Identification of Pyroptosis-Related Molecular Subtypes and Diagnostic Model development in Major Depressive Disorder.

Abstract

Major depressive disorder (MDD) is a prevalent psychological disorder associated with inflammation, with complex pathological mechanisms. Pyroptosis has been suggested to contribute to inflammation in central nervous system diseases. Little research, however, has examined what role pyroptosis played in MDD. In the present study, the differential expression pyroptosis-related genes (DE-PRGs) in MDD were identified from the GEO database (GSE98793 and GSE19738). Then, consensus clustering analysis was used to evaluate differences in MDD molecular subtypes characteristics based on PRGs. The characteristic diagnostic biomarkers for MDD were identified by Weighted Correlation Network Analysis (WGCNA) and multiple machine learning algorithms. Three intersection genes (GZMA, AKR1C3, and CD52) were obtained, which are expected to become potential biomarkers for MDD with excellent reliability and accuracy. Subsequently, the immune infiltration characteristics result indicated that the development of MDD is mediated by immune-related function, where three DE-PRGs were strongly related to the immune infiltration landscape of MDD. The biological experiments in vitro further proved that three unique PRGs are emerging as important players in MDD diagnosis. Our research aimed to provide novel ideas and biomarkers targeting MDD.