Peripheral Blood Non-Coding RNA as Biomarker for Schizophrenia: A Review.

Schizophrenia (SCZ) is a complex and heterogeneous neuropsychiatric disorder that lacks objective diagnostic indicators and the pathogenesis remain unclear. Genetic factors may exert a significant impact on the development of the condition. While obtaining brain tissue for biopsy in the course of adjuvant diagnosis of SCZ patients may not be possible, the collection of peripheral blood is more accessible and easier to implement. In recent years, the development and application of RNA sequencing technology has made seeking biomarkers of SCZ becomes more feasible. There is emerging evidence suggesting that certain non-coding RNAs (ncRNA) are distinctly different in the peripheral blood of SCZ patients and healthy controls. Although the mechanisms remain unclear, these aberrantly expressed ncRNAs may be intimately associated with the onset and development of SCZ and may be of great significance for the diagnosis and treatment of SCZ. Therefore, we reviewed the expression of distinct types of ncRNAs that have been found in the peripheral blood of SCZ patients and explored their potential application as diagnostic biomarkers of SCZ. Differentially expressed ncRNAs in the peripheral blood of SCZ patients could not only serve as potential diagnostic biomarkers and therapeutic targets for SCZ but may also have implications for advancing understanding of the molecular mechanisms underlying the development of SCZ and elucidating the complex etiology of SCZ. Early diagnostic biomarkers obtained directly from peripheral blood are of great significance for the timely diagnosis and treatment of SCZ. Our review will enhance the comprehension of molecular mechanisms of SCZ and contribute to the identification of promising ncRNAs in peripheral blood for both diagnosis and therapy of SCZ.

Causal association of gastroesophageal reflux disease with chronic sinusitis and chronic disease of the tonsils and adenoids.

BACKGROUND: Exploring bidirectional causal associations between gastroesophageal reflux disease (GERD) and chronic disease of the tonsils and adenoids and chronic sinusitis, respectively. METHODS: We first conducted a TSMR (two-sample mendelian randomization) study using the results of the inverse variance weighting method as the primary basis and bidirectional MR to rule out reverse causation. Subsequently, MVMR (multivariate MR) analysis was performed to identify phenotypes associated with SNPs and to explore the independent effect of GERD on two outcomes. Finally, we calculated MR-Egger intercepts to assess horizontal polytropy and Cochran's Q statistic to assess heterogeneity and ensure the robustness of the study. RESULTS: For each standard deviation increase in genetically predicted GERD rate, there was an increased risk of chronic disease of the tonsils and adenoids (OR 1.162, 95% CI 1.036-1.304, P: 1.06E-02) and of developing chronic sinusitis (OR 1.365, 95% CI 1.185-1.572, P: 1.52E-05), and there was no reverse causality. Causality for TSMR was obtained on the basis of IVW (inverse variance weighting) and appeared to be reliable in almost all sensitivity analyses, whereas body mass index may be a potential mediator of causality between GERD and chronic sinusitis. CONCLUSION: There is a causal association between GERD and chronic disease of the tonsils and adenoids and chronic sinusitis, respectively, and the occurrence of GERD increases the risk of developing chronic disease of the tonsils and adenoids and chronic sinusitis.

Association of dietary inflammatory index and leukocyte telomere length with mild cognitive impairment in Chinese older adults.

BACKGROUND: There are minimal data on the relationship between DII and MCI in an elderly Chinese population and no research has assessed the potential effect of LTL. OBJECTIVE: We investigated the association between DII and MCI while taking into account the potential effect of LTL. METHODS: This cross-sectional study included 3,386 participants aged ≥ 60 years of age from the Tianjin Elderly Nutrition and Cognition Cohort study. DII score was constructed based on a validated self-administered food frequency questionnaire was calculated based on the method developed by Shivappa et al. LTL was measured by quantitative real-time polymerase chain reaction. Multivariable logistic regression analysis was used to analyze the association between DII, LTL and MCI. Moreover, mediation analysis was employed to test the mediation effect of LTL on the total effect of DII on MCI. RESULTS: Compared with the participants in the lowest tertiles of LTL and DII score, the odds ratios (ORs) of MCI in the highest tertiles were 0.386(95% CI: 0.281-0.529) and 1.650 (95% CI: 1.232-2.209), respectively. The significant association between DII score and MCI persisted after further adjusting for LTL (OR: 1.595; 95% CI: 1.189-2.140). The link between DII score and MCI was mediated partially by LTL (ßindirect effect= -0.008, P<0.05). CONCLUSION: High DII score was positively associated with MCI prevalence in an elderly Chinese population and the link between DII scores and MCI seemed to be mediated partially by LTL.

