The safety of antidepressants in bipolar disorder (BD) remains controversial, particularly regarding the risk of behavioral activation and worsening Non-Suicidal Self-Injury (NSSI). This multi-center retrospective cohort study included 575 patients with BD from 15 medical centers in China to evaluate the association between antidepressant use and NSSI frequency, suicidal ideation (SI), and suicidal behavior (SB) over a one-year period. Multivariable logistic regression revealed that antidepressant use was associated with higher odds of the worsening of NSSI (OR=1.90, p = 0.030), as well as the presence of SI (OR=1.70, p = 0.016) and SB (OR=1.80, p = 0.010). In exploratory subgroup analyses, point estimates were larger in patients with low household income (OR=2.74, p = 0.038) and non-depressive dominant polarity (OR=7.05, p < 0.001), and the association reached significance only in patients not receiving concurrent lithium (OR=2.29, p = 0.032) but not in lithium-treated patients (OR=1.38, p = 0.462); however, none of the formal interaction tests was statistically significant (all interaction p > 0.05). These findings indicate that antidepressant use in BD is associated with higher odds of worsening NSSI and suicidality. The observed subgroup differences did not reach statistical significance on interaction testing and should be regarded as hypothesis-generating.

BACKGROUND AND HYPOTHESIS:Motivational deficits are core negative symptoms of schizophrenia (SCZ), which have been linked to disruptions in reward network. Recent evidence suggests the cerebellum's role in motivational and hedonic processing. This study examined its connectivity with the reward network in SCZ and hypothesized that decreased connectivity would be found in SCZ patients and correlated with severe negative symptoms. STUDY DESIGN:This study employed a cross-sample validation approach using 2 independent cohorts (Sample 1: NSCZ = 62, NHC = 61; Sample 2: NSCZ = 53, NHC = 55). Resting-state functional connectivity was assessed using network-based analysis to identify disrupted subnetworks, followed by seed-based connectivity analysis to localize specific connections. Effective connectivity was assessed using spectral Dynamic Causal Modeling (DCM) for inferring the directional influences of abnormal connectivity related to amotivation or anhedonia. STUDY RESULTS:Network-based analysis in Sample 1 identified a disrupted subnetwork between the cerebellum (lobules VI, VIIb, VIII) and basal ganglia (putamen, caudate, pallidum) in SCZ, with cerebellar-pallidal connectivity associated with amotivation. Seed-based analysis in Sample 2 revealed reduced putamen/caudate-lobule VI connectivity, correlating with amotivation and anhedonia symptoms in SCZ. Spectral DCM indicated reduced excitatory input from cerebellum to the basal ganglia in Sample 1, but such results could not be replicated in Sample 2. CONCLUSIONS:Our findings highlighted the role of cerebellum-basal ganglia connectivity in the pathophysiology of SCZ, particularly in relation to amotivation and anhedonia. This pathway may be a putative target for neuromodulation to ameliorate negative symptoms of SCZ.

Background Bipolar disorder imposes a substantial global health burden. While international clinical guidelines exist, real-world treatment patterns for bipolar disorder in China remains poorly characterized. This study aimed to characterize initial treatment selection, pharmacologic class distribution, and longitudinal prescription adjustments among inpatients with newly diagnosed bipolar disorder in Beijing, China, from 2010 to 2017. Methods A population-based longitudinal study was conducted utilizing data from the Beijing Medical Claim Data for Employees. We included 3034 inpatients newly diagnosed with bipolar disorder using ICD-10 code. We analyzed initial treatment patterns, annual prescription trends, and treatment modifications from the acute phase to maintenance phase. Results Over half (57.3%) of patients started on polypharmacy. Quetiapine was the most prescribed antipsychotic (43.8%), and lithium the most common mood stabilizer (37.7%). Alarmingly, the rate of treatment discontinuation reached 42.7% by the end of the first year after initiating treatment. Prescribing trends showed increasing use of aripiprazole and valproate over time. The high rate of antidepressant use (44.2% during follow-up) and significant treatment discontinuation highlight the complexity of real-world clinical management compared with international guideline recommendations. Conclusions These findings highlight a gap between real-world practices and guideline recommendations, underscoring need for initiatives to promote evidence-based, continuous care for bipolar disorder management in China.

