Abstract
Context
The effect of daily vitamin D supplementation on the serum concentration of vitamin D (the parent compound) may offer insight into vitamin D disposition.
Objective
To assess the total serum vitamin D response to vitamin D3 supplementation and whether it varies according to participant characteristics. To compare results with corresponding results for total serum 25-hydroxyvitamin D [25(OH)D], which is used clinically and measured in supplementation trials.
Design
Exploratory study within a randomized trial.
Intervention
2000 International Units of vitamin D3 per day (or matching placebo).
Setting
Community-based.
Participants
161 adults (mean ± SD age 70 ± 6 years; 66% males) with type 2 diabetes.
Main Outcome Measures
Changes in total serum vitamin D and total serum 25(OH)D concentrations from baseline to year 2.
Results
At baseline, there was a positive, nonlinear relation between total serum vitamin D and total serum 25(OH)D concentrations. Adjusted effects of supplementation were a 29.2 (95% CI: 24.3, 34.1) nmol/L increase in serum vitamin D and a 33.4 (95% CI: 27.7, 39.2) nmol/L increase in serum 25(OH)D. Among those with baseline 25(OH)D < 50 compared with ≥ 50 nmol/L, the serum vitamin D response to supplementation was attenuated (15.7 vs 31.2 nmol/L; interaction P-value = 0.02), whereas the serum 25(OH)D response was augmented (47.9 vs 30.7 nmol/L; interaction P-value = 0.05).
Conclusions
Vitamin D3 supplementation increases total serum vitamin D and 25(OH)D concentrations with variation according to baseline 25(OH)D, which suggests that 25-hydroxylation of vitamin D3 is more efficient when serum 25(OH)D concentration is low.
Keywords: vitamin D, cholecalciferol, 25-hydroxyvitamin D, biomarkers, liquid chromatography-tandem mass spectrometry
Vitamin D is a nutrient and prohormone that is metabolized through two sequential hydroxylation reactions to form 1,25-dihydroxyvitamin D [1,25(OH)2D], a hormone important for mineral homeostasis and bone health (1). The first hydroxylation takes place primarily in the liver where 25-hydroxylase enzymes convert vitamin D to 25-hydroxyvitamin D [25(OH)D]. Cytochrome P450 family 2 subfamily R member 1 (CYP2R1) is the principal 25-hydroxylase in humans (2). Additional enzymes that catalyze 25-hydroxylation of vitamin D include cytochrome P450 family 27 subfamily A member 1, which is thought to play a role in 25(OH)D3 formation in the presence of pharmacologic doses of vitamin D3 (3).
Because of its long half-life, circulating 25(OH)D concentration is used to assess vitamin D status. Most clinical strategies to correct 25(OH)D deficiency involve supplementation with vitamin D2 or vitamin D3 to achieve a target total 25(OH)D concentration (4). For this reason, studies of vitamin D pharmacokinetics have focused almost exclusively on the dose-response of serum 25(OH)D concentration to vitamin D supplementation. Some (5,6) but not all (7) meta-analyses determined that the dose-response of serum 25(OH)D to total vitamin D intake is nonlinear. In addition, the 25(OH)D response to a given dose of vitamin D is highly varied between individuals. A systematic review explained approximately 50% of the interindividual variation in response with body weight, age, type of supplement (vitamin D2 or D3), concomitant intake of calcium supplements, and baseline serum 25(OH)D concentration (8). More recent evidence highlights the contribution of genetic variation (9). For example, variants of the GC gene encoding the vitamin D binding protein (DBP) are strongly associated with the 25(OH)D response (10,11). Although unconfirmed, this may relate to genetically determined differences in serum DBP concentration, which also varies according to clinical condition, sex, and life stage.
Pharmacokinetic models can comprehensively describe vitamin D disposition and predict the serum 25(OH)D response to vitamin D dose, taking into account individual characteristics. However, such models are built from primary data on how circulating levels of not only 25(OH)D but also parent vitamin D change with supplementation (12-14). As far as we know, few studies have described how the circulating parent vitamin D concentration responds to long-term supplementation, and no studies have identified participant characteristics that modify this response. Doing so could shed light on vitamin D pharmacokinetics and interindividual variation in response to vitamin D treatment.
We quantified total serum vitamin D concentration (the sum of vitamin D2 and vitamin D3 concentrations) at baseline and year 2 in a subset of participants from the VITamin D and OmegA 3 TriaL to Prevent and Treat Diabetic Kidney Disease (VITAL-DKD), which was ancillary to the nationwide VITamin D and OmegA 3 TriaL (VITAL). Our objectives were to determine the effect of 2000 International Units (IU) of vitamin D3 per day on the total serum vitamin D concentration and whether this varied according to participant characteristics. Results were compared with those for total serum 25(OH)D concentration.
