Abstract
African Americans have a disproportionate burden of inflammation-associated chronic diseases such as cancer and lower circulating levels of 25-hydroxyvitamin D [25(OH)D]. The effect of vitamin D3 (cholecalciferol) supplementation on inflammatory markers is uncertain. We conducted a randomized, double-blind, placebo-controlled trial of supplemental oral vitamin D (placebo, 1,000, 2,000, or 4,000 IU/day of vitamin D3 orally for 3 months) in 328 African Americans (median age, 51 years) of public housing communities in Boston, MA, who were enrolled over three consecutive winter periods (2007–2010). Change from 0 to 3 months of plasma levels of 25(OH)D, high-sensitivity C-reactive protein (CRP), interleukin (IL)-6, IL-10, and soluble TNF-α receptor type 2 (sTNF-R2) in 292 (89%) participants were measured. Overall, no statistically significant changes in CRP, IL-6, IL-10, and sTNF-R2 were observed after the vitamin D supplementation period. Baseline CRP was significantly inversely associated with the baseline 25(OH)D level (P < 0.001) in unadjusted and adjusted models. An interaction between baseline 25(OH)D and vitamin D supplementation was observed for outcome change in log CRP (month 3–month 0; P for interaction = 0.04). Within an unselected population of African Americans, short-term exposure to vitamin D supplementation produced no change in circulating inflammatory markers. This study confirms the strong independent association of CRP with 25(OH)D status even after adjusting for body mass index. Future studies of longer supplemental vitamin D3 duration are necessary to examine the complex influence of vitamin D3 on CRP and other chronic inflammatory cytokines for possible reduction of cancer health disparities in African Americans. Cancer Prev Res; 7(2); 218–25. ©2013 AACR.
Introduction
African Americans have a disproportionate elevation in chronic inflammation (1) after accounting for differences in body mass index (BMI) and other potential confounding factors (2, 3). Vitamin D deficiency may contribute to higher levels of inflammation (4). Chronic inflammation has been associated with a number of health outcomes including increased risk of cancer, cardiovascular disease, and diabetes (5–9). Previous observational and intervention studies have suggested that supplemental vitamin D may reduce circulating C-reactive protein (CRP) levels as well as other plasma inflammatory cytokines; nonetheless, results across all completed randomized trials have been inconsistent (10, 11). Of note, the inconsistency in the results of these trials may be related to the dose of vitamin D administered as well as the baseline plasma level of 25(OH)D. Furthermore, none of these trials enrolled a sufficient number of African American participants to examine the specific effects of supplementation on inflammation in this population.
In humans, cytokines such as CRP, interleukin (IL)-6, IL-10, and soluble TNF-α receptor type 2 (sTNF-R2) not only mediate the inflammatory response, but also serve as potential biomarkers of inflammation-related chronic diseases (9, 12, 13). If vitamin D supplementation reduces chronic inflammation among African Americans, its widespread use may have major public health impact on the reduction of cancer health disparities given the disproportionate prevalence of vitamin D deficiency in African Americans (14–16). Thus, we examined whether oral vitamin D supplementation reduces proinflammatory factors CRP, IL-6, and sTNF-R2 or increases the anti-inflammatory marker IL-10 within a randomized, double-blind, placebo-controlled trial designed to evaluate the effect of vitamin D supplementation on circulating 25(OH)D levels.
Materials and Methods
Study design
This is a prospective, randomized, double-blind, placebo-controlled clinical trial of oral cholecalciferol (vitamin D3) in a community-based healthy black population (ClinicalTrials.gov NCT00585637). The protocol has been described in detail elsewhere (17). The primary goal of the trial was to examine the effect of daily supplementation of 1,000 international units (IU) of vitamin D3, 2,000 IU of vitamin D3, and 4,000 IU of vitamin D3 and placebo on plasma 25(OH)D levels. Participants were drawn from Open Doors to Health (ODH), a colorectal cancer prevention intervention study conducted in 12 public housing communities in the Boston metropolitan area (16). All participants provided written informed consent. The project was approved by the Institutional Review Boards of Harvard School of Public Health and the Dana-Farber Cancer Institute. All procedures were followed in accordance with the institutional guidelines.
Recruitment and randomization
Participants in ODH were invited to participate if they were 30 to 80 years old, understood written and spoken English, self-identified as black (18–20), and had permission from their primary care doctors. A total of 328 individuals were enrolled into the parent trial (Fig. 1). Exclusion criteria included pregnancy, renal disease, preexisting parathyroid, thyroid, or calcium metabolism disorders, sarcoidosis, requirement for calcium channel blockers, type I diabetes, and active malignancies (other than nonmelanoma skin cancer). Those taking vitamin D supplementation were enrolled if they agreed to discontinue these medications for 6 months before enrollment and during the study.
Treatment
Participants were randomly assigned to four treatment arms: placebo, 1,000 IU/day, 2,000 IU/day, or 4,000 IU/day (Pharmavite LLC) of vitamin D3 for 3 months. All capsules also contained 200 mg of calcium carbonate. All capsules were indistinguishable, and both participants and research staff were blinded to the treatment assignment. Study medications were started in early winter (November or December) and were taken orally once daily for 3 months (completed in February or March).
