Abstract
OBJECTIVES: (1) Examine associations of a branched-chain amino acid (BCAA) metabolite pattern with metabolic risk across adolescence; (2) use Least Absolute Shrinkage and Selection Operator (LASSO) to identify novel metabolites of metabolic risk. METHODS: We used linear regression to examine associations of a BCAA score with change (∆) in metabolic biomarkers over 5-year follow-up in 179 adolescents 8-14 years at baseline. Next, we applied LASSO, a regularized regression technique well suited for reduction of high-dimensional data, to identify metabolite predictors of ∆biomarkers. RESULTS: In boys, the BCAA score corresponded with decreasing C-peptide, C-peptide-based insulin resistance (CP-IR), total cholesterol (TC), and low-density-lipoprotein cholesterol (LDL). In pubertal girls, the BCAA pattern corresponded with increasing C-peptide and leptin. LASSO identified asparagine as a predictor of decreasing C-peptide (β = -0.33) and CP-IR (β = -0.012), and acetyl-carnitine (β = 2.098), 4-hydroxyproline (β = -0.050), ornithine (β = -0.353), and α-aminoisobutyric acid (β = -0.793) as determinants of TC in boys. In girls, histidine was a negative determinant of TC (β = -0.033). CONCLUSIONS: The BCAA pattern was associated with ∆glycemia and ∆lipids in a sex-specific manner. LASSO identified asparagine, which influences growth hormone secretion, as a determinant of decreasing C-peptide and CP-IR in boys, and metabolites on lipid metabolism pathways as determinants of decreasing cholesterol in both sexes.