolescents: a latent profile analysis.

BACKGROUNDS: The Smartphone Application-Based Addiction Scale (SABAS) is a validated 6-item measurement tool for assessing problematic smartphone use (PSU). However, the absence of established cutoff points for SABAS hinders its utilities. This study aimed to determine the optimal cutoff point for SABAS through latent profile analysis (LPA) and receiver operating characteristic curve (ROC) analyses among 63, 205. Chinese adolescents. Additionally, the study explored whether PSU screening with SABAS could effectively capture problematic social media use (PSMU) and internet gaming disorder (IGD). METHOD: We recruited 63,205. adolescents using cluster sampling. Validated questionnaires were used to assess PSMU, IGD, and mental health (depression, anxiety, sleep disturbances, well-being, resilience, and externalizing and internalizing problems). RESULTS: LPA identified a 3-class model for PSU, including low-risk users (38.6%, n = 24,388.), middle-risk users (42.5%, n = 26,885.), and high-risk users (18.9%, n = 11,932.). High-risk users were regarded as "PSU cases" in ROC analysis, which demonstrated an optimal cut-off point of 23 (sensitivity: 98.1%, specificity: 96.8%). According to the cutoff point, 21.1% (n = 13,317.) were identified as PSU. PSU adolescents displayed higher PSMU, IGD, and worse mental health. PSU screening effectively captured IGD (sensitivity: 86.8%, specificity: 84.5%) and PSMU (sensitivity: 84.5%, specificity: 80.2%). CONCLUSION: A potential ideal threshold for utilizing SABAS to identify PSU could be 23 (out of 36). Employing SABAS as a screening tool for PSU holds the potential to reliably pinpoint both IGD and PSMU.

[Research progress on medical devices of polyhydroxyalkanoate in orthopedics].

Objective: To review the research progress of natural biomaterial polyhydroxyalkanoate (PHA) in orthopedics. Methods: The literature concerning PHA devices for bone defects, bone repair, and bone neoplasms, respectively, in recent years was extensively consulted. The three aspects of the advantages of PHA in bone repair, the preparation of PHA medical devices for bone repair and their application in orthopedics were discussed. Results: Due to excellent biodegradability, biocompatibility, and potential osteoinduction, PHA is a kind of good bone repair material. In addition to the traditional PHA medical implants, the use of electrostatic spinning and three-dimensional printing can be designed to various functional PHA medical devices, in order to meet the orthopedic clinical demands, including the bone regeneration, minimally invasive bone tissue repair by injection, antibacterial bone repair, auxiliary establishment of three-dimensional bone tumor model, directed osteogenic differentiation of stem cells, etc. Conclusion: At present, PHA is a hotspot of biomaterials for translational medicine in orthopedics. Although they have not completely applied in the clinic, the advantages of repair in bone defects have been gradually reflected in tissue engineering, showing an application prospect in orthopedics.

Prevalence and associated factors of depressive and anxiety symptoms among Chinese secondary school students.

BACKGROUND: Depressive and anxiety symptoms affect about one-fourth of Chinese secondary school students. However, the prevalence and correlates of mental distress among secondary school students from Western China remain largely unexplored. This study aimed to examine the prevalence and associations of depressive and anxiety symptoms with demographic, family, school, life, and behavior factors in a large, representative sample of secondary school students in Zigong, a city in Western China. METHODS: Secondary school students were recruited using cluster sampling. The 9-item Patient Health Questionnaire, the 7-item Generalized Anxiety Disorder Questionnaire, Multidimensional Peer-Victimization Scale, the Pittsburgh Sleep Quality Index, and Nine-Item Internet Gaming Disorder Scale-Short Form were used. Descriptive statistic was used to describe the sociodemographic characteristics of participants. The clustering effect was adjusted by the "survey" package of R to calculate weighted prevalence. Univariate and multivariate logistic regression were used to explore associated factors of depression and anxiety, respectively. RESULTS: A total of 63,205 participants were involved, in which the weighted prevalence of depression in all subjects was 23.0% (95% CI: 19.6- 27.0%), and the weighted prevalence of anxiety was 13.9% (95% CI: 11.2- 17.0%). Logistic regression results showed girls, being single-child, non-nuclear family, peer bullying, sleep disturbance, and internet gaming disorder symptoms were positively associated with depressive and anxiety symptoms. CONCLUSION: Depressive and anxiety symptoms were prevalent among secondary school students in Western China. Our results can guide policy strategies for the assessment, prevention, and intervention of psychological status among Chinese secondary school students.