Methods
Study Design
This was an exploratory study among a subgroup of participants in VITAL-DKD (ClinicalTrials.gov registration no. NCT01684722) (15). VITAL-DKD was ancillary to the large VITAL study (ClinicalTrials.gov registration no. NCT01169259) (16). Both the VITAL and VITAL-DKD study designs have been described previously (17,18). In brief, the VITAL study was a randomized controlled trial of vitamin D3 and marine omega-3 fatty acid supplements for primary prevention of cancer and cardiovascular disease. It was conducted by mail and telephone among 25 871 US adults. VITAL-DKD enrolled a subset of 1312 VITAL participants with type 2 diabetes to investigate the effects of vitamin D3 and omega-3 fatty acid supplements on kidney outcomes. The VITAL studies, including this exploratory study, were approved by the institutional review board of Partners HealthCare, and all participants provided written informed consent.
Participants
This exploratory study consisted of the first 200 participants enrolled in VITAL-DKD. Eligible participants were men aged ≥50 years and women aged ≥55 years who reported a physician diagnosis of diabetes and no history of cardiovascular disease or cancer (except nonmelanoma skin cancer) at baseline. Eligible participants agreed to limit vitamin D intake from all supplemental sources to 800 IU/d and to forego use of nonstudy fish oil supplements. They also reported taking at least two thirds of their study pills during the placebo run-in period. Individuals were excluded if they reported a diagnosis of diabetes only during pregnancy, diabetes prior to age 30 years and treatment with insulin for more than 20 years, or a known cause of chronic kidney disease other than diabetes.
Interventions
Participants were randomly assigned to 1 of 4 treatment groups using a 2 × 2 factorial design: (1) 2000 IU/d vitamin D3 plus 1 g/d omega-3 fatty acids; (2) 2000 IU/d vitamin D3 plus omega-3 placebo; (3) vitamin D3 placebo plus 1 g/d omega-3 fatty acids; or (4) both placebos for 5 years. A computer generated the random sequence in blocks of 8 stratified by age, sex, and race. Investigators and participants were blinded to treatment assignment. Calendar packs of study medications were dispensed to participants by mail. Vitamin D3 (2000 IU) and matching placebo capsules were provided by Pharmavite LLC. Omega-3 fatty acids (1 g capsule containing 465 mg of eicosapentaenoic acid and 375 mg of docosahexaenoic acid) and matching placebo capsules were provided by Pronova BioPharma.
Outcomes
We quantified the total serum vitamin D concentration and assessed its response to 2 years of vitamin D3 supplementation. This was compared with the total serum 25(OH)D response to supplementation in the same participants. Blood samples were collected locally by participants at baseline and year 2 and mailed with frozen gel packs overnight to Brigham and Women’s Hospital. Blood was centrifuged to isolate serum, which was stored in aliquots at −70°C. Serum aliquots were shipped to the University of Washington for quantification of vitamins D2 and D3 using liquid chromatography-tandem mass spectrometry (LC-MS/MS). The LC-MS/MS method procedures, validation, and performance were described previously (19). The published method describes 2 alternative solvents for liquid-liquid extraction. For this study, we used 50:50 n-heptane:methyl tert-butyl ether to extract vitamins D2 and D3 from serum. The lower limit of the measuring interval (LLMI) of the assay was 0.327 and 0.356 nmol/L for vitamins D2 and D3, respectively. Between-run variability for both vitamins D2 and D3 was <10%. As part of the VITAL study, serum concentrations of 25(OH)D2 and 25(OH)D3 were quantified with LC-MS/MS (20). The assay lower limit of detection is 10 nmol/L each for 25(OH)D2 and 25(OH)D3. The VITAL study participated in the Vitamin D Standardization Program, and 25(OH)D results were calibrated to the Centers for Disease Control and Prevention reference method (20,21).
Serum vitamin D2 or D3 concentrations below the LLMI were assigned a value half the LLMI. Only 19% of samples had a serum vitamin D2 concentration ≥ the LLMI of our assay, and vitamin D2 contributed only 7% of total vitamin D. Within VITAL, only 4% of participants had detectable serum 25(OH)D2, which contributed only 2% of total 25(OH)D (20). We used the total vitamin D concentration (sum of vitamins D2 and D3 concentrations) and total 25(OH)D concentration [sum of 25(OH)D2 and 25(OH)D3 concentrations] for statistical analyses to avoid misclassification of baseline vitamin D status in the few participants with quantifiable levels of vitamin D2 and 25(OH)D2. The total serum vitamin D and total serum 25(OH)D concentrations are referred to hereafter as simply the serum vitamin D and 25(OH)D concentrations.
Covariates
Participant age, sex, race, ethnicity, height, and weight were self-reported on baseline questionnaires. Intake of nonstudy supplemental vitamin D was reported by participants at baseline, 6 months, 1 year, and 2 years. Adherence to study medications was reported at the same times including at baseline (after the placebo run-in period). LC-MS/MS was used to quantify serum DBP concentrations and determine DBP phenotype (22). The between-run variability of serum DBP concentration was <5%. Serum intact parathyroid hormone (PTH) was measured by chemiluminescent microparticle immunoassay, and serum calcium was measured by spectrophotometry (20).