Objectives Given that DLB is the second most common neurodegenerative dementia and early detection is crucial, this study sought to delineate the pre-diagnostic symptom evolution in patients from a Chinese memory clinic.Methods Prospective patients diagnosed with probable DLB (n = 47, mean age at first symptom 71 years) registered at Dementia Care and Research Center, Peking University Institute of Mental Health were included. A dementia specialist performed data collection, medical history, and examination. We used the unified data form to prospectively collect the data at examinations every 3-6 months. In addition, retrospective data were extracted from medical records to identify the evolution of symptoms before diagnosis, including the first-onset symptom(s) and the time elapsed before diagnosis.Results Most informants (n = 36, 76.6%) reported only one initial symptom. The most frequently reported initial symptom was memory decline (57.4%). Throughout the journey to a diagnosis, the most common symptom was visual hallucination (n = 29, 61.7%), followed by sleep problems and systematized delusions (both n = 20, 42.6%). Anxiety was the earliest recognizable individual psychiatric symptom of DLB, occurring an average of 73 months before diagnosis, followed by depression, memory decline (34 months before diagnosis), RBD, hallucinations and delusions, and motor symptoms of about 15 months before diagnosis. Fluctuating cognition, delirium, and impulsive aggressive behavior were documented relatively shortly before the diagnosis.Conclusions Cognitive and emotional symptoms were the most common early symptoms before a diagnosis of DLB. The findings are informative for the early detection of DLB.

Background and Hypothesis:Tardive dyskinesia (TD) is an often irreversible movement disorder, mostly resulting from exposure to dopamine receptor antagonists. The electrophysiological characteristics of TD remain poorly understood. Resting-state electroencephalography (EEG) may help characterize frequency-specific cortical oscillatory and network alterations related to TD. We hypothesized that TD-related neurophysiological alterations may be reflected in cortical spectral power, hemispheric asymmetry, and large-scale functional connectivity. Study Design:Resting-state EEG was recorded with a 32-channel system in 67 participants: 20 patients with TD, 25 patients without TD, and 22 healthy controls. Analyses focused on spectral power, hemispheric asymmetry, and functional connectivity measured using phase-lag index. Electrode-level spectral power analyses were corrected using the false discovery rate, and network-level connectivity differences were assessed using network-based statistics. Subgroup clinical association analyses within the TD group were considered exploratory. Study Results:Compared with healthy controls, both TD and Non-TD patients showed increased theta relative power at central electrodes, including C4 and Cz, with group effects surviving false discovery rate correction. Cluster-based topographic analyses showed increased gamma2-gamma3 power over frontoparietal regions in TD patients and increased broadband gamma power over frontal-central regions in Non-TD patients relative to healthy controls. Within the TD subgroup, exploratory analyses showed nominal associations between hemispheric asymmetry indices and rapid medication withdrawal or duration of motor disorder, although these associations did not survive false discovery rate correction. Functional connectivity analyses identified frequency-specific network alterations, including reduced phase-locking value in the theta frequency band and reduced phase-lag index connectivity across alpha1, beta, and gamma frequency bands in TD-related comparisons. Conclusion:TD patients showed altered resting-state cortical oscillations and frequency-specific connectivity changes involving central, frontoparietal, and temporo-occipital networks. These findings provide preliminary electrophysiological evidence for cortical network involvement in TD and may inform future mechanistic studies. Given the modest sample size and exploratory nature of subgroup analyses, the findings should be interpreted cautiously and validated in larger longitudinal cohorts.

