Assessing the clinical diagnostic value of anti-Müllerian hormone in polycystic ovarian syndrome and its correlation with clinical and metabolism indicators.

BACKGROUND: This study investigated the association between Anti-Müllerian Hormone (AMH) and relevant metabolic parameters and assessed its predictive value in the clinical diagnosis of polycystic ovarian syndrome (PCOS). METHODS: A total of 421 women aged 20-37 years were allocated to the PCOS (n = 168) and control (n = 253) groups, and their metabolic and hormonal parameters were compared. Spearman correlation analysis was conducted to investigate associations, binary logistic regression was used to determine PCOS risk factors, and receiver operating characteristic (ROC) curves were generated to evaluate the predictive value of AMH in diagnosing PCOS. RESULTS: The PCOS group demonstrated significantly higher blood lipid, luteinizing hormone (LH), and AMH levels than the control group. Glucose and lipid metabolism and hormonal disorders in the PCOS group were more significant than in the control group among individuals with and without obesity. LH, TSTO, and AMH were identified as independent risk factors for PCOS. AMH along with LH, and antral follicle count demonstrated a high predictive value for diagnosing PCOS. CONCLUSION: AMH exhibited robust diagnostic use for identifying PCOS and could be considered a marker for screening PCOS to improve PCOS diagnostic accuracy. Attention should be paid to the effect of glucose and lipid metabolism on the hormonal and related parameters of PCOS populations.

Metabolic profiling identifies Qrich2 as a novel glutamine sensor that regulates microtubule glutamylation and mitochondrial function in mouse sperm.

In our prior investigation, we discerned loss-of-function variants within the gene encoding glutamine-rich protein 2 (QRICH2) in two consanguineous families, leading to various morphological abnormalities in sperm flagella and male infertility. The Qrich2 knockout (KO) in mice also exhibits multiple morphological abnormalities of the flagella (MMAF) phenotype with a significantly decreased sperm motility. However, how ORICH2 regulates the formation of sperm flagella remains unclear. Abnormal glutamylation levels of tubulin cause dysplastic microtubules and flagella, eventually resulting in the decline of sperm motility and male infertility. In the current study, by further analyzing the Qrich2 KO mouse sperm, we found a reduced glutamylation level and instability of tubulin in Qrich2 KO mouse sperm flagella. In addition, we found that the amino acid metabolism was dysregulated in both testes and sperm, leading to the accumulated glutamine (Gln) and reduced glutamate (Glu) concentrations, and disorderly expressed genes responsible for Gln/Glu metabolism. Interestingly, mice fed with diets devoid of Gln/Glu phenocopied the Qrich2 KO mice. Furthermore, we identified several mitochondrial marker proteins that could not be correctly localized in sperm flagella, which might be responsible for the reduced mitochondrial function contributing to the reduced sperm motility in Qrich2 KO mice. Our study reveals a crucial role of a normal Gln/Glu metabolism in maintaining the structural stability of the microtubules in sperm flagella by regulating the glutamylation levels of the tubulin and identifies Qrich2 as a possible novel Gln sensor that regulates microtubule glutamylation and mitochondrial function in mouse sperm.

Systematic analyses of the factors influencing sperm quality in patients with SARS-CoV-2 infection.

