Risk of gestational diabetes mellitus in relation to plasma concentrations of amino acids and acylcarnitines: A nested case-control study

Abstract

AimsGestational diabetes mellitus (GDM) affects between 5 and 10% of all pregnancies in Canada and can lead to adverse health outcomes in both the mother and fetus. Amino acids (AA) and acylcarnitines (AC) have been identified as early biomarkers of type 2 diabetes but their usefulness in screening for GDM has yet to be demonstrated. MethodsWe conducted a nested case-control study involving 50 controls and 50 GDM cases diagnosed between the 24th and 28th week of gestation. Heparinized plasma samples were obtained during the first and early second trimester of pregnancy. Case and controls were matched according to date of recruitment, maternal age, gestational age at blood sampling as well as pre-pregnancy body mass index. Eight AA and eight AC were quantified using an ultra-high pressure liquid-chromatography quadrupole time-of-flight mass spectrometry platform. Conditional regression analyses adjusted for matching factors and smoking habits during pregnancy were performed to identify plasma metabolites associated with GDM risk. ResultsOdds ratio (OR) and 95% confidence interval (CI) for the prediction of GDM per one standard deviation increase of AA or AC in plasma levels were 0.25 (0.08–0.79) for butyrylcarnitine, 0.31 (0.12–0.79) for glutamic acid, 2.5 (1.2–5.3) for acetylcarnitine, 2.9 (1.3–6.8) for isobutyrylcarnitine and 5.3 (1.7–17.0) for leucine. These five metabolites were selected by stepwise conditional logistic regression to create a predictive model with an OR of 2.7 (1.5–4.9). ConclusionWhether the identified metabolites can predict the risk of developing GDM requires additional studies in a larger sample of pregnant women.