To establish disease-specific therapeutic plasma concentration ranges for quetiapine (QTP) and its active metabolite N-desalkylquetiapine (NDQ) in Chinese patients with schizophrenia, manic episode, depressive episode, and depressive episode with comorbid insomnia, and to evaluate the impact of polypharmacy on drug concentrations. Methods: A Retrospective Analysis was conducted from June 2022 to October 2025, enrolling 576 hospitalized patients: 198 with schizophrenia, 186 with manic episode, and 192 with a depressive episode. From the depressive episode group, 35 patients with severe comorbid insomnia as the primary treatment target were analyzed separately. Consequently, the core depressive episode group for efficacy analysis comprised 157 patients, while the depressive episode with comorbid insomnia subgroup (n = 35) was analyzed separately. Detailed administration regimens (dosage frequency) were recorded for all patients. Steady-state concentrations of QTP and NDQ were measured using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Significant differences in optimal QTP concentration ranges were identified across diseases: 150–550 ng/mL for schizophrenia, 180–580 ng/mL for manic episode, 120–480 ng/mL for depressive episode (consistent with both ≥ 30

White matter abnormalities are important for understanding schizophrenia and related behaviors. However, the relationship between a history of suicide attempts and alterations in white matter microstructure among individuals with schizophrenia, and its impact on neurocognition, remains unclear. This study scanned 283 individuals diagnosed with schizophrenia and 189 healthy controls. Fractional anisotropy (FA) derived from diffusion tensor imaging is used to assess white matter microstructure. Neurocognitive performance was assessed using the MATRICS Consensus Cognitive Battery. Compared to healthy controls, schizophrenia patients with a history of suicide attempts showed widespread reductions in white matter FA across multiple brain regions (FDR-corrected p < 0.05). In uncorrected analyses, patients with a history of suicide attempts showed a significant lower FA in the external capsule (EC) (p = 0.033, Cohen’s d = -0.26) compared to patients without such history; two-week suicidal ideation was also associated with lower FA in the inferior fronto-occipital fasciculus (p = 0.018, d = -0.29). After FDR correction, none remained significant (all adjusted p > 0.05). A significant interaction was observed between suicide‑attempt history and EC FA in relation to the social cognition T‑score (p for interaction = 0.022). Contrary to prior findings in mood disorders, we did not observe robust white matter microstructural alterations associated with suicide attempts in schizophrenia. EC FA was significantly associated with social cognition performance only in patients without a history of suicide attempts. Schizophrenia patients with suicide attempts show widespread FA reductions versus healthy controls. EC FA is associated with social cognition only in non‑attempters, with a significant interaction by suicide history. No FA differences between attempters and non-attempters survive FDR correction.

This study aimed to compare the impact of antipsychotic treatment (APs) alone and a combination of antipsychotics and non-invasive brain stimulation (APNIBS) on blood lipid levels in patients with schizophrenia. A retrospective study was conducted. General demographic information and clinical and laboratory data, were collected from hospitalized patients who had received at least one lipid profile test after initiating therapy at the psychiatric hospital between January 2021 and October 2023. Lipid profiles, including triglycerides (TG), total cholesterol (TC), high-density lipoprotein (HDL-C), and low-density lipoprotein (LDL-C), were measured at baseline and multiple time points during treatment. The longitudinal changes in lipid profiles within each group (from baseline to each follow-up) and the differences in these trajectories between the two groups were assessed using linear mixed-effects models. A total of 1,171 patients were included (APs group: n = 704; APNIBS group: n = 467). At baseline, mean levels of TC, HDL-C, and LDL-C were within normal ranges, whereas TG was slightly elevated in the APs group. Linear mixed-effects model analysis revealed no statistically significant differences in the longitudinal trajectories of change between the two treatment groups for any lipid parameter (TG, TC, HDL-C, and LDL-C; all between-group P > 0.05). However, within-group analyses indicated divergent patterns: TG levels exhibited a progressive increase from baseline in the APs group at all follow-ups, while showing a more variable trajectory in the APNIBS group, with a increase at the second assessment after adjustment followed by decreasing trends later. Similarly, the APNIBS group demonstrated reductions from baseline in TC and LDL-C at the third and fourth tests, whereas no such reductions were observed in the APs group. Exploratory within-group analyses revealed favorable lipid trends in the APNIBS group. However, no statistically significant between-group differences were observed in longitudinal lipid trajectories. These hypothesis-generating findings warrant further prospective investigation into the potential role of NIBS in blood lipids management in schizophrenia. Not applicable.