Data Analysis
Correlates of baseline serum vitamin D concentration were identified with the Spearman correlation, Wilcoxon rank-sum, or Kruskal-Wallis test. We considered age; sex; race/ethnicity; body mass index (BMI); month of blood collection; baseline nonstudy supplemental vitamin D intake; geographic region; baseline serum 25(OH)D, PTH, calcium, or DBP concentration; and DBP phenotype. Due to sample size limitations, month of blood collection was collapsed into 2 categories: (1) October through March and (2) April through September. Race/ethnicity was collapsed into 3 categories: non-Hispanic white, non-Hispanic black, and other. To identify independent predictors of baseline serum vitamin D concentration, we used a multivariable linear regression model including all potential correlates as covariates.
For our main analyses, we quantified the effects of vitamin D3 supplementation on changes in serum vitamin D and 25(OH)D concentrations from baseline to year 2 according to treatment assignment. For each outcome, we constructed a model of the year 2 concentration as a function of baseline concentration and vitamin D treatment assignment using multivariable linear regression with Huber-White robust standard errors (23). In this model, the treatment parameter estimate is the estimated difference between vitamin D3 treatment and placebo in the change in the outcome from baseline to year 2. Adjusted models also included baseline serum 25(OH)D concentration (if not already included), age, sex, race/ethnicity, baseline BMI, month of baseline blood collection, omega-3 treatment assignment, and intervention adherence. An interaction with vitamin D3 treatment was used to examine whether the serum vitamin D or 25(OH)D response to supplementation varied according to age; sex; race/ethnicity; baseline BMI; month of baseline blood collection; baseline nonstudy supplemental vitamin D intake; DBP phenotype; or baseline serum vitamin D, 25(OH)D, PTH, or DBP concentration. The P-value for interaction was obtained with a Wald test of interaction terms. Because these regression analyses were exploratory, P-values were not adjusted for multiple comparisons. Two sensitivity analyses were conducted: 1 restricted to participants consuming at least two thirds of their study supplements at year 2, and 1 restricted to participants consuming no more than 800 IU/d of nonstudy supplemental vitamin D at year 2.
Data analyses were conducted with R 3.6.2 statistical computing environment (R Foundation for Statistical Computing, Vienna, Austria). For all tests, a 2-tailed P-value < 0.05 was considered significant.
Results
Participant Characteristics
Supplementary Figure 1 (24) depicts participant flow from enrollment in VITAL-DKD through analysis. Of the 200 participants enrolled and sampled for measurement of serum vitamin D concentration, 161 were included in the statistical analysis. Main reasons for exclusion from analysis were that blood was not obtained at year 2 or the serum vitamin D result did not meet laboratory quality control criteria. Among the 161 participants with complete data, mean age ± SD was 70 ± 5.5 years. The study population was 66% male, 71% non-Hispanic white, 14% non-Hispanic black, and 11% Hispanic. More than half of participants had type 2 diabetes for ≥6 years. Forty-eight percent of participants reported consuming up to 800 IU/d of nonstudy supplemental vitamin D at baseline, which they were allowed to continue upon starting the study (Table 1). By year 2, most participants (80%) reported consuming the same amount of nonstudy supplemental vitamin D (either none or ≤800 IU/d) as at baseline, and 11 participants reported consuming >800 IU/d of nonstudy supplemental vitamin D. Intervention adherence was high, and 96% of participants were taking at least two thirds of their study supplements at year 2.
Table 1.
