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Serum Metabolomics Unveils Novel Biomarkers Predicting Efficacy of Dapoxetine: A Prospective Study on Premature
Guangdong Hou1,2, Yu Zheng2,3, Ping Meng2
1Department of Urology, Tangdu Hospital, Fourth Military Medical University, Xi'an, China.
Background:
As the only approved oral medication for premature ejaculation (PE), dapoxetine faces a high discontinuation rate, primarily due to lower than expected efficacy. The impact of serum metabolites on PE treatment remains undetermined; therefore, we aimed to identify metabolites associated with dapoxetine efficacy.
Methods:
Clinical data and blood samples were collected from 116 patients with lifelong PE before 8 weeks of dapoxetine treatment. Serum was analyzed by untargeted metabolomics profiling. Efficacy was assessed with the Clinical Global Impression of Change (CGIC) scale: scores ≥ 1 were classified as the effective group and ≤ 0 as the ineffective group. Differential serum metabolites between the two groups were identified using the Mann-Whitney U test. Enrichment analysis determined metabolic pathways significantly associated with efficacy.
Results:
Compared to the ineffective group, indoleacrylic acid and (-)-riboflavin were significantly upregulated in the effective group, while 15-keto-13,14-dihydroprostaglandin A2, dienestrol, hippuric acid, and PC (16:0/16:0) were downregulated. The six metabolites showed a discriminatory ability of 0.646, 0.667, 0.633, 0.645, 0.651, and 0.635, respectively. Incorporating them significantly improved the accuracy of the model predicting efficacy (0.892 vs. 0.738, p = 0.001), suggesting that modulating these specific metabolites may be a novel strategy for PE treatment. Moreover, differential metabolic ions between the two groups were mostly enriched in the arachidonic acid metabolism pathway, indicating that this pathway may represent an additional route associated with dapoxetine response.
Conclusions:
This study revealed serum metabolites correlated with dapoxetine efficacy, paving the way for future research into novel therapeutic targets and personalized treatment strategies.