Background: Cardiovascular disease (CVD) is a major cause of the 15–20 year reduced life expectancy in schizophrenia patients. This study aimed to identify CVD comorbidity patterns and medication profiles using real-world data.Methods: We conducted a retrospective multicenter analysis of electronic medical records from psychiatric and general hospitals across three Chinese provinces (2012–2025), including schizophrenia patients with at least one CVD. Latent class analysis (LCA) was used to classify CVD patterns, drug co-occurrence networks to characterize medications, and multivariable logistic regression to identify influencing factors.Results: Among 10,638 patients, LCA revealed four comorbidity classes: cerebrovascular disease (28.7%), hypertension (26.9%), ischemic heart disease with peripheral vascular disease (13.2%), and heart failure with arrhythmia (31.2%). These classes differed significantly by age, sex, and ethnicity (P<0.001). Psychotropic agents dominated medication networks (core: lorazepam, quetiapine, zopiclone). Medication tendencies varied: “quetiapine+acetylsalicylic acid” in cerebrovascular group; antihypertensive-inclusive combinations in hypertension group; and sedation-balancing combinations in the other two groups. Age ≥60 years strongly predicted cerebrovascular group membership (OR=21.00). Cardiovascular drug use was highest in hypertension group (OR=2.80) but markedly lower in heart failure/arrhythmia (OR=0.40) and ischemic heart disease (OR=0.72) groups, indicating inadequate treatment.Conclusions: Four distinct CVD comorbidity patterns exist in schizophrenia. Current treatment is psychotropic-centered, with insufficient standard cardiovascular pharmacotherapy for ischemic heart disease and heart failure, highlighting the need for integrated management.

BACKGROUND AND HYPOTHESIS:Accurate prediction of treatment response is essential for optimizing therapeutic strategies in patients with schizophrenia. Compared to neuroimaging or genetic biomarkers, clinical symptom patterns have received relatively little attention as predictors of treatment outcome. This study aimed to address this gap by comprehensively analyzing early symptom trajectories to predict long-term treatment outcomes. STUDY DESIGN:A cohort of 387 inpatients with schizophrenia during acute episodes was followed for 8 weeks of standardized antipsychotic treatment. Clinical symptom severity was assessed by Positive and Negative Syndrome Scale (PANSS) at baseline, week 2, and week 8. Using network analysis and machine learning model, we evaluated symptom patterns associated with treatment outcome and the predictive value of early clinical symptom trajectories. STUDY RESULTS:(1) Effective treatment responders (ETR) and poor treatment responders (PTR) exhibited distinct clinical symptom profiles at baseline and early treatment response. (2) At week 2, ETR patients showed a denser PANSS change network compared to PTR, indicating more coordinated symptom changes. (3) Early symptom change was significantly correlated with 8-week treatment outcome. (4) Although the absence of early treatment response had limited predictive value, a machine learning model based on early %PANSS change achieved 76% balanced accuracy, with changes in the negative domain emerging as key predictors. CONCLUSIONS:These findings highlight the distinctive symptom profiles associated with different treatment outcomes and underscore the importance of early symptom patterns in predicting 8-week responses in patients with acute schizophrenia.

Schizophrenia (SZ) is characterized by immune dysregulation and abnormalities in white matter; however, the mechanistic role of microRNA-195 (miR-195) remains inadequately understood. Whole-blood transcriptome sequencing was conducted on drug-naïve patients experiencing their first episode of SZ, as well as on healthy controls (HCs), followed by in silico target prediction and in vitro functional validation. A total of 366 potential miR-195 targets were identified, which were significantly enriched in pathways related to translation initiation and cytoskeleton regulation. The eukaryotic translation initiation factor 4E (EIF4E) has been experimentally validated as a direct downstream target. In HMC3 microglial cells, miR-195-5p was observed to suppress the expression of both EIF4E and brain-derived neurotrophic factor (BDNF). Furthermore, miR-195 exhibited context-dependent immunomodulatory effects: under basal conditions, it decreased IL-8 secretion, whereas upon lipopolysaccharide (LPS) stimulation, it increased the release of IL-6 and IL-8. Clinically, peripheral EIF4E levels in patients were significantly lower compared to healthy controls and were associated with an inflammatory mononuclear cell phenotype. Although a positive trend was noted between EIF4E levels and dorsal white matter integrity, this association did not withstand rigorous multiple comparison correction. The miR-195/EIF4E axis regulates BDNF translation and exerts bidirectional control over neuroinflammation, potentially linking peripheral immune dysfunction with central white matter pathology in schizophrenia. This axis represents a promising biomarker candidate and a potential therapeutic target.