To figure out how does SARS-CoV-2 affect sperm parameters and what influencing factors affect the recovery of sperm quality after infection? We conducted a prospective cohort study and initially included 122 men with SARS-CoV-2 infection. The longest time to track semen quality after infection is 112 days and 58 eligible patients were included in our study eventually. We subsequently exploited a linear mixed-effects model to statistically analyze their semen parameters at different time points before and after SARS-CoV-2 infection. Semen parameters were significantly reduced after SARS-CoV-2 infection, including total sperm count (211 [147; 347] to 167 [65.0; 258], P < 0.001), sperm concentration (69.0 [38.8; 97.0] to 51.0 [25.5; 71.5], P < 0.001), total sperm motility (57.5 [52.3; 65.0] to 51.0 [38.5; 56.8], P < 0.001), progressive motility (50.0 [46.2; 58.0] to 45.0 [31.5; 52.8], P < 0.001). The parameters displayed the greatest diminution within 30 days after SARS-CoV-2 infection, gradually recovered thereafter, and exhibited no significant difference after 90 days compared with prior to COVID-19 infection. In addition, the patients in the group with a low-grade fever showed a declining tendency in semen parameters, but not to a significant degree, whereas those men with a moderate or high fever produced a significant drop in the same parameters. Semen parameters were significantly reduced after SARS-CoV-2 infection, and fever severity during SARS-CoV-2 infection may constitute the main influencing factor in reducing semen parameters in patients after recovery, but the effect is reversible and the semen parameters gradually return to normal with the realization of a new spermatogenic cycle.

Relationships among the gut microbiome, brain networks, and symptom severity in schizophrenia patients: A mediation analysis.

The microbiome-gut-brain axis (MGBA) plays a critical role in schizophrenia (SZ). However, the underlying mechanisms of the interactions among the gut microbiome, brain networks, and symptom severity in SZ patients remain largely unknown. Fecal samples, structural and functional magnetic resonance imaging (MRI) data, and Positive and Negative Syndrome Scale (PANSS) scores were collected from 38 SZ patients and 38 normal controls, respectively. The data of 16S rRNA gene sequencing were used to analyze the abundance of gut microbiome and the analysis of human brain networks was applied to compute the nodal properties of 90 brain regions. A total of 1,691,280 mediation models were constructed based on 261 gut bacterial, 810 nodal properties, and 4 PANSS scores in SZ patients. A strong correlation between the gut microbiome and brain networks (r = 0.89, false discovery rate (FDR) -corrected p < 0.05) was identified. Importantly, the PANSS scores were linearly correlated with both the gut microbiome (r = 0.5, FDR-corrected p < 0.05) and brain networks (r = 0.59, FDR-corrected p < 0.05). The abundance of genus Sellimonas significantly affected the PANSS negative scores of SZ patients via the betweenness centrality of white matter networks in the inferior frontal gyrus and amygdala. Moreover, 19 significant mediation models demonstrated that the nodal properties of 7 brain regions, predominately from the systems of visual, language, and control of action, showed significant mediating effects on the PANSS scores with the gut microbiome as mediators. Together, our findings indicated the tripartite relationships among the gut microbiome, brain networks, and PANSS scores and suggested their potential role in the neuropathology of SZ.

Predicting ovarian responses to the controlled ovarian hyperstimulation in elderly infertile women using clinical measurements and random forest regression.

During the past decades, the number of elderly infertile women is obviously increasing in China, and more and more of them are likely to seek medical assisted reproductive technologies. As the in vitro fertilization/embryo transfer (IVF/ET) treatment presents special medical and psychological challenges to elderly infertile women, it is extremely helpful to perform the clinical evaluation and outcome prediction regarding IVF/ET outcomes. In this study, we retrospectively collected 12 clinical measurements in prior to the oocyte recovery for 689 elderly infertile patients (≥35 years of old), and used for predicting ovarian responses to the controlled ovarian hyperstimulation based on random forest regression models. Using different predictor sets and 10-fold cross validation approach, the Mean Square Error (±standard deviation) of prediction models varied from 7.56 ± 0.31 to 13.90 ± 0.37 in the training datasets, and the correlation coefficients between observed and predicted values ranged from 0.86 ± 0.02 to 0.72 ± 0.05 in the testing datasets. Among all clinical measurements involved in this study, the preovulatory follicle count (PFC), antral follicle count (AFC), and anti-Müllerian hormone (AMH) were revealed to be the most important features in prediction models. In conclusion, we successfully established the machine learning approach that could help the elderly infertile patients to better understand the most possible outcomes in subjecting to the controlled ovarian hyperstimulation.

Systemic administration of mesenchymal stem cells loaded with a novel oncolytic adenovirus carrying a bispecific T cell engager against hepatocellular carcinoma.

