Genome-wide association study implicates lipid pathway dysfunction in antipsychotic-induced weight gain: multi-ancestry validation.

Antipsychotic-induced weight gain (AIWG) is a common side effect of antipsychotic medication and may contribute to diabetes and coronary heart disease. To expand the unclear genetic mechanism underlying AIWG, we conducted a two-stage genome-wide association study in Han Chinese patients with schizophrenia. The study included a discovery cohort of 1936 patients and a validation cohort of 534 patients, with an additional 630 multi-ancestry patients from the CATIE study for external validation. We applied Mendelian randomization (MR) analysis to investigate the relationship between AIWG and antipsychotic-induced lipid changes. Our results identified two novel genome-wide significant loci associated with AIWG: rs10422861 in PEPD (P = 1.373 × 10-9) and rs3824417 in PTPRD (P = 3.348 × 10-9) in Chinese Han samples. The association of rs10422861 was validated in the European samples. Fine-mapping and functional annotation revealed that PEPD and PTPRD are potentially causal genes for AIWG, with their proteins being prospective therapeutic targets. Colocalization analysis suggested that AIWG and type 2 diabetes (T2D) shared a causal variant in PEPD. Polygenic risk scores (PRSs) for AIWG and T2D significantly predicted AIWG in multi-ancestry samples. Furthermore, MR revealed a risky causal effect of genetically predicted changes in low-density lipoprotein cholesterol (P = 7.58 × 10-4) and triglycerides (P = 2.06 × 10-3) caused by acute-phase of antipsychotic treatment on AIWG, which had not been previously reported. Our model, incorporating antipsychotic-induced lipid changes, PRSs, and clinical predictors, significantly predicted BMI percentage change after 6-month antipsychotic treatment (AUC = 0.79, R2 = 0.332). Our results highlight that the mechanism of AIWG involves lipid pathway dysfunction and may share a genetic basis with T2D through PEPD. Overall, this study provides new insights into the pathogenesis of AIWG and contributes to personalized treatment of schizophrenia.

STON2 variations are involved in synaptic dysfunction and schizophrenia-like behaviors by regulating Syt1 trafficking.

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 vesicles. In this study, we showed that the C-C (307Pro-851Ala) haplotype of STON2 increases the susceptibility 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 attractive therapeutic targets for treating schizophrenia-like phenotypes.

Replication of previous autism-GWAS hits suggests the association between NAA1, SORCS3, and GSDME and autism in the Han Chinese population.

Background: Autism is a severe neurodevelopmental disorder characterized by social interaction deficits, impairments in communication, and restricted and repetitive stereotyped behavior and activities. Family and twin studies suggested an essential role of genetic factors in the etiology of autism spectrum disorder (ASD). Also, other studies found SORCS3 and GSDME (DFNA5) might be involved in brain development and susceptible to ASD. Methods: In this study, 17 genome-wide significant SNPs reported in previous ASD genome-wide association studies (GWAS) and 7 SNPs in strong linkage disequilibrium with known ASD GWAS hits were selected to investigate the association between these SNPs and autism in the Han Chinese population. Then, 10 tagSNPs in SORCS3 and 11 tagSNPs in GSDME were selected to analyze the association between these SNPs and autism. The selected 24 SNPs and tagSNPs were genotyped using the Agena MassARRAY SNP genotyping assay in 757 Han Chinese autism trios. Results: Rs1484144 in NAA11 was significantly associated with autism; significance remained after the Bonferroni correction (P < 0.0022). Also, rs79879286, rs12154597, and rs12540919 near GSDME, as well as rs9787523 and rs3750261 in SORCS3, were nominally associated with autism. Conclusion: Our study suggests that rs1484144 in NAA11 is a significant SNP for autism in the Han Chinese population, while SORCS3 and GSDME might be the susceptibility genes for autism in this population.

Relationship between autism and brain cortex surface area: genetic correlation and a two-sample Mendelian randomization study.

