Lipid Profiling Predicts Health Risks for Pediatric Obesity

Associations between lipid profiles and cardiometabolic risk in children and adolescents with obesity have been identified in a study published in Nature Medicine. The cross-sectional and longitudinal analysis included 1,331 participants – 958 of whom were classified as overweight or obese. The study also involved a subgroup of 186 children undergoing a personalized, family-based obesity management program. Using mass spectrometry-based lipidomics, the research team identified 227 lipid species targets and examined their correlations with metabolic health outcomes.

Key findings revealed significant differences in lipid profiles between the overweight/obese group and the normal weight group. Elevated levels of ceramides (Cers), phosphatidylethanolamines (PEs), and phosphatidylinositols (PIs) were associated with increased insulin resistance and cardiometabolic risk, while sphingomyelins (SMs) were inversely associated with these risks. Furthermore, the study found that a panel of three lipids – PI(32:1), PE(36:1), and Cer(d42:0) – could predict hepatic steatosis with an area under the curve (AUC) of 0.79, comparable to traditional liver enzyme tests.

The longitudinal portion of the study highlighted the impact of nonpharmacological obesity management on lipid profiles. Children who reduced their body mass index (BMI) standard deviation score (SDS) exhibited reductions in Cers, triglycerides (TGs), and PEs. Notably, a decrease in BMI SDS correlated with improvements in liver enzymes and insulin resistance markers, such as HOMA-IR. Mediation analysis suggested that changes in lipid levels partially explained the association between BMI reduction and cardiometabolic improvements, with mediation proportions ranging from 5 percent to 23 percent.

Overall, the findings underscore the importance of early, personalized obesity management in reversing lipid dysregulation and improving metabolic health outcomes in children and adolescents. Study co-author, Cristina Legido-Quigley, commented: “The number of lipids that we detect and have signaling properties can be potentially used for new personalized medicine diagnoses. Some, like ceramides, are already in clinics and there are others yet to discover.”