Background:Few studies have examined differences in symptom presentation and antidepressant response between patients with major depressive disorder (MDD) with and without psychosocial triggers. Methods:This was a secondary analysis of a multicenter, multistage prospective cohort study conducted at nine top tertiary hospitals across six provinces/municipalities in China. The cohort included patients with first-episode MDD, with or without psychosocial triggers, who received one of six selective serotonin reuptake inhibitors (SSRIs). Results:Of 359 enrolled patients with first-episode MDD, 303 (mean [SD] age, 39.6 [10.1] years; 201 [66.8%] women) were included in the final analysis. There were no significant differences in network structure (M = 0.40; p = 0.97) or global strength (global strength difference [GS] = 0.483; p = 0.91) between the two groups. However, network analyses identified distinct core and influential bridge symptoms: psychic anxiety (node strength [Str] = 2.161; bridge strength [BStr] = 1.908) and somatic anxiety (Str = 2.142; BStr = 1.664) in the MDD with psychosocial triggers group, while depressed mood (Str = 3.114; BStr = 2.793) and genital symptoms (Str = 3.085; BStr = 3.085) in the group without psychosocial triggers. There were no significant differences in response rates at all visits. Median time to first response was 4.0 weeks in both groups (log-rank p = 0.23). Conclusions:While patients with MDD with and without psychosocial triggers shared broadly similar clinical profiles and SSRI responses, differences in symptom network architecture may have implications for individualized symptom monitoring and treatment strategies.

BACKGROUND:Treatment response to antipsychotic drugs in schizophrenia (SCZ) is highly variable, necessitating predictive biomarkers for personalized treatment. While neuroimaging-based predictive models (NPMs) offer promise, their reliance on correlation-based methods renders them vulnerable to confounders. A general framework is required to integrate NPMs with biologically causal information for generalizable and replicable predictions. METHODS:We propose causality-informed neuroimaging prediction (CINP), a framework that incorporates Mendelian randomization-derived causal effects as biological priors into model inference. This framework aims to transcend purely correlational approaches by establishing biologically constrained neuroimaging predictions. To test feasibility, we collected multimodal magnetic resonance imaging data from patients with SCZ across 2 independent longitudinal datasets (Peking University Sixth Hospital: n = 37; Zhumadian Psychiatric Hospital: n = 58). Antipsychotic responses were quantified using the percentage reduction in Positive and Negative Syndrome Scale (PANSS) scores from baseline to follow-up. CINP models were trained to predict individualized PANSS score reduction using neuroimaging data. Model accuracy was evaluated via internal cross-validation and generalizability by intersite cross-validation. RESULTS:CINP achieved an average threefold improvement over conventional NPMs in predicting antipsychotic treatment response. Among various neuroimaging modality configurations, the white matter tract-based CINP yielded the highest prediction accuracy (mean r = 0.652) and cross-site generalizability (mean r = 0.551). Furthermore, predictive features' weights were highly consistent across datasets (similarity = 0.397 to 0.510), indicating replicable patterns. CONCLUSIONS:Beyond feasibility and validity in predicting antipsychotic response, CINP provides a flexible computational framework for incorporating diverse causal constraints, thereby enabling robust neuroimaging-based predictions in multiple clinical contexts.

Sleep problems (SPs) frequently occur in patients with schizophrenia patients experiencing cognitive impairments. Thus, this study aimed to investigate the association between SPs and first-episode drug-naive schizophrenia (FDS), and to examine the impact of SPs on their cognitive function. In this cross-sectional study, we enrolled 291 FDS patients (non-SPs/SPs = 197/94) and 685 subjects from the general population (GP, non-SPs/SPs = 577/108) according to the DSM-IV and Pittsburgh Sleep Quality Index (PSQI) grouping. Cognition and sleep quality of subjects were assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the PSQI, respectively. Compared to GP subjects, patients with FDS had a significantly higher prevalence of SPs (15.77

