Association of non-essential metals with Chinese schizophrenia: A case-control study.

BACKGROUND: The potential link between environmental pollutants, including metals, and schizophrenia development remains debated. This study aimed to explore the association between plasma levels of three non-essential metals-barium (Ba), tungsten (W), and uranium (U)-and schizophrenia risk among Chinese individuals. METHOD: We recruited a total of 221 patients and 219 healthy controls. Plasma levels of three non-essential metals were measured using inductively coupled plasma mass spectrometry. We employed unconditional logistic regression and Bayesian kernel machine regression (BKMR) to explore the relationship between exposure to multiple metals and the risk of schizophrenia. RESULTS: Logistic regression analysis revealed that the highest quartile (Q4) of W had an odds ratio (OR) of 1.87 (95% CI: 1.08-3.21) compared to the lowest quartile (Q1), with a significant P-trend of 0.017. For U, the ORs (95% CI) for Q2, Q3, and Q4 were 2.06 (1.19-3.56), 1.99 (1.15-3.44), and 1.74 (1.00-3.00), respectively. BKMR analyses revealed a progressive increase in the risk of schizophrenia with increasing cumulative levels of the three metals at concentrations below 35%, with U playing a major role in this association. U showed a non-linear positive correlation with schizophrenia, particularly at the 75th percentile level. Moreover, potential interactions were observed between W and Ba, as well as between W and U. CONCLUSION: Higher plasma W and U concentrations were positively associated with the risk of schizophrenia, which was potentially related to the severity of symptoms in schizophrenic patients.

Associations of dietary, sociodemographic, and anthropometric factors with anemia among the Zhuang ethnic adults: a cross-sectional study in Guangxi Zhuang Autonomous Region, China.

BACKGROUND: After decades of rapid economic development, anemia remains a significant public health challenge globally. This study aimed to estimate the associations of sociodemographic, dietary, and body composition factors with anemia among the Zhuang in Guangxi Zhuang Autonomous Region, China. METHODS: Our study population from the baseline survey of the Guangxi ethnic minority Cohort Study of Chronic Diseases consisted of 13,465 adults (6,779 women and 6,686 men) aged 24-82 years. A validated interviewer-administered laptop-based questionnaire system was used to collect information on participants' sociodemographic, lifestyle, and dietary factors. Each participant underwent a physical examination, and hematological indices were measured. Least absolute shrinkage and selection operator (LASSO) regression was used to select the variables, and logistic regression was applied to estimate the associations of independent risk factors with anemia. RESULTS: The overall prevalences of anemia in men and women were 9.63% (95% CI: 8.94-10.36%) and 18.33% (95% CI: 17.42─19.28%), respectively. LASSO and logistic regression analyses showed that age was positively associated with anemia for both women and men. For diet in women, red meat consumption for 5-7 days/week (OR = 0.79, 95% CI: 0.65-0.98, p = 0.0290) and corn/sweet potato consumption for 5-7 days/week (OR = 0.73, 95% CI: 0.55-0.96, p = 0.0281) were negatively associated with anemia. For men, fruit consumption for 5-7 days/week (OR = 0.75, 95% CI: 0.60-0.94, p = 0.0130) and corn/sweet potato consumption for 5-7 days/week (OR = 0.66, 95% CI: 0.46-0.91, p = 0.0136) were negatively correlated with anemia. Compared with a normal body water percentage (55-65%), a body water percentage below normal (< 55%) was negatively related to anemia (OR = 0.68, 95% CI: 0.53-0.86, p = 0.0014). Conversely, a body water percentage above normal (> 65%) was positively correlated with anemia in men (OR = 1.73, 95% CI: 1.38-2.17, p < 0.0001). CONCLUSIONS: Anemia remains a moderate public health problem for premenopausal women and the elderly population in the Guangxi Zhuang minority region. The prevention of anemia at the population level requires multifaceted intervention measures according to sex and age, with a focus on dietary factors and the control of body composition.

Exosomal circCNOT6L Regulates Astrocyte Apoptotic Signals Induced by Hypoxia Exposure Through miR99a-5p/SERPINE1 and Alleviates Ischemic Stroke Injury.

