Introduction to the DISRUPT postprandial database: subjects, studies and methodologies
Jackson, K.G., Clarke, D.T., Murray, P., Lovegrove, J.A., O'Malley, B., Minihane, A.M. and Williams, C.M. (2009) Introduction to the DISRUPT postprandial database: subjects, studies and methodologies. Genes and Nutrition, 5 (1). pp. 39-48. ISSN 1555-8932
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To link to this item DOI: 10.1007/s12263-009-0149-y
Dysregulation of lipid and glucose metabolism in the postprandial state are recognised as important risk factors for the development of cardiovascular disease and type 2 diabetes. Our objective was to create a comprehensive, standardised database of postprandial studies to provide insights into the physiological factors that influence postprandial lipid and glucose responses. Data were collated from subjects (n = 467) taking part in single and sequential meal postprandial studies conducted by researchers at the University of Reading, to form the DISRUPT (DIetary Studies: Reading Unilever Postprandial Trials) database. Subject attributes including age, gender, genotype, menopausal status, body mass index, blood pressure and a fasting biochemical profile, together with postprandial measurements of triacylglycerol (TAG), non-esterified fatty acids, glucose, insulin and TAG-rich lipoprotein composition are recorded. A particular strength of the studies is the frequency of blood sampling, with on average 10-13 blood samples taken during each postprandial assessment, and the fact that identical test meal protocols were used in a number of studies, allowing pooling of data to increase statistical power. The DISRUPT database is the most comprehensive postprandial metabolism database that exists worldwide and preliminary analysis of the pooled sequential meal postprandial dataset has revealed both confirmatory and novel observations with respect to the impact of gender and age on the postprandial TAG response. Further analysis of the dataset using conventional statistical techniques along with integrated mathematical models and clustering analysis will provide a unique opportunity to greatly expand current knowledge of the aetiology of inter-individual variability in postprandial lipid and glucose responses.