Effects of vascular endothelial growth factor (VEGF) on the viability, apoptosis and steroidogenesis of yak (Bos grunniens) granulosa cells.

Vascular endothelial growth factor (VEGF) is crucial for follicle development through the regulation of granulosa cell (GC) function in some mammals, but its mechanism is unclear in yak (Bos grunniens). Therefore, the objectives of this study were to investigate the effects of VEGF on the viability, apoptosis and steroidogenesis of yak GCs. First, we investigated the localization of VEGF and its receptor (VEGFR2) in yak ovaries by immunohistochemistry analysis and evaluated the effect of culture medium containing different VEGF concentrations and culture times on the viability of yak GCs by Cell Counting Kit-8. Then, optimal treatment with 20 ng/mL VEGF for 24 h was selected to analyze the effects of this compound on intracellular reactive oxygen species levels by DCFH-DA kit, cell cycle and apoptosis by flow cytometry, steroidogenesis by ELISA kit and the expression of the related genes by RT‒qPCR. The results showed that VEGF and VEGFR2 were highly coexpressed in GCs and theca cells. GCs cultured in medium containing 20 ng/mL VEGF for 24 h significantly improved cell viability, decreased ROS production, promoted the transition from G1 phase to S phase (P < 0.05), increased the expression of the CCND1 (P < 0.05), CCNE1, CDK2, CDK4, and PCNA genes (P < 0.01) and decreased the expression of the P53 gene (P < 0.05). This treatment significantly reduced GC apoptosis (P < 0.05) by promoting the expression of BCL2 and GDF9 (P < 0.01) and inhibiting the expression of BAX and CASPASE3 (P < 0.05). VEGF promoted progesterone secretion (P < 0.05) accompanied by increased expression of HSD3B, StAR and CYP11A1 (P < 0.05). Taken together, our findings highlight the beneficial influence exerted by VEGF in improving GC viability and reducing ROS production and the apoptosis rate through the modulation of related gene expression.

Detecting individuals with severe mental illness using artificial intelligence applied to magnetic resonance imaging.

BACKGROUND: Identifying individuals at risk for severe mental illness (SMI) is crucial for prevention and early intervention strategies. While MRI shows potential for case identification even before illness onset, no practical model for mental health risk monitoring has been developed. This study aims to develop an initial version of an efficient and practical model for mental health screening among at-risk populations. METHODS: A deep learning model known as Multiple Instance Learning (MIL) was adopted to train and test a SMI detection model with clinical MRI scans of 14,915 patients with SMI (age 32.98 ± 12.01 years, 9102 women) and 4538 healthy controls (age 40.60 ± 10.95 years, 2424 women) in the primary dataset. Validation analysis was conducted in an independent dataset with 290 patients (age 28.08 ± 10.95 years, 169 women) and 310 healthy participants (age 33.55 ± 11.09 years, 165 women). Another three machine learning models of ResNet, DenseNet and EfficientNet were used for comparison. We also recruited 148 individuals receiving high-stress medical school education to characterize the potential real-world utility of the MIL model in detecting risk of mental illness. FINDINGS: Similar performance of successful differentiation of individuals with SMI and healthy controls was observed for the MIL model (AUC: 0.82) and other models (ResNet, DenseNet, EfficientNet, 0.83, 0.81, and 0.80 respectively). MIL had better generalization in the validation test than other models (AUC: 0.82 vs 0.59, 0.66 and 0.59), and less drop-off in performance from 3.0T to 1.5T scanners. The MIL model did better in predicting clinician ratings of distress than self-ratings with questionnaires (84% vs 22%) in the medical student sample. Brain regions that contributed to SMI identification were mainly neocortical, including right precuneus, bilateral temporal regions, left precentral/postcentral gyrus, bilateral medial prefrontal cortex and right cerebellum. INTERPRETATION: Our digital model based on brief clinical MRI protocols identified individual SMI patients with good accuracy and high sensitivity, suggesting that with incremental improvements the approach may offer potentially useful aid for early identification and intervention to prevent illness onset in vulnerable at-risk populations. FUNDING: This study was supported by the National Natural Science Foundation of China, National Key Technologies R&D Program of China, and Sichuan Science and Technology Program.