BACKGROUND: Alterations in surface area (SA) in specific regions of the cortex have been reported in many individuals with autism spectrum disorder (ASD), however, the genetic background between ASD and SA is still unclear. This study estimated the genetic correlation and causal effect of ASD and cortical SA. METHODS: Summarized data of genome-wide association studies (GWAS) were separately downloaded from the Psychiatric Genomics Consortium (18,381 cases of ASD, and 27,969 controls) and the Enhancing Neuroimaging Genetics through Meta-Analysis Consortium (33,992 participants of Europeans). We used Linkage disequilibrium score regression (LDSC) and Heritability Estimation from Summary Statistics (HESS) to calculate the heritability of each trait. As for the genetic correlation between ASD and SA, LDSC was used for global correlation and HESS was used to examine the local genetic covariance further. We used three Mendelian randomization (MR) methods, Inverse-variance weighted, MR-Egger, and weighted median to estimate the causal relationship. RESULTS: LDSC observed a nominal significant genetic correlation (rg = 0.1229, P-value = 0.0346) between ASD and SA of the rostral anterior cingulate gyrus whereas analysis through HESS did not reveal any significant loci having genetic covariance. Based on MR results, statistically meaningful estimations were found in the following areas, postcentral cortex (ß (SE) = 21.82 (7.84) mm, 95% CI: 6.46 to 37.19 mm, PIVW = 5.38 × 10- 3, PFDR = 3.09 × 10- 2), posterior cingulate gyrus (ß (SE) = 6.23 (2.69) mm, 95% CI: 0.96 to 11.49 mm, PIVW = 2.05 × 10- 2, PFDR = 4.26 × 10- 2), supramarginal gyrus (ß (SE) = 19.25 (8.43) mm, 95% CI: 29.29 to 35.77 mm, PIVW = 2.24 × 10- 2, PFDR = 4.31 × 10- 2). CONCLUSION: Our results provided genetic evidence to support the opinion that individuals with ASD tend to develop differences in cortical SA of special areas. The findings contributed to understanding the genetic relationship between ASD and cortical SA.

The Role of Total White Blood Cell Count in Antipsychotic Treatment for Patients with Schizophrenia.

BACKGROUND: Total white blood cell count (TWBCc), an index of chronic and low-grade inflammation, is associated with clinical symptoms and metabolic alterations in patients with schizophrenia. The effect of antipsychotics on TWBCc, predictive values of TWBCc for drug response, and role of metabolic alterations require further study. METHODS: Patients with schizophrenia were randomized to monotherapy with risperidone, olanzapine, quetiapine, aripiprazole, ziprasidone, perphenazine or haloperidol in a 6-week pharmacological trial. We repeatedly measured clinical symptoms, TWBCc, and metabolic measures (body mass index, blood pressure, waist circumference, fasting blood lipids and glucose). We used mixed-effect linear regression models to test whether TWBCc can predict drug response. Mediation analysis to investigate metabolic alteration effects on drug response. RESULTS: At baseline, TWBCc was higher among patients previously medicated. After treatment with risperidone, olanzapine, quetiapine, perphenazine, and haloperidol, TWBCc decreased significantly (p < 0.05). Lower baseline TWBCc predicted greater reductions in Positive and Negative Syndrome Scale (PANSS) total and negative scores over time (p < 0.05). We found significant mediation of TWBCc for effects of waist circumference, fasting low-density lipoprotein cholesterol, and glucose on reductions in PANSS total scores and PANSS negative subscale scores (p < 0.05). CONCLUSION: TWBCc is affected by certain antipsychotics among patients with schizophrenia, with decreases observed following short-term, but increases following long-term treatment. TWBCc is predictive of drug response, with lower TWBCc predicting better responses to antipsychotics. It also mediates the effects of certain metabolic measures on improvement of negative symptoms. This indicates that the metabolic state may affect clinical manifestations through inflammation.

Integrative analysis of long noncoding RNAs dysregulation and synapse-associated ceRNA regulatory axes in autism.

