Synaptic dysfunction is a core component of the pathophysiology of schizophrenia.However,the genetic risk factors and molecular mechanisms related to synaptic dysfunction are still not fully understood.The Stonin 2(STON2)gene encodes a major adaptor for clathrin-mediated endocytosis(CME)of synaptic vesi-cles.In this study,we showed that the C-C(307Pro-851Ala)haplotype of STON2 increases the suscepti-bility to schizophrenia and examined whether STON2 variations cause schizophrenia-like behaviors through the regulation of CME.We found that schizophrenia-related STON2 variations led to protein dephosphorylation,which affected its interaction with synaptotagmin 1(Syt1),a calcium sensor protein located in the presynaptic membrane that is critical for CME.STON2307Pro851Ala knockin mice exhibited deficits in synaptic transmission,short-term plasticity,and schizophrenia-like behaviors.Moreover,among seven antipsychotic drugs,patients with the C-C(307Pro-851Ala)haplotype responded better to haloperidol than did the T-A(307Ser-851Ser)carriers.The recovery of deficits in Syt1 sorting and synaptic transmission by acute administration of haloperidol effectively improved schizophrenia-like behaviors in STON2307Pro851Ala knockin mice.Our findings demonstrated the effect of schizophrenia-related STON2 variations on synaptic dysfunction through the regulation of CME,which might be attrac-tive therapeutic targets for treating schizophrenia-like phenotypes.

BACKGROUND:Objective and quantifiable markers are crucial for developing novel therapeutics for mental disorders by 1) stratifying clinically similar patients with different underlying neurobiological deficits and 2) objectively tracking disease trajectory and treatment response. Schizophrenia is often confounded with other psychiatric disorders, especially bipolar disorder, if based on cross-sectional symptoms. Awake and sleep EEG have shown promise in identifying neurophysiological differences as biomarkers for schizophrenia. However, most previous studies, while useful, were conducted in European and American populations, had small sample sizes, and utilized varying analytic methods, limiting comprehensive analyses or generalizability to diverse human populations. Furthermore, the extent to which wake and sleep neurophysiology metrics correlate with each other and with symptom severity or cognitive impairment remains unresolved. Moreover, how these neurophysiological markers compare across psychiatric conditions is not well characterized. The utility of biomarkers in clinical trials and practice would be significantly advanced by well-powered transdiagnostic studies. The Global Research Initiative on the Neurophysiology of Schizophrenia (GRINS) project aims to address these questions through a large, multi-center cohort study involving East Asian populations. To promote transparency and reproducibility, we describe the protocol for the GRINS project. METHODS:The research procedure consists of an initial screening interview followed by three subsequent sessions: an introductory interview, an evaluation visit, and an overnight neurophysiological recording session. Data from multiple domains, including demographic and clinical characteristics, behavioral performance (cognitive tasks, motor sequence tasks), and neurophysiological metrics (both awake and sleep electroencephalography), are collected by research groups specialized in each domain. CONCLUSION:Pilot results from the GRINS project demonstrate the feasibility of this study protocol and highlight the importance of such research, as well as its potential to study a broader range of patients with psychiatric conditions. Through GRINS, we are generating a valuable dataset across multiple domains to identify neurophysiological markers of schizophrenia individually and in combination. By applying this protocol to related mental disorders often confounded with each other, we can gather information that offers insight into the neurophysiological characteristics and underlying mechanisms of these severe conditions, informing objective diagnosis, stratification for clinical research, and ultimately, the development of better-targeted treatment matching in the clinic.