Dopamine β-hydroxylase (DBH) is an enzyme that catalyzes the conversion of dopamine (DA) to norepinephrine (NE). The dysregulation of these neurotransmitters is implicated in the etiology and cognitive impairments of schizophrenia. However, the relationship between DBH and cognitive impairments of schizophrenia, independent of confounding effects of medication and chronic illness, remains unclear. Thus, this case-control study aimed to investigate plasma DBH levels, cognitive performance, and their association in patients with first-episode drug-naïve schizophrenia (FDS). A total of 56 FDS patients and 56 age- and gender-matched healthy controls (HCs) were enrolled. Cognitive function was assessed using the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), and plasma DBH levels were measured via sandwich enzyme-linked immunosorbent assays (ELISAs). After adjusting for covariates, plasma Log10DBH levels were significantly lower in FDS patients compared to HCs (F = 9.17, p = 0.003). Moreover, plasma Log10DBH levels showed a positive correlation with immediate memory score in patients (r = 0.27, p = 0.04). Linear regression further confirmed a significant association between Log10DBH levels and immediate memory score in patients (β = 50.18, t = 2.82, p = 0.008). Additionally, FDS patients scored significantly lower than HCs on the RBANS total score and all subdomains, except visuospatial/constructional score (all, p < 0.001). These findings suggest that reduced plasma DBH levels might be strongly associated with schizophrenia and might contribute to immediate memory impairment in FDS patients.

BackgroundAnti-amyloid disease-modifying therapies (DMTs) for early Alzheimer's disease (AD) are entering routine care, increasing the need for harmonized, registry-ready real-world data. The International Registry for Alzheimer's Disease and Other Dementias (InRAD) proposed a minimum dataset (MDS) and extended dataset (EDS), but their applicability to psychiatry-led old age mental healthcare practices in China is uncertain.ObjectiveTo adapt the InRAD dataset for real-world AD DMT practice across multiple psychiatry institutions in China and assess the feasibility of routine data capture for the proposed MDS/EDS.MethodsWe conducted a modified Delphi consensus study and a multicenter feasibility survey. Forty-nine experts classified domains/items into the MDS or EDS using predefined agreement thresholds. Thirty-five DMT-initiating mental healthcare teams reported the routine availability of the proposed data elements.ResultsHighly consistent with InRAD, ten domains were included in the China-adapted MDS/EDS, covering patient profiles and lifestyle, diagnostic work-up and biomarkers, treatment, outcomes, safety, treatment-monitoring examinations, and registry discontinuation. However, item prioritization reflected local practice, emphasizing diagnostic traceability, functional and neuropsychiatric outcomes, caregiver burden, and structured safety capture. Feasibility results revealed that many MDS elements were collected, but the consensus-defined MDS exceeded what is currently captured in a standardized, analysis-ready format; most EDS items were moderately feasible, while WHO-5 (patient version) and DAT-scan were least feasible.ConclusionsAn InRAD-aligned dataset is broadly acceptable for psychiatry-led AD DMT practices in China, but implementation gaps remain. A phased registry approach with standardized definitions and workflow-supported capture may improve the completeness and comparability of real-world DMT evidence.

BACKGROUND:Dementia with Lewy bodies (DLB) and Alzheimer's disease (AD) share overlapping cognitive and neuropsychiatric symptoms, complicating early differential diagnosis. This study aimed to compare multidimensional impairment patterns in AD and DLB and develop a simple, interpretable classification model based on clinical scales. METHODS:A total of 249 participants were included: 84 patients with AD, 82 with DLB, and 83 participants with normal cognition (NC). Participants completed assessments covering global cognition, six cognitive domains, neuropsychiatric and depressive symptoms. Missing values in cognitive scales were handled using multiple imputation, and results were pooled across all imputations. Then, Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine (SVM), and Random Forest (RF) were used to identify key variables. A final set of six scales was selected to build a logistic regression model distinguishing DLB from AD. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) in the entire cohort, mild stage and dementia stage. RESULTS:DLB patients showed greater deficits in attention, visuospatial processing, and neuropsychiatric symptoms; AD patients exhibited more pronounced memory impairment. At mild stage, DLB displayed more depressive symptoms and attention deficits but milder memory decline than AD. At dementia stage, DLB presented broader impairments in executive, visuospatial, attentional, with similar global cognition. The six-feature model achieved high diagnostic accuracy in the entire cohort (AUC=0.879, 95%CI: 0.802-0.957), mild stage (AUC=0.866, 95% CI: 0.788-0.943) and dementia stage (AUC=0.939, 95% CI: 0.839-0.999). CONCLUSION:The study identified distinct cognitive profiles of DLB and AD, and developed a concise, clinically practical model with robust diagnostic utility across disease stages, supporting its use in outpatient and resource-limited settings.