We previously established a hepatocellular carcinoma (HCC) targeting system of conditionally replicative adenovirus (CRAd) delivered by human umbilical cord-derived mesenchymal stem cells (HUMSCs). However, this system needed to be developed further to enhance the antitumor effect and overcome the limitations caused by the alpha-fetoprotein (AFP) heterogeneity of HCC. In this study, a bispecific T cell engager (BiTE) targeting programmed death ligand 1 controlled by the human telomerase reverse transcriptase promoter was armed on the CRAd of the old system. It was demonstrated on orthotopic transplantation model mice that the new system had a better anti-tumor effect with no more damage to extrahepatic organs and less liver injury, and the infiltration and activation of T cells were significantly enhanced in the tumor tissues of the model mice treated with the new system. Importantly, we confirmed that the new system eliminated the AFP-negative cells on AFP heterogeneous tumor models efficiently. Conclusion: Compared with the old system, the new system provided a more effective and safer strategy against HCC.

Discovery and characterization of potent pan-variant SARS-CoV-2 neutralizing antibodies from individuals with Omicron breakthrough infection.

The SARS-CoV-2 Omicron variant evades most currently approved neutralizing antibodies (nAbs) and caused drastic decrease of plasma neutralizing activity elicited by vaccination or prior infection, urging the need for the development of pan-variant antivirals. Breakthrough infection induces a hybrid immunological response with potentially broad, potent and durable protection against variants, therefore, convalescent plasma from breakthrough infection may provide a broadened repertoire for identifying elite nAbs. We performed single-cell RNA sequencing (scRNA-seq) and BCR sequencing (scBCR-seq) of B cells from BA.1 breakthrough-infected patients who received 2 or 3 previous doses of inactivated vaccine. Elite nAbs, mainly derived from the IGHV2-5 and IGHV3-66/53 germlines, showed potent neutralizing activity across Wuhan-Hu-1, Delta, Omicron sublineages BA.1 and BA.2 at picomolar NT50 values. Cryo-EM analysis revealed diverse modes of spike recognition and guides the design of cocktail therapy. A single injection of paired antibodies cocktail provided potent protection in the K18-hACE2 transgenic female mouse model of SARS-CoV-2 infection.

Multimodal Magnetic Resonance Imaging Reveals Aberrant Brain Age Trajectory During Youth in Schizophrenia Patients.

Accelerated brain aging had been widely reported in patients with schizophrenia (SZ). However, brain aging trajectories in SZ patients have not been well-documented using three-modal magnetic resonance imaging (MRI) data. In this study, 138 schizophrenia patients and 205 normal controls aged 20-60 were included and multimodal MRI data were acquired for each individual, including structural MRI, resting state-functional MRI and diffusion tensor imaging. The brain age of each participant was estimated by features extracted from multimodal MRI data using linear multiple regression. The correlation between the brain age gap and chronological age in SZ patients was best fitted by a positive quadratic curve with a peak chronological age of 47.33 years. We used the peak to divide the subjects into a youth group and a middle age group. In the normal controls, brain age matched chronological age well for both the youth and middle age groups, but this was not the case for schizophrenia patients. More importantly, schizophrenia patients exhibited increased brain age in the youth group but not in the middle age group. In this study, we aimed to investigate brain aging trajectories in SZ patients using multimodal MRI data and revealed an aberrant brain age trajectory in young schizophrenia patients, providing new insights into the pathophysiological mechanisms of schizophrenia.

A Novel CD3/BCMA Bispecific T-cell Redirecting Antibody for the Treatment of Multiple Myeloma.