Baseline characteristics of a subset of participants in the Vitamin D and Omega-3 Trial to Prevent and Treat Diabetic Kidney Disease (VITAL-DKD)
| Overall | Placebo group | Vitamin D3 group | |
|---|---|---|---|
| n | 161 | 73 | 88 |
| Age, mean (SD), years | 69.7 (5.5) | 69.1 (5.0) | 70.1 (5.9) |
| Male | 107 (66) | 51 (70) | 56 (64) |
| Race/ethnicity | |||
| White | 114 (71) | 53 (73) | 61 (69) |
| Black | 23 (14) | 12 (16) | 11 (12) |
| Hispanic | 18 (11) | 6 (8) | 12 (14) |
| Asian or Pacific Islander | 2 (1) | 0 (0) | 2 (2) |
| American Indian or Alaskan Native | 2 (1) | 0 (0) | 2 (2) |
| Other | 2 (1) | 2 (3) | 0 (0) |
| Duration of diabetes, years | |||
| <1 | 2 (1) | 1 (1) | 1 (1) |
| 1-2 | 18 (11) | 9 (12) | 9 (10) |
| 3-5 | 35 (22) | 17 (23) | 18 (20) |
| 6-10 | 49 (30) | 22 (30) | 27 (31) |
| 11-20 | 39 (24) | 17 (23) | 22 (25) |
| >20 | 18 (11) | 7 (10) | 11 (12) |
| Current smoker | 9 (6) | 5 (7) | 4 (5) |
| Nonstudy supplemental vitamin D intake, IU/d | |||
| None | 84 (52) | 33 (45) | 51 (58) |
| ≤800 | 77 (48) | 40 (55) | 37 (42) |
| Serum 25(OH)D, mean (SD), nmol/L | 76.0 (25.3) | 77.2 (26.9) | 75.0 (23.9) |
| <50 nmol/L | 26 (16) | 13 (18) | 13 (15) |
| Serum vitamin D, geometric mean (−SD, +SD), nmol/L | 6.7 (1.8, 24.5) | 6.7 (1.8, 24.5) | 6.1 (1.6, 22.2) |
| Serum PTH, mean (SD), pg/mL | 42.0 (25.6) | 38.1 (17.2) | 45.3 (30.6) |
| Serum DBP, mean (SD), mg/L | 237.1 (29.5) | 236.1 (31.4) | 237.8 (28.0) |
| BMI, mean (SD), kg/m2 | 30.6 (5.9) | 30.6 (6.1) | 30.6 (5.8) |
| Active omega-3 assignment | 81 (50) | 31 (42) | 50 (57) |
| Month (season) of blood collection | |||
| Apr-Sep | 38 (24) | 19 (26) | 19 (22) |
| Oct-Mar | 123 (76) | 54 (74) | 69 (78) |
Values are mean (SD), geometric mean (−SD, +SD), or n (%).
Abbreviations: 25(OH)D, 25-hydroxyvitamin D; BMI, body mass index; DBP, vitamin D binding protein; IU, International Units; PTH, parathyroid hormone.
Correlates of Baseline Serum Vitamin D Concentration
At baseline, serum vitamin D concentration was positively correlated with serum 25(OH)D concentration (r = 0.71; P < 0.001) (Fig. 1), serum calcium concentration (r = 0.17; P = 0.03), and age (r = 0.19; P = 0.02) and was inversely correlated with serum PTH concentration (r = −0.31; P < 0.001) [Supplementary Figure 2 (24)]. Baseline serum vitamin D concentration was higher in non-Hispanic whites compared with non-Hispanic blacks or other nonwhites (Fig. 2). It was also higher in individuals consuming up to 800 IU/d of nonstudy supplemental vitamin D (Fig. 2).
Figure 1.
Baseline serum 25(OH)D concentration compared with serum vitamin D concentration among participants who reported consuming none (n = 84) or up to 800 IU per day (n = 77) of nonstudy supplemental vitamin D at baseline. Abbreviations: 25(OH)D, 25-hydroxyvitamin D; IU, International Units.
Figure 2.
Distribution of baseline serum vitamin D concentration by (A) race/ethnicity, (B) nonstudy supplemental vitamin D intake, (C) sex, (D) month of baseline blood collection, (E) DBP phenotype, and (F) geographic region in a subset of participants (n = 161) in VITAL-DKD. Boxplots are the interquartile range (IQR) with band at the median and vertical whiskers that extend to the most extreme value within 1.5 times the IQR from the nearest quartile. P-values come from a Wilcoxon rank-sum test or Kruskal-Wallis test with Dunn’s test for post-hoc comparisons. Abbreviations: DBP, vitamin D binding protein; IU, International Units.
In a multivariable model including all potential correlates as independent variables, baseline serum vitamin D concentration was independently associated with baseline serum 25(OH)D concentration, nonstudy supplemental vitamin D intake, serum DBP concentration, and race/ethnicity [Supplementary Table 1 (24)]. Specifically, after controlling for the other potential correlates including baseline serum 25(OH)D concentration, baseline serum vitamin D concentration was 4.8 nmol/L higher in participants consuming ≤800 IU/d of supplemental vitamin D compared with none (P < 0.01), and it was 2.4 nmol/L lower per 30 mg/L (1 SD) greater serum DBP concentration (P < 0.01). It was 3.1 nmol/L higher in white individuals compared with those in the other race/ethnicity category, which included mostly Hispanics and a smaller number of Asians, Pacific Islanders, American Indians, and Alaskan Natives (P = 0.03).
Changes in Serum Vitamin D and 25(OH)D Concentrations From Baseline to Year 2
Serum vitamin D and 25(OH)D concentrations increased from baseline to year 2 in the vitamin D3 compared with placebo group (Fig. 3). The adjusted mean effects of study supplementation were a 29.2 (95% CI: 24.3, 34.1) nmol/L increase in serum vitamin D concentration and 33.4 (95% CI: 27.7, 39.2) nmol/L increase in serum 25(OH)D concentration (Table 2). There was substantial between-person variability in the serum vitamin D and 25(OH)D responses to supplementation (Fig. 4). In the vitamin D3 group, change in serum vitamin D concentration explained 22% of the variance in change in serum 25(OH)D concentration (Fig. 4).