Endpoints and follow-up
The primary endpoints of the study were the changes in plasma inflammatory marker levels, IL-6, IL-10, sTNF-R2, and CRP, from baseline to the initial 3-month follow-up at the conclusion of supplement administration. Inflammatory markers were also measured at the 6-month follow-up. Individuals attended study visits at baseline, 3 months (at the end of randomized treatment), and 6 months (3 months after treatment discontinuation).
Compliance and safety
All participants were assessed for adverse events by study staff over the phone at week 2 of each month and in-person at the beginning of each month when the next month's supply of vitamins was provided. Participants were educated on the warning signs and symptoms of hypercalcemia. Any subject found to have serum calcium >10.5 mg/dL was immediately discontinued from the study and the primary care provider was notified.
Plasma vitamin D levels
Blood samples collected at baseline, 3 months, and 6 months were separated and plasma was stored in liquid nitrogen in the Dana-Farber Cancer Institute Clinical Research Laboratory. Once the study was completed, all plasma samples were sent as a single batch to the laboratory of Dr. Bruce Hollis (Medical University of South Carolina, Charleston, SC), where 25(OH)D concentrations were measured using the Diasorin (DiaSorin, Inc.) radioimmunoassay (21). Masked quality control samples were interspersed among the cases and all laboratory personnel were blinded. The mean coefficient of variation of 25(OH)D measurements was 9%.
Plasma inflammatory biomarker levels
Blood samples from women were collected in tubes treated with liquid sodium heparin, and those from men were collected in EDTA-treated tubes. The tubes were then placed on ice packs, stored in Styrofoam containers, returned to our laboratory by overnight courier, centrifuged, and divided into aliquots for storage in liquid-nitrogen freezers (−130°C or colder).
The levels of CRP were determined by means of a highly sensitive immunoturbidimetric assay with the use of reagents and calibrators from Denka Seiken; this assay has a day-to-day variability of 1% to 2%. Levels of sTNF-R2, IL-6, and IL-10 were measured by means of ELISA (R&D Systems), which have a day-to-day variability of 3.5% to 9.0%. Levels of sTNF-R2 show a strong correlation with TNF-α mRNA expression in human adipose tissue (8). The mean intra-assay coefficients of variations from blinded quality control samples for each analyte were as follows: CRP, 2.6%; IL-6, 3.8%; IL-10, 10.3%; and sTNF-R2, 3.3%.
Statistical analyses
The trial was designed with a statistical power of 80% to detect differences in the plasma 25(OH)D level of 5.3 ng/mL between treatment groups. On the basis of this planned sample size, we estimated that the trial would have 80% power to detect a 25% change in inflammatory biomarkers IL-6, IL-10, sTNF-R2, and CRP per 1,000 IU/day of vitamin D3. All statistical analyses were performed using SAS version 9.2 (SAS Institute). Baseline characteristics of the study population were compared between supplementation arms using the χ2 test for categoric variables and the Kruskal–Wallis test for continuous variables.
The primary endpoints of the study were the changes in plasma inflammatory marker levels, IL-6, IL-10, sTNF-R2, and CRP, from baseline to the initial 3-month follow-up. For our primary analysis, we used linear regression with the dose of vitamin D3 (per 1,000 IU/day) as the independent variable and the log 3-month change in inflammatory marker as the dependent variable. The inflammatory biomarkers had skewed distributions so the data were natural log transformed.
We performed a number of a priori secondary analyses. We evaluated the independent association between baseline 25(OH)D, baseline BMI, smoking status, and inflammatory markers in univariate and multivariable linear regression. The covariates for the multivariable linear regression model included age, gender, and BMI as a continuous variable. Then, we analyzed the change in inflammatory markers according to the change in plasma 25(OH)D levels. Second, we analyzed the effect of any vitamin D supplementation (all 3 treatment groups combined) compared with placebo on inflammatory markers. Finally, to assess whether the effect of supplementation with vitamin D on the primary endpoint, 3-month change in inflammatory markers, varied according to baseline 25(OH)D or baseline BMI, we tested for an interaction between the treatment group and the baseline 25(OH)D level or baseline BMI.
Results
Subject characteristics according to the supplementation arm
Among the 328 eligible participants, baseline characteristics were relatively well balanced with an overall median age of 51 years and a median BMI of 31 kg/m2 (Table 1). Slightly more participants in the placebo and 1,000 IU/day arms had a past history of cancer than those assigned to 2,000 or 4,000 IU/day. Otherwise, there were no significant differences in any of the subject characteristics between the supplementation arms. The compliance rate with study medication in the entire cohort was 96.6%. The 3-month follow-up plasma measurements were completed in 292 of the 328 participants (89%).
