Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder with sex differences, possibly linked to testosterone; however, the relationship remains unclear. This study aimed to clarify the genetic correlation and polygenic overlap between ADHD and testosterone traits, identify shared genomic loci, and investigate the underlying biological mechanisms through functional annotation. Genomic data on ADHD and three testosterone traits (total testosterone [TT], bioavailable testosterone [BT], and sex hormone-binding globulin [SHBG]) were obtained from publicly accessible genome-wide association studies. Employing the MiXeR bivariate causal mixture model, we quantified the polygenic overlap between ADHD and these testosterone traits. Subsequently, we applied the conjunctional false discovery rate (conjFDR) method to identify genomic loci and performed functional annotation with the Functional Mapping and Annotation tool to aid biological interpretation. Using MiXeR, we found negative correlations between TT and ADHD, and SHBG and ADHD, but a positive correlation between BT and ADHD. Over one-third of testosterone-associated variants were predicted to affect ADHD. Using the conjFDR approach, we identified 22-51 genomic loci shared between testosterone traits and ADHD, including MCM9 and MANBA. Functional enrichment analysis highlighted the predominant involvement of these mapped genes in signal transduction pathways, synapses, cell differentiation, and neurogenesis. In conclusion, we reported a substantial polygenic overlap between ADHD and testosterone traits, identified multiple shared genomic loci implicating common biological mechanisms, and highlighted the association of glutamatergic synapses and neurogenesis with ADHD and testosterone levels.

While Western dietary patterns are increasingly linked to neuropsychiatric disorders, the causal mechanisms by which chronic high-fat diet (HFD) contributes to depression remain elusive. Here, we demonstrate that prolonged ( ≥ 10 weeks) HFD exposure in mice robustly induces depressive-like behaviors, phenocopying chronic stress models. Integrating multi-omics and targeted lipidomics, we reveal that HFD-induced behavioral deficits are underpinned by gut microbiota dysbiosis and a profound disruption of polyunsaturated fatty acid (PUFA) homeostasis. This disruption is characterized by a surge in pro-inflammatory ω-6 metabolites, particularly arachidonic acid (AA), alongside a concomitant reduction in anti-inflammatory ω-3 metabolites. These lipid perturbations strongly correlate with marked microglial activation and elevated pro-inflammatory cytokine levels (IL-6, TNF-α, CCL2) in the prefrontal cortex and hippocampus. Functionally, AA supplementation alone was sufficient to recapitulate depressive-like behaviors in vivo and, through neuron-microglia co-culture assays, directly induce pro-inflammatory microglial activation, NF-κB pathway upregulation, and subsequent synaptic impairment in vitro. Critically, therapeutic intervention with aspirin, a dual COX-1/COX-2 inhibitor, effectively reversed HFD-induced behavioral deficits. This protection was mediated by a dual mechanism: directly inhibiting microglial hyperactivation and normalizing the neuroinflammatory milieu by suppressing the biosynthesis of pro-inflammatory ω-6-derived prostanoids, including AA and 12-HETE. Collectively, our findings identify AA as a critical etiological link between HFD and neuroinflammation, establishing a mechanistic framework for "metabolic depression." The profound therapeutic efficacy of aspirin validates the AA metabolic pathway, specifically COX-1/COX-2, as a promising and targetable node for intervention, offering translational insights for the burgeoning field of nutritional psychiatry.

Cluster Validity Indices (CVIs) act as a pivotal tool in machine learning for assisting in the determination of the optimal number of clusters. Nevertheless, traditional CVIs often exhibit subpar performance when confronted with the complex characteristics prevalent in real-world data, such as inter-cluster overlap, outliers and uneven density distribution. To address this challenge, this paper proposes a multiplicative, adaptive and robust Cluster Validity Index, designated as the Robust Adaptive (RA) index. This index takes the kernel density function of sample points as the fundamental tool and reconstructs its two core components: in the measurement of intra-cluster compactness, the concept of density quantiles is incorporated, which markedly enhances its robustness against outliers; in the measurement of inter-cluster separability, a density-based Jeffrey divergence method is developed to effectively characterize inter-cluster differences in overlapping datasets. To mitigate the impact of bandwidth selection on kernel density estimation, this study adopts strategies including Scott’s and Silverman’s heuristic algorithms, thus enabling adaptive learning of the inherent distribution characteristics of data. For experimental validation, a comprehensive set of experiments was conducted on both synthetic and real-world datasets. The results show that, in comparison with the classical indices (CH, DB, SIL, I) that demonstrate prominent performance on overlapping datasets, the RA index delivers superior performance in scenarios involving mild to moderate overlap, uneven density distribution and the presence of outliers. Among nine synthetic datasets, the RA index correctly identified the optimal number of clusters in eight cases, achieving a high success rate of 88.89% and outperforming all the comparative indices. On eight real-world datasets with diverse scales, dimensionalities and inherent structural features, the RA index was also verified to be the most robust and effective metric among the five participating indices for comparison. Meanwhile, its failure on complex datasets such as S-set4 and Iris, which contain both severe inter-cluster overlap and outliers, also indicates that density-based CVIs have inherent limitations when faced with data structures characterized by high overlap and faint cluster boundaries. This finding points to a clear direction for future research: constructing novel CVIs from the perspective of sparse matrices may serve as a feasible breakthrough path to address such limitations.

