Postprandial Dyslipidemia: Pathophysiology and Cardiovascular Disease Risk Assessment

Although the fed state predominates over the course of a day, the fasting lipid profile has traditionally been used to assess cardiovascular disease (CVD) risk. The nonfasting lipid profile may be more reflective of the daily circulating plasma lipids and simplifies lipid monitoring for patients, laboratories, and clinicians. Nonfasting triglyceride levels are also independently associated with cardiovascular events, leading to several clinical guidelines (e.g. in Denmark, the UK, Europe, and Canada) now recommending nonfasting lipid testing in the primary prevention setting. Obese and insulin resistant states are associated with intestinal chylomicron overproduction and subsequent remnant lipoprotein accumulation, leading to development of postprandial dyslipidemia in the fed state. Postprandial dyslipidemia is thought to be a major contributor of atherogenesis and shown to be an important CVD risk factor. As intestinal peptides (e.g. glucagon-like-peptide 1; GLP-1) have been shown to regulate chylomicron output, alterations in these signaling pathways in insulin resistant states may play a role in the development and/or progression of postprandial dyslipidemia. Although several advances have been made in understanding postprandial dyslipidemia in insulin resistance and its association with CVD, several limitations remain. Although nonfasting lipid measurements (i.e. random blood sampling) are now recommended in some countries, a more functional assessment of postprandial lipemia involves ingestion of a high-fat meal with subsequent blood collection over a specified time period (i.e. oral fat tolerance test). However, oral fat tolerance test methodology remains largely unstandardized and reference values to interpret postprandial values remain to be accurately established. Development of standardized methodologies and biomarker profiles for assessment of postprandial dyslipidemia in clinical practice will enable early and accurate identification of those at risk for CVD.