Autism spectrum disorder (ASD) is a complex disorder of neurodevelopment, the function of long noncoding RNA (lncRNA) in ASD remains essentially unknown. In the present study, gene networks were used to explore the ASD disease mechanisms integrating multiple data types (for example, RNA expression, whole-exome sequencing signals, weighted gene co-expression network analysis, and protein-protein interaction) and datasets (five human postmortem datasets). A total of 388 lncRNAs and five co-expression modules were found to be altered in ASD. The downregulated co-expression M4 module was significantly correlated with ASD, enriched with autism susceptibility genes and synaptic signaling. Integrating lncRNAs from the M4 module and microRNA (miRNA) dysregulation data from the literature identified competing endogenous RNA (ceRNA) network. We identified the downregulated mRNAs that interact with miRNAs by the miRTarBase, miRDB, and TargetScan databases. Our analysis reveals that MIR600HG was downregulated in multiple brain tissue datasets and was closely associated with 9 autism-susceptible miRNAs in the ceRNA network. MIR600HG and target mRNAs (EPHA4, MOAP1, MAP3K9, STXBP1, PRKCE, and SCAMP5) were downregulated in the peripheral blood by quantitative reverse transcription polymerase chain reaction analysis (false discovery rate <0.05). Subsequently, we assessed the role of lncRNA dysregulation in altered mRNA levels. Experimental verification showed that some synapse-associated mRNAs were downregulated after the MIR600HG knockdown. BrainSpan project showed that the expression patterns of MIR600HG (primate-specific lncRNA) and synapse-associated mRNA were similar in different human brain regions and at different stages of development. A combination of support vector machine and random forest machine learning algorithms retrieved the marker gene for ASD in the ceRNA network, and the area under the curve of the diagnostic nomogram was 0.851. In conclusion, dysregulation of MIR600HG, a novel specific lncRNA associated with ASD, is responsible for the ASD-associated miRNA-mRNA axes, thereby potentially regulating synaptogenesis.

Calcium Homeostasis and Psychiatric Disorders: A Mendelian Randomization Study.

Observational studies have investigated the impact of calcium homeostasis on psychiatric disorders; however, the causality of associations is yet to be established. Bidirectional Mendelian randomization (MR) analysis of calcium homeostasis hormones was conducted on nine psychiatric disorders. Calcium, serum 25-hydroxyvitamin D levels (25OHD), parathyroid hormone, and fibroblast growth factor 23 are the major calcium homeostasis hormones. The causality was evaluated by the inverse variance weighted method (IVW) and the MR Steiger test, while Cochran's Q test, the MR-Egger intercept test, funnel plot, and the leave-one-out method were used for sensitivity analyses. Bonferroni correction was used to determine the causative association features (p < 6.94 × 10-4). Schizophrenia (SCZ) was significantly associated with decreased 25OHD concentrations with an estimated effect of -0.0164 (Prandom-effect IVW = 2.39 × 10-7). In the Multivariable MR (MVMR) analysis adjusting for potentially confounding traits including body mass index, obesity, mineral supplements (calcium, fish oil, and vitamin D) and outdoor time (winter and summer), the relationship between SCZ and 25OHD remained. The genetically predicted autism spectrum disorder and bipolar disorder were also nominally associated with decreased 25OHD. This study provided evidence for a causal effect of psychiatric disorders on calcium homeostasis. The clinical monitoring of 25OHD levels in patients with psychiatric disorders is beneficial.

Phosphodiesterase and psychiatric disorders: a two-sample Mendelian randomization study.

BACKGROUND: Phosphodiesterases (PDEs) have been associated with psychiatric disorders in observational studies; however, the causality of associations remains unestablished. METHODS: Specifically, cyclic nucleotide PDEs were collected from genome-wide association studies (GWASs), including PDEs obtained by hydrolyzing both cyclic adenosine monophosphate (cAMP) and cyclic guanosine monophosphate (cGMP) (PDE1A, PDE2A, and PDE3A), specific to cGMP (PDE5A, PDE6D, and PDE9A) and cAMP (PDE4D and PDE7A). We performed a bidirectional two-sample Mendelian randomization (MR) analysis to investigate the relationship between PDEs and nine psychiatric disorders. The inverse-variance-weighted (IVW) method, MR-Egger, and weighted median were used to estimate causal effects. The Cochran's Q test, MR-Egger intercept test, MR Steiger test, leave-one-out analyses, funnel plot, and MR pleiotropy residual sum and outlier (MR-PRESSO) were used for sensitivity analyses. RESULTS: The PDEs specific to cAMP were associated with higher-odds psychiatric disorders. For example, PDE4D and schizophrenia (SCZ) (odds ratios (OR) = 1.0531, PIVW = 0.0414), as well as major depressive disorder (MDD) (OR = 1.0329, PIVW = 0.0011). Similarly, PDE7A was associated with higher odds of attention-deficit/hyperactivity disorder (ADHD) (OR = 1.0861, PIVW = 0.0038). Exploring specific PDE subtypes and increase intracellular cAMP levels can inform the development of targeted interventions. We also observed PDEs (which hydrolyzes both cAMP and cGMP) was associated with psychiatric disorders [OR of PDE1A was 1.0836 for autism spectrum disorder; OR of PDE2A was 0.8968 for Tourette syndrome (TS) and 0.9449 for SCZ; and OR of PDE3A was 0.9796 for MDD; P < 0.05]. Furthermore, psychiatric disorders also had some causal effects on PDEs [obsessive-compulsive disorder on increased PDE6D and decreased PDE2A and PDE4D; anorexia nervosa on decreased PDE9A]. The results of MR were found to be robust using multiple sensitivity analysis. CONCLUSIONS: In this study, potential causal relationships between plasma PDE proteins and psychiatric disorders were established. Exploring other PDE subtypes not included in this study could provide a more comprehensive understanding of the role of PDEs in psychiatric disorders. The development of specific medications targeting PDE subtypes may be a promising therapeutic approach for treating psychiatric disorders.