The evidence on the relationship between sleep disorders and the risk of cognitive decline or dementia remains inconsistent. This systematic review and meta-analysis aimed to provide updated evidence on the association between sleep disturbances and cognitive decline. PubMed, EMBASE, and Web of Science were systematically searched from their respective inceptions to 18 February 2025. Cohort studies investigating longitudinal associations between sleep disorders and cognitive decline or dementia were included. Pooled relative risks (RRs) with 95

BACKGROUND:The association between major depressive disorder (MDD) and testosterone levels is controversial, and whether they are genetically correlated remains unclear. The present study aimed to investigate the shared genetic architecture between MDD and three testosterone traits. METHODS:We acquired genetic datasets of MDD and testosterone traits from publicly available genome-wide association studies. The bivariate causal mixture modeling (MiXeR) method was applied to estimate the polygenic overlap between MDD and testosterone, and the conjunctional false discovery rate (conjFDR) tool was used to identify shared genomic loci. RESULTS:Analysis with MiXeR suggested total testosterone (TT) and sex hormone-binding globulin (SHBG) were negative correlated with MDD, while the correlation between bioavailable testosterone (BT) and MDD was negligible. At least 47% of testosterone-related variants were predicted to influence MDD. The conjFDR identified a range of 28 to 79 genomic loci that were jointly associated with testosterone traits and MDD. Among these loci, NT5C2 was simultaneously associated with SHBG, TT and MDD. Functional annotation revealed that the mapped genes were mainly enriched in immune-related pathways. CONCLUSIONS:The present study reported extensive polygenic overlap between MDD and testosterone traits, identified multiple targets delivering shared biological mechanisms, and highlighted the role of the hypothalamic-pituitary-adrenal axis in the pathophysiological processes of MDD and testosterone regulation.

Sex hormones are involved in schizophrenia pathogenesis; however, their direction and genetic overlap remain unknown. By leveraging summary statistics from large-scale genome-wide association studies, we quantified the shared genetic architecture between schizophrenia and four sex hormone traits. Linkage disequilibrium score regression and bivariate causal mixture modeling strategies showed significant positive correlations between sex hormone-binding globulin (SHBG), total testosterone, and schizophrenia, while bioavailable testosterone and schizophrenia were negatively correlated. Estradiol showed a weak positive correlation with schizophrenia, with little polygenic overlap. The conjunctional false discovery rate method identified 303 lead single-nucleotide polymorphisms (SNPs) in jointly shared genomic loci between schizophrenia and SHBG, with 130, 52, and 9 SNPs shared between schizophrenia and total testosterone, bioavailable testosterone, and estradiol, respectively. Functional annotation suggests that mitotic sister chromatid segregation and N-glycan biosynthesis may be involved in common mechanisms underlying sex hormone regulation and schizophrenia onset. In conclusion, this study clarified the inherent relationships between schizophrenia and sex hormone traits, highlighted the roles of mitotic sister chromatid segregation and N-glycan biosynthesis in the pathogenesis of schizophrenia, and delivered potential targets for further validation.

