Effects of Vitamin D₃ and Calcium Supplementation on Serum Levels of Tocopherols, Retinol, and Specific Vitamin D Metabolites

Abstract

γ-Tocopherol (γT) protects against DNA-damaging effects of nitrogen oxides, yet its physiologic regulation in vivo is unknown. Observational studies indicate inverse associations of 25[OH]-vitamin D with γT and leptin. To determine whether vitamin D₃ supplementation alters levels of lipid-soluble micronutrients, serum samples (N = 85 subjects) from a randomized, double-blind, placebo-controlled clinical trial of vitamin D₃ (800 IU) and calcium (2 g), alone and in combination, were analyzed for lipid micronutrients and specific vitamin D metabolites at baseline and after 6 mo of supplementation. Serum 25[OH]-vitaminD₃ levels increased 55% (P < 0.0001) and 48% (P = 0.0005), whereas 25[OH]-vitaminD₂ levels were lower by 48% (P = 0.26) and 21% (P = 0.36) in the vitamin D₃ and vitamin D₃ plus calcium groups, respectively. At baseline, γT levels were inversely associated with 25[OH]D (r = −0.31, P = 0.004). With vitamin D₃ plus calcium treatment, serum α-tocopherol decreased 14% (P = 0.04), whereas similar changes in γT (19% lower, P = 0.14) were observed. No significant effects were observed for D₃ supplementation on leptin or retinol levels. These results are consistent with the hypothesis that vitamin D₃ ± calcium affects serum tocopherol and 25[OH]D₂ levels; however, studies using larger, more homogeneous populations are warranted.

ACKNOWLEDGMENTS

This research was supported in part by the National Institutes of Health grants R01CA104637 and R03CA132149, and Georgia Cancer Coalition Distinguished Scholar award (to Roberd M. Bostick). Weiwen Chai was supported by a postdoctoral fellowship on grant R25 CA90956.

Notes

^a Data are given as mean (SD) unless otherwise specified.

^b By Fisher's exact χ² test for categorical variables or analysis of variance for continues variables.

^c Diet plus supplements.

^a Least-squares means are used.

^b Absolute treatment (Rx) effect = [(treatment group follow-up) – (treatment group baseline)] – [(placebo group follow-up) – (placebo group baseline)].

^c Proportional treatment (Rx) effect = (absolute treatment effect/treatment group baseline) × 100% (e.g., a proportional effect of 55% would mean that a 55% increase in the active treatment group relative to the placebo group).

^d P value for difference between each active treatment group and the placebo group from repeated-measures mixed model.

^a Least-squares means are used.

^b Absolute treatment (Rx) effect = [(treatment group follow-up) – (treatment group baseline)] – [(placebo group follow-up) – (placebo group baseline)].

^c Proportional treatment (Rx) effect = (absolute treatment effect/treatment group baseline) × 100% (e.g., a proportional effect of 55% would mean that a 55% increase in the active treatment group relative to the placebo group).

^d P value for difference between each active treatment group and the placebo group from repeated-measures mixed model.