Genome-wide association study identified six loci associated with adverse drug reactions to aripiprazole in schizophrenia patients.

Aripiprazole is recommended for routine use in schizophrenia patients. However, the biological mechanism for the adverse drug reactions (ADRs) among schizophrenia patients with the antipsychotic drug aripiprazole is far from clear. To explore the potential genetic factors that may cause movement-related adverse antipsychotic effects in patients, we conducted an association analysis between movement-related ADRs and SNPs in schizophrenia patients receiving aripiprazole monotherapy. In this study, multiple ADRs of 384 patients were quantified within 6-week treatment, and the scores of movement-related ADRs at baseline and follow-up time points during treatment were obtained. The highest score record was used as the quantitative index in analysis, and genetic analysis at the genome-wide level was conducted. The SNP rs4149181 in SLC22A8 [P = 2.28 × 10-8] showed genome-wide significance, and rs2284223 in ADCYAP1R1 [P = 9.76 × 10-8], rs73258503 in KCNIP4 [P = 1.39 × 10-7], rs678428 in SMAD9 [P = 4.70 × 10-7], rs6421034 in NAP1L4 [P = 6.80 × 10-7], and rs1394796 in ERBB4 [P = 8.60 × 10-7] were found to be significantly associated with movement-related ADRs. The combined prediction model of these six loci showed acceptable performance in predicting adverse events [area under the curve (AUC): 0.84]. Combined with the function and network of the above genes and other candidate loci (KCNA1, CACNG1, etc.), we hypothesize that SLC22A8 and KCNIP4-Kv channel perform their respective functions as transporter or channel and participate in the in vivo metabolism or effects of aripiprazole. The above results imply the important function of ion transporters and channels in movement-related adverse antipsychotic effects in aripiprazole monotherapy schizophrenia patients.

Prediction of treatment response to antipsychotic drugs for precision medicine approach to schizophrenia: randomized trials and multiomics analysis.

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, R2 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), R2 = 0.478; external validation cohort: AUC = 0.851 (95% CI 0.841-0.861), R2 = 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 ).

Comparison of the probability of four anticonvulsant mood stabilizers to facilitate polycystic ovary syndrome in women with epilepsies or bipolar disorder-A systematic review and meta-analysis.