Observational studies have demonstrated the association between the single-point measurement of oxygen saturation (SpO2) level and mortality in the general population. This study aimed to evaluate whether nocturnal SpO2 level could predict all-cause mortality in a community-based population. The study samples were obtained from the Sleep Heart Health Study, which included 2,280 men and 2,606 women (mean age, 63.8 ± 11.1 years). A pulse oximeter based on overnight in-home polysomnography was used to monitor SpO2 levels during total sleep time (SpO2-TOTAL). Multivariable Cox proportional hazards analysis was performed to examine the association between nocturnal SpO2 and all-cause mortality. During the follow-up period of 10.7 ± 3.0 years, 1,110 (22.7

Previous studies have highlighted the importance of sleep patterns for human health. This study aimed to investigate the association of sleep timing with all-cause and cardiovascular disease mortality. Participants were screened from two cohort studies: the Sleep Heart Health Study (SHHS; n = 4,824) and the Osteoporotic Fractures in Men Study (n = 2,658). Sleep timing, including bedtime and wake-up time, was obtained from sleep habit questionnaires at baseline. The sleep midpoint was defined as the halfway point between the bedtime and wake-up time. Restricted cubic splines and Cox proportional hazards regression analyses were used to examine the association between sleep timing and mortality. We observed a U-shaped association between bedtime and all-cause mortality in both the SHHS and Osteoporotic Fractures in Men Study groups. Specifically, bedtime at 11:00 pm and waking up at 7:00 am was the nadir for all-cause and cardiovascular disease mortality risks. Individuals with late bedtime (> 12:00 am) had an increased risk of all-cause mortality in SHHS (hazard ratio 1.53, 95

Sleep characteristics such as duration, continuity, and irregularity are associated with the risk of hypertension. This study aimed to investigate the association between sleep timing (including bedtime, wake-up time, and sleep midpoint) and the prevalence of hypertension. Participants were selected from the Sleep Heart Health Study (n = 5504). Bedtime and wake-up times were assessed using sleep habit questionnaires. The sleep midpoint was calculated as the halfway point between the bedtime and wake-up time. Restricted cubic splines and logistic regression analyses were performed to explore the association between sleep timing and hypertension. A significant nonlinear association was observed between bedtime (Poverall<0.001; Pnonlinear<0.001), wake-up time (Poverall=0.024; Pnonlinear=0.076), sleep midpoint (Poverall=0.002; Pnonlinear=0.005), and the prevalence of hypertension after adjusting for potential confounders. Multivariable logistic regression showed that both late (> 12:00AM and 23:01PM to 12:00AM) and early (≤ 22:00PM) bedtimes were associated with an increased risk of hypertension compared to bedtimes between 22:01PM and 23:00PM. In addition, individuals with late (> 7:00AM) and early (≤ 5:00AM) wake-up times had a higher prevalence of hypertension than those with wake-up times ranging between 5:01AM and 6:00AM. Delaying the sleep midpoint (> 3:00AM) was also associated with an increased risk of hypertension. Furthermore, no significant interaction effect was found in the subgroup analyses stratified by age, sex, or apnea-hypopnea index. Our findings identified a nonlinear association between sleep timing and hypertension. Individuals with both early and late sleep timing had a high prevalence of hypertension.

BACKGROUND:Rapid eye movement (REM) sleep and three stages of non-REM (NREM) sleep comprise the full sleep cycle. The changes in sleep have been linked to depression risk. This study aimed to explore the association between sleep architecture and depressive symptoms. METHODS:A total of 3247 participants from the Sleep Heart Health Study (SHHS) were included in this cohort study. REM and NREM sleep were monitored by in-home polysomnography at SHHS visit 1. Depressive symptoms was reported as the first occurrence between SHHS visits 1 and 2 (mean follow-up of 5.3 years). Multivariable logistic regression was used to investigate the relationship between sleep stages and depressive symptoms. RESULTS:In total, 225 cases of depressive symptoms (6.9 %) were observed between SHHS visits 1 and 2. A significant linear association between NREM Stage 1 and depressive symptoms was found after adjusting for potential covariates. Multivariable logistic regression analysis showed that percentage in NREM Stage 1 was associated with the incidence of depressive symptoms (odds ratio [OR], 1.06; 95 % confidence interval [CI], 1.02-1.10; P = 0.001), as were time in NREM Stage 1 and depressive symptoms (OR, 1.02; 95 % CI, 1.01-1.03; P = 0.001). However, no significant association with depressive symptoms was found for other sleep stage. LIMITATIONS:The specific follow-up time for depressive symptoms diagnosis was missing. CONCLUSIONS:Increased time or percentage in NREM Stage 1 was associated with a higher risk of developing depressive symptoms. The early change in sleep architecture were important for incidence of depressive symptoms and warrants constant concerns.

