Genetic, Dietary and Environmental Influences on Vitamin D Metabolism

Study Overview
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Brief Summary
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Determine differences in serum vitamin D metabolism by genetic ancestry.

Detailed Description
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Vitamin D metabolites are well-recognized to stop cancer cell growth in culture. However, a clear definition of a sufficient level of serum vitamin D (currently measured as 25(OH)D) for disease prevention has been hampered by inconsistent results from both observational studies and randomized clinical trials. Observational cancer studies report both increased and reduced risks of cancer in subjects with higher serum levels of 25(OH)D, while large randomized trials report no significant benefit of vitamin D supplementation for breast cancer (incidence), colon cancer (incidence and mortality), lung cancer (mortality), or benign proliferative breast disease. The 25(OH)D metabolite of vitamin D (comprised of 25(OH)D3 and 25(OH)D2), is the principal hydroxylated metabolite in serum and is considered a reasonable functional biomarker of vitamin D status. This is because, although subject to seasonal variation, multiple measurements in the same individual are relatively consistent over time. The most biologically active vitamin D metabolite is 1,25(OH)2D3, and may therefore be the most relevant to long-term health outcomes. Nonetheless, 1,25(OH)2D3 is not frequently used as a biomarker in epidemiologic studies as it displays diurnal variation and has a short in vivo half life. Notably, in vivo treatment with 1,25(OH)2D3 is associated with increased metabolic clearance of 25(OH)D3, decreased serum 25(OH)D3 levels, and a higher 25(OH)D3 to 24,25(OH)2D3 conversion rate in humans and animals. This suggests that use of 25(OH)D as single biomarker of vitamin D status does not fully capture the entire picture. Paradoxically, one individual may be classified with 'low' 25(OH)D as a consequence of low dietary intake and little sun exposure while yet another individual classified with 'low' 25(OH)D may actually have a higher concentration of the 1,25(OH)2D3 metabolite-possibly due to genetic differences in enzymes that metabolize vitamin D (CYP2R1, CYP27B1, and CYP24A1). Genome-wide and candidate gene association studies of serum 25(OH)D levels have suggested a role of single nucleotide polymorphisms (SNPs) near the vitamin D binding protein (GC) and CYP2R1. However, the investigators and others have shown that serum 25(OH)D levels are also associated with genetic ancestry. Because existing studies do not adjust for genetic ancestry and the function of these SNPs have yet to be established, it is not known whether these SNPs actually play a role or whether these may be spurious associations due to ancestral background (i.e., population stratification), correlations with truly causal SNPs, or to random chance. In addition, because of the number of SNPs that must be distinguished, genome-wide studies do not capture regions with high homology or sequence repeats, such as the promoter region of CYP24A1 which has a higher guanine-cytosine content. Improved classification of 'low' 25(OH)D levels within the context of a particular genetic background through identification of rapid versus slow vitamin D metabolizers will likely have important implications for cancer risk. It is well-recognized that individuals with African Ancestry have substantially lower ( 2-fold) serum 25(OH)D levels compared with other racial/ethnic groups. These differences have been attributed primarily to skin pigmentation. However, the relation between serum 25(OH)D levels and health outcomes is complex and involves a number of variables including diet, sun exposure and hormone status. For example, despite lower average dietary intake of both calcium and vitamin D, and lower serum 25(OH)D levels, African Americans have higher bone mineral density and a 3-fold lower risk of hip fracture relative to European Americans. There are some lines of evidence which suggest that African Americans may have comparatively higher circulating levels of 1,25(OH)2D3, although most studies are small and do not account for age and/or diurnal variation, and this may explain why other studies report no difference. Among Europeans alone, a moderately high heritability of serum 25(OH)D levels ( 50 to 70% for 25(OH)D) has been observed, as well as associations between 25(OH)D and several genetic polymorphisms in vitamin D metabolizing enzymes, although the functional consequences of these polymorphisms are not known. Small and large clinical trials among healthy individuals have also noted substantial inter-individual differences(as much as 5-fold) in the increases of serum 25(OH)D levels among participants given the same oral dose of vitamin D, the same minimal erythema dose (MED) of UV-B light, or the same dose of UV light. The importance of understanding inter-individual differences in vitamin D synthesis, metabolism and effect have been underscored by results from high dose randomized trials reporting that those in the vitamin D supplementation groups experienced a 31% higher bone