Improved biopharmaceutical performance of antipsychotic drug using lipid nanoparticles via intraperitoneal route.

This study aims to develop, characterize, and examine olanzapine-loaded solid lipid nanocarriers (OLAN-SLNs) for effective brain delivery. OLAN has poor water solubility and low penetration through blood-brain barrier (BBB). Herein, OLAN-SLNs were fabricated using high-pressure homogenization (HPH) method followed by their investigation for particle properties. Moreover, in vitro release and in vivo pharmacokinetics profiles of OLAN-SLNs were compared with pure drug. Anti-psychotic activity was performed in LPS-induced psychosis mice model. Furthermore, expressions of the COX-2 and NF-κB were measured trailed by histopathological examination. The optimized formulation demonstrated nanoparticle size (149.1 nm) with rounded morphology, negative zeta potential (-28.9 mV), lower PDI (0.334), and excellent entrapment efficiency (95%). OLAN-SLNs significantly retarded the drug release and showed sustained release pattern as compared to OLAN suspension. Significantly enhanced bioavailability (ninefold) was demonstrated in OLAN-SLNs when compared with OLAN suspension. Behavioral tests showed significantly less immobility and more struggling time in OLAN-SLNs treated mice group. Additionally, reduced expression of COX-2 and -NF κB in brain was found. Altogether, it can be concluded that SLNs have the potential to deliver active pharmaceutical ingredients to brain, most importantly to enhance their bioavailability and antipsychotic effect, as indicated for OLAN in this study.

Demographic characteristics, family environment and psychosocial factors affecting internet addiction in Chinese adolescents.

BACKGROUND: Internet addiction of adolescents has aroused social concern recently. The present study aims to identify predicting factors of internet addiction on adolescents. METHODS: The demographic characteristics and psychological characteristics of 50, 855 middle school students were investigated through Internet Gaming Disorder Scale- Short Form(IGDS9-SF), Smartphone Application-Based Addiction Scale (SABAS), Bergen Social Media Addiction Scale (BSMAS), Strengths and Difficulties Questionnaire-students (SDQS), 16-Item Version of the Prodromal Questionnaire (PQ-16), Patient Health Questionnaire-9 (PHQ-9), Generalized Anxiety Disorder 7-item (GAD-7), Multidimensional Peer Victimization Scale (MPVS), Warwick-Edinburgh Mental Well-being Scale (WEMWBS), and Connor-Davidson Resilience Scale (CD-RISC10) were used to analyze factors associated with internet addiction by Pearson correlation coefficient and multiple hierarchical regression. RESULTS: IGDS9-SF, SABAS and BSMAS are positively correlated with SDQS, PQ-16, PHQ-9, GAD-7 and MPVS (r-values ranging from 0.180 to 0.488, p < 0.01). IGDS9-SF, SABAS and BSMAS are negatively correlated with WEMWB and CD-RISC (r-values ranging from -0.242 ~ -0.338, p < 0.01). Multiple hierarchical regression shown gender, one-child, twins, left-behind, rural, education (father), drink (father), smoke (father), CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 32.7 % of the variance in internet gaming disorder (IGD) (F = 1174.949, p < 0.001). Group (junior and senior), Gender, Age, One-Child, Twins, Village, Education (father), Drink (father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, SDQS, PQ-16, PHQ-9, GAD-7 and MPVS predicted 28.9 % of the total variance in social media addiction (SMA) (F = 982.932, p < 0.001). Fifteen variables [Gender, Age, Twins, Left-behind, Residence, Residence, Education (mother), Drink(father), Drink (mother), Smoke (father), WEMWBS, CD-RISC-10, PHQ-9, GAD-7 and MPVS] predicted 30.7 % of the variance in smartphone addiction (SA) (F = 1076.02, p < 0.001). CONCLUSION: The present study found that demographic characteristics, family environment and psychosocial factors were associated with internet gaming addiction, social media addiction and smartphone addiction. Negative psychological factors (such as anxiety and depression) play an important role in different behavioral addictions.