Figure 3.
Distributions of (A) serum vitamin D concentration and (B) serum 25(OH)D concentration at baseline and year 2, and (C) serum 25(OH)D concentration compared with serum vitamin D concentration at year 2 in the placebo (n = 73) and vitamin D3 (n = 88) groups.
Abbreviations: 25(OH)D, 25-hydroxyvitamin D; IU, International Units.
Table 2.
Effects of vitamin D3 on serum vitamin D and 25(OH)D concentrations among participant subgroups
| Serum vitamin D | Serum 25(OH)D | ||||
|---|---|---|---|---|---|
| Participants, n | Difference in change from baseline to year 2 (95% CI), nmol/L | Interaction P-value | Difference in change from baseline to year 2 (95% CI), nmol/L | Interaction P-value | |
| Overall | 161 | 29.2 (24.3, 34.1) | 33.4 (27.7, 39.2) | ||
| Baseline BMI, kg/m2 | 0.017 | < 0.001 | |||
| <30 | 82 | 34.8 (28.4, 41.2) | 43.4 (35.3, 51.5) | ||
| ≥30 | 79 | 24.0 (17.5, 30.6) | 23.8 (16.4, 31.2) | ||
| Baseline 25(OH)D, nmol/L | 0.021 | 0.053 | |||
| <50 | 26 | 15.7 (3.3, 28.1) | 47.9 (31.2, 64.5) | ||
| ≥50 | 135 | 31.2 (26.1, 36.4) | 30.7 (24.9, 36.5) | ||
| Nonstudy supplemental vitamin D, IU/da | 0.83 | < 0.001 | |||
| None | 84 | 30.5 (25.8, 35.2) | 44.3 (35.6, 53.1) | ||
| ≤800 | 77 | 29.5 (21.4, 37.6) | 24.5 (17.3, 31.7) | ||
| DBP phenotype | 0.26 | 0.043 | |||
| Any Gc2b | 72 | 26.4 (19.6, 33.3) | 27.2 (19.2, 35.2) | ||
| No Gc2c | 89 | 31.4 (25.1, 37.8) | 38.3 (30.7, 46.0) | ||
| Baseline PTH, pg/mL | 0.31 | 0.93 | |||
| ≤65 | 139 | 30.4 (25.1, 35.8) | 33.3 (27.3, 39.4) | ||
| >65 | 22 | 21.4 (4.8, 38.0) | 34.3 (13.1, 55.5) | ||
| Month of baseline blood collection | 0.27 | 0.43 | |||
| Apr-Sep | 38 | 23.9 (12.2, 35.7) | 29.4 (17.6, 41.1) | ||
| Oct-Mar | 123 | 30.9 (26.0, 35.8) | 34.7 (28.3, 41.2) | ||
| Sex | 0.78 | 0.39 | |||
| Female | 54 | 28.1 (16.9, 39.2) | 29.3 (17.0, 41.5) | ||
| Male | 107 | 29.8 (24.9, 34.6) | 35.4 (29.1, 41.7) | ||
| Race/ethnicity | 0.23 | 0.82 | |||
| White | 114 | 30.1 (24.5, 35.7) | 32.5 (26.2, 38.8) | ||
| Black | 23 | 19.4 (6.0, 32.8) | 34.1 (15.3, 52.8) | ||
| Other | 24 | 34.9 (22.3, 47.6) | 37.5 (22.9, 52.1) | ||
| Age at randomization, years | 0.76 | 0.65 | |||
| >65 | 25 | 29.1 (19.4, 38.8) | 38.5 (25.8, 51.1) | ||
| 65-75 | 114 | 28.7 (22.5, 34.9) | 31.9 (25.3, 38.6) | ||
| >75 | 22 | 32.8 (23.0, 42.6) | 35.7 (18.0, 53.5) | ||
The difference (vitamin D3 minus placebo) in change in serum vitamin D or 25(OH)D concentration in each subgroup was extracted from a linear regression model of the year 2 concentration that included the treatment by subgroup interaction, baseline concentration, age, sex, race/ethnicity, baseline 25(OH)D concentration (if not already included), month of baseline blood collection, BMI, omega-3 treatment assignment, and intervention adherence. The 95% CI around the effect was estimated with robust methods (23). P-value comes from a global test of the treatment by subgroup interaction.
Abbreviations: 25(OH)D, 25-hydroxyvitamin D; DBP, vitamin D binding protein; IU, International Units; PTH, parathyroid hormone.
aNonstudy supplemental vitamin D intake self-reported at baseline.
bIncludes DBP phenotypes Gc2/Gc1f, Gc2/Gc1s, and Gc2/Gc2.
cIncludes DBP phenotypes Gc1f/Gc1f, Gc1f/Gc1s, and Gc1s/Gc1s.
Figure 4.