The causal effect of schizophrenia on fractures and bone mineral density: a comprehensive two-sample Mendelian randomization study of European ancestry.

BACKGROUND: Schizophrenia was clinically documented to co-occur with fractures and aberrant bone mineral density (BMD), but the potential causal relationship remained unclear. This study aimed to test the causal effects between schizophrenia and fractures as well as aberrant BMD by conducting Mendelian randomization (MR) analyses. METHODS: Two-sample MR was utilized, based on instrumental variables from large genome-wide association studies (GWAS) of schizophrenia as exposure, to identify the causal association of schizophrenia with mixed fractures, fractures at different body sites (including skull and facial bones, shoulder and upper arm, wrist and hand, and femur) and BMDs of forearm (FA), femoral neck (FN), lumbar spine (LS) and estimated BMD (eBMD). Multivariable Mendelian randomization (MVMR) analysis was performed to minimize the confounding effect of body mass index (BMI). RESULTS: Result from inverse variance weighting (IVW) method provided evidence schizophrenia increased the risk of fractures of skull and facial bones [odds ratio (OR) = 1.0006, 95% confidence interval (CI): 1.0003 to 1.0010] and femur [OR =1.0007, 95% CI: 1.0003 to 1.0011], whereas, decreased the level of eBMD [ß (95%CI): -0.013 (-0.021, -0.004)]. These causal effects still existed after adjusting for BMI. Sensitivity analyses showed similar results. However, no causal effect of schizophrenia on fracture or BMD in other parts was detected. CONCLUSION: The current finding confirmed that schizophrenia was causally associated with the fractures of skull, face and femur as well as eBMD, which might remind psychiatrists to pay close attention to the fracture risk in schizophrenic patients when formulating their treatment strategies.

Effect of Chemotherapy in Stage II-IV Large-Cell Lung Carcinoma and Construction of Its Predictive Nomograms: A SEER Analysis.

OBJECTIVES: Large-cell lung carcinoma (LCLC) is generally poorly differentiated with a poor prognosis. This study aimed to explore the impact of chemotherapy on the prognosis of patients with stage II-IV LCLC and to construct nomograms to predict overall survival (OS) and cancer-specific survival (CSS). METHODS: Propensity score matching analysis was used to balance the effects of baseline characteristics. The Kaplan-Meier method was used to analyze the prognostic impact of chemotherapy on LCLC patients. Cox regression analysis was used to identify prognostic risk factors, and then nomograms were constructed and validated. RESULTS: Overall, we identified 2,532 patients with LCLC from the Surveillance, Epidemiology, and End Results (SEER) database. The chemotherapy group showed better OS and CSS compared to the non-/unknown chemotherapy group for stage II-IV LCLC patients (p < 0.05). Two nomograms were plotted based on the results of Cox regression analysis. The areas under the curves (AUCs) of 1-, 3-, and 5-year OS were 0.786, 0.824, and 0.837, and the AUCs of CSS were 0.785, 0.821, and 0.836, respectively. The calibration curves showed excellent agreement between the prediction and the actual observation, and the decision curve analysis demonstrated good clinical utility. CONCLUSIONS: Chemotherapy could improve the prognosis among stage II-IV LCLC patients. In addition, the nomograms showed good predictive ability, which could be useful in making clinical decisions.

Association between methionine cycle metabolite-related diets and mild cognitive impairment in older Chinese adults: a population-based observational study.

