Abstract

Background: Depression is a common medical condition with a high prevalence leading to emotional abnormality. Despite some drawbacks, depression currently diagnosed using a combination of patient interviews and self-report questionnaires. Recently, there is emerging emphasis to establish biomarkers to diagnosis and clinical management of depression. This case-control study was designed to develop microRNA (miRNA)-based serum biomarker for depression. Materials and Methods: In this study, 39 patients with depression and 36 healthy controls were enrolled. Serum miRNAs gene expression was measured using real-time polymerase chain reaction (PCR) analysis; finally, the data represent as the 2(-DeltaCt) followed by further statistical analysis. Results: The serum level of miR-16 was significantly (P < 0.001) down-regulated (mean: 0.9123 and standard deviation SD: 0.06) in compared to normal individuals (mean: 1.6848 and SD: 0.09). The concentration of miR-135a was also catastrophically decreased (P < 0.001) in the patients (mean: 1.160 and SD: 0.07) in compared to control (mean: 1.819 and SD: 0.09). The relative miR-1202 expression levels were significantly lower (P < 0.001) in the patients (mean: 0.1755 and SD: 0.01) than in the healthy individuals (mean: 0.2939 and SD: 0.01). The receiver operating characteristic curve analysis indicated the obvious separation between patient and healthy control, with an AUC of 0.75 (95% confidence interval CI = 0.642-0.858, P < 0.001), 0.72 (95% CI = 0.607-0.834, P < 0.001), and 0.74 (95% CI = 0.630-0.861, P < 0.001) for miR-16, miR-135a, and miR-1202, respectively. The data suggest that these miRNAs have a potential to be used as a biomarker of depression with sensitivity 77.8% and specificity of 61.5% for miR-16, 94.4% and 41.0% for miR-135a as well as 86.1% and 61.5% for miR-1202, respectively (P < 0.001). Conclusion: Our findings showed that these miRNA can be used as a biomarker of depression diagnosis. MiR-135a and miR-1202 exhibited better sensitivity and specificity, respectively.