Ferroptosis-related genes as diagnostic markers for major depressive disorder and their correlations with immune infiltration

Jingjing Chen; Xiaolong Jiang; Xin Gao; Wen Wu; Zhengsheng Gu; Ge Yin; Rui Sun; Jiasi Li; Ruoru Wang; Hailing Zhang; Bingying Du; Xiaoying Bi

doi:10.3389/fmed.2023.1215180

Ferroptosis-related genes as diagnostic markers for major depressive disorder and their correlations with immune infiltration

Front Med (Lausanne). 2023 Oct 24:10:1215180. doi: 10.3389/fmed.2023.1215180. eCollection 2023.

Authors

Jingjing Chen^#¹, Xiaolong Jiang^#², Xin Gao^#¹, Wen Wu¹, Zhengsheng Gu¹, Ge Yin¹, Rui Sun¹, Jiasi Li¹, Ruoru Wang¹, Hailing Zhang¹, Bingying Du¹, Xiaoying Bi¹

Affiliations

¹ Department of Neurology, The First Affiliated Hospital of Naval Medical University, Shanghai, China.
² Department of Laboratory Animal Sciences, School of Basic Medicine, Naval Medical University, Shanghai, China.

^# Contributed equally.

Abstract

Background: Major depression disorder (MDD) is a devastating neuropsychiatric disease, and one of the leading causes of suicide. Ferroptosis, an iron-dependent form of regulated cell death, plays a pivotal role in numerous diseases. The study aimed to construct and validate a gene signature for diagnosing MDD based on ferroptosis-related genes (FRGs) and further explore the biological functions of these genes in MDD.

Methods: The datasets were downloaded from the Gene Expression Omnibus (GEO) database and FRGs were obtained from the FerrDb database and other literatures. Least absolute shrinkage and selection operator (LASSO) regression and stepwise logistic regression were performed to develop a gene signature. Receiver operating characteristic (ROC) curves were utilized to assess the diagnostic power of the signature. Gene ontology (GO) enrichment analysis was used to explore the biological roles of these diagnostic genes, and single sample gene set enrichment analysis (ssGSEA) algorithm was used to evaluate immune infiltration in MDD. Animal model of depression was constructed to validate the expression of the key genes.

Results: Eleven differentially expressed FRGs were identified in MDD patients compared with healthy controls. A signature of three FRGs (ALOX15B, RPLP0, and HP) was constructed for diagnosis of MDD. Afterwards, ROC analysis confirmed the signature's discriminative capacity (AUC = 0.783, 95% CI = 0.719-0.848). GO enrichment analysis revealed that the differentially expressed genes (DEGs) related to these three FRGs were mainly involved in immune response. Furthermore, spearman correlation analysis demonstrated that these three FRGs were associated with infiltrating immune cells. ALOX15B and HP were significantly upregulated and RPLP0 was significantly downregulated in peripheral blood of the lipopolysaccharide (LPS)-induced depressive model.

Conclusion: Our results suggest that the novel FRG signature had a good diagnostic performance for MDD, and these three FRGs correlated with immune infiltration in MDD.

Keywords: GEO database; diagnostic biomarkers; ferroptosis; immune infiltration; major depression disorder.

Grants and funding

This work was financially supported by the National Natural Science Foundation of China (81871040 and 82101563), and the Clinical Research Plan of SHDC (No. SHDC2020CR1038B).