Prediction of preeclampsia based on maternal serum endoglin level in women with pregestational diabetes mellitus.

PURPOSE: To evaluate the level of soluble endoglin (sEng) in pregnant women with pregestational diabetes mellitus (DM) and to assess its predictive value for preeclampsia development. METHODS: Ninety pregnant women were enrolled in the study forming five comparison groups: type 1 DM (not planned, n = 20; planned, n = 20), type 2 DM (diet, n = 15; insulin therapy, n = 20), and the control group (n = 15). The primary outcome was clinically confirmed preeclampsia. Maternal serum concentrations of sEng were measured at 11+0-13+6 and 30+0-33+6 weeks. RESULTS: sEng level was elevated in all patients with pregestational DM compared to the control group. Its plasma concentration increased with gestational age and in case of preeclampsia development. In patients with type 1 DM, serum sEng level did not depend on the presence of preeclampsia. This is evidence of severe metabolic disorder and endothelial dysfunction in these patients. The addition of sEng level to logistic models considering established risk factors (body mass index + age + HbA1c level) in the first and third trimesters significantly improved their performance for preeclampsia prediction. CONCLUSIONS: Eng level may become an important marker for early prediction of preeclampsia in women with pregestational DM.

Placental expression of endoglin, placental growth factor, leptin, and hypoxia-inducible factor-1 in diabetic pregnancy and pre-eclampsia.

OBJECTIVE: To evaluate a level of expression of endoglin (Eng), leptin (Lep), placental growth factor (PlGF), and hypoxia-inducible factor-1alpha (HIF-1α) in placenta among women with pre-eclampsia and diabetes mellitus (DM), considering the method of glycemia correction and preconception care. MATERIALS AND METHODS: A retrospective cohort study was conducted. A total of 124 women were divided into following groups: type 1 DM (n = 40), type 2DM (n = 31), gestational DM (n = 33), pre-eclampsia without DM (PE) (n = 10) and the control group (n = 10). The histochemical study was performed by using primary monoclonal antibodies to Eng, PlGF, Lep, and HIF-1α (Abcam, UK). RESULTS: The highest level of placental expression of Eng was observed in the PE group (20.34%). The same trend was also typical for T1DM (not planned) and insulin-treated groups: T2DM and GDM. An amount of cell with an PlGF expression was significantly higher in the control group (12.2%), while the lowest was observed in the pre-eclampsia group (1.18%) and T1DM (not planned) (1.26%). The placental leptin expression within each DM group was increased among the patients with unplanned pregnancy and those who received insulin therapy. We observed the lowest Lep expression in the PE group (6.3%). High level of HIF-1α expression was detected in T1DM (not planned) (30.44%) and PE (29.64%) as compared to the control group (11.62%). In T2DM and GDM insulin groups, the HIF-1α expression was significantly higher as compared to diet groups. CONCLUSION: The obtained data show that DM and pre-eclampsia are associated with changes in angiogenic and metabolic placental factor expressions. The degree of changes depends on preconception care and the control of glycemia level during pregnancy.

Maternal serum leptin, adiponectin, resistin and monocyte chemoattractant protein-1 levels in different types of diabetes mellitus.

