Integrated vaginal secretion metabolomics and weighted co-expression network analysis identify biomarkers for early pregnancy diagnosis in sows

Background and Aim: Early pregnancy diagnosis is essential for improving reproductive efficiency and reducing non-productive days in commercial swine production. Conventional ultrasonography generally provides reliable pregnancy confirmation only 23–25 days after insemination, potentially missing the optimal opportunity to rebreed non-pregnant sows during the estrous cycle. Vaginal secretions represent a readily accessible and minimally invasive biological matrix that may reflect early pregnancy-associated metabolic alterations. This study aimed to identify metabolite biomarkers in vaginal secretions for early pregnancy diagnosis in sows using integrated untargeted metabolomics and weighted co-expression network analysis (WGCNA). Materials and Methods: Vaginal secretion samples were collected from healthy Landrace × Large White crossbred gilts at 18 days post insemination. Pregnancy status was confirmed by ultrasonography at 23–25 days post insemination, resulting in 15 pregnant and 10 non-pregnant animals. Untargeted metabolomic profiling was performed using liquid chromatography-mass spectrometry. Differential metabolites were identified using variable importance in projection ≥1 and adjusted p < 0.05, followed by WGCNA to identify pregnancy-associated metabolite modules and hub metabolites. Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis and receiver operating characteristic (ROC) curve analysis were performed to evaluate biological relevance and diagnostic performance.