Seeking for potential pathogenic genes of major depressive disorder in the Gene Expression Omnibus database

Abstract

Introduction: Major depressive disorder (MDD) is one of the most common mental disorders worldwide. The aim of this study was to identify potential pathological genes in MDD. Methods: We searched and downloaded gene expression data from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) in MDD. Then, Kyoto Encyclopedia of Genes and Genomes pathway, Gene Ontology analysis, and protein-protein interaction (PPI) network were applied to investigate the biological function of identified DEGs. The quantitative real-time polymerase chain reaction and a published dataset were used to validate the result of bioinformatics analysis. Results: A total of 514 DEGs were identified in MDD. In the PPI network, some hub genes with high degrees were identified, such as EEF2, RPL26L1, RPLP0, PRPF8, LSM3, DHX9, RSRC1, and AP2B1. The result of in vitro validation of RPL26L1, RSRC1, TOMM20L, RPLPO, PRPF8, AP2B1, STIP1, and C5orf45 was consistent with the bioinformatics analysis. Electronic validation of C5orf45, STIP1, PRPF8, AP2B1, and SLC35E1 was consistent with the bioinformatics analysis. Discussion: The deregulated genes could be used as potential pathological factors of MDD. In addition, EEF2, RPL26L1, RPLP0, PRPF8, LSM3, DHX9, RSRC1, and AP2B1 might be therapeutic targets for MDD. K E Y W O R D S drug target, gene expression, in vitro validation, major depressive disorder, protein-protein interaction network

The Adaptor Protein 2 (AP2) complex modulates habituation and behavioral selection across multiple pathways and time windows

“…The Adapter Protein 2 (AP2) complex targets specific membrane-associated proteins for clathrin-mediated endocytosis via its α, β, σ, and µ subunits (Traub and Bonifacino, 2013), and these subunits have been linked to diverse aspects of clinically-relevant behavioral control (Chen et al, 2013; Chinoy et al, 2017; Helbig et al, 2019; Bonnycastle et al, 2021). Expression levels of the AP2β subunit ( AP2B1 ) are altered in the brains of individuals with schizophrenia and major depressive disorder, and AP2 subunit expression is reduced in the brains of untreated individuals with bipolar disorder (Chen et al, 2013; Föcking et al, 2015; Forero et al, 2017; Feng et al, 2020). Mutations disrupting the AP2µ subunit ( AP2M1 ) are associated with severe disruption in cognition and behavior in humans (Helbig et al, 2019), while mutations in the AP2σ subunit ( AP2S1 ) are associated with behavior changes characteristic of autism spectrum disorders, attention hyperactivity disorder, learning disorders, and cognitive dysfunction (Hannan et al, 2015; Chinoy et al, 2017; Szalat et al, 2017; Aashiq et al, 2020; Satterstrom et al, 2020).…”

AI Machine Learning Technique Characterizes Potential Markers of Depression in Two Animal Models of Depression

“…Furthermore, the results of our screening were also validated in other studies. On the one hand, through gene database analysis, Feng et al identified AP2B1 as a potential therapeutic target for major depressive disorder [26]. At the same time, fluoxetine treatment can significantly increase the expression of AP2B1 [27].…”

Role of adaptin protein complexes in intracellular trafficking and their impact on diseases

“…Moreover, the pathological consequences of AP2B1 mutation are similar to those of the AP2α subunit mutation and has been shown to have various effects in neural tissue. In fact, AP2B1 affects dendrite cell morphology by controlling the mTOR pathway [ 97 ] through its action as a biosignature upon antidepressant treatment [ 98 ], binding to Dynamin-1, and triggering the process of autophagy, which inhibits dementia [ 99 ] and is putatively linked to depressive disorder [ 100 ]. AP2B1 is also linked to Alzheimer’s disease [ 101 ], which explains the importance of the AP2 complex in controlling autophagy and lysosomal protein degradation that regulate this neuronal degenerative disease.…”