Background: Patients treated with anticonvulsant mood stabilizers have a higher incidence of polycystic ovary syndrome (PCOS). However, there is no comparison between different anticonvulsant mood stabilizers. The purpose of this study was to systematically evaluate the prevalence of PCOS in women taking anticonvulsant mood stabilizers and compare the probability of PCOS caused by different anticonvulsant mood stabilizers. Methods: Five databases, namely PubMed, Embase, Web of Science, Cochrane Library, and Clinical Trials, were searched for literature on anticonvulsant mood stabilizers and PCOS published up to October 28, 2022. This meta-analysis was performed using Revman 5.4, Stata 14.0, and R4.1.0, and effect size pooling was performed in fixed- or random-effects models based on the results of I2 and Q-test, and the surface under the cumulative ranking curve (SUCRA) was used for analysis to assess the cumulative probability of drug-induced PCOS. Publication bias was assessed by funnel plot Egger's test and meta regression. Results: Twenty studies with a total of 1,524 patients were included in a single-arm analysis, which showed a combined effect size (95% CI) of 0.21 (0.15-0.28) for PCOS in patients taking anticonvulsant mood stabilizers. Nine controlled studies, including 500 patients taking medication and 457 healthy controls, were included in a meta-analysis, which showed OR = 3.23 and 95% CI = 2.19-4.76 for PCOS in women taking anticonvulsant mood stabilizers. Sixteen studies with a total of 1416 patients were included in a network meta-analysis involving four drugs, valproate (VPA), carbamazepine (CBZ), oxcarbazepine (OXC), and lamotrigine (LTG), and the results of the network meta-analysis showed that VPA (OR = 6.86, 95% CI = 2.92-24.07), CBZ (OR = 3.28, 95% CI = 0.99-12.64), OXC (OR = 4.30, 95% CI = 0.40-49.49), and LTG (OR = 1.99, 95% CI = 0.16-10.30), with cumulative probabilities ranked as VPA (90.1%), OXC (63.9%), CBZ (50.1%), and LTG (44.0%). Conclusion: The incidence of PCOS was higher in female patients treated with anticonvulsant mood stabilizers than in the healthy population, with VPA having the highest likelihood of causing PCOS. The most recommended medication when considering PCOS factors is LTG. Systematic review registration: identifier: CRD42022380927.

Autism spectrum disorder research: knowledge mapping of progress and focus between 2011 and 2022.

Background: In recent years, a large number of studies have focused on autism spectrum disorder (ASD). The present study used bibliometric analysis to describe the state of ASD research over the past decade and identify its trends and research fronts. Methods: Studies on ASD published from 2011 to 2022 were obtained from the Web of Science Core Collection (WoSCC). Bibliometrix, CiteSpace, and VOSviewer were used for bibliometric analysis. Results: A total of 57,108 studies were included in the systematic search, and articles were published in more than 6,000 journals. The number of publications increased by 181.7% (2,623 in 2011 and 7,390 in 2021). The articles in the field of genetics are widely cited in immunology, clinical research, and psychological research. Keywords co-occurrence analysis revealed that "causative mechanisms," "clinical features," and "intervention features" were the three main clusters of ASD research. Over the past decade, genetic variants associated with ASD have gained increasing attention, and immune dysbiosis and gut microbiota are the new development frontiers after 2015. Conclusion: This study uses a bibliometric approach to visualize and quantitatively describe autism research over the last decade. Neuroscience, genetics, brain imaging studies, and gut microbiome studies improve our understanding of autism. In addition, the microbe-gut-brain axis may be an exciting research direction for ASD in the future. Therefore, through visual analysis of autism literature, this paper shows the development process, research hotspots, and cutting-edge trends in this field to provide theoretical reference for the development of autism in the future.

Therapeutic outcomes wide association scan of different antipsychotics in patients with schizophrenia: Randomized clinical trials and multi-ancestry validation.

AIM: This study identified discrepant therapeutic outcomes of antipsychotics. METHODS: A total of 5191 patients with schizophrenia were enrolled, 3030 as discovery cohort, 1395 as validation cohort, and 766 as multi-ancestry validation cohort. Therapeutic Outcomes Wide Association Scan was conducted. Types of antipsychotics (one antipsychotic vs other antipsychotics) were dependent variables, therapeutic outcomes including efficacy and safety were independent variables. RESULTS: In discovery cohort, olanzapine related to higher risk of weight gain (AIWG, OR: 2.21-2.86), liver dysfunction (OR: 1.75-2.33), sedation (OR: 1.76-2.86), increased lipid level (OR: 2.04-2.12), and lower risk of extrapyramidal syndrome (EPS, OR: 0.14-0.46); risperidone related to higher risk of hyperprolactinemia (OR: 12.45-20.53); quetiapine related to higher risk of sedation (OR = 1.73), palpitation (OR = 2.87), increased lipid level (OR = 1.69), lower risk of hyperprolactinemia (OR: 0.09-0.11), and EPS (OR: 0.15-0.44); aripiprazole related to lower risk of hyperprolactinemia (OR: 0.09-0.14), AIWG (OR = 0.44), sedation (OR: 0.33-0.47), and QTc prolongation (ß = -2.17); ziprasidone related to higher risk of increased QT interval (ß range: 3.11-3.22), nausea (OR: 3.22-3.91), lower risk of AIWG (OR: 0.27-0.46), liver dysfunction (OR: 0.41-0.38), and increased lipid level (OR: 0.41-0.55); haloperidol related to higher risk of EPS (OR: 2.64-6.29), hyperprolactinemia (OR: 5.45-9.44), and increased salivation (OR: 3.50-3.68). Perphenazine related to higher risk of EPS (OR: 1.89-2.54). Higher risk of liver dysfunction in olanzapine and lower risk of hyperprolactinemia in aripiprazole were confirmed in validation cohort, and higher risk of AIWG in olanzapine and hyperprolactinemia in risperidone were confirmed in multi-ancestry validation cohort. CONCLUSION: Future precision medicine should focus on personalized side-effects.