Background Polymorphisms of PLA2G6 are associated with elevation of serum C-reactive protein, and PLA2G6 mutations lead to neurodegeneration and Parkinson’s disease. Age-related abnormalities including hepatic fibrosis have been reported in global Pla2g6-null mice. We recently showed that myeloid-specific Pla2g6-deficient mice exhibited NASH susceptibility (BBA 2023). We therefore evaluated whether these mutants would exhibit inflammatory fibrogenesis during aging.

Artemisinin is a good antimalarial drug independently developed in China. It is highly effective and low toxic. In the process of studying the antimalarial mechanism of artemisinin drugs, we found that there was agglutination when the drugs came into contact with blood. Methods: ABO positive typing test card was used to detect the agglutination reaction of artemisinin and dihydroartemisinic with whole blood, red blood cells, hemolytic solution, hemin chloride, ferrous sulfate, ferric chloride, sodium chloride, DMSO and artemether. Results: artemisinin can agglutinate with many substances, such as red blood cells, red blood cell hemolytic solution, hemin chloride, ferrous sulfate, ferric chloride, sodium chloride and so on. The agglutination reaction in this paper is not related to antigen and antibody, but the result of the interaction between artemisinin drugs and various substances. Whole blood, red blood cells and hemolytic fluid contain biological macromolecular components. Hemin belongs to low molecular organic compounds, and the rest are simple inorganic compounds. Artemisinin drugs can interact with such a wide range of substances and agglutinate, indicating their strong effect. The mechanism is not clear. It is speculated that it is related to the “oxygen bridge” in artemisinin molecule, but the details of the action and how to agglutinate need to be studied. Interestingly, when artemether interacts with artemisinin and dihydroartemisinin, there is no agglutination, but there is a tendency of agglutination in the control, which is contrary to other results. This is a phenomenon, indicating that there is interaction, and its mechanism and significance need to be further studied. Artemisinin can interact with many substances.

BackgroundHeart Failure (HF) is the end-stage cardiovascular syndrome with poor prognosis. Proteomics holds great promise in the discovery of novel biomarkers and therapeutic targets for HF. The aim of this study is to investigate the causal effects of genetically predicted plasma proteome on HF using the Mendelian randomization (MR) approach.MethodsSummary-level data for the plasma proteome (3,301 healthy individuals) and HF (47,309 cases; 930,014 controls) were extracted from genome-wide association studies (GWASs) of European descent. MR associations were obtained using the inverse variance-weighted (IVW) method, sensitivity analyses, and multivariable MR analyses.ResultsUsing single-nucleotide polymorphisms as instrumental variables, 1-SD increase in MET level was associated with an approximately 10% decreased risk of HF (odds ratio [OR]: 0.92; 95% confidence interval [CI]: 0.89 to 0.95; p = 1.42 × 10−6), whereas increases in the levels of CD209 (OR: 1.04; 95% CI: 1.02–1.06; p = 6.67 × 10−6) and USP25 (OR: 1.06; 95% CI: 1.03–1.08; p = 7.83 × 10−6) were associated with an increased risk of HF. The causal associations were robust in sensitivity analyses, and no evidence of pleiotropy was observed.ConclusionThe study findings suggest that the hepatocyte growth factor/c-MET signaling pathway, dendritic cells-mediated immune processes, and ubiquitin-proteasome system pathway are involved in the pathogenesis of HF. Moreover, the identified proteins have potential to uncover novel therapies for cardiovascular diseases.

Different countries have differences in social and cultural context and health system, which may affect the clinical characteristics of psychiatric inpatients. This study was the first to compare cross-cultural differences in the clinical characteristics of psychiatric inpatients in three hospitals from Western China and America. Overall, 905 and 1318 patients from three hospitals, one in America and two in Western China, respectively, were included. We used a standardised protocol and data collection procedure to record inpatients’ sociodemographic and clinical characteristics. Significant differences were found between hospitals from the two countries. Positive symptoms were the main reason for admission in the Chinese hospitals, while reported suicide and self-injury symptoms more frequently led to hospital admission in America. Moreover, there were more inpatients with combined substance abuse in the American hospital (97.6% vs. 1.9%, P < 0.001). The length of stay (LOS) in America was generally shorter than in China (10.5 ± 11.9 vs. 20.7 ± 13.4, P < 0.001). The dosage of antipsychotic drugs used in the American hospital was higher than in China (275.1 ± 306.9 mg vs. 238.3 ± 212.5 mg, P = 0.002). Regression analysis showed that male sex, older age, retirees, being admitted because of physical symptoms, and using higher doses of antipsychotic drugs were significantly associated with longer hospitalisation in the American hospital (P < 0.05). Comparatively, patients who were divorced, experiencing suicidal ideation, admitted involuntarily, admitted because of physical, depression, or anxiety symptoms, and using higher doses of antipsychotic drugs had longer hospitalisation in Chinese hospitals (P < 0.05). Significant variations in clinical characteristics of inpatients were found between hospitals from Western China and America. The LOS in Chinese hospitals was significantly longer, but patients used higher doses of antipsychotic drugs in the American hospital. Admission due to physical symptoms and the use of higher dosage drugs were related to longer LOS in both countries.

