A metabolomic signature of maternal BMI is associated with pregnancy complications across two independent pregnancy cohorts

David Horner*, Rebecca Vinding, Tingting Wang, Mina Ali, Mario Lovric, Nicole Prince, Jessica Lasky-Su, Klaus Bønnelykke, Jakob Stokholm, Bo Chawes, Morten Arendt Rasmussen

*Corresponding author af dette arbejde

Abstract

BACKGROUND: Maternal obesity is increasingly common and linked to pregnancy complications, likely driven by underlying metabolic perturbations. This study investigates the association between maternal pre-pregnancy body mass index (BMI) and pregnancy complications through blood metabolomics, aiming to identify specific metabolites mediating these associations.

METHODS: Data from the Copenhagen Prospective Studies on Asthma in Childhood 2010 (COPSAC2010) and Vitamin D Antenatal Asthma Reduction Trial (VDAART) cohorts were used, with untargeted blood metabolomics performed on blood samples taken during early-, mid-, and late gestation. Associations were assessed using multivariable logistic regression and mediation analyses to explore metabolite pathways linking maternal BMI with pregnancy complications.

RESULTS: In the COPSAC2010 cohort, maternal pre-pregnancy BMI is associated with gestational diabetes (OR 1.90 [1.29-2.74], p = 6.75×10⁻⁴), caesarean section (OR 1.23 [1.03-1.47], p = 0.023), and birth induction (OR 1.42 [1.21-1.67], p = 2.86×10⁻⁵). A BMI-associated metabolite score is even more strongly associated with these complications and is independently associated with preeclampsia (OR 1.54 [1.04-2.26], p = 0.030). Validation in the VDAART cohort confirms the predictive value of the metabolite score for gestational diabetes (OR 2.10 [1.48-3.03], p = 4.97×10⁻⁵) and preeclampsia (OR 2.12 [1.32-3.47], p = 0.002), particularly in late gestation. Mediation analysis in COPSAC2010 identifies 16 metabolites as mediating the effect of BMI on gestational diabetes. A model based on this subset of metabolites significantly outperforms the full maternal BMI model in predicting outcomes during both early (p = 0.009) and late gestation (p = 0.016) in the VDAART cohort.

CONCLUSIONS: These findings suggest that integrating metabolomic profiling into prenatal care could improve the prediction and management of adverse pregnancy outcomes.

OriginalsprogEngelsk
Artikelnummer38
TidsskriftCommunications medicine
Vol/bind6
Udgave nummer1
ISSN2730-664X
DOI
StatusUdgivet - 17 dec. 2025

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