Introduction Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by memory and cognitive decline. Recent studies highlight the significant role of microRNAs (miRNAs) in regulating genes related to AD. This research aims to develop miRNA-associated gene regulatory networks as candidate AD biomarkers.Methods We recruited 85 AD patients and 74 healthy controls, conducting whole blood miRNA sequencing and applying machine learning to identify differentially expressed miRNAs, which were validated by quantitative reverse transcription polymerase chain reaction (qRT-PCR). We used bioinformatics databases to predict target genes for these miRNAs and obtained gene expression data from the Gene Expression Omnibus (GEO) database (GSE122063 and GSE18309). Using the ggplot2 package in R, we discovered the overlap between miRNA target genes and differentially expressed genes (DEGs) from the GSE datasets. Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses of the DEGs were then conducted using the Metascape database. Key hub genes were pinpointed by constructing a protein-protein interaction (PPI) network with the Retrieval of Interacting Genes (STRING) database and analyzing it with cytoHubba. Drug-gene interactions were predicted and examined using the Drug-Gene Interaction database (DGIdb) (http://www.dgidb.org/).Results qRT-PCR was used to confirm the expression of the hub genes. The results showed that four miRNAs (miR-192-5p, miR-484, miR-21-5p, and miR-24-2-5p) were downregulated, while two target RNAs (SLC32A1 and GAD1) were upregulated.Discussion This regulatory network, which is strongly linked to AD, has been initially identified as a candidate biomarker for AD. Our research provides new insights into the pathogenic mechanisms of AD, potentially improving the understanding of miRNAs' role in the disease.

BackgroundHippocampal neurogenesis shapes adaptation and improves responses to stress. Patients with schizophrenia show marked functional impairment and abnormal stress sensitivity. However, it remains unclear how structural abnormalities in specific hippocampal subregions are related to altered perceived stress and clinical symptoms in schizophrenia.MethodsWe recruited 97 first-episode patients with schizophrenia (FEPS) and 47 healthy controls (HC). Perceived stress and psychopathology were assessed using the Perceived Stress Scale (PSS) and the Positive and Negative Syndrome Scale (PANSS), respectively. Structural MRI was acquired on a 3.0-T scanner, and hippocampal subregions were segmented using validated, standardized protocols. Left and right subregional volumes were summed to obtain calculate bilateral volumes.ResultsCompared to HC, the FEPS group showed higher perceived stress, reduced fimbria volumes, and increased hippocampal tail volumes after adjustment for intracranial volume, age, sex, and education. In HC, several hippocampal subregion volumes were positively correlated with stress perception; however, these associations were absent or disrupted in FEPS. In FEPS, stress perception was positively associated with positive and anxiety/depression symptoms. Additionally, specific hippocampal subfield volume was positively associated with negative symptoms.ConclusionsFEPS was characterized by aberrant perceived stress, altered hippocampal subregional volumes, and disrupted links between stress perception and hippocampal structure. The interrelations among stress, clinical symptoms, and hippocampal subfields suggest altered psychological and neurobiological processes underlying stress regulation processes in FEPS.

