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Background Gestational hypertension (GH), a hypertensive disorder of pregnancy (HDP), is a leading cause of maternal and fetal mortality due to the lack of clarity on its exact etiology and clinically feasible prediction models. This study was performed to discover novel biomarkers before 20 weeks gestation and thereby construct an early GH prediction model. Methods This study was designed based on differentially expressed protein screening followed by clinical validation. In the screening phase, a nested case-controlled study was conducted by plasma proteomic analyses using label-free LC-MS/MS and plasma samples from seven pre-GH cases before 20-week gestation and seven age- and gestational week-matched controls. In the validation phase, 10 proteins with differential expression in the screening phase were validated by ELISA or electrochemiluminescence in an independent study consisting of 29 pre-GH cases before 20-week gestation and 29 matched controls. Results In the screening phase, 149 proteins were found to be differentially expressed between the two groups and were predominantly involved in complement and coagulation cascades, platelet degranulation and positive regulation of cell motility. Further validation showed that serpin family C member 1 (SERPINC1), serpin family A member 5 (SERPINA5), complement factor H-related protein 5 (CFHR5), clusterin, cytokeratin 18 (CK18) and histidine-rich glycoprotein (HRG) levels were significantly higher in women who later developed GH compared to women with uncomplicated pregnancies ( P <0.05). Binary logistic regression analysis was used to determine the combination efficacy of models for early prediction of GH. The model with a combination of SERPINC1, CK18 and HRG had a significantly better discriminatory power (AUC = 0.91, 95% CI 0.83–0.98) compared to the models with those proteins alone as independent predictors of GH. Conclusion Plasma levels of SERPINC1, SERPINA5, CFHR5, clusterin, CK18 and HRG are potential novel predictive biomarkers of GH, and a prediction model using a combination of SERPINC1, CK18 and HRG has good discriminatory performance for GH before 20 weeks gestation.

Gestational diseases are associated with altered intestinal microbiota in pregnant women. Characterizing the gut microbiota of gestational anemia (GA) may describe a novel role of gut microbial abnormality in GA. In this study, we investigated differences in gut microbiota between GA patients and healthy pregnant women from the first trimester (n = 24 vs. 54) and the third trimester (n = 30 vs. 56) based on the 16S rRNA gene sequencing method. No statistically significant differences in α-diversity were identified between GA patients and controls in the first trimester of pregnancy, whereas the Shannon index and observed OTUs were significantly lower in GA patients than in healthy controls in the third trimester. Distance-based redundancy analysis revealed striking differences in microbial communities in the third trimester between GA patients and controls. Four genera were significantly different in relative abundance between GA patients and healthy controls, while 12 genera differentiated significantly between GA patients and healthy controls in the third trimester. At the operational taxonomic unit (OTU) level, 17 OTUs and 30 OTUs were identified to be different between GA patients and healthy controls in the first and third trimesters, respectively. Changes in gut microbial composition of GA patients suggest a potential relation with GA, and provide insights into the prediction and intervention of gestational anemia.

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