Subject characteristics by supplementation arma
. | Vitamin D3 dose assignment (IU/d) . | . | |||
---|---|---|---|---|---|
Characteristic . | Placebo (n = 81) . | 1,000 (n = 81) . | 2,000 (n = 83) . | 4,000 (n = 83) . | Pb . |
Median age, years (IQR) | 50.7 (44.1–58.0) | 51.1 (43.4–60.1) | 50.3 (43.5–58.3) | 51.3 (44.1–59.7) | 0.98 |
Sex, No. (%) | 0.72 | ||||
Male | 27 (33.3) | 22 (27.2) | 28 (33.7) | 29 (34.9) | |
Female | 54 (66.7) | 59 (72.8) | 55 (66.3) | 54 (65.1) | |
Median BMI, kg/m2 (IQR) | 31.2 (26.5–35.9) | 30.5 (27.0–37.5) | 31.9 (26.2–36.9) | 31.4 (27.4–35.7) | 0.82 |
Inflammatory markers | |||||
IL-6 (pg/mL) | 2.21 (1.32–3.42) | 2.38 (1.53–4.02) | 2.30 (1.19–4.17) | 2.24 (1.09–3.84) | 0.71 |
IL-10 (pg/mL) | 0.55 (0.46–0.68) | 0.51 (0.47–0.58) | 0.53 (0.48–0.69) | 0.52 (0.47–0.61) | 0.31 |
sTNF-R2 (pg/mL) | 2.047.3 (1.631.0–2,670.5) | 1,984.8 (1,727.2–2,342.9) | 2,143.2 (1,685.4–2,652.5) | 2,011.5 (1,713.1–2,513.7) | 0.93 |
CRP (mg/L) | 2.74 (1.14–4.56) | 1.95 (0.79–5.02) | 2.18 (0.60–6.74) | 2.23 (0.66–5.35) | 0.88 |
25 (OHD) ng/mL | 15.1 (10.4–23.6) | 16.2 (11.0–22.7) | 13.9 (9.5–22.3) | 15.7 (11.0–23.3) | 0.63 |
Smoking status, No. (%) | 0.26 | ||||
Never | 33 (40.7) | 36 (44.4) | 33 (39.8) | 44 (53.0) | |
Past | 20 (24.7) | 16 (19.8) | 27 (32.5) | 20 (24.1) | |
Current | 28 (34.6) | 29 (35.8) | 23 (27.7) | 19 (22.9) | |
Frequency of exercise, days per weekc, median (IQR) | 3.0 (0.5–5.0) | 3.0 (1.0–5.0) | 3.0 (0–5.0) | 3.0 (0–5.0) | 0.99 |
Dietary vitamin D intake, median (IQR) | |||||
Baseline (n = 328) | 147.3 (71.4–262.8) | 162.5 (92.6–295.5) | 144.0 (58.0–265.1) | 198.1 (83.2–306.4) | 0.41 |
Regular multivitamin used, No. (%) | 10 (12) | 18 (22) | 15 (18) | 22 (27) | 0.16 |
Regular vitamin D supplement used, No. (%) | 8 (10) | 6 (8) | 2 (2) | 8 (10) | 0.45 |
Postmenopausal hormone use, No. (%)e | 0 | 0 | 0 | 1 (0.5) | 0.72 |
Yes | |||||
Regular calcium supplement usef, No. (%) | 7 (8.7) | 9 (11.1) | 7 (8.4) | 9 (10.8) | 0.49 |
Regular aspirin useg, No. (%) | 4 (4.9) | 10 (12.3) | 5 (6.0) | 8 (9.6) | 0.23 |
Regular NSAID useh, No. (%) | 6 (7.4) | 10 (12.3) | 10 (12.0) | 7 (8.4) | 0.73 |
Regular acetaminophen useg, No. (%) | 6 (7.4) | 6 (7.4) | 5 (6.0) | 5 (6.0) | 0.96 |
Marital status, married, No. (%) | 23 (28.4) | 30 (37.0) | 23 (27.7) | 24 (28.9) | 0.58 |
Median household income, No. (%) | 0.92 | ||||
<$10,000 | 33 (40.8) | 23 (28.4) | 27 (32.5) | 27 (32.5) | |
$10,000–19,999 | 15 (18.5) | 17 (21.0) | 17 (20.5) | 17 (20.5) | |
$20,000–29,999 | 11 (13.6) | 10 (12.3) | 16 (19.3) | 10 (12.0) | |
$30,000–39,999 | 4 (4.9) | 9 (11.1) | 4 (4.8) | 9 (10.8) | |
$40,000–49,999 | 4 (4.9) | 5 (6.2) | 4 (4.8) | 4 (4.8) | |
≥$50,000 | 9 (11.1) | 11 (13.6) | 11 (13.3) | 11 (13.3) | |
History of canceri, No. (%) | 6 (7.4) | 0 | 3 (3.6) | 15 (4.6) | 0.032 |
History of hypertension, No. (%) | 35 (43.2) | 35 (43.2) | 36 (43.3) | 35 (42.1) | 0.99 |
. | Vitamin D3 dose assignment (IU/d) . | . | |||
---|---|---|---|---|---|
Characteristic . | Placebo (n = 81) . | 1,000 (n = 81) . | 2,000 (n = 83) . | 4,000 (n = 83) . | Pb . |
Median age, years (IQR) | 50.7 (44.1–58.0) | 51.1 (43.4–60.1) | 50.3 (43.5–58.3) | 51.3 (44.1–59.7) | 0.98 |
Sex, No. (%) | 0.72 | ||||
Male | 27 (33.3) | 22 (27.2) | 28 (33.7) | 29 (34.9) | |
Female | 54 (66.7) | 59 (72.8) | 55 (66.3) | 54 (65.1) | |
Median BMI, kg/m2 (IQR) | 31.2 (26.5–35.9) | 30.5 (27.0–37.5) | 31.9 (26.2–36.9) | 31.4 (27.4–35.7) | 0.82 |