BACKGROUND: Homocysteine (Hcy) and folate, involved in a common metabolic pathway supplying essential methyl groups for DNA and protein synthesis, have been found to be associated with cognitive function. Moreover, diet may influence methionine cycle metabolites (MCM) as well as mild cognitive impairment (MCI), but MCM-related dietary patterns are unclear in an older population. OBJECTIVE: The study aimed to identify MCM-related dietary patterns of older Chinese adults, and examine their association with the prevalence of MCI in a large population-based study. METHODS: This study included 4457 participants ≥ 60 years of age from the Tianjin Elderly Nutrition and Cognition Cohort study. Dietary data were collected using a valid self-administered food frequency questionnaire, and factor analysis was used to identify major dietary patterns in the population. MCM-based dietary patterns were derived using reduced rank regression (RRR) based on serum folate and Hcy as response variables. RESULTS: Compared with the participants in the lowest quartile of vegetarian pattern and processed foods pattern, the odds ratios (ORs) of MCI in the highest quartile were 0.72 (95% CI 0.53-0.98) and 1.39 (95% CI 1.03-1.88), respectively. In the MCM-based dietary patterns derived using RRR, the ORs for MCI for the highest quartile of MCM patterns I and II were 0.58 (95% CI 0.44-0.78) and 1.38 (95% CI 1.04-1.83), respectively, compared with participants in the lower quartile. CONCLUSIONS: Findings from this large population-based study suggested that adopting an MCM-related dietary pattern, especially avoiding processed foods, can decrease the occurrence of MCI.

Association analysis between the interaction of RAS family genes mutations and papillary thyroid carcinoma in the Han Chinese population.

Papillary thyroid carcinoma (PTC) is the major subtype of thyroid cancer, accounting for 75%-85% of all thyroid malignancies. This study aimed to identify the association between the interactions of single nucleotide polymorphisms (SNPs) in RAS family genes and PTC in the Han Chinese population, to provide clues to the pathogenesis and potential therapeutic targets for PTC. Hap Map and NCBI-db SNP databases were used to retrieve SNPs. Haploview 4.2 software was used to filter SNPs based on specific parameters, six SNPs of RAS gene (KRAS-rs12427141, KRAS-rs712, KRAS-rs7315339, HRAS-rs12628, NRAS-rs14804 and NRAS-rs2273267) were genotyped by matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF-MS) in 673 PTC patients and 657 healthy controls, the interactive effect was evaluated by crossover analysis, logistic regression and GMDR software. We found that genetic mutation in rs712 have significant associations with PTC risk after Bonferroni correction (p<0.001). The interaction between KRAS-rs12427141 and HRAS-rs12628 increased the risk of PTC (U=-2.119, p<0.05), the interaction between KRAS-rs2273267 and HRAS-rs7315339 reduced the risk of PTC (U=2.195, p<0.05). GMDR analysis showed that the two-factor model (KRAS-rs712, NRAS-rs2273267) was the best (p=0.0107). Summarily, there are PTC-related interactions between RAS family genes polymorphisms in the Han Chinese population.

A Retrospective Study of 268 Patients with SARS-CoV-2 Infection to Evaluate the Association Between Blood Glucose and Severity of COVID-19 Pneumonia and Patient Mortality.

BACKGROUND Diabetes is one of the most commonly reported comorbidities among patients infected with SARS-CoV-2. This retrospective study of patients with SARS-CoV-2 infection was conducted to evaluate the association between blood glucose levels and the severity of COVID-19 pneumonia and patient mortality. MATERIAL AND METHODS A total of 268 patients with confirmed SARS-CoV-2 infection were included in this retrospective study. We obtained demographic characteristics, clinical symptoms, laboratory data, and survival information from patients' electronic medical records. Blood glucose was measured on admission to the hospital. Comorbidities, including hypertension, diabetes, chronic kidney disease, chronic liver disease, chronic obstructive pulmonary disease, and cardiovascular disease, were collected by self-reported medical history. RESULTS Significantly higher risks of severe COVID-19 were found in patients with blood glucose levels ranging from 5.53 to 7.27 mmol/L (odds ratio [OR], 3.98; 95% confidence interval [CI], 1.81-8.75) and in patients with blood glucose ≥7.27 mmol/L (OR, 12.10; 95% CI, 5.53-26.48) than in those with blood glucose <5.53 mmol/L. There was a trend toward better survival in patients with blood glucose <5.53 mmol/L than in patients with blood glucose from 5.53 to 7.27 mmol/L (hazard ratio [HR], 6.34; 95% CI, 1.45-27.71) and ≥7.27 mmol/L (HR, 19.37; 95% CI, 4.68-80.17). Estimated 10-day overall survival rates were 96.8%, 90.6%, and 69.3% in patients with blood glucose <5.53 mmol/L, 5.53 to 7.27 mmol/L, and ³7.27 mmol/L, respectively. CONCLUSIONS Hyperglycemia was association with severity of COVID-19 pneumonia and with increased patient mortality. These findings support the need for blood glucose monitoring and control of hyperglycemia in patients with COVID-19 pneumonia.