Background Previous studies found an association between self‐reported sleep duration and mortality. This study aimed to compare the effects of objective and self‐reported sleep duration on all‐cause and cardiovascular disease (CVD) mortality. Methods and Results A total of 2341 men and 2686 women (aged 63.9±11.1 years) were selected from the SHHS (Sleep Heart Health Study). Objective sleep duration was acquired using in‐home polysomnography records, and self‐reported sleep duration on weekdays and weekends was based on a sleep habits questionnaire. The sleep duration was categorized as ≤4 hours, 4 to 5 hours, 5 to 6 hours, 6 to 7 hours, 7 to 8 hours, and >8 hours. Multivariable Cox regression analysis was used to investigate the association of objective and self‐reported sleep duration with all‐cause and CVD mortality. During a mean follow‐up period of 11 years, 1172 (23.3%) participants died, including 359 (7.1%) deaths from CVD. All‐cause and CVD mortality rates decreased gradually with increasing objective sleep duration. In multivariable Cox regression analysis, the greatest association for all‐cause and CVD mortality was with an objective sleep duration of 5 hours or shorter. In addition, we found a J‐shaped association of self‐reported sleep duration on both weekdays and weekends with all‐cause and CVD mortality. Self‐reported short (≤4 hours) and long (>8 hours) sleep duration on weekdays and weekends were associated with an increased risk of all‐cause and CVD mortality compared with 7 to 8 hours sleep duration. Furthermore, a weak correlation was observed between objective and self‐reported sleep duration. Conclusions This study showed that both objective and self‐reported sleep duration were associated with all‐cause and CVD mortality, but with different characteristics. Registration URL: https://clinicaltrials.gov/ct2/show/NCT00005275 ; Unique identifier: NCT00005275.

ObjectivesRapid eye movement (REM) sleep is closely related to all-cause mortality. The aim of this study is to explore the role of REM sleep on the incident heart failure (HF).MethodsWe selected 4490 participants (2480 women and 2010 men; mean age, 63.2 ± 11.0 years) from the Sleep Heart Health Study. HF was identified as the first occurrence during a mean follow-up period of 10.9 years. REM sleep including percentage of REM sleep and total REM sleep time were monitored using in-home polysomnography at baseline. Multivariable Cox regression analysis was utilized to explore the relationship between REM sleep and HF.ResultsIn total, 436 (9.7%) cases of HF were observed during the entire follow-up period. After adjusting for potential covariates, an increased percentage of REM sleep (per 5%) was independently associated with a reduced incidence of HF [hazard ratio (HR) 0.88, 95% confidence interval (CI) 0.82–0.94, P < 0.001]. A similar result was also found between total REM sleep time (increased per 5 min) and incident HF (HR 0.97, 95% CI 0.95–0.99, P < 0.001). Moreover, the fourth quartile of both percentage of REM sleep (HR 0.65, 95% CI 0.48–0.88, P = 0.005) and total REM sleep time (HR 0.64, 95% CI 0.45–0.90, P = 0.010) had lower risk of incident HF when compared with the first quartile.ConclusionAn increased percentage of REM sleep and total REM sleep time were associated with a reduced risk of HF. REM sleep may be a predictor of the incident HF.Clinical Trial Registration[ClinicalTrials.gov], identifier [NCT00005275].