Multiple myeloma (MM) is a B-cell malignancy for which new treatments are urgently needed. Redirecting the activity of T cells by bispecific antibodies against tumor cells is a potent approach. The B-cell maturation antigen (BCMA) is a highly plasma cell-selective protein and therefore is an ideal therapeutic target for T-cell redirecting therapies. The main objective of this work is to target the BCMA by generating BCMA-specific murine monoclonal antibody and construct a cluster of differentiation 3 (CD3)/BCMA-directed tandem diabodies (Tandab). In brief, using standard hybridoma technology, we developed a novel BCMA-specific monoclonal antibody (clone 69G8), that specifically bind with BCMA+ cell lines and MM patient sample; whereas BCMA- cells were not recognized. For T cells by bispecific antibodies application, we constructed a Tandab (CD3/BCMA) simultaneously targeting both CD3 and BCMA and our studies demonstrated that Tandab (CD3/BCMA) was functional with specific binding capability both for CD3+ cells and BCMA+ cells. It induced selective, dose-dependent lysis of BCMA+ cell lines, activation of T cells, release of cytokines and T-cell proliferation; whereas BCMA- cells were not affected. Furthermore, we demonstrated that Tandab activity correlates with BCMA expression, with higher potency observed in highly BCMA expressing tumor cells. In vivo, the purified Tandab (CD3/BCMA) significantly inhibited the tumor growth in a subcutaneous NCI-H929 xenograft model. Taken together, these results show that the Tandab (CD3/BCMA) displays potent and selective anti-MM activities and represents a promising immunotherapeutic for the treatment of MM.

Effects of Brain Atlases and Machine Learning Methods on the Discrimination of Schizophrenia Patients: A Multimodal MRI Study.

Recently, machine learning techniques have been widely applied in discriminative studies of schizophrenia (SZ) patients with multimodal magnetic resonance imaging (MRI); however, the effects of brain atlases and machine learning methods remain largely unknown. In this study, we collected MRI data for 61 first-episode SZ patients (FESZ), 79 chronic SZ patients (CSZ) and 205 normal controls (NC) and calculated 4 MRI measurements, including regional gray matter volume (GMV), regional homogeneity (ReHo), amplitude of low-frequency fluctuation and degree centrality. We systematically analyzed the performance of two classifications (SZ vs NC; FESZ vs CSZ) based on the combinations of three brain atlases, five classifiers, two cross validation methods and 3 dimensionality reduction algorithms. Our results showed that the groupwise whole-brain atlas with 268 ROIs outperformed the other two brain atlases. In addition, the leave-one-out cross validation was the best cross validation method to select the best hyperparameter set, but the classification performances by different classifiers and dimensionality reduction algorithms were quite similar. Importantly, the contributions of input features to both classifications were higher with the GMV and ReHo features of brain regions in the prefrontal and temporal gyri. Furthermore, an ensemble learning method was performed to establish an integrated model, in which classification performance was improved. Taken together, these findings indicated the effects of these factors in constructing effective classifiers for psychiatric diseases and showed that the integrated model has the potential to improve the clinical diagnosis and treatment evaluation of SZ.

An integrated machine learning framework for a discriminative analysis of schizophrenia using multi-biological data.

Finding effective and objective biomarkers to inform the diagnosis of schizophrenia is of great importance yet remains challenging. Relatively little work has been conducted on multi-biological data for the diagnosis of schizophrenia. In this cross-sectional study, we extracted multiple features from three types of biological data, including gut microbiota data, blood data, and electroencephalogram data. Then, an integrated framework of machine learning consisting of five classifiers, three feature selection algorithms, and four cross validation methods was used to discriminate patients with schizophrenia from healthy controls. Our results show that the support vector machine classifier without feature selection using the input features of multi-biological data achieved the best performance, with an accuracy of 91.7% and an AUC of 96.5% (p < 0.05). These results indicate that multi-biological data showed better discriminative capacity for patients with schizophrenia than single biological data. The top 5% discriminative features selected from the optimal model include the gut microbiota features (Lactobacillus, Haemophilus, and Prevotella), the blood features (superoxide dismutase level, monocyte-lymphocyte ratio, and neutrophil count), and the electroencephalogram features (nodal local efficiency, nodal efficiency, and nodal shortest path length in the temporal and frontal-parietal brain areas). The proposed integrated framework may be helpful for understanding the pathophysiology of schizophrenia and developing biomarkers for schizophrenia using multi-biological data.

