DIA‐Based Plasma Proteomic Profiling Identifies Novel Biomarkers for Diagnosis of Premature Ejaculation and Their Association With Dapoxetine Treatment Outcomes

BACKGROUND: Premature ejaculation (PE) is a highly prevalent male sexual dysfunction with undefined etiopathogenesis and a lack of validated objective biomarkers. Lifelong premature ejaculation (LPE) represents a more severe and persistent form of the disorder. Noninvasive plasma protein biomarkers for LPE diagnosis and their association with dapoxetine treatment outcomes remain insufficiently investigated. OBJECTIVES: This study aims to identify and validate novel plasma protein biomarkers for LPE via data-independent acquisition (DIA) proteomics, construct a diagnosis model and clinical nomogram, and explore the association between these biomarkers and clinical outcomes after dapoxetine treatment. METHODS: The study comprised a discovery phase and a validation phase from three centers. Initially, DIA proteomic analysis was performed on plasma samples from 5 LPE patients and 5 matched healthy controls. Differentially expressed proteins (DEPs) were identified and subsequently subjected to functional enrichment analyses, including GO, KEGG, and Reactome pathway analyses. Then, five core proteins were selected and validated using enzyme-linked immunosorbent assay (ELISA) in a larger cohort of 115 LPE patients and 60 healthy controls. LPE patients received 4-week on-demand dapoxetine treatment, with efficacy assessed by intravaginal ejaculatory latency time (IELT) and premature ejaculation diagnostic tool (PEDT) scores. The diagnostic model and the nomogram were constructed based on logistic regression, and the correlations between hub biomarkers and treatment efficacy were analyzed via the Spearman correlation analysis. RESULTS: Proteomic analysis identified 519 DEPs between groups, functionally enriched in neurotransmitter-related processes and metabolic pathways. ELISA validation confirmed significant differential expression of the five candidate proteins (PC, DDX39B, PPP2R2A, SLC8A2, HYI). The combined diagnostic model demonstrated excellent performance, with an area under the curve (AUC) of 0.902, superior to any single marker, and the derived nomogram showed excellent calibration and clinical net benefit. Furthermore, posttreatment levels of PC, DDX39B, PPP2R2A, and SLC8A2 were negatively correlated with IELT and positively correlated with PEDT scores, whereas HYI exhibited the opposite correlation pattern, suggesting that these biomarkers were associated with clinical outcomes after dapoxetine treatment. CONCLUSION: This study successfully identifies a panel of five plasma protein biomarkers for LPE, which not only facilitate accurate noninvasive diagnosis but also may be associated with clinical outcomes after dapoxetine treatment.