Circular RNAs are involved in intervention strategies for treating ischemic stroke (IS). However, circCNOT6L (hsa_circ_0006168) has not yet been reported in IS. Thus, we aimed to explore the potential role of circCNOT6L and its molecular mechanism in IS. In this study, we first found that the expression of both exosomal circCNOT6L (P = 0.0006) and plasma circCNOT6L (P = 0.0054) was down-regulated in IS patients compared with controls. Clinically, a negative correlation was observed between the relative expression level of circCNOT6L and the National Institutes of Health Stroke Scale (NIHSS) score and infarct volume of the brain. Simultaneously, the relative expression level of circCNOT6L was negatively associated with multiple risk factors for IS, such as mean platelet volume (MPV), red cell distribution width (RDW), very low-density lipoprotein (VLDL), and serum potassium, whereas it was positively correlated with high-density lipoprotein (HDL). In vitro, circCNOT6L silencing blocked cell viability and proliferation, while it promoted cell apoptosis of astrocytes undergoing oxygen-glucose deprivation/reperfusion (OGD/R) treatment. Mechanistically, the RNA antisense purification (RAP) assay and luciferase reporter assay revealed that circCNOT6L acts as a miRNA sponge to absorb miR-99a-5p and then regulates the expression of serine proteinase inhibitor (SERPINE1). In the further rescue experiment, overexpressing SERPINE1 could rescue the cell apoptotic signals due to circCNOT6L depletion. In conclusion, CircCNOT6L attenuated the cell apoptotic signal of astrocytes via the miR99a-5p/SERPINE1 axis and then alleviated injury after hypoxia induced by ischemic stroke.

Importance of GWAS risk loci and clinical data in predicting asthma using machine-learning approaches.

INTRODUCTION: To understand the risk factors of asthma, we combined genome-wide association study (GWAS) risk loci and clinical data in predicting asthma using machine-learning approaches. METHODS: A case-control study with 123 asthmatics and 100 controls was conducted in the Zhuang population in Guangxi. GWAS risk loci were detected using polymerase chain reaction, and clinical data were collected. Machine-learning approaches were used to identify the major factors that contribute to asthma. RESULTS: A total of 14 GWAS risk loci with clinical data were analyzed on the basis of 10 times the 10-fold cross-validation for all machine-learning models. Using GWAS risk loci or clinical data, the best performances exhibited area under the curve (AUC) values of 64.3% and 71.4%, respectively. Combining GWAS risk loci and clinical data, the XGBoost established the best model with an AUC of 79.7%, indicating that the combination of genetics and clinical data can enable improved performance. We then sorted the importance of features and found the top six risk factors for predicting asthma to be rs3117098, rs7775228, family history, rs2305480, rs4833095, and body mass index. CONCLUSION: Asthma-prediction models based on GWAS risk loci and clinical data can accurately predict asthma, and thus provide insights into the disease pathogenesis.

A Potential Immune-Related miRNAs Regulatory Network and Corresponding Diagnostic Efficacy in Schizophrenia.

PURPOSE: Immune-related pathways actively participate in the progression of schizophrenia (SCZ), however, roles of immune-related miRNAs in SCZ are still unclear. METHODS: A microarray expression study was conducted to explored roles of immune-related genes in SCZ. Functional enrichment analysis by using "clusterProfiler" was used to identify molecular alterations of SCZ. Protein-protein interaction (PPI) network was constructed and helped core molecular factors identification. Based on The Cancer Genome Atlas (TCGA) database, clinical significances of hub immune-related genes in cancers were also been explored. Then, correlation analyses were used to determine immune-related miRNAs. We further validated that hsa-miR-1299 could be an effective diagnostic biomarker for SCZ via analyzing multi-cohorts' data and quantitative real-time PCR (qRT-PCR). RESULTS: A total of 455 mRNAs and 70 miRNAs that were differentially expressed between SCZ and control samples. Functional enrichment analysis based on differentially expressed genes (DEGs) hinted that immune-related pathways were significantly correlated with SCZ. Furthermore, a total of 35 immune-related genes that involved in disease onset and showed significant co-expressed relationships. Hub immune-related gene CCL4 and CCL22 are valuable in tumor diagnosis and survival prediction. Furthermore, we also identified 22 immune-related miRNAs that play important roles in this disease. An immune-related miRNAs-mRNAs regulatory network was constructed to provide miRNAs regulatory roles in SCZ. Core miRNAs expression status of hsa-miR-1299 were also validated in another cohort, which suggested its diagnostic performance for SCZ. CONCLUSIONS: Our study reports the downregulation of some miRNAs in the process of SCZ are important. Shared genomics characteristics between SCZ and cancers also provide novel insights for cancers. A significant alteration of hsa-miR-1299 expression is effective as biomarker for the diagnosis of SCZ, suggesting that this miRNA could be a specific biomarker.