Distributions of (A) change in serum vitamin D concentration and (B) change in serum 25(OH)D concentration from baseline to year 2 in the placebo (n = 73) and vitamin D3 (n = 88) groups. (C) Change in serum 25(OH)D concentration compared with change in serum vitamin D concentration in the vitamin D3 group, with linear regression line (y = 9 + 0.64x; R2 = 0.22).
Abbreviations: 25(OH)D, 25-hydroxyvitamin D; IU, International Units.
The effects of supplementation on serum vitamin D and 25(OH)D concentrations varied according to participant characteristics. BMI modified the effects of supplementation on serum vitamin D and 25(OH)D concentrations (Table 2). The magnitude of effects on serum vitamin D and 25(OH)D were smaller in individuals with obesity (baseline BMI ≥ 30 kg/m2) compared to those without obesity.
Lower baseline serum vitamin D concentration was associated with greater serum 25(OH)D response to supplementation [Supplementary Table 2 (24)]. When baseline serum 25(OH)D concentration was categorized as <50 nmol/L (risk for inadequacy) compared with ≥50 nmol/L, it also was associated with a greater serum 25(OH)D response to supplementation, although this interaction was not statistically significant (P = 0.05), and it modified the serum vitamin D response as well, however, in the opposite direction. Baseline serum 25(OH)D <50 compared with ≥50 nmol/L was associated with a greater serum 25(OH)D response to supplementation but a lesser serum vitamin D response (Table 2). This tradeoff between substrate and product was apparent in the longitudinal data of participants in the vitamin D3 group shown in Figure 5. Perhaps related to these findings, intake of additional, nonstudy supplemental vitamin D was associated with a lesser serum 25(OH)D response to the 2000 IU/d intervention but had no effect on the serum vitamin D response (Table 2).
Figure 5.
Individual participant trajectories of serum vitamin D and 25(OH)D concentrations from baseline (black dots) to year 2 (open circles) in the (A) vitamin D3 group (n = 88) and (B) placebo group (n = 73), stratified by baseline 25(OH)D concentration <50 nmol/L (red lines), 50-75 nmol/L (blue lines), or >75 nmol/L (yellow lines).
Abbreviation: 25(OH)D, 25-hydroxyvitamin D.
Baseline serum DBP concentration was positively associated with the serum 25(OH)D response to supplementation [Supplementary Table 2 (24)]. To maximize statistical power, the DBP phenotype was categorized according to Gc2 haplotype carriage because serum DBP concentration was significantly lower in individuals with Gc2 haplotype (Gc1f/Gc2, Gc1s/Gc2, and Gc2/Gc2) relative to those without Gc2 (Gc1f/Gc1f, Gc1f/Gc1s, Gc1s/Gc1s) [Supplementary Figure 3 (24)], which is consistent with the literature (25-29). Gc2 haplotype carriage was associated with diminished serum 25(OH)D response to supplementation (Table 2).
Results from crude and adjusted models were relatively consistent [Supplementary Tables 3 and 4 (24)], especially when restricted to participants consuming at least two thirds of their study supplements [Supplementary Table 5 (24)]. Results were also consistent when analyses were restricted to participants consuming no more than 800 IU/d of nonstudy supplemental vitamin D.
Discussion
Among this group of older adults with type 2 diabetes who participated in VITAL-DKD, serum vitamin D and 25(OH)D concentrations increased with 2 years of 2000 IU vitamin D3 per day. As expected, the serum vitamin D and 25(OH)D responses to supplementation were positively correlated. However, among those randomized to vitamin D3 supplementation, the change in serum vitamin D explained only 22% of the variance in the change in serum 25(OH)D. Obesity attenuated the effects of supplementation on both serum vitamin D and 25(OH)D concentrations. Baseline serum 25(OH)D concentration <50 nmol/L was associated with a diminished serum vitamin D response and an enhanced serum 25(OH)D response to treatment, suggesting that 25-hydroxylation of vitamin D3 was more efficient in participants with low serum 25(OH)D concentration. Perhaps related to this, the serum 25(OH)D response to the vitamin D3 intervention was attenuated in individuals consuming additional, nonstudy supplemental vitamin D. Whether study findings apply to vitamin D2 supplementation is not known.
Few studies have measured serum vitamin D concentrations in humans, unlike serum 25(OH)D concentrations. Serum 25(OH)D concentration is the accepted indicator of vitamin D exposure because it has a longer plasma half-life (2 to 3 weeks) than vitamin D (0.5 to 5 days) (30) and therefore does not rise and fall as abruptly with intermittent exposures. We found that baseline serum vitamin D concentration was associated with common correlates of serum 25(OH)D including age, race/ethnicity, vitamin D supplement use, serum PTH, and serum calcium but unrelated to others including season and serum DBP concentration (20). Note, however, that season was roughly classified (October-March or April-September) because of sample size limitations. The differential correlation with serum DBP concentration is interesting and may relate to the lower affinity of vitamin D for DBP or the association of ingested vitamin D with chylomicrons and other lipoproteins.