This study sought to explore relationships between video gaming time and cognitive functioning in children and adolescents to provide a scientific reference for a reasonable time range of game use. A total of 649 participants aged 6-18 years were recruited through an online survey using convenience sampling. We used a combination of multiple linear regression models, smoothing splines, piecewise linear regression models, and log-likelihood ratio tests to comprehensively analyze the linear and nonlinear relationships between video gaming time and cognitive functions. Neurocognitive functioning was assessed using the digit symbol test, spatial span back test, Stroop task, and Wisconsin card sorting test. Facial and voice emotion recognition tests were used to evaluate social cognitive functioning. Video gaming time had a saturation effect on improving correct answers to the digit symbol test, which means that performance did not increase with increasing video gaming time when the video gaming duration reached 20 h/week (adjusted beta =-0.58; 95% CI:-1.22, 0.05). Furthermore, both the rela-tionship between video gaming time and the Wisconsin Card Sorting Test and the facial emotion recognition score showed a threshold effect. The completed categories of the Wisconsin Card Sorting Test began to decline after 17 h/week of playtime, and a decline in facial emotion recognition occurred after playing video games for over 20 h/week. These results suggest that children and adolescents should restrict their video gaming time to within a certain range, which could help reduce the negative effects of video games and retain their positive effects.

Background Choosing the appropriate antipsychotic drug (APD) treatment for patients with schizophrenia (SCZ) can be challenging, as the treatment response to APD is highly variable and difficult to predict due to the lack of effective biomarkers. Previous studies have indicated the association between treatment response and genetic and epigenetic factors, but no effective biomarkers have been identified. Hence, further research is imperative to enhance precision medicine in SCZ treatment. Methods Participants with SCZ were recruited from two randomized trials. The discovery cohort was recruited from the CAPOC trial ( n = 2307) involved 6 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, Quetiapine, Aripiprazole, Ziprasidone, and Haloperidol/Perphenazine (subsequently equally assigned to one or the other) groups. The external validation cohort was recruited from the CAPEC trial ( n = 1379), which involved 8 weeks of treatment and equally randomized the participants to the Olanzapine, Risperidone, and Aripiprazole groups. Additionally, healthy controls ( n = 275) from the local community were utilized as a genetic/epigenetic reference. The genetic and epigenetic (DNA methylation) risks of SCZ were assessed using the polygenic risk score (PRS) and polymethylation score, respectively. The study also examined the genetic-epigenetic interactions with treatment response through differential methylation analysis, methylation quantitative trait loci, colocalization, and promoter-anchored chromatin interaction. Machine learning was used to develop a prediction model for treatment response, which was evaluated for accuracy and clinical benefit using the area under curve (AUC) for classification, R 2 for regression, and decision curve analysis. Results Six risk genes for SCZ ( LINC01795 , DDHD2 , SBNO1 , KCNG2 , SEMA7A , and RUFY1 ) involved in cortical morphology were identified as having a genetic-epigenetic interaction associated with treatment response. The developed and externally validated prediction model, which incorporated clinical information, PRS, genetic risk score (GRS), and proxy methylation level (proxyDNAm), demonstrated positive benefits for a wide range of patients receiving different APDs, regardless of sex [discovery cohort: AUC = 0.874 (95% CI 0.867–0.881), R 2 = 0.478; external validation cohort: AUC = 0.851 (95% CI 0.841–0.861), R 2 = 0.507]. Conclusions This study presents a promising precision medicine approach to evaluate treatment response, which has the potential to aid clinicians in making informed decisions about APD treatment for patients with SCZ. Trial registration Chinese Clinical Trial Registry ( https://www.chictr.org.cn/ ), 18. Aug 2009 retrospectively registered: CAPOC—ChiCTR-RNC-09000521 ( https://www.chictr.org.cn/showproj.aspx?proj=9014 ), CAPEC—ChiCTR-RNC-09000522 ( https://www.chictr.org.cn/showproj.aspx?proj=9013 ).

目的:采用机器学习模型,探讨预测哌甲酯控释片(OROSMPH)与托莫西汀(ATX)治疗注意缺陷多动障碍(ADHD)疗效的临床和认知特征指标.方法:纳入符合DSM-Ⅳ诊断标准的6～16岁ADHD患者237例,1∶1随机接受OROS MPH或ATX治疗,以缓解作为结局指标.以基线ADHD评定量表、临床总体印象量表、中国韦氏儿童智力量表、执行功能测查结果为特征,分别构建两种药物的疗效预测模型.结果:临床症状较轻、C因子智商较高、执行功能计划和抑制受损较轻的患者,OROSMPH疗效更好,疗效预测模型准确率81.3％;而对于ATX,B因子智商较高、执行功能启动和抑制受损较轻的患者,疗效更好,预测模型准确率80.7％.结论:患者基线智商水平、执行功能受损程度是OROS MPH与ATX疗效的重要预测指标,同时,临床症状严重程度也是OROSMPH疗效的预测指标.

