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Obesity in pregnant women has been associated with an increased risk of maternal complications, including gestational diabetes mellitus (GDM), a process that is related to oxidative stress (OS). To evaluate the biomarkers of OS in red blood cells (RBCs), we assigned 80 pregnant women to one of three groups: control (n = 28), overweight (n = 26) and obese (n = 26). Then, we measured in plasma, the levels of glucose, triacylglycerol (TAG), insulin, free fatty acids (FFAs), leptin and cytokines (e.g. interleukin-6 [IL-6] and tumor necrosis factor-alpha [TNF-alpha]) and OS biomarkers, such as lipohydroperoxides (LHP), malondialdehyde (MDA) and protein carbonylation (PC) in RBCs. We found significant positive correlations between OS biomarkers, body mass index (BMI) and pregnancy progression. Seven (26.9%) obese women who were diagnosed with GDM at 24-28 weeks of pregnancy showed significantly increased concentrations of FFAs, insulin, leptin, TNF-alpha and biomarkers of OS measured at 12-13 weeks of gestation. We propose to quantify LHP, MDA and PC in membranes of erythrocytes as possible markers to diagnose GDM from weeks 12-14.

Maternal obesity has been related to adverse neonatal outcomes and fetal programming. Oxidative stress and adipokines are potential biomarkers in such pregnancies; thus, the measurement of these molecules has been considered critical. Therefore, we developed artificial neural network (ANN) models based on maternal weight status and clinical data to predict reliable maternal blood concentrations of these biomarkers at the end of pregnancy. Adipokines (adiponectin, leptin, and resistin), and DNA, lipid and protein oxidative markers (8-oxo-2'-deoxyguanosine, malondialdehyde and carbonylated proteins, respectively) were assessed in blood of normal weight, overweight and obese women in the third trimester of pregnancy. A Back-propagation algorithm was used to train ANN models with four input variables (age, pre-gestational body mass index (p-BMI), weight status and gestational age). ANN models were able to accurately predict all biomarkers with regression coefficients greater than R² = 0.945. P-BMI was the most significant variable for estimating adiponectin and carbonylated proteins concentrations (37%), while gestational age was the most relevant variable to predict resistin and malondialdehyde (34%). Age, gestational age and p-BMI had the same significance for leptin values. Finally, for 8-oxo-2'-deoxyguanosine prediction, the most significant variable was age (37%). These models become relevant to improve clinical and nutrition interventions in prenatal care., Competing Interests: Otilia Perichart-Perera is a speaker/consultant at the Nestlé Nutrition Institute in Mexico City. All other authors declare that there is no conflict of interest.

Background: Oxidative damage present in obese/overweight mothers may lead to further oxidative stress conditions or inflammation in maternal and cord blood samples. Thirty-four pregnant women/newborn pairs were included in this study to assess the presence of oxidative stress biomarkers and their relationship with serum cytokine concentrations. Oxidative stress biomarkers and antioxidant enzymes were compared between the mother/offspring pairs. The presence of 27 cytokines was measured in maternal and cord blood samples. Analyses were initially performed between all mothers and newborns and later between normal weight and mothers with overweight and obesity, and diabetic/non-diabetic women., Results: Significant differences were found in biomarker concentrations between mothers and newborns. Additionally, superoxide-dismutase activity was higher in pre-pregnancy overweight mothers compared to those with normal weight. Activity for this enzyme was higher in neonates born from mothers with normal pregestational weight compared with their mothers. Nitrites in overweight/obese mothers were statistically lower than in their offspring. Maternal free fatty acids, nitrites, carbonylated proteins, malondialdehyde and superoxide dismutase predicted maternal serum concentrations of IL-4, IL-13, IP-10 and MIP-1β. Arginase activity in maternal plasma was related to decreased concentrations of IL-4 and IL-1β in cord arterial blood. Increased maternal malondialdehyde plasma was associated with higher levels of IL-6 and IL-7 in the offspring., Conclusions: Oxidative stress biomarkers differ between mothers and offspring and can predict maternal and newborn cytokine concentrations, indicating a potential role for oxidative stress in foetal metabolic and immunologic programming. Moreover, maternal obesity and diabetes may affect maternal microenvironments, and oxidative stress related to these can have an impact on the placenta and foetal growth.