Early chest computed tomography to diagnose COVID-19 from suspected patients: A multicenter retrospective study.

Objective: The purpose of this study was to distinguish the imaging features of COVID-19 from those of other infectious pulmonary diseases and evaluate the diagnostic value of chest CT for suspected COVID-19 patients. Methods: Adult patients suspected of COVID-19 aged >18 years who underwent chest CT scans and reverse-transcription polymerase chain reaction (RT-PCR) tests within 14 days of symptom onset were enrolled. The enrolled patients were confirmed and grouped according to the results of the RT-PCR tests. The basic demographics, single chest CT features, and combined chest CT features were analyzed for the confirmed and nonconfirmed groups. Results: A total of 130 patients were enrolled, with 54 testing positive and 76 testing negative. The typical CT imaging features of the positive group were ground glass opacities (GGOs), the crazy-paving pattern and air bronchogram. The lesions were mostly distributed bilaterally and close to the lower lungs or the pleura. When features were combined, GGOs with bilateral pulmonary distribution and GGOs with pleural distribution were more common among the positive patients, found in 31 (57.4%) and 30 patients (55.6%), respectively. The combinations were almost all statistically significant (P < .05), except for the combination of GGOs with consolidation. Most combinations presented relatively low sensitivity but extremely high specificity. The average specificity of these combinations was approximately 90%. Conclusions: The combinations with GGOs could be useful in the identification and differential diagnosis of COVID-19, alerting clinicians to isolate patients for prompt treatment and repeat RT-PCR tests until the end of incubation.

A Machine Learning-Based Investigation of Gender-Specific Prognosis of Lung Cancers.

BACKGROUND AND OBJECTIVE: Primary lung cancer is a lethal and rapidly-developing cancer type and is one of the most leading causes of cancer deaths. MATERIALS AND METHODS: Statistical methods such as Cox regression are usually used to detect the prognosis factors of a disease. This study investigated survival prediction using machine learning algorithms. The clinical data of 28,458 patients with primary lung cancers were collected from the Surveillance, Epidemiology, and End Results (SEER) database. RESULTS: This study indicated that the survival rate of women with primary lung cancer was often higher than that of men (p < 0.001). Seven popular machine learning algorithms were utilized to evaluate one-year, three-year, and five-year survival prediction The two classifiers extreme gradient boosting (XGB) and logistic regression (LR) achieved the best prediction accuracies. The importance variable of the trained XGB models suggested that surgical removal (feature "Surgery") made the largest contribution to the one-year survival prediction models, while the metastatic status (feature "N" stage) of the regional lymph nodes was the most important contributor to three-year and five-year survival prediction. The female patients' three-year prognosis model achieved a prediction accuracy of 0.8297 on the independent future samples, while the male model only achieved the accuracy 0.7329. CONCLUSIONS: This data suggested that male patients may have more complicated factors in lung cancer than females, and it is necessary to develop gender-specific diagnosis and prognosis models.

Exploration of Positive and Negative Schizophrenia Symptom Heterogeneity and Establishment of Symptom-Related miRNA-mRNA Regulatory Network: Based on Transcriptome Sequencing Data.