Age at smoking initiation and smoking cessation influence the incidence of stroke in China: a 10-year follow-up study.

Our study aimed to explore the correlation between age at smoking initiation and smoking cessation for the risk for stroke in China. We investigated 50,174 participants from one of the urban areas of China Kadoorie Biobank (CKB) Study. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) for association between smoking and incidence of stroke were estimated using Cox regression model. During a median of 10.7 years of follow-up, 4370 total stroke cases were documented. Among men, comparing current smokers to never smokers, the HR of total stroke for current smokers was 1.279 (95% CI, 1.134-1.443) for total stroke. The HRs of total stroke were 1.344 (1.151-1.570) for those started smoking at age less than 20 years, 1.254 (1.090-1.443) for those started smoking at age 20-30 years, and 1.205 (1.012-1.435) for those started smoking at age 30 year and above, with a dose-response relation (P for trend, 0.004). Comparing former smokers to current smokers, in the low pack-year group, those stopped smoking at age less than 65 years had a 18.2% decreased risk for total stroke (0.818; 0.673-0.994). The decreased risk was not found in those stopped smoking at age 65 years and above. Similar results were observed in the high pack-year group. In conclusion, we found that current smokers had a higher stroke risk than never smokers, and the risk increased with a younger age at smoking initiation. Smoking cessation can reduce the risk for stroke, especially could benefit from cessation at a younger age.

Bioinformatics analysis based on high-throughput sequencing data to identify hub genes related to different clinical types of COVID-19.

This article aims to explore hub genes related to different clinical types of cases with COVID-19 and predict the therapeutic drugs related to severe cases. The expression profile of GSE166424 was divided into four data sets according to different clinical types of COVID-19 and then calculated the differential expression genes (DEGs). The specific genes of four clinical types of COVID-19 were obtained by Venn diagram and conducted enrichment analysis, protein-protein interaction (PPI) networks analysis, screening hub genes, and ROC curve analysis. The hub genes related to severe cases were verified in GSE171110, their RNA-specific expression tissues were obtained from the HPA database, and potential therapeutic drugs were predicted through the DGIdb database. There were 536, 266, 944, and 506 specific genes related to asymptomatic infections, mild, moderate, and severe cases, respectively. The hub genes of severe specific genes were AURKB, BRCA1, BUB1, CCNB1, CCNB2, CDC20, CDC6, KIF11, TOP2A, UBE2C, and RPL11, and also differentially expressed in GSE171110 (P < 0.05), and their AUC values were greater than 0.955. The RNA tissue specificity of AURKB, CDC6, KIF11, UBE2C, CCNB2, CDC20, TOP2A, BUB1, and CCNB1 specifically enhanced on lymphoid tissue; CCNB2, CDC20, TOP2A, and BUB1 specifically expressed on the testis. Finally, 55 drugs related to severe COVID-19 were obtained from the DGIdb database. Summary, AURKB, BRCA1, BUB1, CCNB1, CCNB2, CDC20, CDC6, KIF11, TOP2A, UBE2C, and RPL11 may be potential diagnostic biomarkers for severe COVID-19, which may affect immune and male reproductive systems. 55 drugs may be potential therapeutic drugs for severe COVID-19.

Healthy sleep pattern reduce the risk of cardiovascular disease: A 10-year prospective cohort study.