Background: Low birth weight (LBW) has been reported to be a risk environmental factor for autism. However, the effects of normal birth weight (NBW) and macrosomia on autism have not been fully explored. This meta-analysis was conducted to explore the association between different birth weight levels and autism.Method: A systematic search was conducted in PubMed, Embase, and Scopus prior to April 26, 2020.Results: A total of 28 studies were recognized as eligible. A significantly increased risk of autism was observed in relation to LBW (OR = 1.63, 95 % CI = 1.48-1.81, P < 0.00001) and macrosomia (OR = 1.11, 95 % CI = 1.05-1.18, P = 0.0005). NBW was found to be associated with a reduced risk of autism (OR = 0.74, 95 % CI = 0.67-0.82, P < 0.00001). Conclusions: LBW and macrosomia may increase the risk of autism, whereas NBW may reduce the risk of autism.

Abstract Background Both knee osteoarthritis (KOA) and depressive symptoms (DS) are major public health issues affecting the quality of life. This study aimed to examine the association between KOA and DS. Methods Data were gathered from the China Health and Retirement Longitudinal Study in 2011–2015 which surveyed middle-aged to elderly individuals and their spouses in 28 provinces in China. An adjusted Cox proportional hazards regression model was used to estimate hazard ratios (HRs). Results The analysis for baseline KOA and the subsequent risk of DS was based on 2582 participants without baseline DS. During the follow-up, KOA patients were more likely to have DS than non-KOA participants (adjusted HR = 1.38: 95% CI = 1.23 to 1.83). The analysis for baseline DS and the subsequent risk of KOA was based on 4293 participants without baseline KOA, those with DS were more likely to develop KOA than non-DS participants (adjusted HR = 1.51: 95% CI = 1.26 to 1.81). Subgroup analysis showed sex and age had no significant moderating effect on the KOA-DS association. Conclusions Our results provide evidence that the association between KOA and DS is bidirectional. Therefore, primary prevention and management of KOA and DS should consider this relationship.

QTc interval prolongation is one of the most common antipsychotic-induced side effects which could lead to ventricular tachycardia or Torsade de Pointes, even cardiac arrest. There is very limited understanding on the genetic factors that associated with antipsychotic-induced QTc interval change. We conducted a genome-wide association study (GWAS) of antipsychotic-induced QTc interval change among patients with schizophrenia. A total of 2040 patients with schizophrenia were randomly assigned to six groups (olanzapine, risperidone, quetiapine, aripiprazole, ziprasidone, and first-generation antipsychotics; first-generation antipsychotics including haloperidol or perphenazine were also assigned randomly) and received 6-week antipsychotic treatment. We identified two novel loci (rs200050752 in ATAD3B and rs186507741 in SKIL) that were associated with antipsychotic-induced QTc interval change at a genome-wide significance level. The combination of polygenic risk score (PRS), based the GWAS of myocardial infarction from BioBank Japan project, and clinical data (sex, heart rate and QTc interval at baseline) could be applied to predict whether patients with schizophrenia have QTc interval prolongation (10 ms was applied as threshold, P < 0.001, area under the curve [AUC] was 0.797), especially for the first episode patients (P < 0.001, AUC was 0.872). We identified two loci located within genes related to mitochondrial function and cell growth and differentiation, which were both associated with schizophrenia and heart function. The combination of PRS and clinical data could predict whether patients with schizophrenia have the side effect of QTc interval prolongation, which could fundamentally guide the choice of antipsychotic in patients with schizophrenia, especially for the first-episode patients.