The Effects of Repetitive Transcranial Magnetic Stimulation in Patients with Chronic Schizophrenia: Insights from EEG Microstates.

The objective of this study was to investigate the effects of 10 Hz repetitive transcranial magnetic stimulation (rTMS) in patients with schizophrenia using EEG microstates. Thirty-eight patients with chronic schizophrenia were included in a double-blind, randomized and sham-controlled trial (19 participants in the active group and 19 participants in the sham group) and received 10 Hz active or sham rTMS stimulation to the left dorsolateral prefrontal cortex (left DLPFC) 5 days per week over for 4 weeks. Four classical microstate classes (i.e., classes A, B, C and D) were identified by clustering, and the parameters (i.e., duration, occurrence and contribution) of each class were computed. Our results showed that (1) after stimulation, the positive and negative syndrome scale (PANSS) positive scores decreased significantly in the active group; (2) the duration of the microstate of class C derived from EEG data decreased significantly in the active group; and (3) the change of the duration of class D in the active group was significantly higher than that in the sham group. Our findings demonstrated that 10 Hz active rTMS stimulation was beneficial to improving the positive symptoms of patients with chronic schizophrenia, and the EEG microstate could be an effective indicator of symptom improvements.

Divergent Alterations of Structural-Functional Connectivity Couplings in First-episode and Chronic Schizophrenia Patients.

Emerging evidence suggests that the coupling relating the structural connectivity (SC) of the brain to its functional connectivity (FC) exhibits remarkable changes during development, normal aging, and diseases. Although altered structural-functional connectivity couplings (SC-FC couplings) have been previously reported in schizophrenia patients, the alterations in SC-FC couplings of different illness stages of schizophrenia (SZ) remain largely unknown. In this study, we collected structural and resting-state functional MRI data from 73 normal controls (NCs), 61 first-episode (FeSZ) and 78 chronic (CSZ) schizophrenia patients. Positive and negative syndrome scale (PANSS) scores were assessed for all patients. Structural and functional brain networks were constructed using gray matter volume (GMV) and resting-state magnetic resonance imaging (rs-fMRI) time series measurements. At the connectivity level, the CSZ patients showed significantly increased SC-FC coupling strength compared with the FeSZ patients. At the node strength level, significant decreased SC-FC coupling strength was observed in the FeSZ patients compared to that of the NCs, and the coupling strength was positively correlated with negative PANSS scores. These results demonstrated divergent alterations of SC-FC couplings in FeSZ and CSZ patients. Our findings provide new insight into the neuropathological mechanisms underlying the developmental course of SZ.

Age-related decline in the expression of GDF9 and BMP15 genes in follicle fluid and granulosa cells derived from poor ovarian responders.

BACKGROUND: Growth differentiation factor 9 (GDF9) and bone morphogenetic protein 15 (BMP15) genes play important roles in folliculogenesis. Altered expression of the two have been found among patients with poor ovarian response (POR). In this prospective cohort study, we have determined the expression of the GDF9 and BMP15 genes in follicle fluid (FF) and granulosa cells (GCs) derived from poor ovarian responders grouped by age, and explored its correlation with the outcome of in vitro fertilization and embryo transfer (IVF-ET) treatment. METHODS: A total of 196 patients with POR were enrolled from a tertiary teaching hospital. The patients were diagnosed by the Bologna criteria and sub-divided into group A (< 35 year old), group B (35-40 year old), and group C (> 40 year old). A GnRH antagonist protocol was conducted for all patients, and FF and GCs were collected after oocyte retrieval. Expression of the GDF9 and BMP15 genes in the FF and GCs was determined with enzyme-linked immunosorbent assay (ELISA), quantitative real-time polymerase chain reaction (qRT-PCR) and Western blotting. RESULTS: Compared with group C, groups A and B had significantly more two pronuclei (2PN) oocytes and transplantable embryos, in addition with higher rates of implantation and clinical pregnancy (P <  0.05). The expression level of GDF9 and BMP15 genes in the FF and GCs differed significantly among the three groups (P <  0.05), showing a trend of decline along with age. The ratio of GDF9/BMP15 mRNA levels were similar among the three groups (P > 0.05). The relative levels of GDF9 and BMP15 proteins in GCs have correlated with the relative mRNA levels in GCs and protein concentrations in FF (P <  0.05). CONCLUSIONS: For poor ovarian responders, in particular those over 40, the expression of GDF9 and BMP15 is declined along with increased age and in accompany with poorer oocyte quality and IVF outcome, whilst the ratio of GDF9/BMP15 mRNA levels remained relatively constant. TRIAL REGISTRATION: Chinese Clinical Trial Registry Center ( ChiCTR1800016107 ). Registered on 11 May 2018.