fracture incidence, and significantly lower prostate cancer survival. There is a clear need to understand individual differences in the metabolism of vitamin D before future high dose trials proceed. Previous Data: Studies by the investigators' lab and others have identified significant racial/ethnic differences in the frequency of variants in genes responsible for vitamin D metabolism (i.e., CYP2R1, CYP27B1 and CYP24A1). In collaboration with the Pike Laboratory (University of Wisconsin), the investigators' laboratory has identified several novel genetic variants in recently identified regulatory regions of the gene which encodes for the major vitamin D catabolic enzyme (CYP24A1). Study Rationale:The role/function of these polymorphisms has not been tested in either epidemiologic association studies or in cell-based assays. It will be important to complement genetic association studies with multiple types of molecular assays that can tell a consistent story about the likely role of a particular genetic variant. The investigators hypothesize that there is a significant influence of genetic variants on serum vitamin D metabolism that is independent of genetic ancestry, skin melanin content, sunlight exposure and dietary/supplement intake. Study Objectives:A small randomized study in healthy subjects will investigate temporal changes in the balance of metabolites (25(OH)D3, 25(OH)D2, 24,25(OH)2D3 and 1,25(OH)2D3) following a two-month course of vitamin D3 (800 IU/d). This study overcomes limitations of existing genetic association studies that may report spurious results due to lack of control for genetic ancestry, skin reflectance, collection of blood specimens during summer months, or the use of assays that do not distinguish 25(OH)D2 and 25(OH)D3. The advantages of this study are: 1) a matched design that incorporates temporal assessment of vitamin D metabolism, 2) genetic Ancestry Informative Markers (AIMs), 3) melanin skin index, 4) a sensitive and reliable assay for four serum vitamin D metabolites, and 5) functional molecular assays related to specific genetic polymorphisms. The investigators' research addresses one of the major research gaps in the understanding of the health-related benefits of vitamin D identified by a recent Institute of Medicine Review. While vitamin D metabolites have significant anti-cancer properties, a better understanding of the genetic influences upon vitamin D metabolism is needed in order to improve the identification of cancer risks associated with vitamin D. Study Design: This study employs two designs-first a cross-sectional study of participants is selected. Among the cross-sectional study participants, a subset is randomly selected and matched based on genetic ancestry, and randomized to either the intervention (800 IU/day of vitamin d) or placebo group. Statistical Plan:In the first portion of this study, an estimated 400 participants will be screened to determine eligibility. Eligibility screening will be completed online through RedCap. In the second portion of this study, participants randomly chosen from the original 400 for the Supplement Intervention Study will be asked to complete 3 additional blood draws at Week 0, 4 and 8 of the Supplement Intervention Study (N=64). The 64 Supplement Intervention study participants will be randomly chosen from the eligible participants in the first part of the study (n=400). Sample size calculations were performed by Dr. Vernon Chinchilli in order to estimate the number of participants that the investigators would need in order to detect differences in their vitamin D levels. The investigators accounted for loss-to-follow-up and normal withdrawal from the study. NOTE: The total participants that will get screened has been changed (from the original AICR grant) and revised in the budget from 300 to 400 participants. The investigators made this revision because the investigators decided that loss to follow-up may be higher than the originally estimated 10%. The investigators then estimated that loss to follow-up may actually be closer to 20%. This proportional difference was calculated from the investigators' original estimate of 52 to 64 (which is about 24% increase in participants) and was revised also to increase the amount of participants that the investigators will screen from the original 300 to an estimated 372 (determined proportionally with a 24% increase). The investigators went ahead and assumed that the upper limit may include 400 participants so that the investigators can end up with 64 participants in the supplementation trial. The investigators will conduct an intention-to-treat analysis to analyze differences in the serum level of vitamin D metabolites and vitamin D metabolite ratios within supplement and placebo group pairs at times 0, 1 month and 2 months. Differences in the pairwise log concentration of metabolites and log metabolite ratios will be tested by Wilcoxon Signed-Rank Tests and linear mixed-effect models (SAS Proc Mixed) using restricted maximum likelihood estimation to account for one time point as well as repeated measures of vitamin D metabolites. Potential confounding and effect modification by dietary intake of vitamin D will be assessed.