BACKGROUND: Schizophrenia is a severe mental disorder with high heritability, and cognitive dysfunction is one of the core features. Growing evidence suggests the genetic risk of schizophrenia may contribute to cognitive impairments. The variant rs1635 (nucleotide sequence: c.455C>A; amino acid sequence: T152N) located on the (NFKB activating protein like) NKAPL gene confers risk for schizophrenia and might play a role in the neurodevelopmental process, which is particularly relevant to cognitive function. However, the relationship between rs1635 and cognitive function remains unclear.METHODS: A total of 130 patients with early-onset schizophrenia (EOS) and 300 patients with adult-onset schizophrenia (AOS) of Han Chinese were recruited and underwent neurocognitive tests by using the MATRICS Consensus Cognitive Battery (MCCB). The NKAPL rs1635 was genotyped by using DNA sequencing. The peripheral blood NKAPL mRNA expression level was examined in 152T or 152N carriers (n = 20) in EOS patients, by using the qRT-PCR. The phosphorylation level of NAKPL T152N polymorphism was detected by cell experiments. In utero electroporation of mouse embryos was examined to explore the effect of Nkapl on neuronal migration.RESULTS: Compared with rs1635 AA and AC carriers, CC (the CC genotype encodes the protein NKAPL-152T) carriers of EOS patients performed better in cognitive domain of speed of processing (t = 2.644, p = 0.009), trail making test (t = 2.221, p = 0.028) and category fluency (t = 2.578, p = 0.011). However, patients with AOS exhibited no significant differences in seven domains among the three genotype groups. There were no significant differences in cognitive performance between EOS and AOS. In EOS patients, NKAPL mRNA level in NKAPL-152N carriers is significantly lower than that of NKAPL-152T carriers. The phosphorylation level of NKAPL-152N is significantly decreased compared to NKAPL-152T. In utero electroporation showed that Nkapl deletion impairs the embryonic radial migration process.CONCLUSION: The present study found that NKAPL rs1635 was associated with cognitive impairments and peripheral blood mRNA expression level in EOS patients. The NKAPL full-length protein is required for embryonic cortical neuronal migration. The phosphorylation level of NKAPL-152N is significantly decreased. The NKAPL T152N may affect the NAKPL mRNA expression level and embryonic cortical neuronal migration by regulating the NAKPL protein phosphorylation. These data suggest that NKAPL rs1635 affects cognitive function by regulating early brain development in early-onset schizophrenia.

Background: Major depressive disorder (MDD) is a common psychiatric disorder associated with working memory (WM) impairment. Neuroimaging studies showed divergent results of the WM process in MDD patients. Stress could affect the occurrence and development of depression, in which childhood maltreatment played an important role. Methods: Thirty-seven MDD patients and 54 healthy control subjects were enrolled and completed a WM functional magnetic resonance imaging task with maintenance and manipulation conditions under stress and non-stress settings. We collected demographical and clinical data, using 17-item Hamilton Depression Scale (HAMD-17) and Childhood Trauma Questionnaire (CTQ) in MDD patients. In the WM task, we analyzed the main diagnosis effect and explored the correlation of impaired brain regions in MDD patients with CTQ and HAMD-17. Results: No group differences were found in the accuracy rate and reaction time between the two groups. MDD patients had lower brain activation in following regions ( P FWE < 0.05). The left fusiform gyrus showed less activation in all conditions. The right supplementary motor area (SMA) exhibited decreased activation under non-stress. The anterior prefrontal cortex showed reduced activation during manipulation under stress, with the β estimations of the peak voxel showing significant group difference negatively correlated with childhood sex abuse ( P Bonferroni < 0.05). Conclusions: In our pilot study, MDD patients had reduced brain activation, affecting emotional stimuli processing function, executive function, and cognitive control function. Childhood maltreatment might affect brain function in MDD. This work might provide some information for future studies on MDD.