Inflammatory markers | |||||
IL-6 (pg/mL) | 2.21 (1.32–3.42) | 2.38 (1.53–4.02) | 2.30 (1.19–4.17) | 2.24 (1.09–3.84) | 0.71 |
IL-10 (pg/mL) | 0.55 (0.46–0.68) | 0.51 (0.47–0.58) | 0.53 (0.48–0.69) | 0.52 (0.47–0.61) | 0.31 |
sTNF-R2 (pg/mL) | 2.047.3 (1.631.0–2,670.5) | 1,984.8 (1,727.2–2,342.9) | 2,143.2 (1,685.4–2,652.5) | 2,011.5 (1,713.1–2,513.7) | 0.93 |
CRP (mg/L) | 2.74 (1.14–4.56) | 1.95 (0.79–5.02) | 2.18 (0.60–6.74) | 2.23 (0.66–5.35) | 0.88 |
25 (OHD) ng/mL | 15.1 (10.4–23.6) | 16.2 (11.0–22.7) | 13.9 (9.5–22.3) | 15.7 (11.0–23.3) | 0.63 |
Smoking status, No. (%) | 0.26 | ||||
Never | 33 (40.7) | 36 (44.4) | 33 (39.8) | 44 (53.0) | |
Past | 20 (24.7) | 16 (19.8) | 27 (32.5) | 20 (24.1) | |
Current | 28 (34.6) | 29 (35.8) | 23 (27.7) | 19 (22.9) | |
Frequency of exercise, days per weekc, median (IQR) | 3.0 (0.5–5.0) | 3.0 (1.0–5.0) | 3.0 (0–5.0) | 3.0 (0–5.0) | 0.99 |
Dietary vitamin D intake, median (IQR) | |||||
Baseline (n = 328) | 147.3 (71.4–262.8) | 162.5 (92.6–295.5) | 144.0 (58.0–265.1) | 198.1 (83.2–306.4) | 0.41 |
Regular multivitamin used, No. (%) | 10 (12) | 18 (22) | 15 (18) | 22 (27) | 0.16 |
Regular vitamin D supplement used, No. (%) | 8 (10) | 6 (8) | 2 (2) | 8 (10) | 0.45 |
Postmenopausal hormone use, No. (%)e | 0 | 0 | 0 | 1 (0.5) | 0.72 |
Yes | |||||
Regular calcium supplement usef, No. (%) | 7 (8.7) | 9 (11.1) | 7 (8.4) | 9 (10.8) | 0.49 |
Regular aspirin useg, No. (%) | 4 (4.9) | 10 (12.3) | 5 (6.0) | 8 (9.6) | 0.23 |
Regular NSAID useh, No. (%) | 6 (7.4) | 10 (12.3) | 10 (12.0) | 7 (8.4) | 0.73 |
Regular acetaminophen useg, No. (%) | 6 (7.4) | 6 (7.4) | 5 (6.0) | 5 (6.0) | 0.96 |
Marital status, married, No. (%) | 23 (28.4) | 30 (37.0) | 23 (27.7) | 24 (28.9) | 0.58 |
Median household income, No. (%) | 0.92 | ||||
<$10,000 | 33 (40.8) | 23 (28.4) | 27 (32.5) | 27 (32.5) | |
$10,000–19,999 | 15 (18.5) | 17 (21.0) | 17 (20.5) | 17 (20.5) | |
$20,000–29,999 | 11 (13.6) | 10 (12.3) | 16 (19.3) | 10 (12.0) | |
$30,000–39,999 | 4 (4.9) | 9 (11.1) | 4 (4.8) | 9 (10.8) | |
$40,000–49,999 | 4 (4.9) | 5 (6.2) | 4 (4.8) | 4 (4.8) | |
≥$50,000 | 9 (11.1) | 11 (13.6) | 11 (13.3) | 11 (13.3) | |
History of canceri, No. (%) | 6 (7.4) | 0 | 3 (3.6) | 15 (4.6) | 0.032 |
History of hypertension, No. (%) | 35 (43.2) | 35 (43.2) | 36 (43.3) | 35 (42.1) | 0.99 |
Abbreviations: IQR, interquartile range; No., number; NSAID, non-steroidal anti-inflammatory drug.
aData are No. (%) unless otherwise indicated. The numbers do not always sum to group totals due to missing information for some variables.
bThe Kruskal–Wallis test was used to calculate P values for continuous variables. All statistical tests were two-sided.
cExercise defined as moderate to vigorous physical activity for at least 30 minutes, resulting in a faster-than-normal heart rate, sweating, and deep breathing.
dRefers to intake during preceding month.
ePercentages calculated from a total of 222 females.
fDefined as supplement use for 7 days per week during preceding month.
gDefined as 3 or more pills per week during the past week.
hDefined as 3 or more pills per week during the past week. Types of NSAIDs included salsalate, diflunisal, ibuprofen, ketoprofen, nabumetone, piroxicam, naproxen, diclofenac, indomethacin, sulindac, tolmetin, etodolac, ketorolac, and oxaprozin.
iReported cancers include breast cancer, cervical cancer, uterine cancer, lung cancer, prostate cancer, and sarcoma.
