Vitamin D-related Genes and Metabolic Disorders

• ClinicalTrials.gov Identifier: NCT03279432
• Recruitment Status: Completed
• First Posted: September 12, 2017
• Last Update Posted: September 12, 2017
• Sponsor: National Institute on Aging (NIA)
• Information provided by (Responsible Party): May Ahmad Baydoun, National Institute on Aging (NIA)

Tracking Information

• First Submitted Date: September 8, 2017
• First Posted Date: September 12, 2017
• Last Update Posted Date: September 12, 2017
• Actual Study Start Date: August 18, 2004
• Actual Primary Completion Date: July 7, 2013 (Final data collection date for primary outcome measure)

Current Primary Outcome Measures (submitted: September 11, 2017)

• Obesity [ Time Frame: 2004-2013 ]
  Obesity was defined as BMI≥30 kg/m2.
• Central Obesity [ Time Frame: 2004-2013 ]
  Central obesity was defined based on waist circumference (WC) ≥ 102 cm or 40 inches (men), ≥ 88 cm or 35 inches (women)
• Metabolic Syndrome [ Time Frame: 2004-2013 ]
  Participants who screened positive on at least 3 of 5 conditions ((1) central obesity (see above); (2) dyslipidemia: TAG≥1.695 mmol/L (150 mg/dl); (3) dyslipidemia: HDL-C<40 mg/dL (male), <50 mg/dL (female); (4) blood pressure≥130/85 mmHg; (5) fasting plasma glucose≥6.1 mmol/L (110 mg/dl).(39)) were classified as MetS-positive (2) Similarly, continuous annual rates of change (Δ) in metabolic outcomes were considered, specifically number of metabolic disturbances (MetD), BMI, WC, SBP, DBP, TAG, HDL-C, and Glucose. Binary incident outcomes included obesity, central obesity, MetS and other metabolic disturbance (i.e. hypertension, dyslipidemia-TAG, dyslipidemia-HDL and hyperglycemia).

• Original Primary Outcome Measures: Same as current
• Change History: No Changes Posted
• Current Secondary Outcome Measures: Not Provided
• Original Secondary Outcome Measures: Not Provided
• Current Other Pre-specified Outcome Measures: Not Provided
• Original Other Pre-specified Outcome Measures: Not Provided

Descriptive Information

• Brief Title: Vitamin D-related Genes and Metabolic Disorders
• Official Title: Vitamin D Receptor and Megalin Gene Polymorphisms and Their Association With Obesity, Central Obesity and the Metabolic Syndrome

Brief Summary

The link between metabolic disturbances and vitamin D receptor (VDR) and MEGALIN (or LRP2) gene polymorphisms remains unclear, particularly among African-American adults. The associations of single nucleotide polymorphisms (SNPs) for VDR [rs1544410(BsmI:G/A), rs7975232(ApaI:A/C), rs731236(TaqI:G/A)] and MEGALIN [rs3755166:G/A,rs2075252:C/T, rs2228171:C/T] genes with incident and prevalent metabolic disturbances, including obesity, central obesity and metabolic syndrome (MetS) were evaluated.

From 1,024 African-Americans participating in the Healthy Aging in Neighborhoods of Diversity across the Life Span (HANDLS, Baltimore, MD, 2004-2013) study, 539 subjects were selected who had complete genetic data as well as covariates selected for metabolic outcomes at two consecutive examinations (visits 1 and 2) with a mean follow-up time of 4.64±0.93y. Haplotype (HAP) analyses generated polymorphism groups that were linked to incident and prevalent metabolic disturbances.

