1. Plasma metabolomics profiles suggest beneficial effects of a low–glycemic load dietary pattern on inflammation and energy metabolism
- Author
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Meredith A. J. Hullar, Ali Shojaie, Johanna W. Lampe, Danijel Djukovic, Paul D. Lampe, Mario Kratz, Katie J Osterbauer, Marian L. Neuhouser, Haiwei Gu, Timothy W. Randolph, Daniel Raftery, Sandi L. Navarro, and Aliasghar Tarkhan
- Subjects
Adult ,Male ,0301 basic medicine ,Adolescent ,Metabolite ,Medicine (miscellaneous) ,Blood sugar ,Creatine ,Young Adult ,03 medical and health sciences ,chemistry.chemical_compound ,medicine ,Humans ,Metabolomics ,Carnitine ,Food science ,Refined grains ,Inflammation ,030109 nutrition & dietetics ,Nutrition and Dietetics ,Glycemic Load ,Tryptophan ,Feeding Behavior ,Diet ,Glutamine ,Original Research Communications ,030104 developmental biology ,chemistry ,Metabolome ,Female ,Energy Metabolism ,Biomarkers ,Kynurenine ,medicine.drug - Abstract
BACKGROUND: Low–glycemic load dietary patterns, characterized by consumption of whole grains, legumes, fruits, and vegetables, are associated with reduced risk of several chronic diseases. METHODS: Using samples from a randomized, controlled, crossover feeding trial, we evaluated the effects on metabolic profiles of a low-glycemic whole-grain dietary pattern (WG) compared with a dietary pattern high in refined grains and added sugars (RG) for 28 d. LC-MS-based targeted metabolomics analysis was performed on fasting plasma samples from 80 healthy participants (n = 40 men, n = 40 women) aged 18–45 y. Linear mixed models were used to evaluate differences in response between diets for individual metabolites. Kyoto Encyclopedia of Genes and Genomes (KEGG)–defined pathways and 2 novel data-driven analyses were conducted to consider differences at the pathway level. RESULTS: There were 121 metabolites with detectable signal in >98% of all plasma samples. Eighteen metabolites were significantly different between diets at day 28 [false discovery rate (FDR)
- Published
- 2019