Baseline inflammatory marker predictors
At baseline, obese participants (BMI ≥ 30 kg/m2) had significantly higher proinflammatory marker levels, IL-6, sTNF-R2, and CRP, than nonobese participants (Table 2). We also assessed the influence of smoking history on baseline circulating inflammatory markers, IL-6, IL-10, sTNF-R2, and CRP. Current smokers had higher CRP levels than nonsmokers, although the finding did not reach the level of statistical significance (P > 0.05).
Baseline inflammatory markers, median (IQR), stratified by potential predictorsa
Variable . | N . | CRP (mg/dL) . | IL-6 (pg/mL) . | sTNF-R2 (pg/mL) . | IL-10 (pg/mL) . |
---|---|---|---|---|---|
25(OH)D <20 ng/mL | 215 | 2.61 (0.89–4.49)b | 2.38 (1.32–3.83)c | 2031.4 (1687.7–2460.8)c | 0.53 (0.46–0.67)c |
25(OH)D ≥20 ng/mL | 113 | 1.68 (0.48–4.19)b | 2.10 (1.16–3.88)c | 2139.0 (1732.8–2610.0)c | 0.52 (0.46–0.63)c |
BMId <30 kg/m2 | 146 | 1.19 (0.38–2.74)b | 1.68 (0.99–2.73)b | 1882.8 (1585.1–2316.5)b | 0.52 (0.46–0.65)c |
BMId ≥30 kg/m2 | 182 | 3.84 (1.51–7.21)b | 3.00 (1.78–4.62)b | 2186.7 (1815.7–2721.7)b | 0.53 (0.46–0.65)c |
Smoker | 99 | 2.76 (0.87–5.51)c | 2.30 (1.60–4.17)c | 2047.3 (1763.1–2728.6)c | 0.52 (0.45–0.64)c |
Nonsmoker | 223 | 2.07 (0.67–4.88)c | 2.30 (1.17–3.81)c | 2045.9 (1658.5–2481.3)c | 0.53 (0.46–0.65)c |
Variable . | N . | CRP (mg/dL) . | IL-6 (pg/mL) . | sTNF-R2 (pg/mL) . | IL-10 (pg/mL) . |
---|---|---|---|---|---|
25(OH)D <20 ng/mL | 215 | 2.61 (0.89–4.49)b | 2.38 (1.32–3.83)c | 2031.4 (1687.7–2460.8)c | 0.53 (0.46–0.67)c |
25(OH)D ≥20 ng/mL | 113 | 1.68 (0.48–4.19)b | 2.10 (1.16–3.88)c | 2139.0 (1732.8–2610.0)c | 0.52 (0.46–0.63)c |
BMId <30 kg/m2 | 146 | 1.19 (0.38–2.74)b | 1.68 (0.99–2.73)b | 1882.8 (1585.1–2316.5)b | 0.52 (0.46–0.65)c |
BMId ≥30 kg/m2 | 182 | 3.84 (1.51–7.21)b | 3.00 (1.78–4.62)b | 2186.7 (1815.7–2721.7)b | 0.53 (0.46–0.65)c |
Smoker | 99 | 2.76 (0.87–5.51)c | 2.30 (1.60–4.17)c | 2047.3 (1763.1–2728.6)c | 0.52 (0.45–0.64)c |
Nonsmoker | 223 | 2.07 (0.67–4.88)c | 2.30 (1.17–3.81)c | 2045.9 (1658.5–2481.3)c | 0.53 (0.46–0.65)c |
aP value calculated using the Kruskal–Wallis test.
bP < 0.0001.
cP > 0.05.
dBMI missing for 3 patients.
Finally, we assessed the relation between baseline inflammatory markers, IL-6, IL-10, sTNF-R2, and CRP and baseline plasma 25(OH)D levels. We stratified participants by 25(OH)D <20 ng/mL and 25(OH)D ≥20 ng/mL (Table 2). No difference in baseline inflammatory markers was noted between the two groups except that participants with 25(OH)D <20 ng/mL had a statistically significant higher CRP level (P < 0.0001; Table 2). Even in models adjusted for BMI as a continuous variable, participants with 25(OH)D <20 ng/mL had a statistically significant higher CRP level (P < 0.0001; Table 3).
