Serum Proteomic Signatures in Umbilical Cord Blood of Preterm Neonates Delivered by Women with Gestational Diabetes

Background

Women who develop diabetes during pregnancy are at higher risk of preterm birth. Here, we identified differentially expressed proteins (DEPs) in the serum of umbilical cord blood samples obtained from preterm neonates delivered by women with gestational diabetes to provide therapeutic targets for clinical drug development.

Materials and Methods

Umbilical cord blood was collected after delivery of preterm neonates by women with gestational diabetes and after delivery of healthy neonates by women without diabetes. DEPs in the serum samples were identified using liquid chromatography-tandem mass spectrometry. Gene Ontology (GO), cluster analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to determine the biological functions associated with these DEPs. Enzyme linked immunosorbent assay was used to confirm the key DEPs.

Results

We found that 21 proteins were significantly upregulated, and 51 proteins were significantly downregulated in 72 DEPs in serum samples. GO analyses showed that the DEPs were mainly associated with the GO terms cellular process, biological regulation, cellular anatomical entity, and binding. KEGG signaling pathway analysis indicated that most of the upregulated DEPs were associated with the complement and coagulation cascades, Staphylococcus aureus infection, pertussis, HIF-1 signaling pathway and PPAR signaling pathway and that most of the downregulated DEPs were associated with the complement and coagulation cascades, dilated cardiomyopathy, pathways in cancer, Chagas disease, and hypertrophic cardiomyopathy. The results of KEGG pathway annotation and enrichment analyses indicated that changes in the complement and coagulation cascades may be importantly associated with preterm delivery of neonates by women with gestational diabetes. The key DEPs were confirmed by enzyme linked immunosorbent assay.

Conclusion

Our proteomics and bioinformatics analyses identified several key proteins and the complement and coagulation cascades pathway that warrant further investigation as potential novel therapeutic targets in preterm delivery among women with gestational diabetes.

Early Prediction Model of Gestational Hypertension by Multi-Biomarkers Before 20 Weeks Gestation

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.

Absolute Quantification of Human Milk Caseins and the Whey/Casein Ratio during the First Year of Lactation

Whey proteins and caseins in breast milk provide bioactivities and also have different amino acid composition. Accurate determination of these two major protein classes provides a better understanding of human milk composition and function, and further aids in developing improved infant formulas based on bovine whey proteins and caseins. In this study, we implemented a LC-MS/MS quantitative analysis based on iBAQ label-free quantitation, to estimate absolute concentrations of α-casein, β-casein, and κ-casein in human milk samples (n = 88) collected between day 1 and day 360 postpartum. Total protein concentration ranged from 2.03 to 17.52 with a mean of 9.37 ± 3.65 g/L. Casein subunits ranged from 0.04 to 1.68 g/L (α-), 0.04 to 4.42 g/L (β-), and 0.10 to 1.72 g/L (α-), with β-casein having the highest average concentration among the three subunits. Calculated whey/casein ratio ranged from 45:55 to 97:3. Linear regression analyses show significant decreases in total protein, β-casein, κ-casein, total casein, and a significant increase of whey/casein ratio during the course of lactation. Our study presents a novel and accurate quantitative analysis of human milk casein content, demonstrating a lower casein content than earlier believed, which has implications for improved infants formulas.