Background Schizophrenia is a severe and complex psychiatric disorder that needs treatment based on extensive experience. Antipsychotic drugs have already become the cornerstone of the treatment for schizophrenia; however, the therapeutic effect is of significant variability among patients, and only around a third of patients with schizophrenia show good efficacy. Meanwhile, drug-induced metabolic syndrome and other side-effects significantly affect treatment adherence and prognosis. Therefore, strategies for drug selection are desperately needed. In this study, we will perform pharmacogenomics research and set up an individualised preferred treatment prediction model. Aims We aim to create a standard clinical cohort, with multidimensional index assessment of antipsychotic treatment for patients with schizophrenia. Method This trial is designed as a randomised clinical trial comparing treatment with different kinds of antipsychotics. A total sample of 2000 patients with schizophrenia will be recruited from in-patient units from five clinical research centres. Using a computer-generated program, the participants will be randomly assigned to four treatment groups: aripiprazole, olanzapine, quetiapine and risperidone. The primary outcomes will be measured as changes in the Positive and Negative Syndrome Scale of schizophrenia, which reflects the efficacy. Secondary outcomes include the measure of side-effects, such as metabolic syndromes. The efficacy evaluation and side-effects assessment will be performed at baseline, 2 weeks, 6 weeks and 3 months. Results This trial will assess the efficacy and side effects of antipsychotics and create a standard clinical cohort with a multi-dimensional index assessment of antipsychotic treatment for schizophrenia patients. Conclusion This study aims to set up an individualized preferred treatment prediction model through the genetic analysis of patients using different kinds of antipsychotics.

Objective: To explore the association of the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism with birth body mass and risk of autism in Chinese Han population.Methods: A total 1,505 Chinese Han autism patients were recruited, using the Diagnostic and Statistical Manual of Mental Disorders, 4th revised version (DSM-IV-R) diagnostic criteria for autism, and 1,308 sex-matched healthy controls were also enrolled for the study. All the participants' birth body masses were counted according to the medical records. The MTHFR C677T genotypes were detected using the polymerase chain reaction-restrict fragment length polymorphism (PCR-RFLP) method. The association between C677T polymorphism, birth body mass, and risk of autism were analyzed using the chi-square tests.Results: The present study found that the MTHFR 677T was significantly associated with risk of autism [P = 0.004, odds ratio (OR) = 1.18, 95% CI = 1.02–1.29). The autism children more frequently showed low birth body mass (<2.5 kg) than healthy control subjects (8.6 vs. 5.3%, P = 0.001, OR = 1.67, 95% CI = 1.24–2.26). The interactive effects between MTHFR 677T and low birth body mass (P = 0.0001, OR = 2.18, 95% CI = 1.44–3.32) were also significantly associated with risk of autism.Conclusions: The MTHFR C677T polymorphism and low birth body mass may be associated with risk of autism in Chinese Han population.

Although antipsychotic medication contributed to the improvement of psychotic symptoms and reduced relapse, it induced weight gain and metabolic syndrome during antipsychotic medication treatment, which was seriously concerning. To investigate the association of methylenetetrahydrofolate reductase ( MTHFR ) gene C677T (rs1801133) polymorphism with antipsychotic-induced weight gain and metabolism parameter change, we employed 1,868 patients with schizophrenia in this study and randomly allocated them to seven antipsychotic medication treatment groups. All patients received antipsychotics monotherapy and were followed up for 6 weeks. Height, body weight, and metabolic parameters of the patients were measured at baseline and at 2, 4, and 6 weeks after antipsychotic treatment. We genotyped blood DNA from patients for MTHFR C677T polymorphisms and performed quantitative analyses using analysis of variance (ANOVA) and the analysis of covariance (ANCOVA) among three genotype groups. We found a predominant association between MTHFR C677T and body weight mass index (BMI) change after 6-week risperidone treatment. After 6-week treatment of risperidone, the BMI change rate (%) of MTHFR C677 carriers was significantly higher than that of MTHFR TT genotype carriers [CC (2.81 ± 6.77)%, CT (3.79 ± 5.22)%, TT (1.42 ± 3.53)%, F = 4.749, P = 0.009]. Some of the abnormal metabolic parameters were found to be associated with the MTHFR 677T, including higher levels of low-density lipoprotein and waist circumference. Validation was performed in an independent cohort, consisting of 252 patients with schizophrenia treated with three atypical antipsychotic drugs. Overall, the MTHFR C677 was associated with high risk of antipsychotic-induced weight gain and metabolism abnormalities.

