Proteomic profiling of acute postprandial responses to five single-meal challenges and implications for cardiometabolic health

Diet influences human health, but the acute molecular effects of individual meals remain incompletely understood. In this prospective crossover study, 20 healthy volunteers underwent five single-meal challenges: high-glucose/OGTT, ketogenic, high-fat high-calorie (HFHC), normal-fat normal-calorie (NFNC), and low-fat low-calorie (LFLC). We collected 500 plasma and 500 urine samples and performed high-throughput proteomic profiling. Mendelian randomization was used to assess the genetic relevance of diet-responsive proteins to cardiometabolic outcomes. The trial was registered at ClinicalTrials.gov (NCT04984642). Each meal induced a distinct proteomic response. Compared with LFLC, the ketogenic meal increased PPBP, SRGN, GSTO1, BLVRB, MIF, and S100A4, implicating platelet activation, inflammation, and oxidative-stress-related processes. Compared with the high-glucose challenge, HFHC altered JUP, DSP, APOA5, TAGLN2, RAP1B, and TMSB4X, involving cell adhesion, cytoskeletal organization, lipid transport, and endothelial-related pathways. The high-glucose challenge reduced PRDX1, CAT, and SOD1, suggesting acute perturbation of redox-defense pathways. Exploratory urinary proteomic analyses showed complementary meal-specific responses, including enrichment of hydrogen peroxide catabolism and cellular oxidant detoxification. Participants with overweight/obesity had higher baseline CRP, LILRA3, and SERPINE1, lower ADIPOQ, and altered postprandial protein-triglyceride associations, including distinct APOA5- and PGM1-triglyceride correlations after HFHC. Single meals induced acute, diet-specific plasma and urinary proteomic responses involving pathways relevant to inflammation, oxidative stress, lipid metabolism, platelet activation, and vascular function. These findings provide mechanistic insights into potential links between meal composition and cardiometabolic health. The publicly available postprandial plasma and urine proteomics dataset provides a valuable resource for studying how daily eating may influence health.