NEURO-LEARN: a Solution for Collaborative Pattern Analysis of Neuroimaging Data.

The development of neuroimaging instrumentation has boosted neuroscience researches. Consequently, both the fineness and the cost of data acquisition have profoundly increased, leading to the main bottleneck of this field: limited sample size and high dimensionality of neuroimaging data. Therefore, the emphasis of ideas of data pooling and research collaboration has increased over the past decade. Collaborative analysis techniques emerge as the idea developed. In this paper, we present NEURO-LEARN, a solution for collaborative pattern analysis of neuroimaging data. Its collaboration scheme consists of four parts: projects, data, analysis, and reports. While data preparation workflows defined in projects reduce the high dimensionality of neuroimaging data by collaborative computation, pooling of derived data and sharing of pattern analysis workflows along with generated reports on the Web enlarge the sample size and ensure the reliability and reproducibility of pattern analysis. Incorporating this scheme, NEURO-LEARN provides an easy-to-use Web application that allows users from different sites to share projects and processed data, perform pattern analysis, and obtain result reports. We anticipate that this solution will help neuroscientists to enlarge sample size, conquer the curse of dimensionality and conduct reproducible studies on neuroimaging data with efficiency and validity.

Homocysteine level, body mass index and clinical correlates in Chinese Han patients with schizophrenia.

Obesity is common comorbidity in patients with schizophrenia. Previous studies have reported that homocysteine (Hcy) is increased in schizophrenia. However, no study has reported the association between BMI and Hcy levels in schizophrenia. This cross-sectional naturalistic study aimed to evaluate the relationship between BMI, Hcy and clinical symptoms in Chinese Han patients with chronic schizophrenia. Clinical and anthropometric data as well as plasma Hcy level and glycolipid parameters were collected. Psychopathology was measured with the Positive and Negative Syndrome Scale (PANSS). Our results showed that compared with the low BMI group, the high BMI group had a higher PANSS general psychopathology subscore, higher levels of blood glucose, total cholesterol and high-density lipoprotein (HDL) cholesterol (all p < 0.05). Hcy levels were negatively associated with BMI in patients (p < 0.001). Hcy level, the PANSS general psychopathology subscale, total cholesterol and education (all p < 0.05) were the influencing factors of high BMI. Our study suggest that Hcy level may be associated with BMI in patients with schizophrenia. Moreover, patients with high BMI show more severe clinical symptoms and higher glucose and lipid levels.

Growth hormone alleviates oxidative stress and improves the IVF outcomes of poor ovarian responders: a randomized controlled trial.