Schizophrenia (SCZ) symptoms can be classified as positive and negative ones, each of which has distinct traits and possibly differences in gene expression and regulation. The co-expression networks linked to PANSS (Positive and Negative Syndrome Scale) scores were identified by weighted gene co-expression network analysis (WGCNA) using the expression profiles of miRNA and mRNA in the peripheral blood of first-episode SCZ patients. The heterogeneity between positive and negative symptoms was demonstrated using gene functional enrichment, gene-medication interaction, and immune cell composition analysis. Then, target gene prediction and correlation analysis of miRNA and mRNA constructed a symptom-related miRNA-mRNA regulatory network, screened regulatory pairs, and predicted binding sites. A total of six mRNA co-expression modules, two miRNA co-expression modules, and ten hub genes were screened to be significantly associated with positive symptoms; five mRNA co-expression modules and eight hub genes were correlated with negative symptoms. Positive symptom-related modules were significantly enriched in axon guidance, actin skeleton regulation, and sphingolipid signaling pathway, while negative symptom-related modules were significantly enriched in adaptive immune response, leukocyte migration, dopaminergic synapses, etc. The development of positive symptoms may have been influenced by potential regulatory pairings such as miR-98-5p-EIF3J, miR-98-5p-SOCS4, let-7b-5p-CLUH, miR-454-3p-GTF2H1, and let-7b-5p-SNX17. Additionally, immune cells were substantially connected with several hub genes for symptoms. Positive and negative symptoms in SCZ individuals were heterogeneous to some extent. miRNAs such as let-7b-5p and miR-98-5p might contribute to the incidence of positive symptoms by targeting mRNAs, while the immune system's role in developing negative symptoms may be more nuanced.

Circulating miR-30e-3p induces disruption of neurite development in SH-SY5Y cells by targeting ABI1, a novel biomarker for schizophrenia.

Schizophrenia (SCZ) represents a set of enduring mental illnesses whose underlying etiology remains elusive, posing a significant challenge to public health. Previous studies have shown that the neurodevelopmental process involving small molecules such as miRNA and mRNA is one of the etiological hypotheses of SCZ. We identified and verified that miR-30e-3p and ABI1 can be used as biomarkers in peripheral blood transcriptome sequencing data of patients with SCZ, and confirmed the regulatory relationship between them. To further explore their involvement, we employed retinoic acid (RA)-treated SH-SY5Y differentiated cells as a model system. Our findings indicate that in RA-induced SH-SY5Y cells, ABI1 expression is up-regulated, while miR-30e-3p expression is down-regulated. Functionally, both miR-30e-3p down-regulation and ABI1 up-regulation promote apoptosis and inhibit the proliferation of SH-SY5Y cells. Subsequently, the immunofluorescence assay detected the expression location and abundance of the neuron-specific protein ß-tubulinIII. The expression levels of neuronal marker genes MAPT, TUBB3 and SYP were detected by RT-qPCR. We observed that these changes of miR-30e-3p and ABI1 inhibit the neurite growth of SH-SY5Y cells. Rescue experiments further support that ABI1 silencing can correct miR-30e-3p down-regulation-induced SH-SY5Y neurodevelopmental defects. Collectively, our results establish that miR-30e-3p's regulation of neurite development in SH-SY5Y cells is mediated through ABI1, highlighting a potential mechanism in SCZ pathogenesis.

Cost of treatment support for multidrug-resistant tuberculosis using patient-centred approaches in Ethiopia: a model-based method.

BACKGROUND: Patient and health system costs for treating multidrug-resistant tuberculosis (MDR-TB) remain high even after treatment duration was shortened. Many patients do not finish treatment, contributing to increased transmission and antimicrobial resistance. A restructure of health services, that is more patient-centred has the potential to reduce costs and increase trust and patient satisfaction. The aim of the study is to investigate how costs would change in the delivery of MDR-TB care in Ethiopia under patient-centred and hybrid approaches compared to the current standard-of-care. METHODS: We used published data, collected from 2017 to 2020 as part of the Standard Treatment Regimen of Anti-Tuberculosis Drugs for Patients with MDR-TB (STREAM) trial, to populate a discrete event simulation (DES) model. The model was developed to represent the key characteristics of patients' clinical pathways following each of the three treatment delivery strategies. To the pathways of 1000 patients generated by the DES model we applied relevant patient cost data derived from the STREAM trial. Costs are calculated for treating patients using a 9-month MDR-TB treatment and are presented in 2021 United States dollars (USD). RESULTS: The patient-centred and hybrid strategies are less costly than the standard-of-care, from both a health system (by USD 219 for patient-centred and USD 276 for the hybrid strategy) and patient perspective when patients do not have a guardian (by USD 389 for patient-centred and USD 152 for the hybrid strategy). Changes in indirect costs, staff costs, transport costs, inpatient stay costs or changes in directly-observed-treatment frequency or hospitalisation duration for standard-of-care did not change our results. CONCLUSION: Our findings show that patient-centred and hybrid strategies for delivering MDR-TB treatment cost less than standard-of-care and provide critical evidence that there is scope for such strategies to be implemented in routine care. These results should be used inform country-level decisions on how MDR-TB is delivered and also the design of future implementation trials.

