Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics
Abstract Background Postpartum hemorrhage (PPH) is the leading cause of maternal mortality worldwide, with uterine atony accounting for approximately 70% of PPH cases. However, there is currently no effective prediction method to promote early management of PPH. In this study, we aimed to screen for...
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2025-01-01
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| Online Access: | https://doi.org/10.1186/s12884-025-07224-9 |
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| author | Jiangxue Qu Hai Jiang Huifeng Shi Nana Huang Jiawen Su Yan Zhang Lian Chen Yangyu Zhao |
| author_facet | Jiangxue Qu Hai Jiang Huifeng Shi Nana Huang Jiawen Su Yan Zhang Lian Chen Yangyu Zhao |
| author_sort | Jiangxue Qu |
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| description | Abstract Background Postpartum hemorrhage (PPH) is the leading cause of maternal mortality worldwide, with uterine atony accounting for approximately 70% of PPH cases. However, there is currently no effective prediction method to promote early management of PPH. In this study, we aimed to screen for potential predictive biomarkers for atonic PPH using combined omics approaches. Methods Collection of cervicovaginal fluid (CVF) samples from 27 women with atonic PPH and 32 women with normal delivery was performed for metabolomic (LC-MS/MS) and proteomic (LC-MS/MS) detection and subsequent confirmation experiments in this nested case-control study. Mass spectrum and enzyme-linked immunosorbent assays (ELISA) were used to validate significantly different metabolites and proteins for screening potential biomarkers of atonic PPH. Furthermore, multivariate logistic regressions were performed for the prediction of PPH using the identified biomarkers mentioned above, and the area under the curve (AUC) was computed. Results We identified 216 and 311 metabolites under positive and negative ion modes, respectively, as well as 1974 proteins. The PPH group had significant differences in metabolites and proteins belonging to the β-alanine metabolic pathway. Specifically, the PPH group had downregulation of critical metabolites, including histidine and protein dihydropyrimidine dehydrogenase (DPYD). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) functional enrichment analysis of significantly differentially expressed proteins revealed that atonic PPH was associated with T cell- and macrophage-related immune inflammatory responses. Furthermore, we verified that concentrations of histidine (350.85 ± 207.87 vs. 648.33 ± 400.87) and DPYD (4.01 ± 2.56 vs. 10.96 ± 10.71), and immune cell-related proteins such as CD163 (0.29 ± 0.19 vs. 1.51 ± 0.83) and FGL2 (5.98 ± 4.23 vs. 11.37 ± 9.42) were significantly lower in the PPH group. Finally, the AUC for independent prediction of PPH using CD163, histidine, DPYD, and FGL2 are 0.969 (0.897-1), 0.722 (0.536–0.874), 0.719 (0.528–0.864), and 0.697 (0.492–0.844), respectively. A relatively high predictive efficiency was obtained when using joint histidine, DPYD, CD163, and FGL2, with AUC = 0. 964 (0.822-1). Conclusions This study suggested that immune inflammation may play a role in the occurrence of PPH. The metabolite histidine and proteins of DPYD, CD163, and FGL2 in CVF were associated with uterine atony and could be used as predictive biomarkers for atonic PPH. |
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| institution | Kabale University |
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| language | English |
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| spelling | doaj-art-6dc2eccdf0744e82bb197de9d01af6682025-02-02T12:46:48ZengBMCBMC Pregnancy and Childbirth1471-23932025-01-0125111410.1186/s12884-025-07224-9Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomicsJiangxue Qu0Hai Jiang1Huifeng Shi2Nana Huang3Jiawen Su4Yan Zhang5Lian Chen6Yangyu Zhao7Department of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in ObstetricsDepartment of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in ObstetricsDepartment of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in ObstetricsDepartment of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in ObstetricsDepartment of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in ObstetricsDepartment of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in ObstetricsDepartment of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in ObstetricsDepartment of Obstetrics and Gynecology, National Clinical Research Center for Obstetrics and Gynecology, Peking University Third Hospital, Peking University Third Hospital), National Center for Healthcare Quality Management in ObstetricsAbstract Background Postpartum hemorrhage (PPH) is the leading cause of maternal mortality worldwide, with uterine atony accounting for approximately 70% of PPH cases. However, there is currently no effective prediction method to promote early management of PPH. In this study, we aimed to screen for potential predictive biomarkers for atonic PPH using combined omics approaches. Methods Collection of cervicovaginal fluid (CVF) samples from 27 women with atonic PPH and 32 women with normal delivery was performed for metabolomic (LC-MS/MS) and proteomic (LC-MS/MS) detection and subsequent confirmation experiments in this nested case-control study. Mass spectrum and enzyme-linked immunosorbent assays (ELISA) were used to validate significantly different metabolites and proteins for screening potential biomarkers of atonic PPH. Furthermore, multivariate logistic regressions were performed for the prediction of PPH using the identified biomarkers mentioned above, and the area under the curve (AUC) was computed. Results We identified 216 and 311 metabolites under positive and negative ion modes, respectively, as well as 1974 proteins. The PPH group had significant differences in metabolites and proteins belonging to the β-alanine metabolic pathway. Specifically, the PPH group had downregulation of critical metabolites, including histidine and protein dihydropyrimidine dehydrogenase (DPYD). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) functional enrichment analysis of significantly differentially expressed proteins revealed that atonic PPH was associated with T cell- and macrophage-related immune inflammatory responses. Furthermore, we verified that concentrations of histidine (350.85 ± 207.87 vs. 648.33 ± 400.87) and DPYD (4.01 ± 2.56 vs. 10.96 ± 10.71), and immune cell-related proteins such as CD163 (0.29 ± 0.19 vs. 1.51 ± 0.83) and FGL2 (5.98 ± 4.23 vs. 11.37 ± 9.42) were significantly lower in the PPH group. Finally, the AUC for independent prediction of PPH using CD163, histidine, DPYD, and FGL2 are 0.969 (0.897-1), 0.722 (0.536–0.874), 0.719 (0.528–0.864), and 0.697 (0.492–0.844), respectively. A relatively high predictive efficiency was obtained when using joint histidine, DPYD, CD163, and FGL2, with AUC = 0. 964 (0.822-1). Conclusions This study suggested that immune inflammation may play a role in the occurrence of PPH. The metabolite histidine and proteins of DPYD, CD163, and FGL2 in CVF were associated with uterine atony and could be used as predictive biomarkers for atonic PPH.https://doi.org/10.1186/s12884-025-07224-9ProteomicMetabonomicAtonic postpartum hemorrhageMaternal mortalityPrediction |
| spellingShingle | Jiangxue Qu Hai Jiang Huifeng Shi Nana Huang Jiawen Su Yan Zhang Lian Chen Yangyu Zhao Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics BMC Pregnancy and Childbirth Proteomic Metabonomic Atonic postpartum hemorrhage Maternal mortality Prediction |
| title | Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics |
| title_full | Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics |
| title_fullStr | Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics |
| title_full_unstemmed | Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics |
| title_short | Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics |
| title_sort | novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics |
| topic | Proteomic Metabonomic Atonic postpartum hemorrhage Maternal mortality Prediction |
| url | https://doi.org/10.1186/s12884-025-07224-9 |
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