OBJECTIVE:This study investigated the relationships between baseline peptide antigen-related IgG levels and 8-week antipsychotic drug (APD) treatment response rates and one-year treatment outcomes, as well as the relationships between changes in peptide antigen-related IgG levels and one-year treatment outcomes, in first-episode schizophrenia (FES) patients. METHODS:Sixteen peptide antigen-related IgGs from proteins encoded by schizophrenia-related genes were selected on the basis of several selection criteria from a 2022 genome-wide association study. Novel peptide antigen-related IgG levels were measured in drug-naïve FES patients at baseline (n = 155) and in plasma samples from 60 healthy controls (HCs). At the one-year follow-up, 57 patients completed both symptom and autoantibody assessments. Statistical analyses included t tests, Pearson correlation analysis, linear regression analysis, linear mixed-effects models, and simple slope analysis. RESULTS:Anti-MOB4 IgG and anti-PDIA3 IgG levels were significantly lower in drug-naïve FES patients compared to HCs and showed a negative correlation with baseline excitement factor scores. Baseline anti-EMB IgG levels were associated with the 8-week treatment response, whereas anti-MAD1L1 IgG levels were correlated with one-year outcomes in drug-naïve FES patients. The one-year trajectory of changes in anti-FURIN IgG, anti-MAPK3 IgG, and anti-ACTR1B IgG levels was related to remission. CONCLUSION:This study revealed that patients with schizophrenia had autoimmune abnormalities, with different peptide antigen-related IgG being associated with short-term or long-term treatment efficacy, and that these antibody levels were regulated by APDs.

BACKGROUND:This study aimed to identify the risk factors for suicide attempts among Chinese patients with major depressive disorder (MDD) and explore the mediating role of suicidal ideation between childhood sexual abuse and suicide attempts. METHODS:Data were derived from a multi-center investigation conducted in nine hospitals across six provinces of China. Suicide attempt status was assessed using the suicide module of the Mini International Neuropsychiatric Interview (MINI), and childhood maltreatment was evaluated via the Childhood Trauma Questionnaire (CTQ). Multivariable logistic regression was used to identify factors associated with suicide attempts, and path analysis-based mediation models were performed to examine the mediating role of suicidal ideation in the relationship between childhood sexual abuse and suicide attempts. RESULTS:A total of 1084 MDD patients were enrolled, among whom 120 (10.1%) had a history of suicide attempts. Logistic regression analysis showed that suicidal ideation (OR = 8.73, P < 0.001) and an earlier age at depression onset (OR = 0.95, P = 0.015) were independent factors associated with suicide attempts. Mediation analysis revealed that childhood sexual abuse was significantly and positively associated with suicidal ideation (β = 0.072, P = 0.018), which in turn was strongly positively associated with suicide attempts (β = 0.267, P < 0.001). CONCLUSION:Earlier depression onset and suicidal ideation are associated with suicide attempts in Chinese MDD patients. Childhood sexual abuse is indirectly associated with suicide attempts through its positive association with suicidal ideation. This finding provides targeted insights for suicide prevention strategies for Chinese MDD patients.