The positive association between antipsychotic-induced weight gain and therapeutic response: New biotypes of schizophrenia.

Co-occurrence of antipsychotic-induced weight gain (AIWG) and therapeutic response (TR) did exist in clinic but was rarely studied. This study aims to identify potential TR/ AIWG biotypes and explore the clinical, genetic and neuroimaging features. This study enrolled 3030 patients to identify potential TR/AIWG biotypes and explore the clinical, genetic and neuroimaging features. We found three biotypes: TR+nonAIWG (46.91%), TR+AIWG (18.82%), and nonTR+nonAIWG (34.27%). TR+AIWG showed lower weight and lipid level at baseline, but higher changing rate, and higher genetic risk of obesity than TR+nonAIWG and nonTR+nonAIWG. GWAS identified ADIPOQ gene related to TR+AIWG biotypes and top-ranked loci enriched in one-carbon metabolic process, which related to both schizophrenia and metabolic dysfunction. Genetically predicted TR+AIWG was associated with higher odds of diabetes (OR=1.05). The left supplementary motor area was significantly negatively correlated with PRS of obesity. The distinguishing ability with multi-omics data to identify TR+AIWG reached 0.787. In a word, the "thin" patients with a higher risk of obesity are the target population of early intervention.

Early Efficacy of Antipsychotic Medications at Week 2 Predicts Subsequent Responses at Week 6 in a Large-scale Randomized Controlled Trial.

BACKGROUND: Since the early clinical efficacy of antipsychotics has not yet been well perceived, this study sought to decide whether the efficacy of antipsychotics at week 2 can predict subsequent responses at week 6 and identify how such predictive capacities vary among different antipsychotics and psychotic symptoms. METHODS: A total of 3010 patients with schizophrenia enrolled in a randomized controlled trial (RCT) and received a 6-week treatment with one antipsychotic drug randomly chosen from five atypical antipsychotics (risperidone 2-6 mg/d, olanzapine 5-20 mg/d, quetiapine 400-750 mg/d, aripiprazole 10-30 mg/d, and ziprasidone 80-160 mg/d) and two typical antipsychotics (perphenazine 20-60 mg/d and haloperidol 6-20 mg/d). Early efficacy was defined as the reduction rate using the Positive and Negative Syndrome Scale (PANSS) total score at week 2. With cut-offs at 50% reduction, logistic regression, receiver operating characteristic (ROC) and random forests were adopted. RESULTS: The reduction rate of PANSS total score and improvement of psychotic symptoms at week 2 enabled subsequent responses to 7 antipsychotics to be predicted, in which improvements in delusions, lack of judgment and insight, unusual thought content, and suspiciousness/ persecution were endowed with the greatest weight. CONCLUSION: It is robust enough to clinically predict treatment responses to antipsychotics at week 6 using the reduction rate of PANSS total score and symptom relief at week 2. Psychiatric clinicians had better determine whether to switch the treatment plan by the first 2 weeks.

Longitudinal Network Analysis Reveals Interactive Change of Schizophrenia Symptoms During Acute Antipsychotic Treatment.

