Evaluating neonatal cord serum metabolome in association with adolescent cardiometabolic risk factors
摘要
Risk factors for cardiometabolic disease may have fetal origins, but the biological pathways linking gestational conditions to these risk factors are only partially understood.
MethodsAmong 145 Cincinnati-based HOME Study mother-child dyads, we detected 14,384 cord serum metabolic features using liquid chromatography high-resolution mass spectrometry. We measured cardiometabolic risk factors, including visceral fat, serum triglyceride, high-density lipoprotein cholesterol (HDL), leptin, adiponectin, insulin concentration, glucose, and systolic blood pressure (SBP) at age 12 years. Using sparse Partial Least Squares Regression (sPLS-R), we simultaneously modeled the association of metabolic features with all 8 risk factors. We prioritized features with the highest sPLS-R-derived CM risk factor correlations for metabolic pathway enrichment analysis.
ResultsWe identified two groups of cardiometabolic risk factors in adolescents maximally associated with neonatal metabolic features. The first was visceral fat, triglycerides, HDL, insulin, and leptin; the second was glucose and SBP. The 178 metabolic features with the highest sPLS-R-derived feature-outcome correlations were enriched in 31 pathways related to short-chain fatty acid, vitamins C and B3, and amino acid metabolism, as well as glycolysis and gluconeogenesis.
ConclusionsWe identified 31 pathways that may help elucidate underlying mechanisms between fetal environmental stressors and the development of cardiometabolic risk factors.
ImpactUsing non-targeted metabolomics, we identified neonatal metabolic features linked to two groups of cardiometabolic risk factors in adolescents, suggesting distinct early-life CM risk trajectories and adolescent subphenotypes. One cardiometabolic group was characterized by higher visceral fat, triglycerides, insulin, leptin, as well as lower HDL; the other group was related to elevated glucose and systolic blood pressure. Using a variable selection and data-dimension reduction technique, these two groups were associated with 178 metabolic features and 31 biological pathways related to short-chain fatty acid, vitamins C and B3, and amino acid metabolism, as well as glycolysis and gluconeogenesis.