Novel predictive biomarkers for atonic postpartum hemorrhage as explored by proteomics and metabolomics

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.

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.

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).

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.