OBJECTIVE: To identify the association between quantified sleep factors and the incidence of cardiovascular disease (CVD) through a 10-year prospective cohort study. METHODS: A total of 45,919 individuals were recruited in this population-based prospective study. The healthy sleep score was constructed by four sleep measures (sleep duration, insomnia symptoms, snoring and daytime sleepiness), which were collected by questionnaire. The hazard ratio (HR) and 95% confidence intervals (CIs) were calculated by the multivariate-adjusted Cox proportional hazards model. Restricted cubic spline analysis was used to examine the dose‒response relationships between healthy sleep scores and outcomes. RESULTS: During a median follow-up of 10.73 years (interquartile range: 10.08-11.72 years), 10,523 cases of total CVD incidence, 3766 cases of CHD, and 3967 cases of stroke incidence were documented. Our results found that participants who maintained four healthy sleep measures (including no insomnia, snoring, or frequent daytime sleepiness and sleeping 7-8 h/d) had a 12% (HR: 0.88, 95% CI: 0.84-0.93) and 16% (HR: 0.84, 95% CI: 0.78-0.92) lower risk of developing CVD and CHD, respectively, but not stroke. There was a dose‒response relationship between sleep scores and the risk of cardiovascular events. With an increasing healthy sleep score, the risk of cardiovascular events decreases. Compared to those with a sleep score of 0-1, participants with a score of 4 had 27% (HR: 0.73, 95% CI: 0.67-0.79), 25% (HR: 0.75, 95% CI: 0.65-0.87), and 24% (HR: 0.76, 95% CI: 0.66-0.86) reduced risks of CVD, CHD, and stroke, respectively. CONCLUSIONS: In this large prospective cohort study, a healthy sleep pattern effectively reduced the risk of CVD, CHD, and stroke.

Effects of PM2.5 pollution and single nucleotide polymorphisms of neurotrophin signaling pathway genes acting together on schizophrenia relapse.

PURPOSE: The objective of this study was to investigate the co-effect of long-term exposure to atmospheric particulate matter PM2.5 and single nucleotide polymorphisms on schizophrenia relapse. METHODS: A total of 332 patients with schizophrenia were recruited. Genotyping of eight SNPs for five genes along the neurotrophin signaling pathway was performed by the Sequenom Massarray technology platform. Based on the data from the monitoring stations, the PM2.5 level of each patient's residence was assessed by the inverse distance weighting method using Arc GIS software. Cox regression analysis was used to determine independent risk factors. The relationship between PM2.5 levels and the risk of schizophrenia relapse was evaluated using the restricted cubic spline (RCS) method. RESULTS: In this study, a total of 191 of 332 patients with schizophrenia relapsed with hospitalization. The risk of schizophrenia relapse was 13.62 (95% CI 8.29 to 22.37) in areas with PM2.5 concentrations of 48.43 to 75.35 µg/m3. The risk of schizophrenia relapse was 5.81 (95% CI 3.58-9.42, p < 0.001) and 13.62 (95% CI 8.29-22.37, p < 0.001) in the exposure categories Q3 and Q4, respectively, compared with Q1, and non-linear relationship between cumulative PM2.5 exposure and risk of schizophrenia relapse. A greater association was observed in the YWHAB gene polymorphic locus rs6031849 genotype TG (Hazard ratio 16.62, 95% CI 5.73 to 48.24). CONCLUSIONS: PM2.5 levels, YWHAB gene polymorphism locus rs6031849, and gender jointly influenced schizophrenia relapse, with long-term exposure to high levels of PM2.5 having the greatest effect on schizophrenia relapse.

Exploring biomarkers for ischemic stroke through integrated microarray data analysis.

Stroke is the third leading cause of disability-adjusted life years worldwide, and drugs available for its treatment are limited. This study aimed to explore high-confidence candidate genes associated with ischemic stroke (IS) through bioinformatics analysis and identify potential diagnostic biomarkers and gene-drug interactions. Weighted gene coexpression network analysis (WGCNA) and differentially expressed genes (DEGs) were integrated to identify overlapping genes. Then, high-confidence candidate genes were screened by least absolute shrinkage and selection operator (LASSO) regression. Receiver operating characteristic (ROC) curves were used to evaluate the diagnostic value of high-confidence candidate genes as biomarkers for IS. The NetworkAnalyst database was used to construct the TF-gene network and miRNA-TF regulatory network of the high-confidence candidate genes. The DGIdb database was used to identified gene-drug interactions. Through the comprehensive analysis of GSE58294 and GSE16561, 10 high-confidence candidate genes were identified by LASSO regression: ARG1, LY96, ABCA1, SLC22A4, CD163, TPM2, SLC25A42, ID3, FAM102A and CD79B. FAM102A had the highest diagnostic value, and the area under curve (AUC), sensitivity and specificity values were 0.974, 0.919 and 0.936, respectively. The HPA database demonstrated that 10 high-confidence candidate genes were expressed in the brain and blood in normal humans. Finally, DGIdb database analysis identified 8 gene-drug interactions. We identified IS-related diagnostic biomarkers and gene-drug interactions that potentially provide new insights into the diagnosis and treatment of IS.