OBJECTIVE:This study aimed to explore differences in clinical symptom profiles and symptom network structures of inpatients with schizophrenia among early-onset schizophrenia (EOS), typical-onset schizophrenia (TOS), and late-onset schizophrenia (LOS) patients. METHODS:Symptom severity was assessed using the Positive and Negative Syndrome Scale (PANSS) in 654 EOS, 1664 TOS, and 369 LOS inpatients with schizophrenia from an open dataset. Symptom severity comparisons were conducted among the three age of onset groups. Symptom networks were constructed, and measurements such as betweenness and closeness centrality were employed to investigate the interconnectivity between symptoms. RESULTS:EOS inpatients exhibited significantly more severe symptoms compared to TOS and LOS, primarily attributable to more severe negative symptoms and general psychopathology. Analysis of the symptom networks revealed that uncontrolled hostility emerged as a core feature across EOS, TOS, and LOS. In the EOS network, anxiety domain served as bridge symptoms, while positive and disorganized thought were strongly associated with disease manifestations. TOS inpatients exhibited a similar pattern to EOS, but TOS showed higher betweenness and lower closeness in positive and negative symptoms, indicating that these domains play a crucial role in the overall network connectivity. In LOS, positive symptoms showed high betweenness centrality, suggesting their pivotal role in network connectivity. CONCLUSIONS:These findings suggest that the symptom severity and symptoms network structure differ across different age of onset groups in schizophrenia inpatients. A deeper understanding of these network-level differences could shed light on the distinct pathogenesis mechanisms and guide the development of personalized treatment strategies for schizophrenia. HYPOTHESIS:It has been consistently observed that inpatients with early-onset schizophrenia (EOS) have poorer treatment outcomes compared to typical-onset schizophrenia patients (TOS), while those with late-onset schizophrenia (LOS) tend to have better outcomes than typical-onset inpatients. The reasons behind these phenomena remain unclear. In this work, we aim to utilize network analysis to uncover potential symptom interactions that may contribute to the different treatment outcomes observed across different ages of onset schizophrenia inpatient groups.

ABSTRACT Schizophrenia is a serious mental disorder with high disability rates, and antipsychotics, especially second‐generation ones like aripiprazole, are the cornerstone of treatment. As a novel formulation, oral soluble films (OSF) offer an alternative to tablets or capsules, improving patient compliance. This study aimed to assess the bioequivalence, pharmacokinetic (PK) properties, and safety of aripiprazole OSF and aripiprazole orally disintegrating tablets (ODT) in healthy Chinese participants. A single‐dose, randomized, open‐label, and crossover study was conducted. Participants received 10 mg of test aripiprazole OSF (Qilu Pharmaceutical) and reference aripiprazole ODT (Otsuka Pharmaceutical) under fasting and fed states. The fasting trial comprised a three‐sequence, three‐period design, while the fed trial comprised a two‐sequence, two‐period design. In the fasting trial, after single oral dosing of aripiprazole OSF (with water), aripiprazole OSF (without water), and aripiprazole ODT, Cmax were 55 ± 10 ng/mL, 54 ± 10 ng/mL, and 48 ± 13 ng/mL, respectively; the AUC0‐72h were 1857 ± 377 h·ng/mL, 1823 ± 350 h·ng/mL, and 1745 ± 405 h·ng/mL, respectively. In the fed trial, after single oral dosing of aripiprazole OSF and ODT with water, the Cmax were 43 ± 9 ng/mL and 43 ± 10 ng/mL, respectively; AUC0‐72h were 2024 ± 387 h·ng/mL and 1994 ± 426 h·ng/mL, respectively. In terms of bioequivalence evaluation, the 90% confidence intervals of the geometric mean ratio of the main PK parameters of aripiprazole OSF and ODT in the fasting and fed states were all within the acceptable equivalence range (80%–125%). Both formulations were well‐tolerated. In conclusion, aripiprazole OSF and ODT reached bioequivalence, and aripiprazole OSF demonstrates significant potential for application in the treatment of psychiatric disorders.

Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) share common genetic and environmental risk factors, with immune-inflammatory dysregulation playing a crucial role in their pathophysiology. However, further research is needed to clarify causal relationships. We conducted a Mendelian randomization (MR) study using summary statistics from large-scale genome-wide association studies (GWAS) of European ancestry as instrumental variables to assess the association between 95 circulating inflammatory proteins and the risk of SCZ, BD, and MDD. Initially, a bidirectional two-sample MR analysis was performed to clarify the direction of causality. Subsequently, multivariable MR analysis was employed to investigate whether the effects of different circulating proteins on psychiatric disorders exhibit complex overlap or interrelated effects. Finally, colocalization analysis was applied to determine whether circulating proteins share causal genetic variants with psychiatric disorders. To enhance the robustness of our findings, a series of sensitivity analyses were conducted, including tests for horizontal pleiotropy, heterogeneity, and rigorous quality control procedures. Discovery analyses were based on data from the Psychiatric Genomics Consortium (PGC), while validation was performed using data from the FinnGen biobank. Meta-analysis was used to integrate results from multiple data sources. Evidence strength was evaluated based on consistency across MR, replication, and colocalization. Forward univariable MR and meta-analysis revealed that elevated circulating C-reative protein (CRP) (OR = 0.93, Pmeta = 0.013) and fractalkine(CX3CL1) (OR = 0.92, PIVW = 0.040) significantly reduced the risk of SCZ, whereas Delta and Notch-like epidermal growth factor-related receptor (DNER) (OR = 1.07, Pmeta = 0.007) and eukaryotic translation initiation factor 4E-binding protein 1 (EIF4EBP1)(OR = 1.09, PIVW = 0.015) was associated with an increased risk of SCZ. For MDD, fibroblast growth factor 23 (FGF23) (OR = 0.97, Pmeta = 0.015) and interleukin-20 (IL20) (OR = 0.96, PIVW = 0.028) significantly reduced the risk, whereas tumor necrosis factor ligand superfamily member 12 (TNFSF12) was associated with an increased risk of MDD (OR = 1.02, Pmeta = 0.039). In BD, elevated circulating levels of C-X-C motif chemokine 5 (CXCL5) (OR = 0.95, PIVW = 0.024), TRANCE (OR = 0.95, Pmeta = 0.016), and CC motif chemokine ligand 7 (CCL7) (OR = 0.94, Pmeta = 0.023) were significantly associated with reduced risk, suggesting potential protective effects. In multivariable MR analysis, after adjusting for other inflammatory protein levels, CRP showed a significant protective effect on SCZ (OR = 0.91, PIVW = 0.008), FGF23 demonstrated a significant protective effect on MDD (OR = 0.96, PIVW = 0.038), and TNFSF12 significantly increased the risk of MDD (OR = 1.03, PIVW = 0.032). Colocalization analysis provided strong evidence for shared genetic variants between DNER and SCZ (PH4 = 0.89), with the rs35975053 locus being the most significant. This MR study suggests potential causal links between inflammatory proteins and psychiatric disorders. CRP and CX3CL1 were protective for SCZ, while DNER and EIF4EBP1 increased risk. FGF23 and IL20 were protective for MDD, whereas TNFSF12 increased risk. CXCL5, TRANCE, and CCL7 were suggestively protective for BD. The shared causal genetic variants between DNER and SCZ suggest a mechanism underlying neuropsychiatric pathogenesis. Further experimental studies are warranted to elucidate the underlying biological mechanisms and identify novel diagnostic biomarkers and therapeutic targets.

The high metabolic risk and inherent brain structural changes in patients with schizophrenia are associated with cognitive impairment; however, the underlying mechanism remains unclear. This study investigated whether cortical surface area (CSA) and cortical thickness (CT) mediate obesity-related cognitive impairment in patients with first-episode schizophrenia (FEPS). We included 160 patients with FEPS and 150 healthy controls (HCs). Cognitive function and psychiatric symptoms were assessed with the Positive and Negative Syndrome Scale (PANSS) and the Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery (MCCB). The CSA and CT of 34 grey matter regions in each hemisphere were measured using 3.0-T magnetic resonance imaging. Obesity metrics included waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), and body mass index (BMI). HCs had significantly higher CSA and CT in several brain regions than FEPS after adjusting for covariates (p < 0.05). WHR significantly correlated with Verbal Learning, Working Memory, and MCCB composite scores, while WHtR was linked to Social Cognition and MCCB composite scores (p < 0.05). Bilateral CSA mediated the associations between WHR, WHtR, and MCCB scores (p < 0.05), with stronger mediation observed for WHtR. Right inferior parietal gyrus CSA specifically mediated WHR and WHtR links to cognitive outcomes. CSA, particularly in the right inferior parietal gyrus, mediates the relationship between obesity metrics and cognitive function. WHtR may be a more reliable marker than BMI or WHR for assessing abdominal obesity’s impact on cognition, offering insights into the mechanisms of cognitive deficits in schizophrenia.