Objective: This study evaluated the concurrent validity of emotional lability (EL) in children with ADHD. Method: A total of 2,015 children with ADHD and 745 typically developed controls (TDCs) were assessed and compared on EL. Results: ADHD participants expressed higher EL scores than TDCs, not influenced by gender or IQ. Higher levels of EL symptoms were found in children with comorbid oppositional defiant disorder (ODD) and with ADHD-combined subtype. Receiver operating characteristic (ROC) analyses showed a strong screening efficacy of EL symptoms on ADHD. The effect of developmental age on EL showed a desisting pattern in TDCs, as opposed to a persisting pattern in ADHD (not influenced by ODD comorbid status). ODD symptoms in ADHD showed an ascending pattern. Conclusion: EL can potentially serve as a sentinel index for the presence of ADHD, especially when the ADHD presentation is atypical. ODD may embody a developmental entity distinct from EL.

The aim of this study was to provide dose recommendations for risperidone in Asian people based on cytochrome P450 enzyme CYP2D6 genotype. First, we investigated the influence of CYP2D6 polymorphism on the pharmacokinetics of risperidone in Chinese patients with schizophrenia. Then, we performed a search for studies covering the relationship between pharmacokinetic parameters of risperidone and CYP2D6 genotype. Pooled pharmacokinetic parameters were meta-analyzed using a random-effects model. Lastly, we calculated the dose adjustment for risperidone based on CYP2D6 genotype for white and Asian people. Significant differences between the extensive metabolizer and intermediate metabolizer groups were observed for dose-adjusted risperidone level, 9-hydroxyrisperidone level, and risperidone/9-hydroxyrisperidone ratio, but not for the total active moiety. Meta-analysis showed that significant differences were observed among the four phenotype groups, including steady state concentration, peak risperidone concentration, and the area under the curve, using the Kruskal-Wallis test. No differences were found in oral clearance. For risperidone, dose recommendations for poor and ultrarapid metabolizers of CYP2D6 for Asians were different compared to that for white people for poor metabolizers (dose adjustment around 45% for white people, while for Asians the risperidone dose should be reduced by 26%). For ultrarapid metabolizers, risperidone dose should be increased by about 33% for white people and 30% for Asians. This was a first attempt to apply pharmacogenetics to suggest dose-regimens for Asian people; further research to replicate and extend these findings is recommended.

Objective: This study aimed to explore the association between monoaminergic genetic variants and emotional lability (EL) symptoms in children with ADHD. In addition, genetic effects on prefrontal cortex (PFC)–amygdala functional connectivity (FC) were investigated. Method: Children with ADHD and controls were genotyped for five monoaminergic genetic variants and were evaluated for EL symptoms. Imaging genetic exploration was conducted with previously reported aberrant PFC–amygdala resting-state functional connectivities (RSFCs) as target features. Results: A genotypic effect on EL symptoms was only found for NET1-rs3785143, indicating higher EL symptoms in TT genotype carriers than in C-allele carriers. Imaging genetic analyses indicated a marginal effect of NET1-rs3785143 on ADHD-altered FC between the superficial amygdala (SFA) and middle frontal gyrus (MFG). Mediation analysis suggested potential effects of NET1-rs3785143 via RSFC (SFA–MFG) on EL. Conclusion: NET1 variants might participate in the pathogenesis of EL in children with ADHD by influencing the function of the PFC–amygdala circuit.

Objective: A recent pharmacoimaging study suggested that methylphenidate (MPH) and atomoxetine (ATX) might have common mechanisms for the treatment of attention-deficit/hyperactivity disorder (ADHD). Previous pharmacogenetic studies have by and large only involved genes in neurotransmitter systems, which accounted for very small variances. Therefore, this study aimed to investigate whether the neurodevelopmental genes identified in a prior ADHD etiology Genome-Wide Association Study (GWAS) could predict patients' responses to MPH and ATX, given the aforementioned mechanisms of action. Methods: For our sample of 241 patients with ADHD, we assessed the change in the ADHD rating scale (ADHD-RS) total symptom scores from baseline to the end of the 12th week of treatment with either MPH or ATX. We performed association analyses at the genetic single-marker, gene-based, set-based, and GWAS-based polygenic levels. Results: In our analyses, neither single nucleotide polymorphism (SNP) nor gene-level analyses yielded significant markers associated with the change in the ADHD-RS score after multiple comparison correction. The polygenic risk score model, which was based on SNPs associated with ADHD etiology at a threshold of p <= 0.0001 in a recent Han Chinese GWAS, predicted symptomatic improvement with ADHD medication (p = 0.018, R-2 = 0.023). Conclusion: Our results provide new evidence for a small influence of neurodevelopmental genes on the efficacy of medications for ADHD.