The nonlinear relation observed between serum vitamin D and 25(OH)D levels replicates findings from our previous pilot studies (19) and earlier studies (31,32). Heaney et al aggregated data from 6 studies that measured circulating vitamin D3 and 25(OH)D in humans receiving varied doses of vitamin D3 (32). They concluded that with vitamin D3 inputs <2000 IU/d, little vitamin D3 is present in the systemic circulation due to its efficient metabolism to 25(OH)D3. With higher inputs, vitamin D3 accumulates in the blood and tissues. The input that must be exceeded for this to occur has not been determined definitively given the dose-response of serum vitamin D concentration to vitamin D intake is not well understood. Heaney et al concluded that when circulating vitamin D concentration is low, stored vitamin D is slowly released and quantitatively converted to 25(OH)D (32). This is supported by our findings that individuals with serum 25(OH)D3 <50 nmol/L have little to no vitamin D3 in the circulation but may have an appreciable amount in adipose tissue (19).
The effect of vitamin D3 supplementation on serum 25(OH)D concentration in this VITAL-DKD subset (33.4 nmol/L) was comparable to the increase in serum 25(OH)D in the vitamin D3 group from baseline to year 1 in the VITAL study (20) and from baseline to year 5 in the VITAL-DKD study (15). This effect equates to a 1.7 nmol/L increase in serum 25(OH)D per 100 IU of vitamin D3 per day, which is at the low end of the expected range (1.75 to 2.5 nmol/L per 100 IU) (4), possibly owing to the relatively high baseline serum 25(OH)D concentrations or prevalence of obesity in this study population. The serum 25(OH)D response to vitamin D supplementation is attenuated when baseline serum 25(OH)D concentration is >40 nmol/L (33) or >50 nmol/L (34). In 1660 VITAL participants, Luttmann-Gibson et al found that the efficacy of supplementation for increasing serum 25(OH)D depended on baseline serum 25(OH)D concentration (20), and our results were similar in this subset of VITAL-DKD participants. The effect of supplementation on serum 25(OH)D was 47.9 nmol/L when baseline 25(OH)D was <50 nmol/L compared with 30.7 nmol/L when baseline 25(OH)D was ≥50 nmol/L. The mechanistic explanation for this result is uncertain but may also explain why the serum 25(OH)D response to supplementation was attenuated in individuals consuming additional, nonstudy supplemental vitamin D in this study and the parent VITAL study (20).
We previously described potential mechanistic explanations for the nonlinear dose-response of serum 25(OH)D to vitamin D intake and the strong response of serum 25(OH)D to supplementation when baseline 25(OH)D is low (19). These include capacity-limited 25(OH)D formation (35,36), negative cooperativity, regulation of CYP2R1 expression (37), induction of 25(OH)D eliminating enzymes (38,39), or a combination of these factors. Early studies in rats indicated that 25(OH)D3 formation efficiency declines with increasing vitamin D3 input as a result of substrate saturation or local product inhibition of hepatic enzymes (35,36). Another early study suggested that hepatic 25-hydroxylase activity can be suppressed by 1,25(OH)2D (37). Furthermore, 1,25(OH)2D stimulates production of major 25(OH)D eliminating enzymes CYP24A1 (38) and SULT2A1 (39), so vitamin D supplementation may induce 25(OH)D elimination, especially in those with high baseline 25(OH)D concentration. However, the few data available on the pharmacokinetics of oral 25(OH)D (calcifediol) indicate that serum 25(OH)D concentration responds linearly to the dose of oral 25(OH)D, regardless of starting concentration (3,40). The current study adds the novel finding that in people with low, compared with high, baseline serum 25(OH)D, the effect of vitamin D3 supplementation on serum vitamin D concentration was attenuated, whereas the effect on serum 25(OH)D concentration was enhanced. This is indirect yet in vivo evidence suggesting that 25(OH)D3 formation is more efficient in people with low serum 25(OH)D. This finding emerged when we modeled the effects of supplementation according to prespecified clinically relevant subgroups, but a future study with larger sample size could explore whether these differential effects by baseline status appear to be influenced more by the baseline substrate (vitamin D) concentration or baseline product [25(OH)D] concentration in a linear or threshold manner.
Meta-analyses have explained up to 50% of the interindividual variation in serum 25(OH)D response to vitamin D supplementation (8), primarily via body weight and baseline serum 25(OH)D (41). The current study shows that, in addition, lower serum DBP concentration was associated with a diminished 25(OH)D response to supplementation, perhaps due to faster clearance of 25(OH)D. Gc2 haplotype carriage also was associated with a diminished serum 25(OH)D response to supplementation, which agrees with some (11) but not all (42) prior randomized trials. Inconsistent results may relate to differences in baseline 25(OH)D concentration between study populations and haplotypes as well as the statistical models used. Furthermore, these prior trials could not investigate the potential mediating effect of DBP concentration, which was not measured. In our study, Gc2 carriage was associated with lower serum DBP concentration, and post-hoc modeling showed that the effect modification by DBP phenotype was partially attenuated when accounting for effect modification by DBP concentration. As to whether DBP genotypes should inform personalized vitamin D dosing requires further study to determine, for example, whether the effects of DBP genotypes on serum 25(OH)D concentration are mediated entirely by differences in DBP concentration and whether it is the plasma unbound or total 25(OH)D concentration that is more clinically relevant.
