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Metabolic profiles in hypertensive disorders of pregnancy and gestational diabetes: a prospective longitudinal study
Lorenzo Annesi1, Davide Agnoletti1, Emiliana Angilletta2
1Department of Medical and Surgical Sciences, University of Bologna, Bologna, Italy; Cardiovascular Internal Medicine Unit, IRCCS AOU S. Orsola, Bologna, Italy.
Background And Aims:
Altered lipid and metabolic indices have been linked to cardiometabolic complications of pregnancy. However, longitudinal changes and differences across healthy pregnancies, gestational diabetes mellitus (GDM), and hypertensive disorders of pregnancy (HDP) remain incompletely defined. This study aimed to characterize metabolic trajectories across healthy pregnancies, GDM, and HDP.
Methods And Results:
We studied 166 nulliparous women at 11-13 and 24-27 weeks' gestation. Laboratory profiling included uric acid, creatinine, HDL cholesterol, triglycerides (TG), transaminases, total bilirubin, high-sensitivity C-reactive protein, lipoprotein(a), and apolipoprotein B (ApoB). Group and temporal differences were assessed by ANOVA, and logistic regression evaluated associations with GDM and HDP. HDP tended to be associated with higher triglycerides at both timepoints and higher total cholesterol at the first timepoint, although not consistently in all adjusted models. HDL cholesterol at the second timepoint was inversely associated with GDM across all models. ApoB, lipoprotein(a) and LDL cholesterol were not associated with either HDP or GDM. The triglyceride-to-HDL ratio tended to be associated with HDP at both timepoints and with GDM at the second timepoint although these associations were not retained after adjustment. The ApoB/HDL ratio at the second timepoint and its increase over gestation, was consistently associated with GDM but not with HDP.
Conclusion:
GDM and HDP may be associated with insulin resistance, with GDM tending to be associated with lower HDL cholesterol and HDP with higher triglycerides. However, these differences were modest and not consistent across all models, underscoring the need for larger studies to validate these findings and define clinically actionable markers.
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