Baseline mean adjusted and unadjusted CRP levels stratified by the baseline 25(OH)D level and the baseline BMI level, mean (95% confidence interval)
. | Unadjusted mean (95% confidence interval) . | Adjusted mean (95% confidence interval) . | ||||
---|---|---|---|---|---|---|
Variable . | N . | CRP (mg/L) . | P . | N . | CRP (mg/L) . | Pa . |
25(OH)D <20 ng/mL | 212 | 2.15 (1.77–2.60) | 0.03 | 212 | 2.01 (1.66–2.43)b | 0.03 |
25(OH)D ≥20 ng/mL | 107 | 1.49 (1.14–1.96) | 107 | 1.42 (1.08–1.88)b | ||
BMI <30 kg/m2 | 140 | 0.99 (0.79–1.23) | <0.0001 | 140 | 1.01 (0.81–1.27)c | <0.0001 |
BMI ≥30 kg/m2 | 179 | 3.17 (2.61–3.84) | 179 | 3.23 (2.60–4.02)c | ||
Smoker | 99 | 1.83 (1.51–2.21) | 0.33 | 97 | 1.69 (1.43–2.04)c | 0.06 |
Nonsmoker | 223 | 2.16 (1.63–2.87) | 222 | 2.25 (1.67–2.81)c |
. | Unadjusted mean (95% confidence interval) . | Adjusted mean (95% confidence interval) . | ||||
---|---|---|---|---|---|---|
Variable . | N . | CRP (mg/L) . | P . | N . | CRP (mg/L) . | Pa . |
25(OH)D <20 ng/mL | 212 | 2.15 (1.77–2.60) | 0.03 | 212 | 2.01 (1.66–2.43)b | 0.03 |
25(OH)D ≥20 ng/mL | 107 | 1.49 (1.14–1.96) | 107 | 1.42 (1.08–1.88)b | ||
BMI <30 kg/m2 | 140 | 0.99 (0.79–1.23) | <0.0001 | 140 | 1.01 (0.81–1.27)c | <0.0001 |
BMI ≥30 kg/m2 | 179 | 3.17 (2.61–3.84) | 179 | 3.23 (2.60–4.02)c | ||
Smoker | 99 | 1.83 (1.51–2.21) | 0.33 | 97 | 1.69 (1.43–2.04)c | 0.06 |
Nonsmoker | 223 | 2.16 (1.63–2.87) | 222 | 2.25 (1.67–2.81)c |
aP value was computed by the linear regression model, PROC GLM; unadjusted and adjusted means are geometric mean of log CRP.
bAdjusted for age, BMI (as continuous variable), sex, smoking status.
cAdjusted for age, sex, smoking status.
Response to vitamin D3 supplementation by the treatment arm
The primary endpoint of the study was change in the plasma inflammatory marker level from baseline to the 3-month follow-up according to treatment arms. Overall, there was no statistically significant change in circulating levels of IL-6, IL-10, sTNF-R2, and CRP associated with treatment arms (Table 4) even after adjustment for BMI as a continuous variable (data not shown). Furthermore, there was no statistically significant change with any vitamin D supplementation (all 3 treatment groups combined) compared with placebo on inflammatory markers (data not shown).
Change in inflammatory markers and 25(OH)D by treatment arm, median (IQR)
. | Vitamin D3 dose assignment (IU/d) . | . | |||
---|---|---|---|---|---|
Time point/variable . | Placebo . | 1,000 . | 2,000 . | 4,000 . | Pa . |
3 months | |||||
No. of participants | 71 | 67 | 76 | 78 | |
25(OH)D (ng/mL) | 13.7 (7.2–18.6) | 29.7 (25.6–32.9) | 34.7 (28.8–41.0) | 45.9 (39.4–55.2) | 0.001 |
IL-6 (pg/mL) | 2.25 (1.30–3.46) | 2.53 (1.57–4.16) | 2.24 (1.29–4.28) | 1.97 (1.09–3.78) | 0.42 |
IL-10 (pg/mL) | 0.51 (0.47–0.63) | 0.49 (0.45–0.57) | 0.52 (0.45–0.59) | 0.52 (0.45–0.61) | 0.63 |
sTNF-R2 (pg/mL) | 2033.4 (1595.4–2542.1) | 2061.4 (1670.5–2586.8) | 2198.6 (1851.0–2632.3) | 1946.0 (1674.5–2537.9) | 0.32 |
CRP (mg/L) | 2.46 (1.27–4.06) | 2.21 (0.92–4.70) | 2.39 (0.75–5.29) | 1.98 (0.49–5.96) | 0.98 |
Δ3 month–baseline | |||||
No. of participants | 71 | 67 | 76 | 78 | |
25(OH)D ng/mL | −2.3 (−5.4–1.7) | 10.8 (2.5–18.9) | 19.2 (11.5–26.2) | 30.2 (21.5–37.6) | <0.001 |
IL-6 (pg/mL) | −0.03 (−0.96–0.88) | −0.07 (−1.07–0.93) | 0.01 (−0.57–0.89) | 0.08 (−0.61–0.71) | 0.84 |
IL-10 (pg/mL) | 0 (−0.06–0.07) | −0.01 (−0.08–0.02) | −0.02 (−0.09–0.02) | 0.00 (−0.06–0.04) | 0.40 |
sTNF-R2 (pg/mL) | −0.89 (−187.75–160.10) | −9.88 (−130.28–149.19) | 59.16 (−132.66–214.59) | 13.29 (−137.03–144.32) | 0.35 |
CRP (mg/L) | −0.05 (−1.13–0.98) | 0.07 (−0.58–0.86) | 0.02 (−0.68–1.21) | 0.03 (−0.68–0.79) | 0.91 |
. | Vitamin D3 dose assignment (IU/d) . | . | |||
---|---|---|---|---|---|
Time point/variable . | Placebo . | 1,000 . | 2,000 . | 4,000 . | Pa . |