Altered spontaneous brain activity in major depressive disorder: An activation likelihood estimation meta-analysis.

BACKGROUND: Wide application of resting-state functional magnetic resonance imaging (fMRI) in psychiatric research has revealed that major depressive disorder (MDD) manifest abnormal neural activities in several brain regions involving key resting state networks. However, inconsistent results have hampered our understanding of the exact neuropathology associated with MDD. Therefore, our aim was to conduct a meta-analysis to identify the consistent vulnerable brain regions of MDD in resting state, and to reveal the potential pathogenesis of MDD. METHODS: A systematic review analysis was conducted on studies involving brain resting-state changes in MDD using low-frequency amplitude (ALFF), fractional low-frequency amplitude (fALFF) and regional homogeneity (ReHo) analysis. The meta-analysis was based on the activation likelihood estimation method, using the software of Ginger ALE 2.3. RESULTS: 25 studies (892 MDD and 799 healthy controls) were included. Based on the meta-analysis results of ReHo, we found robust reduction of resting-state spontaneous brain activity in MDD, including the left cuneus and right middle occipital gyrus (cluster size = 216, 256 mm3, uncorrected P < 0.0001), while no increased spontaneous activation in any of the brain regions. We also found reduced ALFF in the left middle occipital gyrus (cluster size = 224 mm3, uncorrected P < 0.0001), and no increased spontaneous brain activation in any regions. CONCLUSION: Our meta-analysis study using the activation likelihood estimation method demonstrated that MDD showed significant abnormalities in spontaneous neural activity, compared with healthy controls, mainly in areas associated with visual processing, such as the cuneus and the middle occipital gyrus. Dysfunction of these brain regions may be one of the pathogenesis of MDD.

Sleep duration and auditory hallucinations: Genetic correlation and two-sample Mendelian randomization study.

OBJECTIVES: Previous studies have found that sleep problems are associated with psychotic experiences (PEs) across clinical designs, but many confounding factors from uncertain variables have been unclear in observational designs. The aim of the present study was to detect the genetic correlations and causal relationship between sleep-related traits and PEs using the largest current genome-wide association study (GWAS) summary statistics. METHODS: GWAS results were obtained for positive PEs (N = 116,787-117,794) and sleep-related traits [insomnia complaints (N = 386,533), morningness (N = 345,552), sleep duration (N = 384,317), ease of getting up in the morning (N = 385,949), daytime napping (N = 386,577), daytime sleepiness (N = 386,548), and snoring (N = 359,916)]. Linkage disequilibrium score regression (LDSC) was used to investigate genetic correlations. Mendelian randomization (MR) was conducted on trait pairs with significant genetic associations. RESULTS: We found that auditory hallucinations were significantly genetically correlated with insomnia complaints (rg = -0.27, p = 1.1 × 10-3), sleep duration (rg = 0.21, p = 9.7 × 10-3), and ease of getting up (rg = 0.31, p = 2 × 10-4). Visual hallucinations and insomnia complaints were highly genetically correlated (rg = 0.36, p = 6.4 × 10-5). Mendelian randomization indicated a unidirectional causal relationship between sleep duration with auditory hallucinations (ß = -0.93, p = 7.9 × 10-4 for sleep duration as the exposure). We used large GWAS summary statistics across the LDSC and MR programs to determine that sleep duration as exposure to increase the risk of auditory hallucinations. CONCLUSIONS: Taken together, these findings suggest that treatment of sleep problems should be considered as a higher priority for future mental health services.