Background Childhood neurodevelopmental disorders, including autism spectrum disorder (ASD), attention-deficit hyperactivity disorder (ADHD), and Tourette syndrome (TS), comprise a major cause of health-related disabilities in children. However, biomarkers towards pathogenesis or novel drug targets are still limited. Our study aims to provide a comprehensive investigation of the causal effects of the plasma proteome on ASD, ADHD, and TS using the two-sample Mendelian Randomization (MR) approach. Methods Genetic associations with 2994 plasma proteins were selected as exposures and genome-wide association data of ASD, ADHD, TS were utilized as outcomes. MR analyses were carried out using the inverse-variance weighted method, and the MR-Egger and weighted median methods were used for sensitivity analysis. Findings Using single-nucleotide polymorphisms as instruments, the study suggested increased levels of MAPKAPK3 (OR: 1.09; 95% CI: 1.05-1.13; P = 1.43 x 10-6) and MRPL33 (OR: 1.07; 95% CI: 1.04-1.11; P = 5.37 x 10-6) were causally associated with a higher risk of ASD, and increased MANBA level was associated with a lower risk of ADHD (OR: 0.91; 95% CI: 0.88-0.95; P = 8.97 x 10-6). The causal associations were robust in sensitivity analysis, leave-one-out analysis and Multivariable MR, and no pleiotropy was observed. No significant risk protein was identified for TS. Interpretation The study findings support the idea that the MAPK/ERK signaling pathway and mitochondrial dysfunction are involved in the pathogenesis of ASD, while a deficiency in beta-mannosidase might play a role in the development of ADHD Copyright (c) 2022 The Author(s). Published by Elsevier B.V.

Objectives Obesity is associated with coronary artery disease (CAD) and its risk factors in observational studies. This two-sample Mendelian randomization (MR) study investigated the effect of visceral adipose tissue (VAT) mass on coronary artery disease (CAD), myocardial infarction (MI) and heart failure (HF). Methods Genetic variants (220 SNPs, P < 5 × 10 −8 ) associated with VAT mass were obtained from a genome-wide association study (GWAS) in the UK Biobank. Genetic associations with CAD outcomes including CAD and myocardial infarction (MI) were obtained from the CARDIoGRAMplusC4D 1000 Genomes-based GWAS (including up to 60,801 cases and 123,504 controls) and data on patients with HF were obtained from the HERMES Consortium (47,309 cases and 930,014 controls). The effects of VAT mass on CAD outcomes and HF were estimated using the inverse variance weighted (IVW) method. Sensitivity analysis and multi-variable MR were used to examine the stability of the IVW results. Results Our results showed that genetically predicted higher VAT mass was associated with increased risk of CAD (odds ratio [OR] 1.57, 95% confidence interval [CI], 1.44–1.71; P = 7.62 × 10 −24 ), MI (OR 1.63, 95% CI: 1.48–1.79; P = 3.76 × 10 −24 ) and HF (OR 1.71, 95% CI: 1.60–1.83; P = 1.72 × 10 −53 ). These findings remained significant in the sensitivity analysis and multi-variable MR. Conclusion This MR study suggests that genetic determinants of VAT mass are causally associated with CAD, MI and HF.

Schizophrenia (SCZ) is associated with several immune dysfunctions, including elevated levels of pro-inflammatory cytokines. Microorganisms and their metabolites have been found to regulate the immune system, and that intestinal microbiota is significantly disturbed in schizophrenic patients. To systematically investigate aberrant gut-metabolome-immune network in schizophrenia, we performed an integrative analysis of intestinal microbiota, serum metabolome, and serum inflammatory cytokines in 63 SCZ patients and 57 healthy controls using a multi-omics strategy. Eighteen differentially abundant metabolite clusters were altered in patients displayed higher cytokine levels, with a significant increase in pro-inflammatory metabolites and a significant decrease in anti-inflammatory metabolites (such as oleic acid and linolenic acid). The bacterial co-abundance groups in the gut displayed more numerous and stronger correlations with circulating metabolites than with cytokines. By integrating these data, we identified that certain bacteria might affect inflammatory cytokines by modulating host metabolites, such as amino acids and fatty acids. A random forest model was constructed based on omics data, and seven serum metabolites significantly associated with cytokines and α-diversity of intestinal microbiota were able to accurately distinguish the cases from the controls with an area under the receiver operating characteristic curve of 0.99. Our results indicated aberrant gut-metabolome-immune network in SCZ and gut microbiota may influence immune responses by regulating host metabolic processes. These findings suggest a mechanism by which microbial-derived metabolites regulated inflammatory cytokines and insights into the diagnosis and treatment of mental disorders from the microbial-immune system in the future.