Changes of Plasma Phospholipid Fatty Acids Profiles in Pregnancy in Relation to the Diagnosis and Treatment of Gestational Diabetes Mellitus

Protocol for a randomized placebo-controlled clinical trial using pure palmitoleic acid to ameliorate insulin resistance and lipogenesis in overweight and obese subjects with prediabetes

Palmitoleic acid (POA), a nonessential, monounsaturated omega-7 fatty acid (C16:1n7), is a lipid hormone secreted from adipose tissue and has beneficial effects on distant organs, such as the liver and muscle. Interestingly, POA decreases lipogenesis in toxic storage sites such as the liver and muscle, and paradoxically increases lipogenesis in safe storage sites, such as adipose tissue. Furthermore, higher POA levels in humans are correlated with better insulin sensitivity, an improved lipid profile, and a lower incidence of type-2 diabetes and cardiovascular pathologies, such as myocardial infarction. In preclinical animal models, POA improves glucose intolerance, dyslipidemia, and steatosis of the muscle and liver, while improving insulin sensitivity and secretion. This double-blind placebo-controlled clinical trial tests the hypothesis that POA increases insulin sensitivity and decreases hepatic lipogenesis in overweight and obese adult subjects with pre-diabetes. Important to note, that this is the first study ever to use pure (>90%) POA with < 0.3% palmitic acid (PA), which masks the beneficial effects of POA. The possible positive findings may offer a therapeutic and/or preventative pathway against diabetes and related immunometabolic diseases.

The interplay between the gut microbiota and metabolism during the third trimester of pregnancy

The gut microbiota undergoes dynamic changes during pregnancy. The gut microbial and metabolic networks observed in pregnant women have not been systematically analyzed. The primary purpose of this study was to explore the alterations in the gut microbiota and metabolism during late pregnancy and investigate the associations between the gut microbiota and metabolism. A total of thirty healthy pregnant women were followed from 30 to 32 weeks of gestation to full term. Fecal samples were collected for microbiome analysis and untargeted metabolomic analysis. The characteristics of the gut microbiota were evaluated by 16S ribosomal RNA gene sequencing of the V3-V4 regions. The plasma samples were used for untargeted metabolomic analysis with liquid chromatography-tandem mass spectrometry. The interplay between the gut microbiota and metabolism was analyzed further by bioinformatics approaches. We found that the relative abundances of Sellimonas and Megamonas were higher at full term, whereas that of Proteobacteria was lower. The correlation network of the gut microbiota tended to exhibit weaker connections from 32 weeks of gestation to the antepartum timepoint. Changes in the gut microbiota during late pregnancy were correlated with the absorbance and metabolism of microbiota-associated metabolites, such as fatty acids and free amino acids, thereby generating a unique metabolic system for the growth of the fetus. Decreasing the concentration of specific metabolites in plasma and increasing the levels of palmitic acid and 20-hydroxyarachidonic acid may enhance the transformation of a proinflammatory immune state as pregnancy progresses.

Associations of Plasma Fatty Acid Patterns During Pregnancy With Gestational Diabetes Mellitus

Background

Limited studies have explored the difference of fatty acid profile between women with and without gestational diabetes mellitus (GDM), and the results were inconsistent. Individual fatty acids tend to be interrelated because of the shared food sources and metabolic pathways. Thus, whether fatty acid patters during pregnancy were related to GDM odds needs further exploration.

Objective

To identify plasma fatty acid patters during pregnancy and their associations with odds of GDM.

Methods

A hospital-based case-control study including 217 GDM cases and 217 matched controls was carried out in urban Wuhan, China from August 2012 to April 2015. All the participants were enrolled at the time of GDM screening and provided fasting blood samples with informed consent. We measured plasma concentrations of fatty acids by gas chromatography-mass spectrometry, and derived potential fatty acid patterns (FAPs) through principal components analysis. Conditional logistic regression and restricted cubic spline model were used to evaluate the associations between individual fatty acids or FAPs and odds of GDM.

Results

Twenty individual fatty acids with relative concentrations ≥0.05% were included in the analyses. Compared with control group, GDM group had significantly higher concentrations of total fatty acids, 24:1n-9, and relatively lower levels of 14:0, 15:0, 17:0, 18:0, 24:0, 16:1n-7, 20:1n-9,18:3n-6, 20:2n-6, 18:3n-3, 20:3n-3, 22:5n-3. Two novel patterns of fatty acids were identified to be associated with lower odds of GDM: (1) relatively higher odd-chain fatty acids, 14:0, 18:0, 18:3n-3, 20:2n-6, 20:3n-6 and lower 24:1n-9 and 18:2n-6 [adjusted odds ratio (OR) (95% confidence interval) (CI) for quartiles 4 vs. 1: 0.42 (0.23-0.76), P-trend = 0.002], (2) relatively higher n-3 polyunsaturated fatty acids, 24:0, 18:3n-6 and lower 16:0 and 20:4n-6 [adjusted OR (95% CI) for quartiles 4 vs. 1: 0.48 (0.26-0.90), P-trend = 0.018].

Conclusion

Our findings suggested that two novel FAPs were inversely associated with GDM odds. The combination of circulating fatty acids could be a more significant marker of GDM development than individual fatty acids or their subgroups.

Identification of differential metabolites using untargeted metabolomics between gestational diabetes and normal pregnant women

OBJECTIVE

To study the metabonomics differences between pregnant women with gestational diabetes mellitus (GDM) in the third trimester and those in a group without GDM by screening a group of highly efficient and sensitive markers for GDM and validating previously published early metabolic markers of GDM.

METHODS

A cross-sectional cohort study based on ultra performance liquid chromatography tandem mass spectrometry untargeted metabolomics analysis of serum samples collected from 59 pregnant women with GDM and 59 pregnant women without GDM.

RESULTS

A total of 121 metabolites were detected, and 27 were identified as differential metabolites between GDM and control. The combination of 27 metabolic peaks had area under curve (AUC) values of 0.90, 0.92, and 0.93 in the prediction models using support vector machine, partial least squares, and random forest, respectively. Finally, five metabolite biomarkers were selected to construct logistic regression models: L-valine, hypoxanthine, eicosapentaenoic acid, 2-amino-1,3,4-octadecanotriol, and choline. The AUC value of these metabolites was 0.769 between the GDM group and the control group.

CONCLUSIONS

The discovery of a group of differential metabolites in pregnant women with GDM in the third trimester and in pregnant women without GDM may facilitate the study of the pathologic mechanism of GDM; it may be possible to find an efficient and sensitive alternative GDM detection method.