MiR-574-5P, miR-1827, and miR-4429 as Potential Biomarkers for Schizophrenia.

Schizophrenia is a severe chronic debilitating disorder with millions of affected individuals. Diagnosis is based on clinical presentations, which are made when the progressive disease has appeared. Early diagnosis may help improve the clinical outcomes and response to treatments. Lack of a reliable molecular diagnostic invokes the identification of novel biomarkers. To elucidate the molecular basis of the disease, in this study we used two mRNA expression arrays, including GSE93987 and GSE38485, and one miRNA array, GSE54914, and meta-analysis was conducted for evaluation of mRNA expression arrays via metaDE package. Using WGCNA package, we performed network analysis for both mRNA expression arrays separately. Then, we constructed protein-protein interaction network for significant modules. Limma package was employed to analyze the miRNA array for identification of dysregulated miRNAs (DEMs). Using genes of significant modules and DEMs, a mRNA-miRNA network was constructed and hub genes and miRNAs were identified. To confirm the dysregulated genes, expression values were evaluated through available datasets including GSE62333, GSE93987, and GSE38485. The ability of the detected hub miRNAs to discriminate schizophrenia from healthy controls was evaluated by assessing the receiver-operating curve. Finally, the expression levels of genes and miRNAs were evaluated in 40 schizophrenia patients compared with healthy controls via Real-Time PCR. The results confirmed dysregulation of hsa-miR-574-5P, hsa-miR-1827, hsa-miR-4429, CREBRF, ARPP19, TGFBR2, and YWHAZ in blood samples of schizophrenia patients. In conclusion, three miRNAs including hsa-miR-574-5P, hsa-miR-1827, and hsa-miR-4429 are suggested as potential biomarkers for diagnosis of schizophrenia.

Identification of Risk Factors to Predict the Occurrences of Relapses in Individuals with Schizophrenia Spectrum Disorder in Iran.

Schizophrenia Spectrum Disorder (SSD) is a chronic psychiatric disorder with a modest treatment outcome. In addition, relapses are commonplace. Here, we sought to identify factors that predict relapse latency and frequency. To this end, we retrospectively analyzed data for individuals with SSD. Medical records of 401 individuals with SSD were analyzed (mean age: 25.51 years; 63.6% males) covering a five-year period. Univariate and multivariate Penalized Likelihood Models with Shared Log-Normal Frailty were used to determine the correlation between discharge time and relapse and to identify risk factors. A total of 683 relapses were observed in males, and 422 relapses in females. The Relapse Hazard Ratio (RHR) decreased with age (RHR = 0.99, CI: (0.98-0.998)) and with participants' adherence to pharmacological treatment (HR = 0.71, CI: 0.58-0.86). In contrast, RHR increased with a history of suicide attempts (HR = 1.32, CI: 1.09-1.60), and a gradual compared to a sudden onset of disease (HR = 1.45, CI: 1.02-2.05). Gender was not predictive. Data indicate that preventive and therapeutic interventions may be particularly important for individuals who are younger at disease onset, have a history of suicide attempts, have experienced a gradual onset of disease, and have difficulties adhering to medication.

The relationship between Life Style and mental health among medical students in Kermanshah.

INTRODUCTION: Given the close relationship between life style and mental health and the importance of students as valuable human resources, the present study aimed at determining the relationship between life style and mental health among medical students in Kermanshah. METHODS: This is a descriptive-correlational study that was conducted in 2018. The study involved 200 medical students. The sampling method was convenience sampling. Demographic questionnaire, general health questionnaire, and life style questionnaire were used for data collection. The data were analyzed Pearson's correlation test and regression analysis. The significance level was considered 0.05. RESULTS: The mean mental health score of the students was 25.43 ± 13.02 (2 points higher than the cutoff point of this test). The life style of 59.5 students was moderate. The results showed that all life style subscales had a negative significant relationship with the total mental health score and all its subscales (P < 0.05). Among the life style subscales, the highest relationship and predictive power to mental health were obtained for psychological health, social health, sport and fitness, and environmental health (R 2 = 0.48, P < 0.001). CONCLUSION: According to the results, the life style of most medical students in the final year of Kermanshah University of Medical Sciences was moderate. Further, the students had a better life style, and they had higher mental health. Therefore, considering the vital role of medical students in providing and promoting community health, the need for more detailed planning and interventions to improve their life style and mental health is essential.