Patients with schizophrenia (SCZ) face multiple health challenges due to the complication of chronic diseases and psychiatric disorders. Among these, cardiovascular comorbidities are the leading cause of their life expectancy being 15–20 years shorter than that of the general population. Identifying comorbidity patterns and uncovering differences in immune and metabolic function are crucial steps toward improving prevention and management strategies. A retrospective cross-sectional study was conducted using electronic medical records of inpatients discharged between 2015 and 2024 from a municipal psychiatric hospital in China. The study included patients diagnosed with Schizophrenia, Schizotypal, and Delusional Disorders (SSDs) (ICD-10: F20–F29). Comorbidity patterns were identified through latent class analysis (LCA) based on the 20 most common comorbid conditions among SSD patients. To investigate differences in peripheral blood metabolic and immune function, linear regression or generalized linear models were applied to 44 laboratory test indicators collected during the acute episode. The Benjamini-Hochberg method was used for p-value correction, and the false discovery rate (FDR) was calculated, with statistical significance set at FDR < 0.05. Among 3,697 inpatients with SSDs, four distinct comorbidity clusters were identified: SSDs only (Class 1), High-Risk Metabolic Multisystem Disorders (Class 2, n = 39), Low-Risk Metabolic Multisystem Disorders (Class 3, n = 573), and Sleep Disorders (Class 4, n = 205). Compared to Class 1, Class 2 exhibited significantly elevated levels of apolipoprotein A (ApoA; β = 90.62), apolipoprotein B (ApoB; β = 0.181), mean platelet volume (MPV; β = 0.994), red cell distribution width–coefficient of variation (RDW-CV; β = 1.182), antistreptolysin O (ASO; β = 276.80), and absolute lymphocyte count (ALC; β = 0.306), along with reduced apolipoprotein AI (ApoAI; β = –0.173) and hematocrit (HCT; β = –35.13). Class 3 showed moderate increases in low-density lipoprotein cholesterol (LDL-C; β = 0.113), MPV (β = 0.267), white blood cell count (WBC; β = 0.476), and absolute neutrophil count (ANC; β = 0.272), with decreased HCT (β = –9.81). Class 4 was characterized by elevated aggregate index of systemic inflammation (AISI; β = 81.07), neutrophil-to-lymphocyte ratio (NLR; β = 0.465), and systemic inflammation response index (SIRI; β = 0.346), indicating a heightened inflammatory state. The comorbidity patterns of patients with SCZ can be distinctly classified. During the acute episode, those with comorbid metabolic disorders exhibit a higher risk of cardiovascular diseases and immune system abnormalities, while patients with comorbid sleep disorders present a pronounced systemic inflammatory state and immune dysfunction. This study provides a basis for the chronic disease management and anti-inflammatory treatment, while also offering objective biomarker insights for transdiagnostic research.

OBJECTIVE:The mechanisms underlying cognitive deficits in schizophrenia remain unclear. Accumulating evidence suggests that insulin resistance (IR) is closely related to brain structure and cognitive impairment. We aimed to determine whether IR mediates or moderates the association between cortical surface area (CSA) and cognitive function in patients with first-episode schizophrenia (PFES). METHODS:We enrolled 140 PFES and 190 age- and sex-matched healthy controls (HCs). The Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery (MCCB) and the Positive and Negative Symptom Scale were used to assess cognitive function and psychopathology, respectively. The CSA was determined using 3.0-T magnetic resonance imaging. Serum insulin and glucose levels were measured for calculating the Homeostasis Model of Assessment of IR (HOMA-IR) index. RESULTS:The MCCB composite score and subscores for the HCs were significantly higher than those for the PFES (P < 0.001). In the PFES, the CSA was significantly positively correlated with the MCCB composite score and with subscores in some domains (P < 0.05). Furthermore, in patients, HOMA-IR positively moderated the association between the left precentral CSA and two MCCB domains: Reasoning and Problem Solving, and Visual Learning. HOMA-IR also positively moderated the association between Verbal Learning and CSA in the left middle temporal gyrus and the right caudal anterior cingulate gyrus (P < 0.05). CONCLUSION:Cognitive deficits were worse in PFES than in HCs. Moreover, HOMA-IR moderated the association between cortical structure and cognitive function, which might provide clues about the mechanisms of cognitive impairment in schizophrenia.

In this study, we aimed to integrate serum cytokine and kynurenine metabolite levels to identify key biomarkers for diagnosing and predicting treatment outcomes in bipolar disorder during manic episodes (BDM). A total of 52 patients with BDM and 49 healthy controls (HCs) were recruited. Serum levels of cytokines and kynurenine metabolites were measured at baseline. Manic symptom severity was assessed using the Young Mania Rating Scale (YMRS) at baseline and after 8 weeks of treatment. Correlations between cytokines and kynurenine metabolites were analysed. Support Vector Machine (SVM) classifiers and Partial Least Squares (PLS) regression were employed to differentiate individuals with BDM from HCs and to predict treatment outcomes based on these profiles. Key findings included: (1) significant differences in kynurenine metabolites between individuals with BDM and HCs, whereas cytokine levels did not differ significantly; (2) weaker correlations between cytokines and kynurenine metabolites in individuals with BDM compared to HCs; (3) integrated models of kynurenine and cytokine systems achieved 89 % cross-validated accuracy in classifying individuals with BDM and HCs, outperforming models based on either system alone; and (4) interleukin (IL)-10, IL-8, kynurenine, IL-4, and tryptophan were key predictors of treatment outcomes, with IL-10 correlating significantly with 8-week treatment response. This study highlights the potential of integrating these systems to improve diagnostic accuracy and predict treatment outcomes in individuals with BDM, offering insights into novel therapeutic targets.