Establishment of a schizophrenia classifier based on peripheral blood signatures and investigation of pathogenic miRNA-mRNA regulation.

To date, the diagnosis of schizophrenia (SCZ) mainly relies on patients' or guardians' self-reports and clinical observation, and the pathogenesis of SCZ remains elusive. In this study, we sought to develop a reliable classifier for diagnosing SCZ patients and provide clues to the etiology and pathogenesis of SCZ. Based on the high throughput sequencing analysis of peripheral blood miRNA expression profile and weighted gene co-expression network analysis (WGCNA) in our previous study, we selected eleven hub miRNAs for validation by qRT-PCR in 51 SCZ patients and 51 controls. miR-939-5p, miR-4732-3p let-7d-3p, and miR-142-3p were confirmed to be significantly up-regulated, and miR-30e-3p and miR-23a-3p were down-regulated in SCZ patients. miR-30e-3p with the most considerable fold change and statistically significance was selected for targeting validation. We first performed bioinformatics prediction followed by qRT-PCR and verified the up-regulation of potential target mRNAs (ABI1, NMT1, HMGB1) expression. Next, we found that the expression level of ABI1 was significantly up-regulated in SH-SY5Y cells transfected with miR-30e-3p mimics. Lastly, we conducted a luciferase assay in 293T cells confirming that miR-30e-3p could directly bind with the 3'untranslated region (3'-UTR) of ABI1, revealing that miR-30e-3p might play a role in the polymerization of neuronal actin and the reconstruction of the cytoskeleton via the downstream regulation of ABI1. In addition, we constructed a classifier by a series of bioinformatics algorithms and evaluated its diagnostic performance. It appears that the classifier consists of miRNAs and mRNAs possess a better discrimination performance than individual miRNA or mRNA in SCZ.

Protective role of antioxidant supplementation for depression and anxiety: A meta-analysis of randomized clinical trials.

BACKGROUND: New research supports an integrated approach to treating depression, and lifestyle modifications should be a regular component of both preventative and treatment programs. Therefore, in order to investigate the relationship between various antioxidant supplements and depressive status, we carried out a meta-analysis of randomized controlled trials (RCT). METHODS: We thoroughly searched PubMed, Medline, Scopus, and Web of Science databases to screen publications focusing on the effects of antioxidant supplements on depression status. The meta-analysis mainly compared depression scores between groups that received antioxidant supplements and controls. We also pooled studies reporting changes in anxiety status as a secondary outcome. RESULTS: 52 studies with 4049 participants were eventually identified. The meta-analysis found that the positive effect of antioxidant supplementation, such as magnesium (SMD = 0.16, p = 0.03), zinc (SMD = 0.59, p = 0.01), selenium (SMD = 0.33, p = 0.009), CoQ10 (SMD = 0.97, p = 0.05), tea and coffee (SMD = 1.15, p = 0.001) and crocin (MD = 6.04, p < 0.00001), on depressive status were all significant. And antioxidant supplementation also showed significant improvement in anxiety (SMD = 0.40, p < 0.00001). Subgroup analysis by scale types and countries were performed, and antioxidant supplementation's positive effects on depressive and anxiety states remained significant. LIMITATIONS: This study did not limit the characteristics of the included population, and the diversity of scales also contributed to the heterogeneity. CONCLUSION: Intake of antioxidant supplements is associated with improved depression and anxiety states, further affirms the therapeutic potential of antioxidant supplements as adjunctive therapy to conventional antidepressants.

Assessment of causal relationships between omega-3 and omega-6 polyunsaturated fatty acids in bipolar disorder: a 2-sample bidirectional mendelian randomization study.