BACKGROUND: Oxidative stress (OS), defined as an imbalance between excessive reactive oxygen species (ROS) and/or reactive nitrogen species (RNS) production and antioxidant insufficiency, has been suggested to be involved in the pathogenesis of poor ovarian response (POR). Growth hormone (GH) can reduce OS in some cell types. This study investigated whether GH can improve OS and the in vitro fertilization and embryo transfer (IVF-ET) outcomes of poor ovarian responders. METHODS: This study enrolled 105 patients with POR and 58 patients without POR (controls) who were diagnosed according to the Bologna criteria and underwent conventional IVF-ET. Poor ovarian responders were randomly assigned to two groups: the POR-GH group, which received pretreatment with GH 4 IU/d on day 2 of the previous menstrual cycle before IVF until the trigger day, and the POR-C group, which received no pretreatment. OS markers in follicular fluid (FF), ROS levels in granulosa cells (GCs), and the IVF outcomes of the groups were compared. RESULTS: Endometrial thickness on trigger day, the number of cleaved embryos, the number of higher-quality embryos, and the rates of embryo formation, higher-quality embryo formation, implantation and clinical pregnancy were significantly increased in the POR-GH group compared with the POR-C group (P < 0.05). Moreover, compared to those in the non-POR group, FF malondialdehyde (MDA), total oxidant status (TOS), oxidative stress index (OSI) and ROS levels in GCs were significantly higher, whereas superoxide dismutase (SOD) and the total antioxidant capacity (TAC) were significantly lower in the POR-C group (P < 0.05). Furthermore, compared with those in the POR-C group, the FF TAC was significantly increased in the POR-GH group, and TOS, OSI and intracellular ROS levels were significantly reduced (P < 0.05). CONCLUSIONS: Pretreatment with GH alleviates OS and improves oocyte quality and IVF outcomes of poor ovarian responders. TRIAL REGISTRATION: Chinese Clinical Trial Registry. ChiCTR1900021269 . Registered 8 February 2019, http://www.chictr.org.cn/edit.aspx?pid=35837&htm=4 .

Altered gut microbiota associated with symptom severity in schizophrenia.

BACKGROUND: The gut microbiome and microbiome-gut-brain (MGB) axis have been receiving increasing attention for their role in the regulation of mental behavior and possible biological basis of psychiatric disorders. With the advance of next-generation sequencing technology, characterization of the gut microbiota in schizophrenia (SZ) patients can provide rich clues for the diagnosis and prevention of SZ. METHODS: In this study, we compared the differences in the fecal microbiota between 82 SZ patients and 80 demographically matched normal controls (NCs) by 16S rRNA sequencing and analyzed the correlations between altered gut microbiota and symptom severity. RESULTS: The alpha diversity showed no significant differences between the NC and SZ groups, but the beta diversity revealed significant community-level separation in microbiome composition between the two groups (pseudo-F =3.337, p < 0.001, uncorrected). At the phylum level, relatively more Actinobacteria and less Firmicutes (p < 0.05, FDR corrected) were found in the SZ group. At the genus level, the relative abundances of Collinsella, Lactobacillus, Succinivibrio, Mogibacterium, Corynebacterium, undefined Ruminococcus and undefined Eubacterium were significantly increased, whereas the abundances of Adlercreutzia, Anaerostipes, Ruminococcus and Faecalibacterium were decreased in the SZ group compared to the NC group (p < 0.05, FDR corrected). We performed PICRUSt analysis and found that several metabolic pathways differed significantly between the two groups, including the Polyketide sugar unit biosynthesis, Valine, Leucine and Isoleucine biosynthesis, Pantothenate and CoA biosynthesis, C5-Branched dibasic acid metabolism, Phenylpropanoid biosynthesis, Ascorbate and aldarate metabolism, Nucleotide metabolism and Propanoate metabolism pathways (p < 0.05, FDR corrected). Among the SZ group, the abundance of Succinivibrio was positively correlated with the total Positive and Negative Syndrome Scale (PANSS) scores (r = 0.24, p < 0.05, uncorrected) as well as the general PANSS scores (r = 0.22, p < 0.05, uncorrected); Corynebacterium was negatively related to the negative scores of PANSS (r = 0.22, p < 0.05, uncorrected). CONCLUSIONS: Our findings provided evidence of altered gut microbial composition in SZ group. In addition, we found that Succinvibrio and Corynebacterium were associated with the severity of symptoms for the first time, which may provide some new biomarkers for the diagnosis of SZ.