3 months | |||||
No. of participants | 71 | 67 | 76 | 78 | |
25(OH)D (ng/mL) | 13.7 (7.2–18.6) | 29.7 (25.6–32.9) | 34.7 (28.8–41.0) | 45.9 (39.4–55.2) | 0.001 |
IL-6 (pg/mL) | 2.25 (1.30–3.46) | 2.53 (1.57–4.16) | 2.24 (1.29–4.28) | 1.97 (1.09–3.78) | 0.42 |
IL-10 (pg/mL) | 0.51 (0.47–0.63) | 0.49 (0.45–0.57) | 0.52 (0.45–0.59) | 0.52 (0.45–0.61) | 0.63 |
sTNF-R2 (pg/mL) | 2033.4 (1595.4–2542.1) | 2061.4 (1670.5–2586.8) | 2198.6 (1851.0–2632.3) | 1946.0 (1674.5–2537.9) | 0.32 |
CRP (mg/L) | 2.46 (1.27–4.06) | 2.21 (0.92–4.70) | 2.39 (0.75–5.29) | 1.98 (0.49–5.96) | 0.98 |
Δ3 month–baseline | |||||
No. of participants | 71 | 67 | 76 | 78 | |
25(OH)D ng/mL | −2.3 (−5.4–1.7) | 10.8 (2.5–18.9) | 19.2 (11.5–26.2) | 30.2 (21.5–37.6) | <0.001 |
IL-6 (pg/mL) | −0.03 (−0.96–0.88) | −0.07 (−1.07–0.93) | 0.01 (−0.57–0.89) | 0.08 (−0.61–0.71) | 0.84 |
IL-10 (pg/mL) | 0 (−0.06–0.07) | −0.01 (−0.08–0.02) | −0.02 (−0.09–0.02) | 0.00 (−0.06–0.04) | 0.40 |
sTNF-R2 (pg/mL) | −0.89 (−187.75–160.10) | −9.88 (−130.28–149.19) | 59.16 (−132.66–214.59) | 13.29 (−137.03–144.32) | 0.35 |
CRP (mg/L) | −0.05 (−1.13–0.98) | 0.07 (−0.58–0.86) | 0.02 (−0.68–1.21) | 0.03 (−0.68–0.79) | 0.91 |
Abbreviations: No., number; IQR, interquartile range.
aP value calculated using the Kruskal–Wallis test.
Effect of vitamin D3 supplementation on plasma 25(OH)D
Among 328 participants, the median 25(OH)D level at baseline was 15.3 ng/mL. Plasma 25(OH)D did not differ significantly between treatment arms (P = 0.63; Table 4). Circulating 25(OH)D levels at 3 months differed significantly by the vitamin D3 supplementation arm, with a median of 13.7, 29.7, 34.8, and 45.9 ng/mL for the placebo, 1,000 IU/day, 2,000 IU/day, and 4,000 IU/day arms, respectively (P = 0.001). Notably, plasma 25(OH)D decreased at 3 months among participants treated with placebo (Table 3).
Interaction analyses
Interaction analyses were performed to determine the treatment effects of vitamin D by baseline 25(OH)D levels. With the exception of CRP, no interaction between baseline 25(OH)D and vitamin D treatment was found. For CRP, the interaction remained after adjustment for age, sex, BMI, and log baseline CRP. For BMI, no interaction between baseline BMI and vitamin D treatment for change in inflammatory markers at 3 months was observed.
Discussion
To our knowledge, this is the largest randomized placebo-controlled trial to examine the impact of oral vitamin D supplementation for 3 months on circulating inflammatory markers in an African American cohort. Overall, vitamin D3 supplementation did not reduce proinflammatory markers CRP, IL-6, and sTNF-R2 or increase anti-inflammatory marker IL-10. Despite a clear trend in the change of follow-up serum 25(OH)D concentrations with increasing doses of supplemental vitamin D3, we did not observe a significant association between supplemental vitamin D3 dose and change in the measured inflammatory markers, IL-6, IL-10, sTNF-R2, and CRP, even after adjustment for BMI.
Our null finding is similar to Jorde and colleagues, who also found no overall change in inflammatory markers with vitamin D supplementation (D3 20,000 IU/week or D3 40,000 IU/week; ref. 22). No gender differences between 25(OH)D baseline levels and inflammatory markers of inflammation were observed. These plasma inflammatory markers may be a relatively nonspecific measurement of short-term changes in the tissue-specific inflammatory pathways relevant to inflammatory chronic diseases such as diabetes and cardiovascular disease. Several researchers report significant favorable effects of vitamin D supplementation in randomized control trials on proinflammatory cytokines such as IL-6, sTNF-R2, and CRP, but only in strictly selected groups of patients such as type 2 diabetics (23) and patients with congestive heart failure (24).
