This study aimed to characterize metabolite differences and correlations between hypertensive disorders of pregnancy (HP) and gestational diabetes mellitus (GDM) using univariate, multivariate analyses, RF, and pathway analyses in a cross-sectional study. Dietary surveys were collected and targeted metabolomics was applied to measure levels of serum fatty acids, amino acids, and organic acids in 90 pregnant women at 24–28 weeks gestation at the First Affiliated Hospital of Harbin Medical University. Principal components analysis (PCA) and partial least squares-discriminatory analysis (PLS-DA) models were established to distinguish HP, GDM, and healthy, pregnant control individuals. Univariate and multivariate statistical analyses and Random Forest (RF) were used to identify and map co-metabolites to corresponding pathways in the disease states. Finally, risk factors for the disease were assessed by receiver operating characteristics (ROC) analysis. Dietary survey results showed that HP and GDM patients consumed a high-energy diet and the latter also consumed a high-carbohydrate and high-fat diet. Univariate analysis of clinical indices revealed HP and GDM patients had glycolipid disorders, with the former possessing more severe organ dysfunction. Subsequently, co-areas with significant differences identified by basic discriminant analyses and RF revealed lower levels of pyroglutamic acid and higher levels of 2-hydroxybutyric acid and glutamic acid in the GDM group. The number of metabolites increased in the HP group as compared to the healthy pregnant control group, including pyroglutamic acid, γ-aminobutyric acid (GABA), glutamic acid, oleic acid (C18:1), and palmitic acid (C16:0). ROC curves indicated that area under curve (AUC) for pyroglutamic acid in the GDM group was 0.962 (95% CI, 0.920–1.000), and the AUC of joint indicators, including pyroglutamic acid and GABA, in the HP group was 0.972 (95% CI, 0.938–1.000). Collectively, these results show that both GDM and HP patients at mid-gestation possessed dysregulated glucose and lipid metabolism, which may trigger oxidative stress via glutathione metabolism and biosynthesis of unsaturated fatty acids.

Background: Many investigations have explored the relationship between dietary intake and obesity risk/incidence, but they have only assessed obesity-related dietary patterns and/or single nutrients, not taking into account the diversity of dietary variables or multicollinearity among multiple nutrients. Therefore, this study aimed to use logistic LASSO regression combined with logistic regression to overcome multicollinearity, and overall investigate the possible association between dietary factors and obesity by the National Health and Nutrition Examination Survey (NHANES) (2007-2016). Method: Logistic LASSO regression was performed to examine the relationship between 59 dietary variables, and subsequently identify the most relevant variables associated with obesity. Then we used logistic regression to test the relevant variables, and finally used the receiver operating characteristic curve (ROC) to test the effect of logistic regression. Using the methods described above, we explored the relationship between dietary intake and obesity in 12135 NHANES participants (2007-2016). Result: The set of factors screened by LASSO regression, obesity risk factors including cholesterol and PFUA 20:4 (β>0); protective factors including vitamin E, caffeine, folate, vitamin C and copper (β<0). Ultimately, after multivariate unadjusted and adjusted logistic regression tests as well as ROC tests, four in the factor set associated with obesity were selected. Statistically significant dietary factors only folate (OR=0.80), vitamin C (OR=0.95), copper (OR=0.60) and PFUA 20:4 (OR=2.57) in adjusted logistic regression. Conclusion: Dietary intake of folate, vitamin C and copper negatively correlated with obesity, but PFUA 20:4 positively inversely. Necessary to assess the effective levels of folate, vitamin C and copper supplementation in obese subjects.

The onset of complex diseases at a later stage of life has been linked with maternal folic acid (FA) ingestion. However, little is known regarding the underlying molecular fingerprints of the offspring. We integrated proteomics-metabolomics profiles and analyzed the influence of maternal FA supplementation on the metabolism of adult offspring rats. Twenty pregnant female rats were randomly assigned to a FA supplementation (FolS group, 10 mg/kg FA) or control group (2 mg/kg FA respectively).Such an omics approach revealed that the dopaminergic synapse pathway, tricarboxylic acid cycle and neural development-related metabolites such as glutamic acid and γ-aminobutyric acid were significantly up-regulated in the FolS group, whereas pyruvic acid, oxalic acid and adipic acid were reduced. Maternal FA supplementation can cause alterations of metabolites and protein in the offspring rats.