Gestational Diabetes Mellitus Changes Human Colostrum Immune Composition.

Breast milk is considered a complete food for babies. Up to 7 days postpartum, it is known as colostrum, rich in immunological compounds, responsible for providing nutrition and ensuring immune protection. However, some maternal factors, such as gestational diabetes mellitus (GDM), can change the concentration of bioactive compounds present in the colostrum and may affect the development of the newborn's immune system. The effect of GDM on colostrum cytokine, chemokine, and growth factors is not well described. Thus, the present study evaluated whether the occurrence of GDM changes the concentration of biomarkers in the colostrum. A cross-sectional study was carried out on postpartum women who had healthy pregnancies and women who had been diagnosed with GDM. A sample of colostrum was collected for Luminex analysis. Our results showed that GDM mothers had higher secretion of cytokines and chemokines in the colostrum, with a higher concentration of IFN-g, IL-6, and IL-15, and a lower concentration of IL-1ra. Among growth factors, we identified a decreased concentration of GM-CSF in the colostrum of GDM mothers. Thus, the data obtained support the idea that the disease leads to immune alterations in the colostrum.

CCL3, CCL5, IL-15, IL-1Ra and VEGF compose a reliable algorithm to discriminate classes of adverse events following 17DD-YF primary vaccination according to cause-specific definitions.

In the present study, a range of serum biomarkers were quantified in suspected cases of adverse events following YF immunization (YEL-AEFI) to propose a reliable laboratorial algorithm to discriminate confirmed YEL-AEFI ("A1" class) from cases with other illnesses ("C" class). Our findings demonstrated that increased levels of CXCL8, CCL2, CXCL10, IL-1ß, IL-6 and TNF-α were observed in YEL-AEFI ("A1" and "C" classes) as compared to primary vaccines without YEL-AEFI [PV(day 3-28)] and reference range (RR) controls. Notably, increased levels of CCL3, CCL4, CCL2, CCL5, IL-1ß, IL-15, IL-1Ra and G-CSF were found in "A1" as compared to "C" class. Venn diagrams analysis allowed the pre-selection of biomarkers for further analysis of performance indices. Data demonstrated that CCL3, CCL5, IL-15 and IL-1Ra presented high global accuracy (AUC = 1.00) to discriminate "A1" from "C". Decision tree was proposed with a reliable algorithm to discriminate YEL-AEFI cases according to cause-specific definitions with outstanding overall accuracy (91%). CCL3, CCL5, IL-15 and IL-1Ra appears as root attributes to identify "A1" followed by VEGF as branch nodes to discriminate Wild Type YFV infection ("C(WT-YFV)") from cases with other illnesses ("C*"). Together, these results demonstrated the applicability of serum biomarker measurements as putative parameters towards the establishment of accurate laboratorial tools for complementary differential diagnosis of YEL-AEFI cases.