The alteration of ­­­­­­metabolic profiling in the second trimester of GDM and high risk pregnancy, and a nomogram for predicting macrosomia

Abstract

Objective Dyslipidemia in the second trimester and associated gestational diabetes are increasing worldwide. Carnitine plays a key role in lipid metabolism. We aim to describe metabolic profiling in the second trimester based on carnitine related metabolomics in GDM and high risk pregnancy, and to find the potential risk factors in GDM and candidate metabolites for diagnosing GDM induced macrosomia.Methods We have randomly investigated 450 pregnant women and their neonates in this retrospective study and 56 (12.4%) GDM cases were diagnosed. We used LC-MS/MS performing metabolic profiling about 12 amino acids and 31 acylcarnitines (containing C0) to assess circulating metabolites concentration in different subgroup according maternal and newborn clinical characteristic. We also calculated the correlation coefficient between maternal and newborn. GDM potential metabolic risk factors were screened by PLS-DA. Multivariate regression analyses were used in identifying independent risk factors for GDM and macrosomia. Based on these carnitine-related factors, a nomogram for estimating macrosomia was developed.Results We found 14 AA (Ala, Arg, Met, BCAA, AAA) and AC (C0, C2, C3, C4DC+C5OH, C5, C16, C18, C18:1) were increased in Age > 35 group, BMI ≥ 30, weight gain > 20 kg group, using assistant reproductive technology group, but the level of C0, Gly were decreased. In fetal clinical data, we obtained AA and AC level in fetuses are higher than their mothers and the metabolic trend was similar with maternal result. PLS-DA showed 15 metabolism(C0, LEU+ILE+PRO-OH, Phe, C18, TYR, etc)play main roles in class separation of GDM. Multivariate analysis showed pre-pregnancy BMI, weight gain, LEU+ILE+PRO-OH, TYR, C0/acylcarnitine, C0, C3, C16, C18 are independent risk factors associated with GDM. Finally, we developed a nomogram predicting macrosomia based on carnitine-related metabolic variables.Conclusion Metabolomics was proved as a powerful tool in identifying the metabolic alteration during the second trimester. These metabolic risk factors in GDM may help understanding of the underlying biochemical pathology of GDM and help physician diagnosing macrosomia.