Whole Transcriptome Sequencing Identified CircRNA Profiles and the Related Networks in Schizophrenia.

Schizophrenia (SCZ) is a complex psychiatric syndrome with uncertain etiology. This study aimed to uncover the expression profiles and related regulatory networks of circular RNA (circRNA) in SCZ. Whole transcriptome sequencing was performed to assess the expression profiles of circRNAs and microRNAs (miRNAs) in the peripheral blood of three patients with SCZ and three healthy controls. Five circRNAs were validated by quantitative real-time PCR (RT-qPCR). TargetScan, RNAhybrid, and miRanda were performed to predict the target miRNAs of the top 10 dysregulated circRNAs. MiRTarBase was applied to predict the target mRNAs of miRNAs to construct circRNA-miRNA-mRNA (ceRNA) networks. CatRAPID and StarBase were used to predict the target RNA-binding proteins (RBPs) of circRNAs to construct circRNA-RBP networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were performed to predict the potential functions of the maternal genes of circRNAs and target mRNAs. In total, 450 circRNAs and 160 miRNAs were found to be significantly differentially expressed, with hsa_circ_0003999 and hsa_circ_0030042 being significantly different between patients with SCZ and healthy controls (P < 0.05). The PI3K-AKT, MAPK, and cell cycle pathways were predicted to be associated with SCZ. GO analysis showed that focal adhesion was related to SCZ. The ceRNA networks, especially hsa_circ_0006151/hsa-miR-4685-3p/ZBTB16, hsa_circ_0000008/hsa-miR-1976/ZBTB16, and the hsa_circ_0007963/hsa-miR-3127-3p/UBE2K axes have the greatest probability of being involved in the pathophysiology of SCZ. The RBP networks, FXR1, FXR2, DGCR8, XRN2, FMR1, and QKI were the RBPs associated with SCZ. In conclusion, the circRNAs, ceRNAs, and RBP network expression patterns and related pathways indicate the potential role of circRNAs in the pathogenesis and development of SCZ.

CircUSP36 attenuates ischemic stroke injury through the miR-139-3p/SMAD3/Bcl2 signal axis.

Circular RNAs (circRNAs) play important roles in a variety of physiological and pathological processes. Researches demonstrated that circRNAs provided novel strategies for the prevention and treatment of IS. However, the biological function of hsa_circ_0045932 (circUSP36) has not been revealed yet. Here, we explored the effect of circUSP36 on IS and its mechanism. In the present study, we found that circUSP36 expression was significantly decreased in the peripheral blood of IS patients and was negatively correlated with the severity, infarct volume and poor prognosis of IS. Functionally, circUSP36 silencing inhibited cellular activity and proliferation and promoted apoptosis after oxygen-glucose deprivation/reperfusion (OGD/R) treatment, while circUSP36 overexpression reversed these cellular phenotypes in vitro. Adeno-associated virus (AAV)-mediated overexpression of circUSP36 attenuates brain injury and neurological deficit and promotes motor function recovery of transient middle cerebral artery occlusion (tMCAO) mice. Subsequently, the RNA antisense purification (RAP) and luciferase reporter assay confirmed that circUSP36 acts as a sponge to adsorb miR-139-3p, and miR-139-3p could bind and inhibit SMAD3 expression. Further rescue experiments showed that both miR-139-3p overexpression and SMAD3 silencing could abolish the antiapoptotic effect of circUSP36. In summary, we reveal for the first time that circUSP36 attenuates ischemic stroke injury through the miR-139-3p/SMAD3/Bcl2 signal axis, which make circUSP36 a potential therapeutic target for IS.

Serum uric acid is not associated with major depressive disorder in European and South American populations: a meta-analysis and two-sample bidirectional Mendelian Randomization study.

