Use of Population-Based Compartmental Modeling and Retinol Isotope Dilution to Study Vitamin A Kinetics and Total Body Stores among Ghanaian Women of Reproductive Age

Background: Limited data are available on vitamin A kinetics and total body stores (TBS) in women. Such information can be obtained using compartmental modeling and retinol isotope dilution (RID). Objectives: Objectives were to apply population-based (“super-subject”) modeling to determine retinol kinetics in nonpregnant Ghanaian women of reproductive age and to use RID to predict TBS in the group and its individuals. Methods: Women (n = 89) ingested a dose of [2H6]retinyl acetate and blood samples (3/woman) were collected from 6 h to 91 d, with all participants sampled at 14 d, about half at either 21 or 28 d, and each at one other time. Composite data (plasma retinol fraction of dose; FDp) were analyzed using Simulation, Analysis and Modeling software to obtain kinetic parameters, TBS, and other state variables as well as model-derived values for the RID composite coefficient FaS. The latter were used in the RID equation TBS (μmol) = FaS × 1/SAp (where SAp is plasma retinol specific activity) to predict TBS at various times. Results: Model-predicted TBS was 973 μmol (n = 87). Geometric mean RID-predicted TBS was 965, 926, and 1006 μmol at 14, 21, and 28 d, respectively, with wide ranges [for example, 252–3848 μmol on day 14 (n = 86)]; TBS predictions were similar at later times. Participants had a mean 2 y of vitamin A in stores and estimated liver vitamin A concentrations in the normal range. Model-predicted vitamin A disposal rate was 1.3 μmol/d and plasma recycling number was 37. Conclusions: Super-subject modeling provides an estimate of group mean TBS as well as group-specific values for the RID coefficient FaS; the latter can be used to confidently predict TBS by RID for individual participants in the group under study or in similar individuals at 14 d or more after isotope ingestion. Trial registration number: Trial is registered (NCT04632771) at https://clinicaltrials.gov.