Integrative profiling of R-loop and immune microenvironment uncovers diagnostic biomarkers in major depressive disorder

The pathological mechanisms of Major Depressive Disorder (MDD) are complex. Current diagnostic methods are highly subjective, highlighting an urgent need for objective molecular biomarkers. R-loop (DNA:RNA hybrid) imbalance is implicated in various neurodegenerative diseases, yet its role in MDD and its interaction with the immune microenvironment remain unclear. This study aims to investigate the synergistic role of R-loop and the immune microenvironment in MDD through integrative analysis and to identify novel diagnostic biomarkers and molecular subtypes. Transcriptomic data from MDD patients and R-loop-related gene sets were obtained from public databases. Differentially expressed genes were screened, and a diagnostic model was constructed using LASSO regression. Consensus clustering was employed to identify molecular subtypes. Validation and mechanistic exploration were conducted using single-cell RNA-seq data, immune infiltration assessment, molecular docking, and experimental validation via Western blot and qRT-PCR in an MDD mouse model. Twenty-one R-loop-related diagnostic biomarkers for MDD were identified. Based on these markers, MDD patients were stratified into two distinct immune subtypes: Cluster A exhibited an immunosuppressive/reparative signature, while Cluster B showed a pro-inflammatory/cytotoxic phenotype. Single-cell analysis revealed the highest activity of R-loop-related genes in excitatory and inhibitory neurons. Molecular docking suggested that active compounds from traditional Chinese medicine may stably bind to the core target HSPH1. Furthermore, experimental validation confirmed the significant upregulation of DNAJC13 and UPF1, and downregulation of HSPH1 at both protein and mRNA levels in MDD mice. This study systematically reveals for the first time the potential role of the association between R-loop dysregulation and the immune microenvironment in MDD, identifies diagnostic biomarkers and immunologically heterogeneous molecular subtypes, and provides experimental evidence supporting these findings. It proposes a novel "R-loop–immune axis" framework for advancing precision diagnosis and treatment in MDD.