Identification of potential biomarkers and pathways related to major depressive disorder by integrated bioinformatic analysis and experimental validation

Abstract

Objective: To identify promising biomarkers for the pathogenesis of major depressive disorder (MDD).

Methods: Microarray chips of MDD patients, including the GSE98793, GSE52790, and GSE39653 datasets, were obtained from the Gene Expression Omnibus database. The biological processes and pathways related to MDD were investigated using the GO and KEGG pathway tools. Weighted gene coexpression network analysis was conducted to identify modules related to MDD. The hub genes associated with MDD were obtained via protein-protein interaction analysis. Finally, the expression of hub genes in the hippocampal tissues of depression-like rats was detected by reverse transcription-polymerase chain reaction and Western blotting.

Results: A total of 658 differentially expressed genes were identified from the Gene Expression Omnibus datasets; thus, these genes and the GSE98793 dataset were used to conduct weighted gene coexpression network analysis. A total of 244 module-related genes were identified and these genes were highly correlated with MDD. These genes were involved in the Ras signaling pathway, regulation of the actin cytoskeleton, and axon guidance according to the KEGG analysis. Hub genes, including MAPK14, SOCS1, TLR2, PTK2B, and GRB2, were obtained via protein-protein interaction analysis. All these hub genes showed better diagnostic efficiency in the GSE52790, GSE39653, and GSE98793 datasets. In vivo experiments revealed that compared with those in control rats, SOCS1 and MAPK14 expression was significantly decreased; while GRB2, TLR2, and PTK2B expression was increased in the hippocampi of depression-like rats.

Conclusions: Our study demonstrates that GRB2, TLR2, SOCS1, PTK2B, and MAPK14 are promising hub genes, and targeting these five genes may be an effective treatment strategy for MDD.

Keywords

Major depressive disorder / Bioinformatic / Biomarkers / Microarray / Hub genes / Weighted gene coexpression network analysis

Conflict of interest statement

The authors declare that there is no conflict of interest.

Funding

This work was supported by the National Natural Science Foundation of China (No. 81774281 and No.82474303), the Natural Science Foundation of Hunan Province (2023JJ30888), and the leading national joint discipline of Chinese and Western medicines to the Chinese Medicine Department, Xiangya Hospital, CSU.

Data availability statement

The data supporting the findings of this study are available from the corresponding author upon request.

Authors’ contributions

YZ performed the experiments and wrote the paper. MZ, LQP, RZ, and KCN contributed to data analysis and interpretation, and provided experimental reagents and materials. WH was responsible for designing the experimental framework and supervising the entire project. All authors reviewed and approved the final manuscript.

Publisher’s note

The Publisher of the Journal remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.