• Detailed Description: Adiposity, especially central adiposity, is a key component of the metabolic syndrome (MetS), which is accompanied by hyperglycemia, elevated blood pressure, lower HDL cholesterol and hypertriglyceridemia.(Ford, et al., 2003,Grundy, 1999)_ENREF_4 MetS increases the risk of type 2 diabetes (T2D) and cardiovascular disease by 1.7- and 5-folds, respectively.(Alberti, et al., 2009,Ford, et al., 2003,Galassi, et al., 2006) MetS is heritable and polygenic.(Maes, et al., 1997) Genetic variability contributes to 16%-85% of changes in Body Mass Index (BMI)(Yang, et al., 2007) and 37%-81% in waist circumference (WC) (e.g.(Ochs-Balcom, et al., 2011)). MetS is a major public health concern, increasing all-cause mortality rates, disability and health care costs.(Appels and Vandenbroucke, 2006,Bender, et al., 2006,Colditz, 1999,Doig, 2004,Ferrucci and Alley, 2007,Hill, et al., 2004,Solomon and Manson, 1997,Stevens, 2000,Wolf and Colditz, 1998) Obesity is implicated in the etiology of vitamin D deficiency. Serum 25-hydroxyvitamin D [25(OH)D] concentration correlates inversely with adiposity.(Beydoun, et al., 2010,Dorjgochoo, et al., 2012) Conversely, vitamin D3 may play a role in obesity by modulating intracellular calcium homeostasis, because higher intracellular calcium triggers lipogenesis and suppresses lipolysis.(Zemel, 2003) Many organs express vitamin D receptor (VDR), a part of the nuclear hormone receptor super-family. The VDR-1,25(OH)2D3 complex modulates transcription of vitamin D responsive genes(Kato, 2000) and influences adipocyte differentiation both in vitro and in vivo.(Wood, 2008) Epidemiological studies have shown associations of VDR gene polymorphisms with adiposity and related metabolic disorders.(Filus, et al., 2008,Grundberg, et al., 2004,Gu, et al., 2009,Ochs-Balcom, et al., 2011,Oh and Barrett-Connor, 2002,Ortlepp, et al., 2001,Ortlepp, et al., 2003,Speer, et al., 2001,Ye, et al., 2001) However, studies specifically examining adiposity outcomes either had small sample sizes (<400), (e.g.(Filus, et al., 2008,Grundberg, et al., 2004,Speer, et al., 2001)) or were restricted to one sex, (e.g. (Grundberg, et al., 2004,Ochs-Balcom, et al., 2011)) but more importantly were all cross-sectional or case-control by design.(Filus, et al., 2008,Grundberg, et al., 2004,Gu, et al., 2009,Ochs-Balcom, et al., 2011,Oh and Barrett-Connor, 2002,Ortlepp, et al., 2001,Ortlepp, et al., 2003,Speer, et al., 2001,Ye, et al., 2001) MEGALIN (aka low-density lipoprotein receptor-related protein-2 [LRP-2]), is the endocytic vitamin D-binding protein receptor which allows vitamin D entry into cells and whose expression is directly regulated by both vitamin D (Gressner, et al., 2008)) and vitamin A.(Liu, et al., 1998) MEGALIN may influences obesity by mediating leptin transport through the blood-brain barrier and modulating leptin signaling,(Dietrich, et al., 2008) or by facilitating transcytosis of its precursor hormone thyroglobulin.(Lisi, et al., 2005) Collectively, leptin and thyroid hormones affect adiposity through energy metabolism regulation.(Beydoun, et al., 2011) MEGALIN acting also as the receptor for sex-hormone binding globulin (SHBG) may play a role in the interaction between estrogen, vitamin D and intracellular calcium in adipocytes, resulting in sex-specific effects of MEGALIN polymorphisms on obesity phenotypes.(Ding, et al., 2008) In this study, it is hypothesized that selected polymorphisms in VDR and MEGALIN genes have sex-specific associations with several key metabolic disturbances in a longitudinal study of African-American urban adults.
• Study Type: Observational
• Study Design: Observational Model: Cohort; Time Perspective: Prospective
• Target Follow-Up Duration: Not Provided

Biospecimen

Retention:   Samples With DNA

Description:

Study participants were genotyped to 907,763 single nucleotide polymorphisms (SNPs) using the Illumina 1M and 1M-Duo genotyping arrays. Sample quality control inclusion criteria were: (1) concordance between self-reported sex and X-chromosome estimated sex; (2) sample call rate >95%, (3) concordance between self-reported African ancestry and ancestry estimated using genotyped SNPs, and (4) proportional sharing of genotypes < 15% between samples, excluding close relatives from the final sample. SNPs in HANDLS were selected when the following criteria were met: (1) Hardy-Weinberg equilibrium p-value (HWE P >10-7); (2) Missing by haplotype P > 10-7; (3) Minor allele frequency>0.01, and (4) SNP call rate >95%. Quality control and data management for each genotype was conducted using PLINKv1.06.

