Vitamin A Absorption Efficiency Determined by Compartmental Analysis of Postprandial Plasma Retinyl Ester Kinetics in Theoretical Humans

ABSTRACT Background Better methods are needed for determining vitamin A absorption efficiency in humans to support development of dietary recommendations and to improve the accuracy of predictions of vitamin A status. Objectives We developed and evaluated a method for estimating vitamin A absorption efficiency based on compartmental modeling of theoretical data on postprandial plasma retinyl ester (RE) kinetics. Methods We generated data on plasma RE and retinol kinetics (30 min to 8 h or 56 d, respectively) after oral administration of labeled vitamin A for 12 theoretical adults with a range of values assigned for vitamin A absorption (55–90%); we modeled all data to obtain best-fit values for absorption and other parameters using Simulation, Analysis, and Modeling software. We then modeled RE data only (16 or 10 samples), with or without added random error, and compared assigned to predicted absorption values. We also compared assigned values to areas under RE response curves (RE AUCs). Results We confirmed that a unique value for vitamin A absorption cannot be identified by modeling plasma retinol tracer kinetics. However, when RE data were modeled, predicted vitamin A absorptions were within 1% of assigned values using data without error and within 12% when 5% error was included. When the sample number was reduced, predictions were still within 13% for 10 of the 12 subjects and within 23% overall. Assigned values for absorption were not correlated with RE AUC (P = 0.21). Conclusions We describe a feasible and accurate method for determining vitamin A absorption efficiency that is based on compartmental modeling of plasma RE kinetic data collected for 8 h after a test meal. This approach can be used in a clinical setting after fasting subjects consume a fat-containing breakfast meal with a known amount of vitamin A or a stable isotope label.

Validation of a Method for Estimating Vitamin A Absorption Efficiency Based on Compartmental Analysis of Post-Prandial Plasma Retinyl Ester Kinetics

Objectives Because good methods are not available to estimate vitamin A (VA) absorption, we evaluated an approach based on modeling retinyl ester response to an oral VA dose. Methods We generated data for 12 theoretical subjects, assigning values for VA absorption, stores, and kinetic parameters; we used WinSAAM (Simulation, Analysis and Modeling software) to simulate data (without and with 5% average error) for plasma chylomicron retinyl esters (RE) and retinol versus time (30 min to 8 h or 56 d, respectively) after ingestion of labeled VA; next we fit data to a previously-published 9-component model for VA metabolism to obtain “known” values for VA absorption. Then RE data only were modeled for each subject using a robust (n = 16 times) vs truncated sampling schedule (n = 10) and model-predicted absorptions were compared to known values. Areas under the plasma RE response curves (AUCs) were also calculated and compared to known absorption values. Results Known values for VA absorption based on modeling all data with error ranged from 54 – 92% (mean, 72%), VA stores from 160 – 1775 μmol, and chylomicron t1/2 from 6 – 12 min. Using the full sampling scheme for RE, the ratio of model-predicted to known absorption ranged from 0.927 – 1.06 (mean, 0.997); using the truncated scheme, the ratio was 0.814 – 1.13 (mean, 0.973). AUCs were not significantly correlated with known values for VA absorption (R2 = 0.112; P > 0.05), presumably because absorption and chylomicron catabolism are occurring simultaneously. Conclusions By modeling chylomicron RE tracer data after ingestion of labeled VA, absorption efficiency was estimated accurately using error-free data; using data with 5% error, estimates were within 10% of known values (full sampling) or within 20% (truncated). If subjects, after an overnight fast, consume a breakfast containing some fat and a known amount of VA, then no tracer is required to estimate VA absorption using this modeling approach. By incorporating a population-based design, the method could be used in children. Funding Sources Supported by Bill & Melinda Gates Foundation (Project Number OPP1115464) and HarvestPlus (BH183438).

Lecithin:Retinol Acyl Transferase (LRAT) induces the formation of lipid droplets

Lipid droplets are unique and nearly ubiquitous organelles that store neutral lipids in a hydrophobic core, surrounded by a monolayer of phospholipids. The primary neutral lipids are triacylglycerols and steryl esters. It is not known whether other classes of neutral lipids can form lipid droplets by themselves. Here we show that production of retinyl esters by lecithin:retinol acyl transferase (LRAT) in yeast cells, incapable of producing triacylglycerols and steryl esters, causes the formation of lipid droplets. By electron microscopy, these lipid droplets are morphologically indistinguishable from those in wild-type cells. In silico and in vitro experiments confirmed the propensity of retinyl esters to segregate from membranes and to form lipid droplets. The hydrophobic N-terminus of LRAT displays preferential interactions with retinyl esters in membranes and promotes the formation of large retinyl ester-containing lipid droplets in mammalian cells. Our combined data indicate that the molecular design of LRAT is optimally suited to allow the formation of characteristic large lipid droplets in retinyl ester-storing cells.