Official Title
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Genetic, Dietary and Environmental Influences on Vitamin D Metabolism

Conditions
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Vitamin D Deficiency

Intervention / Treatment
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* Dietary Supplement: 800 IU Vitamin D
* Dietary Supplement: Placebo


Participation Criteria
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Eligibility Criteria
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Inclusion Criteria: Healthy African American and Caucasian adult volunteers Aged 18 to 35 At least 50% African American or at least 50% Caucasian Willing to take a vitamin D supplement for two months Willing to attend monthly visits to the clinic for blood draw and vital check Willing to refrain from taking other dietary supplements including herbal supplements, multi-vitamins and vitamin D supplements other than the supplements provided in the trial. Willing to avoid tanning bed use during the above mentioned period. Willing to avoid extensive use of analgesics and have the consumption of the following drugs recorded: Acetaminophen, Celecoxib, Codeine, Fentanyl, any antibiotics, and Hormonal IUD. Exclusion Criteria: Participants with a fever (100 degrees F or higher) at the time of the visit Participants with severe chronic disease (i.e., chronic kidney disease, cirrhosis of the liver, heart attack, HIV/AIDS, alcoholism, hemophilia, sickle cell disease, or other serious underlying illness that prevents blood donation), Participants that have received radiation therapy or chemotherapy within the past 4 weeks, Participants with any of the following on the upper right arm: rashes, a cast, swelling, paralysis, open sores or wounds. Individuals with blindness and/or deafness Pregnant participants will be excluded from the study. Participants taking any of the following medications will be excluded from the study: Long-term antibiotic use: Clarithromycin, Ciprofloxacin, Erythromycin, Telithromycin, Nafcillin Chemotherapy for cancer Prescription vitamin supplement Anti-convulsants: Carbamazepine, Pentobarbital, Phenobarbital, Phenytoin, Primidone, Fosphenytoin Erectile dysfunction drugs: sildenafil, vardenafil, tadalafil Immunosuppressants: Tacrolimus, Cyclosporine A, Sirolimus, Mycophenolate, Glucocorticoids (like Dexamethasone) Proton-pump inhibitors: omeprazole lansoprazole, dexlansoprazole, rabeprazole, pantoprazole, and esomeprazole Calcium Channel Blockers: nifedipine, felodipine, isradipine, nicardipine, nifedipine, nisoldipine, amlodipine, lacidipine, Verapamil, diltiazem Diuretics : furosemide, bumetanide, torsemide, ethacrynic acid, amiloride, triamterene, spironolactone, eplerenone, Statins: lovastatin, simvastatin, atorvastatin, Pravastatin, fluvastatin, rosuvastatin, pitavastatin, Orlistat (Xenical, Alli), Anti-fungal: Itraconazole, Ketoconazole, Posaconazole, Voriconazole, Fluconazole, Isavuconazole (isavuconazonium sulfate) Clotrimazole HIV protease inhibitors and other anti-retrovirals : Atazanavir, Boceprevir, Darunavir, Indinavir, Lopinavir, Nelfinavir, Ombitasvirparitaprevirritonavir, Ombitasvirparitaprevirritonavir plus dasabuvir, Ritonavir and ritonavir containing coformulations, Saquinavir, Telaprevir TB medications: Rifabutin, Rifampin (rifampicin), Rifapentine As well as CYP3A4 inhibitors including: Ceritinib, Cobicistat and cobicistat containing coformulations, Idelalisib, Nefazodone, Amiodarone, Aprepitant, Cimetidine, Conivaptan, Crizotinib, Delavirdine, Desipramine, Dronedarone, Fosaprepitant Mifepristone, Netupitant, Nilotinib, and Tibolone As well as CYP3A4 inducers including: Dexamethasone, Enzalutamide, Lumacaftor, Mitotane, St. John's wort, Bexarotene, Bosentan, Dabrafenib, Efavirenz, Eslicarbazepine, Etravirine, Modafinil Other drugs that will cause a participant to be excluded include: Cholestyramine, Ferric carboxymaltose (treatment of iron deficiency anemia), Dapsone, Metformin

Ages Eligible for Study
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Minimum Age: 18 Years
Maximum Age: 35 Years

Sexes Eligible for Study
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All

Accepts Healthy Volunteers
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Accepts Healthy Volunteers

Study Plan
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How is the study designed?
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Design Details

Primary Purpose: Basic Science
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Triple


Arms and Interventions

| Participant Group/Arm | Intervention/Treatment |
| --- | --- |
| Experimental: 800 IU Vitamin D<br>Participants will be taking 800 IU/d of vitamin D3 for two months | Dietary Supplement: 800 IU Vitamin D<br>* Among the cross-sectional study participants, a subset is randomly selected and matched based on genetic ancestry, and randomized to the intervention group.<br>* Other names: Vital Nutrients;|
| Placebo Comparator: Placebo<br>Placebo made by Vital Nutrients, Inc. to look exactly like the 800 IU/d caplets by the same company. | Dietary Supplement: Placebo<br>* Among the cross-sectional study participants, a subset is randomly selected and matched based on genetic ancestry, and randomized to the placebo group<br>* Other names: Vital Nutrients Placebo;|

What is the study measuring?
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Primary Outcome Measures

| Outcome Measure | Measure Description | Time Frame |
| --- | --- | --- |
| Serum concentrations of 25(OH)D3 | Differences in the increase in fasting serum levels of vitamin D metabolite 25(OH)D3 between African American and European American ancestry pairs will be determined at 0, 1 and 2 months. | Three month change | 
| Serum concentrations of 24,25(OH)2D3 | Differences in the increase in fasting serum levels of vitamin D metabolite 24,25(OH)D3 between African American and European American ancestry pairs will be determined at 0, 1 and 2 months. | Three month change | 
| Serum concentrations of 1,25(OH)2D3 | Differences in the increase in fasting serum levels of vitamin D metabolite 1,25(OH)D3 between African American and European American ancestry pairs will be determined at 0, 1 and 2 months. | Three month change | 
| Metabolite Ratio | Difference in the upstream to downstream vitamin D metabolite ratios (24,25(OH)2D3 to 25(OH)D3 and 1,25(OH)2D3 to 25(OH)D3) between African American and European American ancestry pairs will be determined at 0, 1 and 2 months. | Three months |