Metabolomic Profiles of Nonobese and Obese Women With Gestational Diabetes

Abstract

<p><strong>Context </strong><br></p><p>In non-pregnant population, nonobese individuals with obesity-related metabolome have increased risk for type 2 diabetes and cardiovascular diseases. The risk of these diseases is also increased after gestational diabetes. <br></p><p><strong>Objective </strong><br></p><p>This work aimed to examine whether nonobese (body mass index [BMI] < 30) and obese (BMI ≥ 30) women with gestational diabetes mellitus (GDM) and obese non-GDM women differ in metabolomic profiles from nonobese non-GDM controls. <br></p><p><strong>Methods</strong> <br></p><p>Levels of 66 metabolic measures were assessed in early (median 13, IQR 12.4-13.7 gestation weeks), and across early, mid (20, 19.3-23.0), and late (28, 27.0-35.0) pregnancy blood samples in 755 pregnant women from the PREDO and RADIEL studies. The independent replication cohort comprised 490 pregnant women. <br></p><p><strong>Results</strong> <br></p><p>Nonobese and obese GDM, and obese non-GDM women differed similarly from the controls across early, mid, and late pregnancy in 13 measures, including very low-density lipoprotein-related measures, and fatty acids. In 6 measures, including fatty acid (FA) ratios, glycolysis-related measures, valine, and 3-hydroxybutyrate, the differences between obese GDM women and controls were more pronounced than the differences between nonobese GDM or obese non-GDM women and controls. In 16 measures, including HDL-related measures, FA ratios, amino acids, and inflammation, differences between obese GDM or obese non-GDM women and controls were more pronounced than the differences between nonobese GDM women and controls. Most differences were evident in early pregnancy, and in the replication cohort were more often in the same direction than would be expected by chance alone. <br></p><p><strong>Conclusion</strong> <br></p><p>Differences between nonobese and obese GDM, or obese non-GDM women and controls in metabolomic profiles may allow detection of high-risk women for timely targeted preventive interventions.<br></p>