Effects of maternal western-style diet on amniotic fluid volume and amnion VEGF profiles in a nonhuman primate model

Short-term Western-style diet negatively impacts reproductive outcomes in primates

A maternal Western-style diet (WSD) is associated with poor reproductive outcomes, but whether this is from the diet itself or underlying metabolic dysfunction is unknown. Here, we performed a longitudinal study using regularly cycling female rhesus macaques (n = 10) that underwent 2 consecutive in vitro fertilization (IVF) cycles, one while consuming a low-fat diet and another 6–8 months after consuming a high-fat WSD. Metabolic data were collected from the females prior to each IVF cycle. Follicular fluid (FF) and oocytes were assessed for cytokine/steroid levels and IVF potential, respectively. Although transition to a WSD led to weight gain and increased body fat, no difference in insulin levels was observed. A significant decrease in IL-1RA concentration and the ratio of cortisol/cortisone was detected in FF after WSD intake. Despite an increased probability of isolating mature oocytes, a 44% reduction in blastocyst number was observed with WSD consumption, and time-lapse imaging revealed delayed mitotic timing and multipolar divisions. RNA sequencing of blastocysts demonstrated dysregulation of genes involved in RNA binding, protein channel activity, mitochondrial function and pluripotency versus cell differentiation after WSD consumption. Thus, short-term WSD consumption promotes a proinflammatory intrafollicular microenvironment that is associated with impaired preimplantation development in the absence of large-scale metabolic changes.

Pre-Pregnancy Obesity vs. Other Risk Factors in Probability Models of Preeclampsia and Gestational Hypertension

In the face of the obesity epidemic around the world, attention should be focused on the role of maternal obesity in the development of pregnancy. The purpose of this analysis was to evaluate the prediction of preeclampsia (PE) and isolated gestational hypertension (GH) for a number of maternal factors, in order to investigate the importance of pre-pregnancy obesity (body mass index, BMI ≥ 30 kg/m²), compared to other risk factors (e.g., prior PE, pregnancy weight gain (GWG), infertility treatment, interpregnancy interval, family history, the lack of vitamin supplementation, urogenital infection, and socioeconomic factors). In total, 912 women without chronic diseases were examined in a Polish prospective cohort of women with a singleton pregnancy (recruited in 2015–2016). Separate analyses were performed for the women who developed GH (n = 113) vs. 775 women who remained normotensive, as well as for those who developed PE (n = 24) vs. 775 controls. The probability of each disease was assessed for the base prediction model (age + primiparity) and for the model extended by one (test) variable, using logistic regression. Three measures were used to assess the prediction: area under curve (AUC) of the base and extended model, integrated discrimination improvement (IDI) (the index shows the difference between the value of the mean change in the predicted probability between the group of sick and healthy women when a new factor is added to the model), and net reclassification improvement (NRI) (the index focuses on the reclassification table describing the number of women in whom an upward or downward shift in the disease probability value occurred after a new factor had been added, including results for healthy and sick women). In the GH prediction, AUC increased most strongly when we added BMI (kg/m²) as a continuous variable (AUC = 0.716, p < 0.001) to the base model. The highest IDI index was obtained for prior GH/PE (IDI = 0.068, p < 0.001). The addition of BMI as a continuous variable or BMI ≥ 25 kg/m² improved the classification for healthy and sick women the most (NRI = 0.571, p < 0.001). In the PE prediction, AUC increased most strongly when we added BMI categories (AUC = 0.726, p < 0.001) to the base model. The highest IDI index was obtained for prior GH/PE (IDI = 0.050, p = 0.080). The addition of BMI categories improved the classification for healthy and sick women the most (NRI = 0.688; p = 0.001). After summing up the results of three indexes, the probability of hypertension in pregnancy was most strongly improved by BMI, including BMI ≥ 25 kg/m² for the GH prediction, and BMI ≥ 30 kg/m² for the PE prediction. Main conclusions: Pre-pregnancy BMI was the most likely factor to increase the probability of developing hypertension in pregnancy, compared to other risk factors. Hierarchies of PE and GH risk factors may suggest different (or common) mechanisms of their development.