Omega-3 fatty acids may be protective against bipolar disorder (BD), whereas omega-6 fatty acids and an increased omega-6:omega-3 ratio may increase the risk of BD. This causal relationship has not yet been established. We attempted to prove the existence of these causal relationships in this study. Datasets on omega-3, omega-6, and omega-6:omega-3 ratios were obtained from the UK Biobank. The EBI database was used to obtain the BD dataset. SNPs associated with fatty acids were identified as instrumental variables (IVs) that met the criteria of P < 5 × 10-8, LD (R2 > 0.01), and kb < 10 000. The main analytical method in this study was the inverse variance weighted (IVW) method. Furthermore, we employ a variety of methods for sensitivity analysis. According to the IVW analysis, higher omega-3 levels were associated with a lower risk of BD (OR = 0.884, 95%CI: 0.796-0.982, P < 0.05). An increase in the omega-6:omega-3 ratio was associated with an increased risk of BD (OR = 1.172, 95%CI: 1.046-1.314, P < 0.05), but no causal relationship between omega-6 levels and BD risk was unearthed. Our MR findings suggest that the ratio of omega-3, omega-6:omega-3 is associated with the risk of BD. It is important to be concerned about the risk of BD in individuals with low serum omega-3 intake and a high omega-6:omega-3 ratio.

Dietary Intake of Carotenoids and Risk of Depressive Symptoms: A Systematic Review and Meta-Analysis.

Given the important role of oxidative stress in the pathogenesis of depression, the potential role of dietary antioxidant supplementation in the prevention of depression has attracted considerable attention. Most studies suggest that dietary carotenoids may play a role in maintaining depressive symptoms due to their antioxidant activity, but some studies concluded the contrary. This study conducted a meta-analysis of observational studies to test the relationship between carotenoid supplements and depressive symptoms. After a comprehensive search of the Cochrane Library, PubMed, Embase Scopus, and Web of Science databases from their inception to 28 July 2022, 12 publications met the inclusion and exclusion criteria, of which 8 were cross-sectional studies, 3 were case−control studies, and 1 was a cohort study, involving a total of 33,466 participants. Pooled meta-analysis found that intake of total carotenoids (OR = 0.61, 95% CI [0.53, 0.71], p < 0.01), beta-carotene (OR = 0.61, 95% CI [0.52, 0.70], p < 0.01), alpha-carotene (OR = 0.71, 95% CI [0.60, 0.83], p < 0.01), lycopene (OR = 0.71, 95% CI [0.55, 0.90], p < 0.01), lutein, and/or corn xanthin (OR = 0.53, 95% CI [0.43, 0.66], p < 0.01) was significantly inversely associated with depressive symptoms, while beta-cryptoxanthin (OR = 1.07, 95% CI [0.52, 2.21], p = 0.86) had no significance. At the same time, this meta-analysis was free of publication bias and heterogeneity. Although further studies are needed to elucidate the causal relationship between carotenoids and depressive symptoms, and to further reveal the mechanism of their association, the results of our meta-analysis suggest that carotenoids are protective factors for depressive symptoms, and dietary intake may help in reducing the risk of depressive symptoms.

Identification of potential biomarkers and their correlation with immune infiltration cells in schizophrenia using combinative bioinformatics strategy.

Many studies have identified changes in gene expression in brains of schizophrenia patients and their altered molecular processes, but the findings in different datasets were inconsistent and diverse. Here we performed the most comprehensive analysis of gene expression patterns to explore the underlying mechanisms and the potential biomarkers for early diagnosis in schizophrenia. We focused on 10 gene expression datasets in post-mortem human brain samples of schizophrenia downloaded from gene expression omnibus (GEO) database using the integrated bioinformatics analyses including robust rank aggregation (RRA) algorithm, Weighted gene co-expression network analysis (WGCNA) and CIBERSORT. Machine learning algorithm was used to construct the risk prediction model for early diagnosis of schizophrenia. We identified 15 key genes (SLC1A3, AQP4, GJA1, ALDH1L1, SOX9, SLC4A4, EGR1, NOTCH2, PVALB, ID4, ABCG2, METTL7A, ARC, F3 and EMX2) in schizophrenia by performing multiple bioinformatics analysis algorithms. Moreover, the interesting part of the study is that there is a correlation between the expression of hub genes and the immune infiltrating cells estimated by CIBERSORT. Besides, the risk prediction model was constructed by using both these genes and the immune cells with a high accuracy of 0.83 in the training set, and achieved a high AUC of 0.77 for the test set. Our study identified several potential biomarkers for diagnosis of SCZ based on multiple bioinformatics algorithms, and the constructed risk prediction model using these biomarkers achieved high accuracy. The results provide evidence for an improved understanding of the molecular mechanism of schizophrenia.

