Bioinformatics analysis of regulatory network of long non-coding RNA LOC107987438 in depressive disorder
10.3760/cma.j.cn371468-20230421-00193
- VernacularTitle:长链非编码RNA LOC107987438在抑郁障碍调控网络中的生物信息学分析
- Author:
Tianyi BU
1
;
Kexin QIAO
;
Yan WANG
;
Jili ZHANG
;
Xiaohui QIU
;
Zhengxue QIAO
;
Jiawei ZHOU
;
Jiarun YANG
;
Wenjuan HE
;
Yanjie YANG
Author Information
1. 哈尔滨医科大学心理科学与健康管理中心，哈尔滨 150081
- Keywords:
Long non-coding RNA, LOC107987438;
Depressive disorder;
Bioinformatics analysis;
Competing endogenous RNA mechanism
- From:
Chinese Journal of Behavioral Medicine and Brain Science
2023;32(8):714-720
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the regulatory role of defferentially expressed LOC107987438 in the pathogenesis of depressive disorder and provide a theoretical basis for its clinical application in depressive disorder.Methods:Differential expression of LOC107987438 was verified by quantitative real-time polymerase chain reaction(qRT-PCR)in peripheral blood monocular cells(PBMCs)of 60 patients with depressive disorder and 60 health controls. In addition, its diagnostic value was assessed by receiver operating characteristic(ROC)curves. Based on the ceRNA mechanism of lncRNA, the miRDB database was applied to predict the target miRNAs of LOC107987438, and the miRNAs with target score ≥ 80 among them were screened out.The screened miRNAs were then used to predict their potential target mRNAs through four databases which were TargetScan 8.0, miRTarBase, mirDIP and miRPathDB. Moreover, the predicted target mRNAs were annotated for gene ontology(GO)function annotation and tokoyo encyclopedia of genes and genomes(KEGG) pathway enrichment analysis via ClusterProfiler 4.0.5 package of R 4.1.1. Finally, a protein-protein interaction network was constructed using the STRING 11.5 platform to retrieve the interacting genes.Results:The qRT-PCR results showed that normalized expression of LOC107987438 in PBMCs of patients with depressive disorder was higher than that in health controls(depressive disorder: 2.084±1.357, health controls: 1.000±0.660, P<0.001). The ROC curve results showed that the area under curves(AUC)of LOC107987438 was 0.759(95% CI: 0.675-0.842, P<0.05), indicating its high potential diagnostic value. Bioinformatics analysis showed that hsa-miR-4670-3p, hsa-miR-619-3p, hsa-miR-6721-5p and hsa-miR-297 were the miRNAs with high bindings to LOC107987438. The results of KEGG signaling pathway enrichment revealed that hypoxia-inducible factor 1(HIF-1)signaling pathway, phosphatidylinositol 3-kinase-AKT(PI3K-Akt) signaling pathway and erythroblastic oncogene B(ErbB) signaling pathway were closely associated with depressive disorder. Among the top ten key genes screened by the protein-protein interaction network, kirsten rats arcomaviral oncogene homolog(KRAS), androgen receptor(AR), cyclic-AMP response binding protein1(CREB1), insulin-like growth factor 1(IGF1), cyclin-dependent kinase inhibitor 1B(CDKN1B) and calcium/calmodulin-dependent protein kinase type Ⅱ alpha(CAMK2A)were strongly associated with depressive disorder. Conclusion:The establishment of ceRNA regulatory network of LOC107987438 provides a theoretical basis for exploring the pathophysiology of depressive disorders.
