Identification and experimental validation of biomarkers associated with mitochondrial and programmed cell death in major depressive disorder

Shengjie Xiong^*Lixin LiaoMeng ChenQing Gan

• Chengdu Second People's Hospital, Chengdu, China

The pathogenesis of major depressive disorder (MDD) is linked to mitochondrial dysfunction and programmed cell death. However, the underlying mechanisms remain elusive. This study aimed to investigate the molecular pathways involved in MDD using a transcriptomic analysis approach. Transcriptomic data related to MDD were sourced from public databases. Initially, intersections between differentially expressed genes (DEGs), programmed cell death-related genes (PCDs), and mitochondrial-related genes (MitoGs) were identified, resulting in the creation of PCD-DEGs and MitoG-DEGs sets. Correlation analysis (|correlation coefficient (cor)| > 0.9, p < 0.05) was performed to select candidate genes with strong associations. Key candidate genes were identified through protein-protein interaction (PPI) network analysis and intersection analysis of four algorithms. Machine learning and gene expression validation were employed to identify biomarkers, which were then validated using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Subsequently, a nomogram was developed to predict MDD probability based on these biomarkers. Further analyses on immune infiltration, regulatory networks, and drug predictions were performed for the identified biomarkers. CD63, IL17RA, and IL1R1 emerged as potential biomarkers, exhibiting significantly higher expression levels in the MDD cohort, with RT-qPCR validating these findings. A nomogram based on these biomarkers was also developed and validated, demonstrating its predictive capacity for MDD. Additionally, nine immune cell types, including activated T cells and eosinophils, showed significant differential infiltration between the MDD and control groups. ATF1 was identified as a common transcription factor for the three biomarkers. Notably, the shared miRNAs for CD63 and IL1R1 were hsa-miR-490-3p and hsa-miR-125a-3p. Furthermore, 50 potential drugs, such as verteporfin, etynodiol, and histamine, were predicted to target these biomarkers. The findings highlight CD63, IL17RA, and IL1R1 as key biomarkers for MDD, providing critical insights for diagnosis and the development of targeted therapies.