Clinical Research Development Center, Imam Khomeini and Mohammad Kermanshahi and Farabi Hospitals, Kermanshah University of Medical Sciences, Kermanshah, Iran.
Student Research Committee, Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
J Mol Neurosci. 2022 Feb;72(2):226-238. doi: 10.1007/s12031-021-01945-0. Epub 2021 Nov 22.
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.
精神分裂症是一种严重的慢性致残性疾病，影响着数以百万计的患者。目前的诊断基于临床表现，而这些表现是在疾病进展后才出现的。早期诊断可能有助于改善临床结局和治疗反应。由于缺乏可靠的分子诊断方法，因此需要寻找新的生物标志物。为了阐明疾病的分子基础，在这项研究中，我们使用了两个 mRNA 表达谱，包括 GSE93987 和 GSE38485，以及一个 miRNA 表达谱 GSE54914，并通过 metaDE 包对 mRNA 表达谱进行了荟萃分析。我们使用 WGCNA 包分别对两个 mRNA 表达谱进行了网络分析。然后，我们构建了显著模块的蛋白质-蛋白质相互作用网络。使用 Limma 包分析 miRNA 表达谱以鉴定失调的 miRNAs（DEMs）。利用显著模块和 DEMs 的基因构建了 mRNA-miRNA 网络，并鉴定了枢纽基因和 miRNA。为了验证失调基因，我们通过可用数据集（包括 GSE62333、GSE93987 和 GSE38485）评估了表达值。通过评估接收者操作曲线评估了检测到的枢纽 miRNA 区分精神分裂症患者和健康对照者的能力。最后，通过实时 PCR 比较 40 名精神分裂症患者和健康对照者的基因和 miRNA 表达水平。结果证实 hsa-miR-574-5P、hsa-miR-1827、hsa-miR-4429、CREBRF、ARPP19、TGFBR2 和 YWHAZ 在精神分裂症患者的血液样本中存在失调。总之，hsa-miR-574-5P、hsa-miR-1827 和 hsa-miR-4429 这三个 miRNA 可能作为精神分裂症诊断的潜在生物标志物。