Genome-wide association study (GWAS) has determined the metabotropic glutamate receptor 7 ( GRM7 ) gene as potential locus for schizophrenia risk variants; However, the relationship between the GRM7 variants and the risk of schizophrenia is still uncertain, and there are significant individual variations in response to the antipsychotic drugs. In order to identify susceptible gene and drug-response-related markers, 2413 subjects in our research were chosen for determining drug-response-related markers in schizophrenia. The rs1516569 variant (OR = 0.95, P < 3.47 × 10 −4 ) was a significant risk factor, and a single-nucleotide polymorphism of GRM7 gene- rs9883258 (OR = 0.84, P = 2.18 × 10 −3 ) has been determined as potential biomarkers for therapeutic responses of seven commonly used antipsychotic drugs (aripiprazole, haloperidol, olanzapine, perphenazine, quetiapine, risperidone and ziprasidone) in Chinese Han population; Significant associations with treatment response for several single-nucleotide polymorphisms in every antipsychotic drugs, such as rs779746 (OR = 1.39, P = 0.03), rs480409 (OR = 0.73, P = 0.04), rs78137319 (OR = 3.09, P = 0.04), rs1154370 (OR = 1.51, P = 0.006) have been identified in our study. Hence our research elucidates that GRM7 variants play the critical role of predicting the risk of schizophrenia and antipsychotic effect of seven common drugs.

Risperidone has been used to treat the symptoms of schizophrenia and to reduce its relapse. However, the responses to treatment show great variability among patients. The potassium channel has been reported as an effective target for antipsychotics. KCNH7, a member of the voltage-gated K+ channel Kv11 family, is primarily expressed in the brain. Here, we assessed the genetic association of KCNH7 with risperidone responses in 393 schizophrenia patients. The patients were treated with risperidone for 6 weeks. The reduction rates of Positive and Negative Syndrome Scale (PANSS) scores were determined to quantify drug response. We also examined the associations between six single-nucleotide polymorphisms (SNPs) of KCNH7 and the risperidone responses for a total of 6 weeks. The SNP rs77699177 (C > T) in the KCNH7 gene intron was significantly associated with the treatment response reflected by the PANSS reduction rate (CC, 55.8 ± 23.0; TC, 70.9 ± 20.3, P = 0.000110), indicating that patients with the TC genotype have better efficacy for antipsychotic therapy. The rs2241240 SNP also showed a significant association with treatment responses after 6 weeks of treatment (P = 0.00256). The findings indicate that the voltage-gated K+ channel KCNH7 is a potential functional marker for the identification of the response to risperidone treatment in schizophrenia patients. Note: The study was registered under clinical trial number ChiCTR-RNC-09000522 (http://www.chictr.org/).

Attention Deficit/Hyperactivity Disorder (ADHD) is one kind of neurodevelopmental disorders common in children. Due to the complexity of the pathological mechanism, there is a lack of objective diagnostic methods up to now. This paper aimed to propose automatic ADHD diagnostic method using resting state functional magnetic resonance imaging (rs-fMRI) data with the spatio-temporal deep learning models. Unlike traditional methods, this paper constructed a deep learning method called 4-D CNN based on granular computing which were trained based on derivative changes in entropy, and can calculate granularity at a coarse level by stacking layers. Considering the structure of rs-fMRI as time-series 3-D frames, several models of spatial and temporal granular computing and fusion were proposed, including feature pooling, long short-term memory (LSTM) and spatio-temporal convolution. This paper introduced an approach to augment dataset which can sample one subject's rs-fMRI frames into several relatively short term pieces with a fixed stride. The public dataset of ADHD-200 Consortium was used to train and validate our method. And the results of evaluations showed that our method outperformed traditional methods on the dataset (accuracy: 71.3%, AUC: 0.80). Therefore, our 4-D CNN method can be used to build more accurate automatic assistant diagnosis tool of ADHD. (C) 2019 Elsevier Inc. All rights reserved.