BACKGROUND AND HYPOTHESIS: Complex schizophrenia symptoms were recently conceptualized as interactive symptoms within a network system. However, it remains unknown how a schizophrenia network changed during acute antipsychotic treatment. The present study aimed to evaluate the interactive change of schizophrenia symptoms under seven antipsychotics from individual time series. STUDY DESIGN: Data on 3030 schizophrenia patients were taken from a multicenter randomized clinical trial and used to estimate the partial correlation cross-sectional networks and longitudinal random slope networks based on multivariate multilevel model. Thirty symptoms assessed by The Positive and Negative Syndrome Scale clustered the networks. STUDY RESULTS: Five stable communities were detected in cross-sectional networks and random slope networks that describe symptoms change over time. Delusions, emotional withdrawal, and lack of spontaneity and flow of conversation featured as central symptoms, and conceptual disorganization, hostility, uncooperativeness, and difficulty in abstract thinking featured as bridge symptoms, all showing high centrality in the random slope network. Acute antipsychotic treatment changed the network structure (M-test = 0.116, P < .001) compared to baseline, and responsive subjects showed lower global strength after treatment (11.68 vs 14.18, S-test = 2.503, P < .001) compared to resistant subjects. Central symptoms and bridge symptoms kept higher centrality across random slope networks of different antipsychotics. Quetiapine treatment network showed improvement in excitement symptoms, the one featured as both central and bridge symptom. CONCLUSION: Our findings revealed the central symptoms, bridge symptoms, cochanging features, and individualized features under different antipsychotics of schizophrenia. This brings implications for future targeted drug development and search for pathophysiological mechanisms.

A deep learning-based model for detecting depression in senior population.

Objectives: With the attention paid to the early diagnosis of depression, this study tries to use the biological information of speech, combined with deep learning to build a rapid binary-classification model of depression in the elderly who use Mandarin and test its effectiveness. Methods: Demographic information and acoustic data of 56 Mandarin-speaking older adults with major depressive disorder (MDD), diagnosed with the Mini-International Neuropsychiatric Interview (MINI) and the fifth edition of Diagnostic and Statistical Manual of Mental Disorders (DSM-5), and 47 controls was collected. Acoustic data were recorded using different smart phones and analyzed by deep learning model which is developed and tested on independent validation set. The accuracy of the model is shown by the ROC curve. Results: The quality of the collected speech affected the accuracy of the model. The initial sensitivity and specificity of the model were respectively 82.14% [95%CI, (70.16-90.00)] and 80.85% [95%CI, (67.64-89.58)]. Conclusion: This study provides a new method for rapid identification and diagnosis of depression utilizing deep learning technology. Vocal biomarkers extracted from raw speech signals have high potential for the early diagnosis of depression in older adults.

Association of NKAPL rs1635 With Cognitive Function in Early-Onset Schizophrenia.

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.

Altered Expression of Brain-specific Autism-Associated miRNAs in the Han Chinese Population.

Autism is a complex neurodevelopmental disorder. However, its etiology is still unknown. MicroRNAs (miRNAs) are key post-transcriptional regulators. They play an important role in neurodevelopment and brain functions and may be involved in the pathogenesis of autism. Previous studies indicated altered expression of miRNAs in patients with autism. However, the findings were not consistent, and further explorations were needed. This study aimed to investigate whether miRNAs were dysregulated in autism. We examined the expression of 30 brain-specific autism-associated miRNAs in 110 patients with autism and 113 controls in the Han Chinese population using quantitative reverse transcription-polymerase chain reaction. The results demonstrated that 10 miRNAs (hsa-miR-191-5p, hsa-miR-151a-3p, hsa-miR-139-5p, hsa-miR-181a-5p, hsa-miR-432-5p, hsa-miR-181b-5p, hsa-miR-195-5p, hsa-miR-328-3p, hsa-miR-106a-5p, and hsa-miR-484) were significantly differentially expressed (false discovery rate <0.05). All of them were up-regulated in patients with autism compared with controls. The targets of these miRNAs were enriched for genes and pathways related to neurodevelopment, brain functions and autism. These findings suggested the participation of these 10 miRNAs in the pathogenesis of autism in the Han Chinese population.

ATAD3B and SKIL polymorphisms associated with antipsychotic-induced QTc interval change in patients with schizophrenia: a genome-wide association study.

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.