Cognitive impairment is a core characteristic of schizophrenia. Immunosenescence has been consistently implicated in the cognitive dysfunction observed in neurodegenerative diseases, but how it may relate to cognitive deficits in schizophrenia is still unclear. We explored the associations between immunosenescence and cognitive impairment in patients with schizophrenia (SCZ, n = 65) and healthy controls (HCs, n = 39). Immunosenescence markers were assessed by flow cytometry and included the percentage of naïve or memory T cell subsets labeled by CD4+/CD8+, CD45RA+(naïve)/CD45RO (memory), or CD95+(memory), as well as the intracellular levels of selected cytokines (IL-1β, IL-6, TNF-α, and IFN-γ) in T cell subsets. T1-weighted magnetic resonance imaging was performed to assess the subcortical volume and cortical thickness. Participants were evaluated using the Positive and Negative Syndrome Scale and the Chinese version of the MATRICS Consensus Cognitive Battery.The results indicated that (1) Compared with HCs, SCZ patients were characterized by fewer naïve and more memory T cell subsets, accompanied by altered intracellular cytokine levels, indicating immunosenescence phenotypes. (2) The intracellular IL-1β level in naïve CD8+CD45RA+CD95+ T cells was associated with working memory deficit in SCZ patients. (3) In a moderated mediation model, the effect of the IL-1β level on the working memory score was mediated by the thickness of the right inferior parietal lobule (IPL_R), and the volume of the right choroid plexus (CP) moderated the indirect pathway between the IL-1β level and IPL_R thickness. Our findings highlighted immunosenescence-related T cell phenotypes and the CP as potential biomarkers of cognitive deficit in SCZ.

OBJECTIVE:The study aims to examine the network structures of childhood trauma (CT) and psychotic symptoms in patients with first-episode schizophrenia (FES) and treatment-resistant schizophrenia (TRS). Specifically, it seeks to elucidate how different dimensions of CT influence symptoms across FES and TRS. METHODS:289 patients with FES and 50 patients with TRS were assessed using Positive and Negative Syndrome Scale (PANSS) and Childhood Trauma Questionnaire. Partial correlation was used to elucidate the network connections between CT and symptoms in FES and TRS patients. Betweenness, closeness coefficient, and community detection were further calculated to investigate the interactions between CT and psychotic symptoms. RESULTS:The analysis revealed three key findings: (1) Symptom-trauma networks differ between FES and TRS patients; (2) Based on network analysis, CT in TRS forms tight interlinks, as evidenced by a larger value of closeness coefficient, which influences psychotic symptoms in TRS compared to FES. Sexual abuse plays a vital role in the TRS network while emotional neglect is more important in FES; and (3) The divergent community structures suggest distinct pathways through which CT and symptoms in FES and TRS patients. Specifically, in the FES symptom-CT network, CT influences the symptoms through traditional symptom patterns, while in TRS the pathway cannot be divided by traditional divisions and it involves a complex manner. CONCLUSION:The findings suggest that the pathways linking childhood trauma experiences and clinical symptoms differ between FES and TRS patients, providing valuable insights into how early traumatic stress may contribute to symptom evolution in schizophrenia.

