Abstract
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.
Highlights
Obesity during pregnancy is associated with adverse maternal and neonatal outcomes, and with a higher risk of developing cardiovascular and metabolic diseases in childhood and adult stages
Maternal obesity is linked to dysregulation of adipose tissue (AT) metabolism [8], and an imbalance in the pro-oxidant-antioxidant system with an increase of reactive oxygen species (ROS) that results in oxidative stress [10,11,12,13]
Normal weight women were younger compared to obese women and had significantly higher concentrations of adiponectin and resistin together with lower MDA and Carbonylated proteins (CP) levels (p < 0.05)
Summary
Obesity during pregnancy is associated with adverse maternal and neonatal outcomes, and with a higher risk of developing cardiovascular and metabolic diseases in childhood and adult stages. Obesity programming of the offspring has been postulated to occur periconceptionally and at the end of pregnancy, when an increase in lipid and leptin expression is observed (reviewed by [4]). Maternal obesity is linked to dysregulation of adipose tissue (AT) metabolism [8], and an imbalance in the pro-oxidant-antioxidant system with an increase of reactive oxygen species (ROS) that results in oxidative stress [10,11,12,13]. ROS alter different cellular components such as proteins, lipids and DNA, generating oxidized biomolecules that can be used as biomarkers of oxidative stress. Carbonylated proteins (CP), malondialdehyde (MDA) and the oxidized base 8-oxo-2 -deoxyguanosine (8-oxodG) are indicators of protein oxidation, lipid peroxidation and DNA oxidation, respectively [13]
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