Construction of diagnostic model and subtype analysis of major depressive disorder based on PANoptosis key genes

Major depressive disorder (MDD) is a serious neuropsychiatric disorder. While emerging evidence suggests that PANoptosis may play a role in MDD pathogenesis, the precise involvement of PANoptosis-related genes remains unclear.

The study conducted a systematic bioinformatics investigation utilizing the GSE98793 dataset. First, we identified differentially expressed PANoptosis-related genes (DE-PRGs). Second, Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis were carried out based on DE-PRGs. Additionally, Random Forest analysis, LASSO regression analysis, immune infiltration analysis, consensus cluster analysis, and single sample genome enrichment analysis were performed. Finally, the expression levels of PANoptosis key genes (PKGs) in MDD were verified using qRT-PCR.

Eight PKGs associated with MDD were identified: TRAF1, TNFSF13, TLR2, SH2D1A, RNF144B, ICAM1, HK2, and ADA. Moreover, these PKGs enabled construction of a diagnostic model for MDD PANoptosis risk and stratification of MDD patients into two distinct PANoptosis subtypes (cluster 1 and cluster 2) with differential immune characteristics. Notably, RNF144B and HK2 demonstrated neutrophil-stimulating potential and significant upregulation in MDD patients.

This study established a PANoptosis-based diagnostic framework for MDD and identified PANoptosis-stratified MDD subtypes, providing compelling evidence for PANoptosis-mediated immune dysregulation in MDD pathogenesis. These results offered a novel perspective for the diagnosis and management of MDD.