Michael S Lustgarten1, Lori Lyn Price2, Angela Chale1, Edward M Phillips1, Roger A Fielding3. 1. Nutrition, Exercise Physiology, and Sarcopenia Laboratory, Jean Mayer USDA Human Nutrition Research Center, Tufts University, Boston, Massachusetts. 2. The Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, and Tufts Clinical and Translational Science Institute, Tufts University, Boston, Massachusetts. 3. Nutrition, Exercise Physiology, and Sarcopenia Laboratory, Jean Mayer USDA Human Nutrition Research Center, Tufts University, Boston, Massachusetts. roger.fielding@tufts.edu.
Abstract
BACKGROUND: Metabolic profiling may provide insight into biologic mechanisms related to the maintenance of muscle and fat-free mass in functionally limited older adults. The objectives of the study were to characterize the association between thigh muscle cross-sectional area (CSA) and the fat-free mass index (FFMI; total lean mass/height(2)) with the serum metabolite profile, to further identify significant metabolites as associated with markers of insulin resistance or inflammation, and to develop a metabolite predictor set representative of muscle CSA and the FFMI in functionally limited older adults. METHODS: Multivariable-adjusted linear regression was used on mass spectrometry-based metabolomic data to determine significant associations between serum metabolites with muscle CSA and the FFMI in 73 functionally limited (Short Physical Performance Battery ≤ 10) older adults (age range: 70-85 years). Significant metabolites were further examined for associations with markers of insulin resistance (homeostasis model assessment of insulin resistance) or inflammation (tumor necrosis factor-α and interleukin-6). Multivariable-adjusted stepwise regression was used to develop a metabolite predictor set representative of muscle CSA and the FFMI. RESULTS: Seven branched chain amino acid-related metabolites were found to be associated with both muscle CSA and the FFMI. Separately, two metabolites were identified as insulin resistance-associated markers of the FFMI, whereas four metabolites were identified as inflammation-associated markers of either muscle CSA or the FFMI. Stepwise models identified combinations of metabolites to explain approximately 68% of the variability inherent in muscle CSA or the FFMI. CONCLUSIONS: Collectively, we report multiple branched chain amino acids and novel inflammation-associated tryptophan metabolites as markers of muscle CSA or the FFMI in functionally limited older adults.
RCT Entities:
BACKGROUND: Metabolic profiling may provide insight into biologic mechanisms related to the maintenance of muscle and fat-free mass in functionally limited older adults. The objectives of the study were to characterize the association between thigh muscle cross-sectional area (CSA) and the fat-free mass index (FFMI; total lean mass/height(2)) with the serum metabolite profile, to further identify significant metabolites as associated with markers of insulin resistance or inflammation, and to develop a metabolite predictor set representative of muscle CSA and the FFMI in functionally limited older adults. METHODS: Multivariable-adjusted linear regression was used on mass spectrometry-based metabolomic data to determine significant associations between serum metabolites with muscle CSA and the FFMI in 73 functionally limited (Short Physical Performance Battery ≤ 10) older adults (age range: 70-85 years). Significant metabolites were further examined for associations with markers of insulin resistance (homeostasis model assessment of insulin resistance) or inflammation (tumor necrosis factor-α and interleukin-6). Multivariable-adjusted stepwise regression was used to develop a metabolite predictor set representative of muscle CSA and the FFMI. RESULTS: Seven branched chain amino acid-related metabolites were found to be associated with both muscle CSA and the FFMI. Separately, two metabolites were identified as insulin resistance-associated markers of the FFMI, whereas four metabolites were identified as inflammation-associated markers of either muscle CSA or the FFMI. Stepwise models identified combinations of metabolites to explain approximately 68% of the variability inherent in muscle CSA or the FFMI. CONCLUSIONS: Collectively, we report multiple branched chain amino acids and novel inflammation-associated tryptophan metabolites as markers of muscle CSA or the FFMI in functionally limited older adults.
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