OBJECTIVE: Although previous epidemiological studies have demonstrated that serum uric acid (SUA) is associated with major depressive disorder (MDD), these analyses are prone to biases. Here, we applied the Mendelian Randomization approach to determine whether SUA is causally associated with MDD. METHODS: We conducted a meta-analysis to evaluate the relationship between SUA and MDD, then applied summary data from the Global Urate Genetics Consortium and the Psychiatric Genomics Consortium to estimate their causal effect using a two-sample bidirectional Mendelian Randomization (MR) analysis. Thereafter, the causal effect was further researched using genetic risk scores (GRS) as instrumental variables (IVs). RESULTS: Results of a meta-analysis of articles comprising 6975 and 13,589 MDD patients and controls, respectively, revealed that SUA was associated with MDD (SMD = -0.690, 95% CI: -0.930 to -0.440, I2 = 97.4%, P < 0.001). In addition, the five MR methods revealed no causal relationship existed between SUA and MDD, which corroborated the results obtained via the GRS approach. CONCLUSION: This paper found little evidence that this association between SUA and MDD is casual. Genetically, there was no significant causal association between SUA and MDD.

Association of MTOR and PDGFRA gene polymorphisms with different degrees of myopia severity.

This study aims to investigate the associations of SNPs in the mammalian target of rapamycin (MTOR) and the platelet derived growth factor receptor alpha (PDGFRA) genes with different degrees of myopia severity in Han and Zhuang populations. The SNPs of MTOR (rs1057079, rs1064261, and rs2536) and PDGFRA (rs1800812, rs35597368, rs4358459, rs6554162, and rs7677751) were analyzed among 1347 patients with myopia (849 patients with high myopia and 498 patients with mild to moderate myopia) and 453 controls without myopia in Guangxi, China (collected 2016-2018). Genetic model association analysis was performed on each SNP in different myopia subgroups. The associations of rs1057079 and rs1064261 with mild to moderate myopia were observed under the dominant models (rs1057079: OR = 1.324, 95%CI: 1.005-1.744, P = 0.046; rs1064261: OR = 1.597, 95%CI: 1.099-2.319, P = 0.014). However, the association of SNP rs1057079 could not withstand multiple correction. The number of adverse genotypes in each sample was counted. Results showed that in the high myopia group, the levels of risk of myopia in patients carrying three to four and five to eight adverse genotypes were 1.734 and 2.062 times the level of risk in patients carrying two or lower genotypes, respectively. After the stratified analyses of Han and Zhuang populations, the Zhuang populations consistently had high frequencies of myopia. This study provides evidence suggesting that the MTOR and PDGFRA genes are associated with different degrees of myopia severity and have gene-gene interactions. In addition, this study discovered a new SNP of MTOR (rs1064261) that is associated with myopia. Thus, further longitudinal studies are warranted.

Application of machine learning in diagnostic value of mRNAs for bipolar disorder.

PURPOSE: Bipolar disorder (BD) is a type of severe mental illness with symptoms of mania or depression, it is necessary to find out effective diagnostic biomarkers for BD due to diagnosing BD is based on clinical interviews without objective indicators. MATERIALS AND METHODS: The mRNA expression levels of genes included PIK3R1, FYN, TP53, PRKCZ, PRKCB, and YWHAB in the peripheral blood of 43 patients with bipolar disorder and 47 healthy controls were detected. Machine learning methods included Artificial Neural Networks, Extreme Gradient Boosting, Random Forest, and Support Vector Machine were adopted to fit different gene combinations to evaluate diagnostic value for bipolar disorder. RESULTS: The combination 'PIK3R1 + FYN' in the SVM model showed the best diagnostic value, with AUC, sensitivity, and specificity values of 0.951, 0.928, and 0.937, respectively. CONCLUSIONS: The diagnostic efficiency for bipolar disorder was significantly improved by fitting PIK3R1 and FYN through the Support Vector Machine model.

Machine Learning Analysis of MicroRNA Expression Data Reveals Novel Diagnostic Biomarker for Ischemic Stroke.