Strengths of our study include the randomized placebo-controlled design and leverage of the parent VITAL and VITAL-DKD studies. Participant retention and intervention adherence were high (15). Serum vitamin D concentration was measured using a validated LC-MS/MS method (19), which is the gold-standard method for quantification of vitamin D and its metabolites in biospecimens. Serum 25(OH)D concentration was also measured by LC-MS/MS, and results were calibrated to the Centers for Disease Control and Prevention reference method.
Study limitations include the restriction to participants with diabetes and the small sample size, as this was a proof of concept study to explore interindividual variability in the serum vitamin D response to supplementation. A convenience sample was selected, and we did not adjust for multiple testing. Thus, the results should be replicated in a larger sample as well as in people without diabetes. We did not have information on sun exposure and dietary intake in the week prior to blood sampling, which may have introduced error into our estimates of how supplementation impacts serum vitamin D concentration. Although CYP2R1 and other genotypes have been associated with the 25(OH)D response to vitamin D supplementation (10), we did not genotype participants, so we were unable to investigate fully the potential genetic influences on study outcomes. We did not measure 25(OH)D3 formation kinetics, which would require administering an isotopic tracer or collecting liver biopsies, and we did not measure serum concentrations of 1,25(OH)2D, 24,25(OH)2D, 4β,25(OH)2D, or the sulfated and glucuronidated conjugates of 25(OH)D, which would have provided a view of 25(OH)D elimination pathway efficiencies. However, studies that directly measured plasma 25(OH)D clearance (43) or half-life (44) using deuterium-labeled 25(OH)D showed that 25(OH)D elimination efficiency was unrelated (43) or inversely related (44) to serum 25(OH)D concentration. Moreover, the serum 25(OH)D response to oral 25(OH)D appears to be independent of baseline concentration (3,40). Nonetheless, the nonlinear dose-response of serum 25(OH)D concentration to vitamin D intake may arise from multiple mechanisms whose relative influences vary according to dose, and more research is needed to address this. Finally, this study did not address clinical outcomes, and a greater understanding of variability in the serum vitamin D and 25(OH)D responses to vitamin D supplementation may provide insight into the heterogeneity in the clinical response (45,46).
To summarize, there was a moderate positive correlation between the serum vitamin D response and 25(OH)D response to vitamin D3 supplementation. Individuals with baseline 25(OH)D concentration less than 50 nmol/L appeared to more efficiently clear vitamin D3 through formation of 25(OH)D3. Assessment of serum vitamin D in addition to 25(OH)D in this supplementation trial provided further insight into interindividual variation in vitamin D exposure and vitamin D3 pharmacokinetics.
Acknowledgments
We thank the Centers for Disease Control and Prevention (Dr. Hubert Vesper and Dr. Julianne Cook Botelho) for their collaboration on the standardization and calibration of the 25(OH)D measurements for the VITAL study.
Financial Support: This study was funded by grant R01DK088762 from the National Institute of Diabetes and Digestive and Kidney Diseases and administrative supplement R01DK088762-S1 from the Office of Dietary Supplements. Additional support was provided by grant T32HL007028 from the National Heart, Lung, and Blood Institute and an unrestricted fund from the Northwest Kidney Centers. Waters Corporation provided equipment support. The parent trial was funded by grants U01CA138962 and R01CA138962, which include support from the National Cancer Institute; National Heart, Lung, and Blood Institute; Office of Dietary Supplements; National Institute of Neurological Disorders and Stroke; and National Center for Complementary and Integrative Health. Pharmavite, Pronova, BioPharma/BASF, and Quest Diagnostics provided study medications and diagnostic services.
Clinical Trial Information: VITAL-DKD: ClinicalTrials.gov registration no. NCT01684722. VITAL: ClinicalTrials.gov registration no. NCT01169259
Additional Information
Disclosure Summary: A.N.H. has served as an expert witness regarding mass spectrometry for Kilpatrick Townsend & Stockton LLP. S.M. has served as a consultant to Quest Diagnostics and Pfizer. A.N.H., I.H.dB., J.E.M., and S.M. received research funding from the National Institutes of Health. The remaining authors have nothing to declare.
Data Availability
Restrictions apply to the availability of some or all data generated or analyzed during this study to preserve patient confidentiality or because they were used under license. The corresponding author will on request detail the restrictions and any conditions under which access to some data may be provided.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Restrictions apply to the availability of some or all data generated or analyzed during this study to preserve patient confidentiality or because they were used under license. The corresponding author will on request detail the restrictions and any conditions under which access to some data may be provided.