Chronic stress can trigger major depressive disorder through peripheral immune factors. Enhanced circulating levels of complement component 3 (C3), a key innate immunity molecule that is predominantly produced by the liver, have been observed in depressed patients. However, the role of liver-derived C3 in the regulation of behavior under chronic stress remains ambiguous. Here, we found that liver-derived C3 critically contributes to stress susceptibility and blood-brain barrier (BBB) impairment in the nucleus accumbens (NAc) by inhibiting endothelial cell claudin-5, a pivotal tight junction protein for BBB integrity. In three mouse models of depression, hepatic C3 expression was notably increased in mice, with no comparable changes in other peripheral organs. Genetic ablation of C3 ameliorated chronic social defeat stress (CSDS)-induced increases in NAc BBB permeability and depressive-like behavior, and this amelioration was reversed upon re-expression of hepatic C3. Consistently, knockdown of hepatic C3 similarly improved these deleterious effects induced by CSDS. Furthermore, overexpression of hepatic C3 was sufficient to induce depressive-like behavior following subthreshold social stress. Hepatic C3 manipulation bidirectionally regulated expression of claudin-5 in NAc endothelial cells. Mechanistically, the liver-derived C3 suppressed claudin-5 expression in brain endothelial cells and increased stress susceptibility in mice through the C3a receptor-CCAAT/enhancer-binding protein-α signaling pathway in the NAc. Moreover, corticosterone upregulated hepatic C3 release by activation of nuclear factor-κB (NF-κB). Taken together, these results demonstrate that liver-derived C3 promotes susceptibility to depression by increasing BBB permeability under chronic stress, and propose targeting hepatic C3 as a promising therapeutic strategy for depression.

INTRODUCTIONS:Lithium remains the first-line maintenance treatment for bipolar disorder (BD), yet its safety in older-age BD (OABD) is uncertain due to limited large-scale data. OABD patients often experience more severe physical comorbidities compared to younger BD patients, but systematic evidence regarding lithium's association with these conditions is lacking. This study examined the association between lithium use and physical comorbidities across age groups using the international Global Aging and Geriatric Experiments in Bipolar Disorder (GAGE-BD) dataset. METHODS:A cross-sectional analysis was conducted using combined Wave 1 and 2 data from GAGE-BD project, encompassing 37 studies from 20 sites worldwide. Participants aged ≥ 18 years with BD were classified according to current lithium use. Physical comorbidities were harmonised into eight organ-system domains. Sociodemographic and clinical variables were compared between individuals receiving lithium treatment and those not prescribed lithium. Generalised linear mixed models adjusted for age, site and lithium × age interaction were applied to evaluate associations with physical comorbidities. RESULTS:Of the 2873 total participants included in the study, 1069 were currently receiving lithium treatment and 1804 were not prescribed lithium. Participants treated with lithium showed a lower overall prevalence of physical comorbidities compared with those not receiving lithium. Regression analyses revealed significant age-by-lithium interactions for cardiovascular (χ2 = 9.27, p = 0.002), respiratory (χ2 = 7.56, p = 0.006), genitourinary (χ2 = 8.66, p = 0.003) and endocrine (χ2 = 16.96, p < 0.001) comorbidities. Model-estimated curve crossings occurred at approximately 43 years (cardiovascular), 32 years (respiratory), 51 years (genitourinary) and 59 years (endocrine), above which predicted prevalence was lower among participants treated with lithium, whereas no differences were observed for gastrointestinal, hepatic, renal or musculoskeletal systems. CONCLUSIONS:Lithium use in OABD was associated with a lower burden of specific physical comorbidities, particularly cardiovascular, respiratory and endocrine conditions. Although prescription bias cannot be excluded, the findings challenge the perception that lithium exacerbates physical health risks in older adults. Instead, they support lithium's continued use-with appropriate monitoring-as a safe and effective treatment option for OABD, and highlight the need for prospective studies to further clarify the relationship between lithium exposure and physical health outcomes.

