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 (Δ) in metabolic biomarkers over 5-years 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 Δbiomarkers.Results:In boys, the BCAA score corresponded with decreasing C-peptide, C-peptide insulin resistance (CP-IR), total (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 acetylcarnitine (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 Δglycemia and Δlipids 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.
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