OBJECTIVES: Ischemic stroke (IS) is one of the leading causes of morbidity and mortality worldwide. Circulating microRNAs have a potential as minimally invasive biomarkers for disease prediction, diagnosis, and prognosis. In this study, we sought to use different machine learning algorithms to identify an optimal model of microRNA by integrating the expression data of pre-selected microRNAs for discriminating patients with IS from controls. METHODS: The expression level of microRNAs in the peripheral blood of 50 patients with IS and 50 matched controls were assessed through real-time polymerase chain reaction (qRT-PCR). Machine learning algorithms, including artificial neural network, random forest, extreme gradient boosting, and support vector machine (SVM) were employed via R 3.6.3 software to establish diagnostic models for IS. RESULTS: The IS group had significantly increased expression levels of miR-19a (P < 0.001), miR-148a (P < 0.001), miR-320d (P = 0.003), and miR-342-3p (P < 0.001) compared with the control group. MiR-148a, miR-342-3p, miR-19a, and miR-320d yielded areas under the receiver operating characteristic curve (AUC) of 0.872, 0.844, 0.721, and 0.673, respectively, with 0.740, 0.940, 0.740, and 0.840 sensitivity and 0.920, 0.640, 0.600, and 0.440 specificity, respectively. Model miR-148a + miR-342-3p + miR-19a had the best predictive value when analyzed via SVM algorithm with AUC, sensitivity, and specificity values of 0.958, 0.937, and 0.889, respectively. CONCLUSION: The diagnostic value of the combination of miR-148a, miR-342-3p, and miR-19a through SVM algorithm has the potential to serve as a feasible approach to promote the diagnosis of IS.

The machine learning algorithm for the diagnosis of schizophrenia on the basis of gene expression in peripheral blood.

BACKGROUND: Schizophrenia (SCZ) is a highly heritable mental disorder with a substantial disease burden. Machine learning (ML) method can be used to identify individuals with SCZ on the basis of blood gene expression data with high accuracy. METHODS: This study aimed to differentiate patients with SCZ from healthy individuals by using the messenger RNA expression level in peripheral blood of 48 patients with SCZ and 50 controls via ML algorithms, namely, artificial neural networks, extreme gradient boosting, support vector machine (SVM), decision tree, and random forest. The expression of six mRNAs was detected using quantitative real-time polymerase chain reaction (qRT-PCR). RESULTS: The relative expression levels of GNAI1 (P < 0.001), PRKCA (P < 0.001), and PRKCB (P = 0.021) increased in the SCZ group, whereas those of FYN (P < 0.001), LYN (P = 0.022), and YWHAZ (P < 0.001) decreased in the SCZ group. We generated models with various combinations of genes based on five ML algorithms. The SVM model with six factors (GNAI1, FYN, PRKCA, YWHAZ, PRKCB, and LYN genes) was the best model for distinguishing patients with SCZ from healthy individuals (AUC = 0.993, sensitivity = 1.000, specificity = 0.895, and Youden index = 0.895). CONCLUSIONS: This study suggested that the combination of genes using the ML method is better than the use of a single gene to discriminate patients with SCZ from healthy individuals. The combination of GNAI1, FYN, PRKCA, YWHAZ, PRKCB, and LYN under the SVM model can be used as a diagnostic biomarker for SCZ.

LncRNA SNHG7 Functions as an Oncogene in Cervical Cancer by Sponging miR-485-5p to Modulate JUND Expression.

BACKGROUND: Long non-coding RNA (LncRNA) SNHG7 is involved in the development of multiple cancers. However, its role in cervical cancer (CC) has not been elucidated. This study aimed to explore the function of SNHG7 in CC progression and the underlying mechanisms. MATERIALS AND METHODS: The expression levels of SNHG7 and miR-485-5p in CC tissues and cell lines were measured by qPCR. Functional experiments including CCK-8 assay, wound healing assay, transwell assay, flow cytometry, Western blot, luciferases reporter assay and immunoprecipitation (RIP) were performed to explore the SNHG7/miR-485-5p/JUND pathway. Additionally, in vivo study was carried out by establishing tumor xenograft models. RESULTS: We found that SNHG7 was markedly enhanced in CC tissues and cell lines, and associated with poor clinical characteristics. In vitro, knockdown of SNHG7 inhibited CC cell proliferation, migration and invasion, as well as aggravated cell apoptosis. As to mechanism investigation, rescue experiments revealed that miR-485-5p inhibitor could partially reverse the effects on CC cells induced by SNHG7 knockdown. SNHG7 upregulated JUND expression via miR-485-5p. Moreover, tumor xenograft models were established to confirm the findings in vivo. CONCLUSION: SNHG7 promoted CC progression through miR-485-5p/JUND axis. The SNHG7/miR-485-5p/JUND pathway might provide a novel therapeutic target for CC treatment.