Identifying crucial biomarkers in peripheral blood of schizophrenia and screening therapeutic agents by comprehensive bioinformatics analysis.

Schizophrenia (SCZ) is a sophisticated neurodevelopmental disorder, but the mechanisms remain ambiguous. Thus, we analyzed the transcriptomic datasets to investigate the molecular mechanisms of SCZ to pinpoint novel biomarkers and suggest treatment agents. Four peripheral blood datasets were retrieved from the Gene Expression Omnibus (GEO) database, altogether 27 robust Differentially Expressed Genes (DEGs) were ascertained by robust rank aggregation (RRA) methodology. Enrichment analysis, which performed by Enrichr platform, demonstrated that DEGs are predominantly engaged in immune and inflammatory. Protein-protein interaction (PPI) network was constructed by STRING then visualized by Cytoscape. Hub genes identified by cytohubba plug-in were CXCL2, TLR9, SLPI, LY96, G0S2, EGR2, SELENBP1, NDUFA4, GNLY, CCL22. CIBERSORT algorithm was applied to evaluate the situation of immune infiltration, which revealed differences in T-cell CD8, T-cell CD4 memory resting and macrophage M0. The NetworkAnalyst platform was adopted to detect transcription factors (TFs), microRNAs (miRNAs), diseases and chemicals that interact with DEGs, while drugs interacted with DEGs were detected by Enrichr. TFs such as FOXC1, GATA2, NFIC, USF2, E2F1, miRNAs like mir-16-5p, mir-1-3p, mir-124-3p, mir-155-5p, mir-27a-3p are essential in the regulation of DEGs. mir-367-SMAD7-EGR1, mir-367-SMAD7-ARNT, mir-21-SMAD7-EGR1 may be promising biomarkers for SCZ. DEGs were intimately associated with Myocardial Ischemia, Inflammation, Reperfusion Injury. Chemicals such as VPA, cyclosporine, Aflatoxin B1, arsenic trioxide, drugs like diphenylpyraline, trimethoprim, 4-Aminobenzohydrazide, lanatoside C, may have significant implications for treatment of SCZ. These results would shed light on the molecular mechanisms of SCZ and suggest promising diagnostic biomarkers in peripheral blood and therapeutic tactics.

Identification of potential blood biomarkers for early diagnosis of schizophrenia through RNA sequencing analysis.

Schizophrenia (SCZ) is a highly heritable, polygenic complex mental disorder with imprecise diagnostic boundaries. Finding sensitive and specific novel biomarkers to improve the biological homogeneity of SCZ diagnosis is still one of the research hotspots. To identify the blood specific diagnostic biomarkers of SCZ, we performed RNA sequencing (RNA-seq) on 30 peripheral blood samples from 15 first-episode drug-naïve SCZ patients and 15 healthy controls (CTL). By performing multiple bioinformatics analysis algorithms based on RNA-seq data and microarray datasets, including differential expression genes (DEGs) analysis, WGCNA and CIBERSORT, we first identified 6 specific key genes (TOMM7, SNRPG, KRT1, AQP10, TMEM14B and CLEC12A) in SCZ. Moreover, we found that the proportions of lymphocyte, monocyte and neutrophils were significantly distinct in SCZ patients with CTL samples. Therefore, combining various features including age, sex and the novel blood biomarkers, we constructed the risk prediction model with three classifiers (RF: Random Forest; SVM: support vector machine; DT: decision tree) through repeated k-fold cross validation ensuring better generalizability. Finest result of Area under Receiver Operating Characteristic (AUROC) score of 0.91 was achieved by RF classifier and with a comparable good performance of AUROC 0.77 in external validation dataset. A lower AUROC of 0.63 was demonstrated when it was further applied to a Bipolar disorder (BPD) cohort. In conclusion, the study identified three peripheral core immunocytes and six key genes associated with the occurrence of SCZ, and further studies are required to test and validate these novel biomarkers for early diagnosis and treatment of SCZ.