An ensemble method associates prepregnancy BMI and maternal ethnicity with key cord blood metabolomic changes in a multi-ethnic cohort from Hawaii

Maternal obesity poses significant risks to fetal health, influencing metabolomic profiles in newborn cord blood. Despite the growing application of metabolomics, limited research has explored how BMI-associated metabolite alterations may vary across different ethnic groups. We analyzed metabolomic data from a multi-ethnic cohort of 87 participants, including Native Hawaiian and Pacific Islander (NHPI) individuals. We used an ensemble machine learning model with a meta-learner to predict cord blood metabolomic changes associated with maternal BMI, the continuous obesity metric. The meta-learner integrated linear and nonlinear approaches and achieved significantly enhanced performance compared to the baseline linear regression model. In cord blood samples, glycine, serine, and threonine metabolism are activated by maternal obesity, while fatty acid biosynthesis and biosynthesis of unsaturated fatty acids are repressed. Some metabolites associated with these pathways show ethnicity-specific patterns. Compared to Asians and caucasians, 1,5-anhydrosorbitol, glycine, L-threonine show a unique increase from normal to obese maternally associated groups in NHPI, while PC(O-44:6) is significantly decreased in NHPI. The finding reveals the impact of maternal obesity on offspring health, and calls on future research to investigate the maternal and newborn health in underrepresented populations, such as NHPI.