IntroductionBody fat distribution is strongly associated with cardiometabolic disease (CMD), but the relative importance of hepatic fat as an underlying driver remains unclear. Here, we applied a systems biology approach to compare the clinical and molecular subnetworks that correlate with hepatic fat, visceral fat, and abdominal subcutaneous fat distribution.Research design and methodsThis was a cross-sectional sub-study of 283 children/adolescents (7–19 years) from the Yale Pediatric NAFLD Cohort. Untargeted, high-resolution metabolomics (HRM) was performed on plasma and combined with existing clinical variables including hepatic and abdominal fat measured by MRI. Integrative network analysis was coupled with pathway enrichment analysis and multivariable linear regression (MLR) to examine which metabolites and clinical variables associated with each fat depot.ResultsThe data divided into four communities of correlated variables (|r|>0.15, p<0.05) after integrative network analysis. In the largest community, hepatic fat was associated with eight clinical biomarkers, including measures of insulin resistance and dyslipidemia, and 878 metabolite features that were enriched predominantly in amino acid (AA) and lipid pathways in pathway enrichment analysis (p<0.05). Key metabolites associated with hepatic fat included branched-chain AAs (valine and isoleucine/leucine), aromatic AAs (tyrosine and tryptophan), serine, glycine, alanine, and pyruvate, as well as several acylcarnitines and glycerophospholipids (all q<0.05 in MLR adjusted for covariates). The other communities detected in integrative network analysis consisted of abdominal visceral, superficial subcutaneous, and deep subcutaneous fats, but no clinical variables, fewer metabolite features (280, 312, and 74, respectively), and limited findings in pathway analysis.ConclusionsThese data-driven findings show a stronger association of hepatic fat with key CMD risk factors compared with abdominal fats. The molecular network identified using HRM that associated with hepatic fat provides insight into potential mechanisms underlying the hepatic fat–insulin resistance interface in youth.
Integrative network analysis of TCGA data for ovarian cancer