OBJECTIVE: Evaluation of serum concentration of leptin, adiponectin, resistin, and MCP-1 in pregnant patients with different types of diabetes mellitus (DM) considering preconception planning and method of DM correction in 11-14th and 30-34th weeks of pregnancy. STUDY DESIGN: Longitudinal, prospective study included 130 pregnant women divided into the following comparison groups: type 1 DM (T1DM, n = 40), type 2 DM (T2DM, n = 35), GDM (n = 40), and the control group (n = 15). The ELISA method defined the levels of leptin, resistin, adiponectin, and MCP-1 concentration in serum, which was assessed in 11-14th and 30-34th weeks of pregnancy. Statistical analysis was accomplished using SPSS 23.0 and "Prism 8-GraphPad" software. RESULTS: The leptin level in the 1st trimester was the highest in T2DM insulin group compared to the control due to gestational age, hence in the 3rd trimester in all groups its serum concentrations appeared higher than in healthy patients (p = 0.0001). In the 1st trimester leptin levels directly correlated with women's BMI, newborns' weight and macrosomia rate, in the 3rd trimester - with OGTT levels, HbA1c, gestational hypertension, and preeclampsia rates. Resistin levels in the 1st and 3rd trimesters were increased in almost all DM groups compared to the control group (p = 0.0001). The study established direct positive correlation between resistin and HbA1c, birth weight, and preeclampsia. In the 1st trimester, adiponectin demonstrated the lowest levels in T2DM insulin compared to T1DM and the control group (p = 0.0001) while in the 3rd trimester, adiponectin levels declined alongside gestational age in DM patients and all the groups compared to the control group (p < 0.05). Adiponectin negatively correlated with BMI, OGTT levels, and preeclampsia rate. MCP-1 levels in T2DM appeared higher than in T1DM patients and the control group in the 1st trimester, whereas in the 3rd trimester MCP-1 declined, correlating with BMI, preeclampsia and OGTT levels. CONCLUSION: High rate of adverse perinatal outcomes in diabetic pregnancy might be developed due to more severe metabolic failures and further disturbances of adipokines expression.

Molecular association of pathogenetic contributors to pre-eclampsia (pre-eclampsia associome).

BACKGROUND: Pre-eclampsia is the most common complication occurring during pregnancy. In the majority of cases, it is concurrent with other pathologies in a comorbid manner (frequent co-occurrences in patients), such as diabetes mellitus, gestational diabetes and obesity. Providing bronchial asthma, pulmonary tuberculosis, certain neurodegenerative diseases and cancers as examples, we have shown previously that pairs of inversely comorbid pathologies (rare co-occurrences in patients) are more closely related to each other at the molecular genetic level compared with randomly generated pairs of diseases. Data in the literature concerning the causes of pre-eclampsia are abundant. However, the key mechanisms triggering this disease that are initiated by other pathological processes are thus far unknown. The aim of this work was to analyse the characteristic features of genetic networks that describe interactions between comorbid diseases, using pre-eclampsia as a case in point. RESULTS: The use of ANDSystem, Pathway Studio and STRING computer tools based on text-mining and database-mining approaches allowed us to reconstruct associative networks, representing molecular genetic interactions between genes, associated concurrently with comorbid disease pairs, including pre-eclampsia, diabetes mellitus, gestational diabetes and obesity. It was found that these associative networks statistically differed in the number of genes and interactions between them from those built for randomly chosen pairs of diseases. The associative network connecting all four diseases was composed of 16 genes (PLAT, ADIPOQ, ADRB3, LEPR, HP, TGFB1, TNFA, INS, CRP, CSRP1, IGFBP1, MBL2, ACE, ESR1, SHBG, ADA). Such an analysis allowed us to reveal differential gene risk factors for these diseases, and to propose certain, most probable, theoretical mechanisms of pre-eclampsia development in pregnant women. The mechanisms may include the following pathways: [TGFB1 or TNFA]-[IL1B]-[pre-eclampsia]; [TNFA or INS]-[NOS3]-[pre-eclampsia]; [INS]-[HSPA4 or CLU]-[pre-eclampsia]; [ACE]-[MTHFR]-[pre-eclampsia]. CONCLUSIONS: For pre-eclampsia, diabetes mellitus, gestational diabetes and obesity, we showed that the size and connectivity of the associative molecular genetic networks, which describe interactions between comorbid diseases, statistically exceeded the size and connectivity of those built for randomly chosen pairs of diseases. Recently, we have shown a similar result for inversely comorbid diseases. This suggests that comorbid and inversely comorbid diseases have common features concerning structural organization of associative molecular genetic networks.