Phosphoinositide-3-kinase regulatory subunit 1 gene polymorphisms are associated with schizophrenia and bipolar disorder in the Han Chinese population.

Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric disorders that share many genetic risk factors. This study aimed to investigate the association of phosphoinositide-3-kinase regulatory subunit1 (PIK3R1) gene rs3756668 and rs3730089 polymorphisms with SCZ and BD risks and determine the expression levels of PIK3R1. A total of 548 SCZ cases, 512 BD cases, and 598 healthy controls were included in this study. Single nucleotide polymorphisms (SNPs) were genotyped using the Sequenom MassARRAY platform, and quantitative reverse transcription polymerase chain reaction was conducted to examine the mRNA expression of PIK3R1. The genotypic distribution of rs3756668 in the BD group was significantly different from that in the healthy controls (P = 0.038). After adjustment for gender and age was made, rs3730089 was significantly associated with the risk of SCZ [AA/(AG + GG): OR = 2.25, Padj = 0.040; AA/GG: OR = 2.27, Padj = 0.038]. The SNP rs3756668 was associated with the susceptibility of BD (AA+GG/AG: OR = 0.73, P = 0.011) and the association remained after adjusting for gender and age. The mRNA level of PIK3R1 was significantly upregulated in patients with BD compared with that in the control group (P < 0.001). In terms of the diagnostic value of PIK3R1 for BD, the receiver operating characteristic curve analysis showed an area under the curve of 0.809 with 74.0% sensitivity and 73.9% specificity. PIK3R1 may be the shared susceptibility gene of SCZ and BD and may be a potential diagnostic biomarker for BD.

CXCR7, a Prognostic Biomarker in Cervical Squamous Cell Carcinoma, May Be a Screening Index for Treatment Options at Stages IB1 and IIA1.

PURPOSE: Recent studies indicate that CXC chemokine receptor type 7 (CXCR7) is associated with tumorigenesis, progression, and metastasis of various cancers, but its roles and molecular mechanisms of action in cervical squamous cell carcinoma (CSCC) remain unclear. Our purpose was to explore the expression patterns of CXCR7 and epidermal growth factor receptor (EGFR) in CSCC and to identify possible correlations with clinical characteristics. We also tested whether CXCR7 can be a screening index for treatment options for CSCC stages IB1 and IIA1. METHODS: Expression of CXCR7 and EGFR in tumors from 165 patients with CSCC was evaluated by immunohistochemistry and compared with the clinical data including survival. RESULTS: Patients at CSCC stages IB1 and IIA1 received different treatment options, including radical hysterectomy, pelvic lymph node dissection, and para-aortic lymph node sampling (RH group, 67 patients) or pelvic external-beam radiation therapy with brachytherapy (EBRT group, 34 patients). Disease-free survival (DFS) and overall survival (OS) were compared between two groups at different CXCR7 expression levels. Immunohistochemical staining showed that CXCR7, EGFR, phospho-ERK, and phospho-AKT amounts increased from normal cervical epithelia and cervical intraepithelial neoplasia to CSCC, and CXCR7 was associated with the disease stage, lymph node metastasis, tumor size ≥40 mm, and EGFR expression. Kaplan-Meier analysis revealed that CXCR7 and EGFR expression was associated with shorter DFS and OS. Multivariate analysis suggested that CXCR7 was independently associated with DFS and OS. Prevalence of recurrence and distant metastasis was significantly lower in the EBRT group than in the RH group during CXCR7 expression. Besides, CXCR7 knockdown significantly decreased the proliferation and invasion of CSCC cells. CONCLUSION: CXCR7 is coexpressed with EGFR, which may be involved in ERK or AKT pathway activation. CXCR7 may be a screening index for treatment options at CSCC stages IB1 and IIA1.