Transcriptome Sequencing Reveals the Potential Mechanisms of Modified Electroconvulsive Therapy in Schizophrenia.

OBJECTIVE: Schizophrenia (SCZ) is one of the most common and severe mental disorders. Modified electroconvulsive therapy (MECT) is the most effective therapy for all kinds of SCZ, and the underlying molecular mechanism remains unclear. This study is aim to detect the molecule mechanism by constructing the transcriptome dataset from SCZ patients treated with MECT and health controls (HCs). METHODS: Transcriptome sequencing was performed on blood samples of 8 SCZ (BECT: before MECT; AECT: after MECT) and 8 HCs, weighted gene co-expression network analysis (WGCNA) was used to cluster the different expression genes, enrichment and protein-protein interaction (PPI) enrichment analysis were used to detect the related pathways. RESULTS: Three gene modules (black, blue and turquoise) were significantly associated with MECT, enrichment analysis found that the long-term potentiation pathway was associated with MECT. PPI enrichment p-value of black, blue, turquoise module are 0.00127, <1×10-16 and 1.09×10-13, respectively. At the same time, EP300 is a key node in the PPI for genes in black module, which got from the transcriptome sequencing data. CONCLUSION: It is suggested that the long-term potentiation pathways were associated with biological mechanism of MECT.

Maladaptive metacognitive beliefs mediated the effect of intolerance of uncertainty on depression.

Both elevated intolerance of uncertainty (IU) and maladaptive metacognitive beliefs (MBs) were associated with depression. However, the relationship between MBs and IU in clinical depression is unclear. The current study aimed to investigate the putative impairment of MBs and IU in major depressive disorder (MDD) and explore the relationship between these two factors with depressive symptoms. Metacognition Questionnaire-30 Items (MCQ-30), Intolerance of Uncertainty Scale-Short Form (IUS-12) and clinical rating scales were administered to 53 patients with MDD and 56 healthy controls (HCs). Stepwise regressions were performed to explore independent contributions of MBs and IU on depression. Mediation analysis was used to examine associations among variables. Patients with MDD reported higher IUS-12 and MCQ-30 scores than HCs. Stepwise regressions revealed a unique contribution of negative MBs concerning the consequences of not controlling thoughts (MCQ-NC) on depression symptoms while controlling the effects of age, gender, anxiety symptoms and IU. MCQ-NC and negative MBs concerning the uncontrollability and danger of negative thinking (MCQ-NEG) completely mediated the effects of IU on depression and anxiety symptoms. Our results provided clear evidence that maladaptive negative MBs are directly associated with depression symptoms, and mediated the effect of IU on depression and anxiety symptoms, suggesting that IU and MBs influence clinical symptoms in a hierarchical manner.

Exploring the role and mechanism of sodium benzoate in CUMS-induced depression model of rats.

AIM: This study was aimed to investigate the effects of sodium benzoate in chronic unpredictable mild stress (CUMS)-induced depression model in rats. MATERIAL AND METHOD: Male rats were exposed to CUMS stress for 6 weeks which includes with multiple unpredictable stressors to induce depression related symptoms and the treatment with sodium benzoate was started at the 4th week of stress protocol (i.e. on the 22nd day) for 21 days during stress protocol . RESULTS: CUMS significantly increased the immobility period in the forced swimming test and decrease sucrose consumption in the sucrose preference test in rats. In the prefrontal cortex region (PFC) of the brain, a significant decline in the Brain-derived neurotrophic factor (BDNF) levels and Protein kinase A (PKA) was observed in rats. However, sodium benzoate (400 and 800 mg/kg i.p.) significantly restored sucrose preference behavior as well as reduced immobility in CUMS-subjected rats in a dose-dependent manner, suggesting the antidepressant potential of sodium benzoate. Also, sodium benzoate treatment significantly increased BDNF levels and PKA activity in the PFC region of the stress subjected rat brain. Moreover, co-administration of H-89, PKA inhibitor (1 and 5 mg/kg) along with sodium benzoate (800 mg/kg) in CUMS subjected rats notably attenuated antidepressant effects of sodium benzoate. H-89 also abolished sodium benzoate-mediated increase in BDNF levels and PKA activity in stress-subjected rats. CONCLUSION: Sodium benzoate mediated antidepressant actions may be due to a decrease in the d-amino oxidase activity, an increase in BDNF, and PKA levels in PFC region of the brain. Sodium benzoate-mediated modulation of BDNF/PKA signaling may contribute to attenuating depressive-symptoms in unpredictable stress-subjected rats.