Baseline 25(OH)D may be a good predictor of long-term vitamin D status. Baseline inflammatory marker CRP adjusted for BMI was inversely associated with the baseline 25(OH)D level with a significantly lower CRP level noted in participants with 25(OH)D ≥20 ng/mL compared with 25(OH)D <20 ng/mL. This inverse relationship is consistent with prior observational studies that reported an inverse relationship between CRP and 25(OH)D in patients with colorectal adenoma (24) and in overweight and obese individuals (25). These results were different from a non–African American cohort. The Framingham Offspring Cohort study also found no correlation between 25(OH)D and CRP (26). The lack of correlation between 25(OH)D and CRP in the Framingham Offspring Cohort study may be related to that fact that it is a leaner cohort with few African Americans and less confounding by BMI. Factors that contribute to ongoing inflammation and immune activation in these chronic diseases are incompletely understood. In human and in vitro studies, vitamin D exerts a diverse array of immunomodulatory effects by interacting with the vitamin D system in a complex pathway that includes precursors, active metabolites, enzymes, and receptors (27, 28).
Strengths of our study include its prospective design, the use of a double-blind–controlled intervention, the broad set of inflammatory markers that were evaluated, and the collection of cytokine data in community dwelling adults. Moreover, the precision of inflammatory marker measurement seemed adequate with low coefficients of variation for each marker: CRP, 2.6%; IL-6, 3.8%; IL-10, 10.3%; and sTNF-R2, 3.3%.
Some limitations should also be considered. Given the 3-month duration of vitamin D supplementation, the endpoint of the study was not long-term benefit of supplementation on inflammation. In this heterogeneous convenience sample of healthy African American participants, exogenous factors may bias the trial to null, and this trial may be underpowered to detect clinically significant effects of vitamin D on inflammatory markers. Although CRP is a reliable marker of systemic inflammation (29), we cannot exclude the possibility that the inflammatory markers chosen for the analysis may not have adequately captured systemic inflammation.
Furthermore, we selected a target 25(OH)D of ≥33 ng/mL based on prospective observational studies (30), but clinical trials assessing the effect of achieving this level are not available. Finally, because the highest dose of vitamin D3 in our trial was 4,000 IU/day, we were not able to evaluate the influence of higher doses on inflammatory markers. Given the variation of these inflammatory markers that may occur with acute infection and other conditions, a large-scale longitudinal study of longer duration, such as the VITamin D and OmegA-3 TriaL (VITAL) with over 20,000 participants and oversampling of African Americans (31, 32), would be a good way to evaluate the effect of vitamin D on these inflammatory markers.
The theory of vitamin D playing a role in cancer prevention is biologically plausible (15). Studies in cell culture and experimental models show that calcitriol may promote cell differentiation, inhibit cancer-cell proliferation, and exhibit anti-inflammatory, proapoptotic, and antiangiogenic properties (33, 34). A compartmental model such as colonic mucosa may be a better way to evaluate the local effect of vitamin D on inflammatory cytokines because blood dilutes the inflammatory cytokines. Yet, this study does validate the association of low plasma 25(OH)D with elevated CRP (24, 35) and provide evidence that vitamin D supplementation does not increase the production of proinflammatory cytokines.
In conclusion, we failed to find an influence of relatively short-term supplementation with vitamin D3 on inflammatory markers in a cohort of African Americans. For analyses stratified by baseline 25(OH)D status, we did observe a significant interaction of baseline 25(OH)D and vitamin D supplementation on change in log CRP at 3 months. This study contributes to the growing body of literature evaluating the impact of vitamin D3 supplementation on inflammation for cancer risk reduction and confirms the strong independent association of CRP with obesity (36) and CRP with 25(OH)D status even after adjusting for BMI. Nonetheless, future studies with larger sample sizes and longer durations of supplemental vitamin D3 intervention are necessary to examine the influence of vitamin D3 on CRP and other inflammatory cytokines for reduction of cancer disparities in African Americans.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
Authors' Contributions
Conception and design: K. Ng, G.G. Bennett, B.W. Hollis, E.L. Giovannucci, C.S. Fuchs
Development of methodology: N. Rifai, A.T. Chan, G.G. Bennett, B.W. Hollis, E.L. Giovannucci, C.S. Fuchs
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): P.D. Chandler, J.B. Scott, B.F. Drake, K. Ng, C.S. Fuchs
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): P.D. Chandler, J.B. Scott, K. Ng, J.E. Manson, A.T. Chan, B.W. Hollis, K.M. Emmons, C.S. Fuchs
Writing, review, and/or revision of the manuscript: P.D. Chandler, J.B. Scott, B.F. Drake, K. Ng, J.E. Manson, N. Rifai, A.T. Chan, G.G. Bennett, B.W. Hollis, E.L. Giovannucci, K.M. Emmons, C.S. Fuchs
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): J.B. Scott, K. Ng, J.E. Manson, C.S. Fuchs
Study supervision: J.B. Scott, C.S. Fuchs
Acknowledgments
The authors thank Cara Marcus, MSLIS, AHIP, Director of Library Services, Brigham, and Women's Faulkner Hospital for facilitating access to reference articles and Harvard Catalyst for statistical support.
Grant Support
This study was funded by the National Cancer Institute [P50CA127003; K07CA148894 (K. Ng); K22CA126992; 5K05CA124415 (K.M. Emmons); U01CA138962 (P.D. Chandler)], the Department of Defense Prostate Cancer Research Program (PC081669; to B.F. Drake), the American Society of Clinical Oncology Career Development Award (K. Ng), and Pharmavite LLC.
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