Stress plays a critical role in schizophrenia pathogenesis, and blunted cortisol responses to acute stress exposure among patients with schizophrenia may be related to damaged white matter (WM) fibers in specific brain regions. The present aim was to assess correlations between cortisol response patterns and changes in WM integrity in patients with schizophrenia and to determine if such changes relate to the duration of illness. This study included patients with chronic schizophrenia (PCS, n = 92), patients with first-episode schizophrenia (PFS, n = 86), and healthy controls (HC, n = 77). All participants were subjected to the Paced Auditory Serial Addition Task and the Mirror Tracing Persistence Task. Saliva samples were collected 0 min before tasks, 20 and 40 min after task completion. Cortisol levels were assessed using highly sensitive liquid chromatography and tandem mass spectrometry. We used diffusion tensor imaging (DTI) to assess WM microstructural integrity. Clinical psychopathology was assessed using the Positive and Negative Syndrome Scale. The repeated measures analysis of variance and pairwise comparisons demonstrated distinct cortisol response patterns across groups. In the HC group, cortisol levels peaked before tasks, declining rapidly thereafter. In the PFS group, cortisol levels significantly increased 20 min post-exposure, with no significant decrease observed at the final 40-minutes time point. In the PCS group, cortisol levels remained relatively high, with no significant fluctuations over time. Furthermore, WM integrity progressively deteriorated as disease duration increased. A negative correlation was observed between WM tract integrity and prolonged cortisol reactivity in the PFS group, whereas this correlation was positive in the HC group and absent in the PCS group. Changes in salivary cortisol levels did not correlate with clinical symptoms in our patients with schizophrenia. These findings suggest that stress has the potential to contribute to schizophrenia by exacerbating WM damage. Stress-induced cortisol response patterns, which vary according to disease duration, may represent a potential biomarker of schizophrenia.

Cardiovascular diseases (CVDs) are the leading cause of premature mortality in patients with schizophrenia spectrum disorders (SSDs). However, the detailed categorization of these conditions remains insufficiently explored. This study aims to identify CVDs comorbidity patterns among inpatients with SSDs and to investigate associated factors. Electronic medical records (EMRs) data from three neuropsychiatric hospitals (2015–2023) in China was conducted. Comorbidity patterns were revealed through latent class analysis (LCA), and multinomial logit analysis were utilized to evaluate the effect of factors on these patterns, calculating odds ratios (ORs) and 95% confidence intervals (CIs). Among the 2830 inpatients with SSD, four distinct comorbidity patterns were identified based on their dominant characteristics: low-risk CVDs (47.86%), primary hypertension (30.15%), heart failure (12.99%), and cardiac valve and vascular disorders (8.99%). Compared to the low-risk CVD group, male patients demonstrated a higher probability of primary hypertension (OR = 1.15) and heart failure (OR = 5.36). Significant associations were observed between comorbid CVDs and the use of typical antipsychotics, atypical antipsychotics, anxiolytics and sedatives, antidepressants, and mood stabilizers. Notably, perphenazine (OR = 22.06) and chlorpromazine hydrochloride (OR = 7.09) were strongly linked to comorbid heart failure. Among Chinese patients with SSDs, four distinct CVD comorbidity patterns were identified, with hypertension and heart failure displaying strong specificity. Variations in demographic characteristics and psychotropic medication use provide valuable insights for treatment and management.

Tryptophan, an essential precursor metabolite within the kynurenine pathway, has been implicated in the neurobiological mechanisms underlying both schizophrenia and associated suicidality. Despite this link, the lack of validated biomarkers to identify patients with dysregulated kynurenine pathway activity hinders patient stratification, thereby impeding the clinical development of pathway-targeted interventions. This study enrolled 288 individuals diagnosed with schizophrenia (36 with prior suicide attempts, 252 without) and 202 healthy controls. Saliva samples were collected to quantify concentrations of tryptophan and associated kynurenine pathway metabolites using liquid chromatography-tandem mass spectrometry (LC-MS/MS). Patients with a history of suicide attempts exhibited significantly elevated salivary tryptophan concentration (p = 0.006) and a reduced kynurenine/tryptophan ratio (p = 0.028) compared to patients without such a history. However, within the schizophrenia cohort, no differences in the level of kynurenine, kynurenic acid, quinolinic acid, the kynurenic-acid-to-kynurenine ratio, or the quinolinic-acid-to-kynurenic-acid ratio were observed between patients with and without a history of suicide attempts. The findings suggest that a history of suicide attempts is associated with alterations in salivary tryptophan concentration and the metabolic shift from tryptophan to kynurenine. These results contribute to the understanding of the potential biochemical factors involved in suicidal behavior, especially among individuals with schizophrenia. Given its non-invasive nature, monitoring salivary kynurenine metabolic shifts may serve as an early-warning biomarker for suicidal behavior. Suicide attempt history in schizophrenia associates with reduced salivary tryptophan concentration. Elevated kynurenine/tryptophan ratio links to suicide attempts in schizophrenia patients. Key kynurenine metabolites remain unchanged with suicide risk in schizophrenia patients. Adjusted for demographics and smoking; limited by non-naïve medication samples.