Background:Neurocognitive deficits are a core feature of schizophrenia. The specific impact of antipsychotics on neurocognitive function in drug-naïve first-episode schizophrenia (FES) remains unclear, especially for newer agents like blonanserin. This study compared the neurocognitive effects of blonanserin, olanzapine, aripiprazole, and risperidone during the first 6 months of treatment in FES patients. Study Design:Data were derived from two clinical trials in which FES patients received initial treatment with blonanserin, olanzapine, aripiprazole, or risperidone. Neurocognitive function was assessed at baseline and 6 months using multiple measures. Paired t-tests evaluated within-group changes, and repeated measures ANOVA examined differential effects across groups. Study Results:Of 594 recruited patients, 294 completed follow-up. All four groups showed comparable improvements in processing speed and working memory. A significant group-by-time interaction was observed for verbal (p = 0.005) and visuospatial memory (p = 0.054). Notably, blonanserin-treated patients demonstrated greater improvements in verbal learning (p = 0.005) and visuospatial memory (p = 0.045) compared to risperidone. Conclusion:Initial antipsychotic treatment in drug-naïve FES patients is associated with neurocognitive benefits, particularly in processing speed and working memory. Furthermore, blonanserin may offer advantages in ameliorating learning and memory deficits compared to risperidone.

The Disrupted-in-Schizophrenia 1 (DISC1) gene and negative symptoms in schizophrenia are both implicated in neurodevelopmental abnormalities. However, their relationship remains unclear. Thus, this study aimed to compare plasma DISC1 levels and negative symptoms severity between first-episode schizophrenia (FDS) patients and healthy controls (HCs), and examine their association. Sixty-six FDS patients meeting the DSM-IV diagnostic criteria, and 66 age- and sex-matched HCs were enrolled in this case-control study. Plasma DISC1 protein levels were measured by enzyme-linked immunosorbent assay (ELISA). Negative symptoms were assessed using the Clinical Assessment Interview for Negative Symptoms (CAINS). Compared to HCs, patients showed significantly higher CAINS scores for Motivation and Pleasure (MAP, F (1,130) = 5.24, p = 0.02), Expression (EXP, F (1, 130) = 33.89, p < 0.001), and total symptoms (F (1, 130) = 15.14, p < 0.001), alongside lower plasma DISC1 levels (F (1, 130) = 4.622, p = 0.034) after adjusting for convariates. Plasma DISC1 levels were negatively correlated with EXP score in patients (r = -0.30, p = 0.02), but not shown in HCs (r = -0.14, p = 0.26). Multiple linear regression identified lower plasma DISC1 levels as an independent predictor of higher EXP score in patients (β = -3.46, t = 2.23, p = 0.03), but not in HCs (β = 0.15, t = 0.29, p = 0.77). These findings suggest that reduced plasma DISC1 levels in FDS patients are significantly associated with greater expressive deficits, further supporting a potential role for DISC1 in the neurobiology of negative symptoms of schizophrenia.

Cognitive deficits across multiple domains are prevalent in patients with schizophrenia (PWS), and metabolic syndrome (MetS) may significantly contribute to this impairment. To clarify the complex relationships between individual MetS components and multidimensional cognitive dysfunction in PWS, we conducted a multicenter study involving 727 clinically stable patients recruited from ten psychiatric hospitals. Cognitive function was assessed using the Chinese Brief Cognitive Test (C-BCT). We employed network analysis and structural equation modeling (SEM) to explore these associations, with machine learning techniques applied for further validation. The results revealed statistically significant differences in several cognitive domains between patients with and without dyslipidemia (DL). Patients with hypertension (HT) also exhibited overall poorer cognitive performance. Network analysis indicated meaningful distinctions between patients presenting two or more MetS components (MetS-2+) and those without, showing a sparser network configuration in the MetS-2+ group. Across both groups, the Symbol Coding task demonstrated the highest strength centrality. SEM indicated that metabolic indicators, specifically DL and HT, mediated the relationship between clinical symptoms and cognitive function. Furthermore, a transformer-based machine learning model performed effectively in predicting cognitive dimensions, supporting the predictive utility of MetS components for multidimensional cognitive outcomes. In summary, specific MetS components, particularly DL and HT, show intricate associations with cognitive function in stable-phase PWS. Our findings suggest that management of HT in this population may represent a potential pathway for cognitive enhancement and improved social functioning. Trial registration: MR-11-23-007343.

