Elaine A Yu1, Tianwei Yu2, Dean P Jones3, Reynaldo Martorell1, Manuel Ramirez-Zea4, Aryeh D Stein1. 1. Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA. 2. Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA. 3. Clinical Biomarkers Laboratory, Division of Pulmonary, Allergy, and Critical Care Medicine, School of Medicine, Emory University, Atlanta, GA, USA. 4. Institute of Nutrition of Central America and Panama Research Center for the Prevention of Chronic Diseases, Institute of Nutrition of Central America and Panama, Guatemala City, Guatemala.
Abstract
BACKGROUND: The healthy human metabolome, including its physiological responses after meal consumption, remains incompletely understood. One major research gap is the limited literature assessing how human metabolomic profiles differ between fasting and postprandial states after physiological challenges. OBJECTIVES: Our study objective was to evaluate alterations in high-resolution metabolomic profiles following a standardized meal challenge, relative to fasting, in Guatemalan adults. METHODS: We studied 123 Guatemalan adults without obesity, hypertension, diabetes, metabolic syndrome, or comorbidities. Every participant received a standardized meal challenge (520 kcal, 67.4 g carbohydrates, 24.3 g fat, 8.0 g protein) and provided blood samples while fasting and at 2 h postprandial. Plasma samples were assayed by high-resolution metabolomics with dual-column LC [C18 (negative electrospray ionization), hydrophilic interaction LC (HILIC, positive electrospray ionization)] coupled to ultra-high-resolution MS. Associations between metabolomic features and the meal challenge timepoint were assessed in feature-by-feature multivariable linear mixed regression models. Two algorithms (mummichog, gene set enrichment analysis) were used for pathway analysis, and P values were combined by the Fisher method. RESULTS: Among participants (62.6% male, median age 43.0 y), 1130 features (C18: 777; HILIC: 353) differed between fasting and postprandial states (all false discovery rate-adjusted q < 0.05). Based on differing C18 features, top pathways included: tricarboxylic acid cycle (TCA), primary bile acid biosynthesis, and linoleic acid metabolism (all Pcombined < 0.05). Mass spectral features included: taurine and cholic acid in primary bile acid biosynthesis; and fumaric acid, malic acid, and citric acid in the TCA. HILIC features that differed in the meal challenge reflected linoleic acid metabolism (Pcombined < 0.05). CONCLUSIONS: Energy, macronutrient, and bile acid metabolism pathways were responsive to a standardized meal challenge in adults without cardiometabolic diseases. Our findings reflect metabolic flexibility in disease-free individuals.
BACKGROUND: The healthy human metabolome, including its physiological responses after meal consumption, remains incompletely understood. One major research gap is the limited literature assessing how human metabolomic profiles differ between fasting and postprandial states after physiological challenges. OBJECTIVES: Our study objective was to evaluate alterations in high-resolution metabolomic profiles following a standardized meal challenge, relative to fasting, in Guatemalan adults. METHODS: We studied 123 Guatemalan adults without obesity, hypertension, diabetes, metabolic syndrome, or comorbidities. Every participant received a standardized meal challenge (520 kcal, 67.4 g carbohydrates, 24.3 g fat, 8.0 g protein) and provided blood samples while fasting and at 2 h postprandial. Plasma samples were assayed by high-resolution metabolomics with dual-column LC [C18 (negative electrospray ionization), hydrophilic interaction LC (HILIC, positive electrospray ionization)] coupled to ultra-high-resolution MS. Associations between metabolomic features and the meal challenge timepoint were assessed in feature-by-feature multivariable linear mixed regression models. Two algorithms (mummichog, gene set enrichment analysis) were used for pathway analysis, and P values were combined by the Fisher method. RESULTS: Among participants (62.6% male, median age 43.0 y), 1130 features (C18: 777; HILIC: 353) differed between fasting and postprandial states (all false discovery rate-adjusted q < 0.05). Based on differing C18 features, top pathways included: tricarboxylic acid cycle (TCA), primary bile acid biosynthesis, and linoleic acid metabolism (all Pcombined < 0.05). Mass spectral features included: taurine and cholic acid in primary bile acid biosynthesis; and fumaric acid, malic acid, and citric acid in the TCA. HILIC features that differed in the meal challenge reflected linoleic acid metabolism (Pcombined < 0.05). CONCLUSIONS: Energy, macronutrient, and bile acid metabolism pathways were responsive to a standardized meal challenge in adults without cardiometabolic diseases. Our findings reflect metabolic flexibility in disease-free individuals.
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