Association between genetic polymorphism and antidepressants in major depression: a network meta-analysis.

This network meta-analysis was conducted to compare the predictive value of eight SNPs on the efficacy of antidepressants in major depressive disorder (MDD), including 5-HTTLPR, 5HTR2A (rs6311, rs6314, rs7997012 and rs6313), 5HTR2A (rs6295), BDNF (rs6265) and 5HTTSTin2. Databases were searched for related studies published up to December 2019. A total of 16 studies were included in this study. The predictive value were evaluated by the use of the odd ratios (OR) and drawing surface under the cumulative ranking curves (SUCRA). The pairwise meta-analysis indicated that in terms of overall response ratio, the SNPs were not associated with the efficacy of antidepressants in MDD. The result of this network meta-analysis suggested that there was no significant difference in predictive value of eight SNPs on the efficacy of antidepressants in MDD. More research is needed to explore the relationship between SNPs and antidepressant response.

A Combined Analysis of Genetically Correlated Traits Identifies Genes and Brain Regions for Insomnia.

AIMS: Previous studies have inferred that there is a strong genetic component in insomnia. However, the etiology of insomnia is still unclear. This study systematically analyzed multiple genome-wide association study (GWAS) data sets with core human pathways and functional networks to detect potential gene pathways and networks associated with insomnia. METHODS: We used a novel method, multitrait analysis of genome-wide association studies (MTAG), to combine 3 large GWASs of insomnia symptoms/complaints and sleep duration. The i-Gsea4GwasV2 and Reactome FI programs were used to analyze data from the result of MTAG analysis and the nominally significant pathways, respectively. RESULTS: Through analyzing data sets using the MTAG program, our sample size increased from 113,006 subjects to 163,188 subjects. A total of 17 of 1,816 Reactome pathways were identified and showed to be associated with insomnia. We further revealed 11 interconnected functional and topologically interacting clusters (Clusters 0 to 10) that were associated with insomnia. Based on the brain transcriptome data, it was found that the genes in Cluster 4 were enriched for the transcriptional coexpression profile in the prenatal dorsolateral prefrontal cortex (P = 7 × 10-5), inferolateral temporal cortex (P = 0.02), medial prefrontal cortex (P < 1 × 10-5), and amygdala (P < 1 × 10-5), and detected RPA2, ORC6, PIAS3, and PRIM2 as core nodes in these 4 brain regions. CONCLUSIONS: The findings provided new genes, pathways, and brain regions to understand the pathology of insomnia.

Intelligence quotient level and treatment of obsessive-compulsive disorders: Meta-analyses.

BACKGROUND: Obsessive-compulsive disorder (OCD) is a highly heterogeneous mental disorder that could affect mental capacity and requires different treatment methods. The purpose of this meta-analysis study was to evaluate the OCD subjects' intelligence quotient (IQ) and the effect of different treatments on OCD. METHODS: Through a systematic literature search up to December-2019, 108-studies were identified, with 8049-subjects with 6719-OCD subjects. The studies identified were 45 reporting IQs in OCD and 38 reporting comparisons between selective-serotonin reuptake-inhibitors (SSRIs) to placebo in the treatment of OCD, 9 reporting comparison between SSRIs to each other, 8 reporting comparison between cognitive-behavioral therapy (CBT) to placebo and 8 reporting comparison between CBT to SSRIs. Odds ratio (OR) with 95% confidence intervals (CIs) were calculated comparison was made according to the study content using a continuous method with a random or fixed-effects model. RESULTS: Subjects with OCD had significantly lower IQ (OR, -3.74; 95% CI, -4.83 to -2.64) than normal subjects. SSRIs (OR, -4.09; 95% CI, -4.87 to -3.30) and CBT (OR, -15.13; 95% CI, -19.27 to -10.99) had better effect than placebo in OCD treatment. No significant difference were found between different types of SSRIs (OR, -0.42; 95% CI, -1.32-0.49) or between CBT and SSRIs (OR, -1.99; 95% CI, -4.20 to 0.22) with non-significant better values favoring CBT. CONCLUSIONS: The IQ of the OCD subjects was significantly lower than in normal subjects. The SSRIs and the CBT had a significant effect on treating OCD. Different SSRIs are similar in their effect on OCD. More studies are required to separate between CBT and SSRIs' insignificant differences.