BACKGROUND:Lithium has long been associated with reduced suicide risk in bipolar disorder; however, evidence from real-world clinical populations remains susceptible to confounding, and the behavioral correlates related to this association are not well characterized. METHODS:In this multicenter cross-sectional study, 616 individuals aged 12-45 years with bipolar disorder were recruited from 14 psychiatric centers, of whom 585 had complete data for the present analyses. Lithium exposure within the past year was determined from clinical records. The primary outcome was a composite of suicide-related behaviors, including suicidal ideation, suicide attempts, and non-suicidal self-injury. A pre-specified analytical framework was applied, with multivariable logistic regression as the primary analysis and propensity score matching (PSM) as the principal approach to improve covariate balance. Regression-based decomposition analyses were conducted to examine whether aggression was statistically associated with the exposure-outcome relationship, and restricted cubic spline models were used to characterize the dose-response association between aggression and suicide-related behaviors. Robustness analyses included inverse probability of treatment weighting (IPTW), alternative matching specifications, E-value analyses, cluster-robust standard errors, and exploratory age-stratified analyses. RESULTS:Lithium exposure was associated with lower odds of suicide-related behaviors in both the fully adjusted model (OR = 0.55, 95% CI: 0.34-0.89) and the propensity score-matched sample (OR = 0.53, 95% CI: 0.33-0.86). Higher aggression scores were linearly associated with increased suicide-related risk. Exploratory regression-based decomposition analyses indicated that approximately 20.93% of the observed lithium-outcome association was statistically accounted for by aggression. Results from robustness analyses were directionally consistent with the primary findings. CONCLUSIONS:In this multicenter clinical sample, lithium exposure was consistently associated with lower odds of suicide-related behaviors across multiple analytic approaches. Aggression was independently associated with suicide-related risk and statistically accounted for part of the observed association between lithium exposure and suicide-related outcomes. However, causal inference is limited by the cross-sectional design, and residual confounding-particularly confounding by indication-remains a key concern. Prospective longitudinal studies are required to clarify temporal relationships and disentangle treatment effects from selection processes.

The genetic mechanisms underlying heterogeneity in symptom presentation and antipsychotic response in schizophrenia remain unclear, limiting the development of personalized treatment. We integrated genome-wide schizophrenia polygenic risk scores (SZ-PRS) and pathway-specific PRSs (pPRSs) for four major neurotransmitter systems to examine their associations with clinical phenotypes across the course of illness. Primary analyses were conducted in 394 drug-naïve, first-episode patients from the Chinese First-Episode Schizophrenia Trial (CNFEST) to investigate associations with baseline symptom severity, neurocognitive impairment, and longitudinal treatment response. The CNFEST cohort included 52-week longitudinal assessments of symptoms and neurocognition using the Positive and Negative Syndrome Scale and a modified version of the MATRICS Consensus Cognitive Battery. An independent case-control cohort evaluated associations with schizophrenia diagnosis, while a cohort of 514 healthy adults assessed whether PRS-cognition associations are specific to schizophrenia. Higher SZ-PRS predicted schizophrenia diagnosis (OR = 2.28, Pfdr = 0.003) and poorer baseline executive function (β = -0.44, Pfdr = 0.006) and working memory (β = -0.49, Pfdr = 0.018), but these associations were absent in healthy adults. In contrast, pPRSs showed weaker associations with diagnosis and baseline cognition but were more informative for treatment outcomes: higher serotonin-pPRS predicted greater improvement in depressive symptoms (Pfdr = 0.023-0.032), and higher GABA-pPRS predicted greater improvement in overall symptoms (Pfdr = 0.038-0.043) during weeks 4-24. Exploratory drug-specific analyses further suggested that treatment response varied across antipsychotics and was differentially associated with pPRSs. These findings demonstrate that genome-wide and pathway-specific PRSs contribute distinctly to schizophrenia phenotypes, supporting their integration for personalized stratification and treatment.