Metabolomic Changes Upon Conjugated Linoleic Acid Supplementation and Predictions of Body Composition Responsiveness

Abstract

Context: Conjugated linoleic acid (CLA) may optimize body composition, yet mechanisms underlining its benefits are not clear in humans. Objective: We aimed to reveal the CLA-induced changes in the plasma metabolome associated with body composition improvement and the predictive performance of baseline metabolome on intervention responsiveness. Methods: Plasma metabolome from overnight fasted samples at pre- and post-intervention of 65 participants in a 12-week randomized, placebo-controlled trial (3.2 g/day CLA vs 3.2 g/day sunflower oil) were analyzed using untargeted LC-MS metabolomics. Mixed linear model and machine learning were applied to assess differential metabolites between treatments, and to identify optimal panel (based on baseline conventional variables vs metabolites) predicting responders of CLA-derived body composition improvement (increased muscle variables or decreased adiposity variables) based on dual-energy x-ray absorptiometry. Results: Compared with placebo, CLA altered 57 metabolites (P < 0.10) enriched in lipids/lipid-like molecules including glycerophospholipids (n = 7), fatty acyls (n = 6), and sphingolipids (n = 3). CLA-upregulated cholic acid (or downregulated aminopyrrolnitrin) was inversely correlated with changes in muscle and adiposity variables. Inter-individual variability in response to CLA-derived body composition change. The areas under the curves of optimal metabolite panels were higher than those of optimal conventional panels in predicting favorable response of waist circumference (0.93 [0.82-1.00] vs 0.64 [0.43-0.85]), visceral adiposity index (0.95 [0.88-1.00] vs 0.58 [0.35-0.80]), total fat mass (0.94 [0.86-1.00] vs 0.69 [0.51-0.88]) and appendicular fat mass (0.97 [0.92-1.00] vs 0.73 [0.55-0.91]) upon CLA supplementation (all FDR P < 0.05). Conclusion: Post-intervention metabolite alterations were identified, involving in lipid/energy metabolism, associated with body composition changes. Baseline metabolite profiling enhanced the prediction accuracy for responsiveness of CLA-induced body composition benefits.