Anatomic abnormalities of hippocampal subfields in never-treated and antipsychotic-treated patients with long-term schizophrenia.

Hippocampal volume deficits have been reported in chronically-treated schizophrenia patients, however, the longer-term effects of antipsychotic medications on hippocampal anatomy are unclear. This case-control study investigated volume differences in hippocampal subfields of never-treated and antipsychotic-treated patients with long-term schizophrenia. High spatial-resolution T1-weighted magnetic resonance images were collected from 29 never-treated and 40 antipsychotic-treated patients with long-term schizophrenia matched for illness duration (all ≥ 5 years), and 40 demographically-matched healthy controls. Hippocampal subfield volumes were measured using FreeSurfer v6.0, compared across groups and between hemispheres, and correlated with clinical features. Volume reductions were found in both patient groups compared to healthy controls in 8 of 26 hippocampal subfields (Cohen's d = 0.46 - 1.17, P = < .001 - .03), and more diffusely and obviously in never-treated than treated patients (Cohen's d = 0.50 - 0.90, P = < .001 - .04). Greater right-than-left volumes were seen in treated patients and healthy controls in 11 of 13 subfields (T = 2.30 - 7.29, P = < .001 - .03), but not in never-treated patients, in whom the volumes were reduced more on the right than on the left. Subfield volumes were negatively correlated with symptom severity and illness duration, and declined with age in never-treated patients. Findings indicate clinically-relevant and age-related volume reductions in hippocampal subfields of never-treated patients with long-term schizophrenia. Broader and greater subfield deficits in never-treated than treated patients, especially in the right hippocampus, suggest that long-term antipsychotic treatment may benefit hippocampal structures over the longer-term course of illness.

Dysconnectivity of Multiple Brain Networks in Schizophrenia: A Meta-Analysis of Resting-State Functional Connectivity.

Background: Seed-based studies on resting-state functional connectivity (rsFC) in schizophrenia have shown disrupted connectivity involving a number of brain networks; however, the results have been controversial. Methods: We conducted a meta-analysis based on independent component analysis (ICA) brain templates to evaluate dysconnectivity within resting-state brain networks in patients with schizophrenia. Seventy-six rsFC studies from 70 publications with 2,588 schizophrenia patients and 2,567 healthy controls (HCs) were included in the present meta-analysis. The locations and activation effects of significant intergroup comparisons were extracted and classified based on the ICA templates. Then, multilevel kernel density analysis was used to integrate the results and control bias. Results: Compared with HCs, significant hypoconnectivities were observed between the seed regions and the areas in the auditory network (left insula), core network (right superior temporal cortex), default mode network (right medial prefrontal cortex, and left precuneus and anterior cingulate cortices), self-referential network (right superior temporal cortex), and somatomotor network (right precentral gyrus) in schizophrenia patients. No hyperconnectivity between the seed regions and any other areas within the networks was detected in patients, compared with the connectivity in HCs. Conclusions: Decreased rsFC within the self-referential network and default mode network might play fundamental roles in the malfunction of information processing, while the core network might act as a dysfunctional hub of regulation. Our meta-analysis is consistent with diffuse hypoconnectivities as a dysregulated brain network model of schizophrenia.