Maternal obesity (MO) causes maternal and fetal oxidative stress (OS) and metabolic dysfunction. We investigated whether supplementing obese mothers with resveratrol improves maternal metabolic alterations and reduces OS in the placenta and maternal and fetal liver. From weaning through pregnancy female Wistar rats ate chow (C) or a high-fat diet (MO). One month before mating until 19 days' gestation (dG), half the rats received 20 mg resveratrol/kg/d orally (Cres and MOres). At 19dG, maternal body weight, retroperitoneal fat adipocyte size, metabolic parameters, and OS biomarkers in the placenta and liver were determined. MO mothers showed higher body weight, triglycerides and leptin serum concentrations, insulin resistance (IR), decreased small and increased large adipocytes, liver fat accumulation, and hepatic upregulation of genes related to IR and inflammatory processes. Placenta, maternal and fetal liver OS biomarkers were augmented in MO. MOres mothers showed more small and fewer large adipocytes, lower triglycerides serum concentrations, IR and liver fat accumulation, downregulation of genes related to IR and inflammatory processes, and lowered OS in mothers, placentas, and female fetal liver. Maternal resveratrol supplementation in obese rats improves maternal metabolism and reduces placental and liver OS of mothers and fetuses in a sex-dependent manner. [ABSTRACT FROM AUTHOR]

Maternal obesity has been related to adverse neonatal outcomes and fetal programming. Oxidative stress and adipokines are potential biomarkers in such pregnancies; thus, the measurement of these molecules has been considered critical. Therefore, we developed artificial neural network (ANN) models based on maternal weight status and clinical data to predict reliable maternal blood concentrations of these biomarkers at the end of pregnancy. Adipokines (adiponectin, leptin, and resistin), and DNA, lipid and protein oxidative markers (8-oxo-2'-deoxyguanosine, malondialdehyde and carbonylated proteins, respectively) were assessed in blood of normal weight, overweight and obese women in the third trimester of pregnancy. A Back-propagation algorithm was used to train ANN models with four input variables (age, pre-gestational body mass index (p-BMI), weight status and gestational age). ANN models were able to accurately predict all biomarkers with regression coefficients greater than R² = 0.945. P-BMI was the most significant variable for estimating adiponectin and carbonylated proteins concentrations (37%), while gestational age was the most relevant variable to predict resistin and malondialdehyde (34%). Age, gestational age and p-BMI had the same significance for leptin values. Finally, for 8-oxo-2'-deoxyguanosine prediction, the most significant variable was age (37%). These models become relevant to improve clinical and nutrition interventions in prenatal care. [ABSTRACT FROM AUTHOR]

The aim of this study was to examine the efficacy of intensive medical nutrition therapy (MNT) plus metformin in preventing gestational diabetes mellitus (GDM) among high-risk Mexican women. An open-label randomized clinical trial was conducted. Inclusion criteria were pregnant women with three or more GDM risk factors: Latino ethnic group, maternal age >35 years, body mass index >25 kg/m2, insulin resistance, and a history of previous GDM, prediabetes, a macrosomic neonate, polycystic ovarian syndrome, or a first-degree relative with type 2 diabetes. Women before 15 weeks of gestation were assigned to group 1 (n = 45): intensive MNT-plus metformin (850 mg twice/day) or group 2 (n = 45): intensive MNT without metformin. Intensive MNT included individual dietary counseling, with ≤50% of total energy from high carbohydrates. The primary outcome was the GDM incidence according to the International Association of Diabetes Pregnancy Study Groups criteria. There were no significant differences in baseline characteristics and adverse perinatal outcomes between the groups. The GDM incidence was n = 11 (24.4%) in the MNT plus metformin group versus n = 7 (15.5%) in the MNT without metformin group: p = 0.42 (RR: 1.57 [95% CI: 0.67–3.68]). There is no benefit in adding metformin to intensive MNT to prevent GDM among high-risk Mexican women. Clinical trials registration: NCT01675310. [ABSTRACT FROM AUTHOR]

The primary aim of this study was to compare the prevalence of subclinical hypothyroidism (SCH) using two different cut-off levels for TSH values (≥2.5 mIU/L versus ≥4.1 mIU/L). The secondary objective was to analyze the clinical-biochemical characteristics in women with and without SCH. This was a retrospective cross-sectional study. In total, 1496 Mexican women with infertility were included: Group 1, women with TSH levels ranging between 0.3 and 2.49 mIU/L, n = 886; Group 2, women with TSH between 2.5 and 4.09 mIU/L, n = 390; and Group 3, women with TSH ≥4.1 mIU/L n = 220. SCH prevalence was 40.7% (CI 95%: 38.3–43.3%) with TSH cut-off ≥ 2.5 mIU/L, and 14.7% (CI 95%: 12.7–16.5%) with TSH cut-off ≥ 4.1 mIU/L, (p = 0.0001). The prevalence of overweight was higher in Group 2 than in Groups 1 and 3. Thyroid autoimmunity, obesity and insulin resistance were higher in Group 3 than in Group 1 (p < 0.05). No other differences were observed between groups. Conclusions: The prevalence of SCH in our selected patients increased almost three times using a TSH cut-off ≥ 2.5 mIU/L compared with a TSH cut-off ≥ 4.1 mIU/L. Women with TSH ≥4.1 mIU/L compared with TSH cut-off ≤ 2.5 mIU/L more often presented with obesity, thyroid autoimmunity and insulin resistance. [ABSTRACT FROM AUTHOR]