• Sampling Method: Probability Sample
• Study Population: Of the 3,720 baseline participants (mean±SD age(y) of 48.3±9.4, 45.3% men, and 59.1% African-American), genetic data were available on 1,024 African-American participants. Incomplete covariate data reduced the sample to n=769, while additional exclusions lead to a sample size ranging between 574 and 598 participants, with 539 having complete data on all baseline and follow-up outcome measures (cross-sectional part of the analysis). In the longitudinal analysis, metabolic disturbance-free at baseline participants were selected for each outcome. Sample sizes ranged from n=246 (central obesity-free) to n=466 (hyperglycemia-free). There were n=294 MetS-free individuals at baseline (Figure 1).

Condition

• Metabolic Syndrome
• Obesity
• Central Obesity

• Intervention: Not Provided
• Study Groups/Cohorts: Not Provided

Publications *

• Ford ES, Mokdad AH, Giles WH, Brown DW. The metabolic syndrome and antioxidant concentrations: findings from the Third National Health and Nutrition Examination Survey. Diabetes. 2003 Sep;52(9):2346-52.
• Grundy SM. Hypertriglyceridemia, insulin resistance, and the metabolic syndrome. Am J Cardiol. 1999 May 13;83(9B):25F-29F. Review.
• Galassi A, Reynolds K, He J. Metabolic syndrome and risk of cardiovascular disease: a meta-analysis. Am J Med. 2006 Oct;119(10):812-9.
• Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, Fruchart JC, James WP, Loria CM, Smith SC Jr; International Diabetes Federation Task Force on Epidemiology and Prevention; Hational Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; International Association for the Study of Obesity. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009 Oct 20;120(16):1640-5. doi: 10.1161/CIRCULATIONAHA.109.192644. Epub 2009 Oct 5.
• Maes HH, Neale MC, Eaves LJ. Genetic and environmental factors in relative body weight and human adiposity. Behav Genet. 1997 Jul;27(4):325-51. Review.
• Yang W, Kelly T, He J. Genetic epidemiology of obesity. Epidemiol Rev. 2007;29:49-61. Epub 2007 Jun 12. Review.
• Ochs-Balcom HM, Chennamaneni R, Millen AE, Shields PG, Marian C, Trevisan M, Freudenheim JL. Vitamin D receptor gene polymorphisms are associated with adiposity phenotypes. Am J Clin Nutr. 2011 Jan;93(1):5-10. doi: 10.3945/ajcn.2010.29986. Epub 2010 Nov 3.
• Appels CW, Vandenbroucke JP. Overweight, obesity, and mortality. N Engl J Med. 2006 Dec 21;355(25):2699; author reply 2700-1.
• Bender R, Zeeb H, Schwarz M, Jöckel KH, Berger M. Causes of death in obesity: relevant increase in cardiovascular but not in all-cancer mortality. J Clin Epidemiol. 2006 Oct;59(10):1064-71. Epub 2006 May 30.
• Doig GS. Obesity-related excess mortality: What should we do now? Crit Care Med. 2004 Apr;32(4):1084-5.
• Ferrucci L, Alley D. Obesity, disability, and mortality: a puzzling link. Arch Intern Med. 2007 Apr 23;167(8):750-1.
• Solomon CG, Manson JE. Obesity and mortality: a review of the epidemiologic data. Am J Clin Nutr. 1997 Oct;66(4 Suppl):1044S-1050S. doi: 10.1093/ajcn/66.4.1044S. Review.
• Stevens J. Obesity and mortality in African-Americans. Nutr Rev. 2000 Nov;58(11):346-53. Review.
• Colditz GA. Economic costs of obesity and inactivity. Med Sci Sports Exerc. 1999 Nov;31(11 Suppl):S663-7. Review.
• Hill JO, Sallis JF, Peters JC. Economic analysis of eating and physical activity: a next step for research and policy change. Am J Prev Med. 2004 Oct;27(3 Suppl):111-6. Review.
• Wolf AM, Colditz GA. Current estimates of the economic cost of obesity in the United States. Obes Res. 1998 Mar;6(2):97-106. Review.
• Beydoun MA, Boueiz A, Shroff MR, Beydoun HA, Wang Y, Zonderman AB. Associations among 25-hydroxyvitamin D, diet quality, and metabolic disturbance differ by adiposity in adults in the United States. J Clin Endocrinol Metab. 2010 Aug;95(8):3814-27. doi: 10.1210/jc.2010-0410. Epub 2010 May 12.
• Dorjgochoo T, Shi J, Gao YT, Long J, Delahanty R, Xiang YB, Cai Q, Shu XO. Genetic variants in vitamin D metabolism-related genes and body mass index: analysis of genome-wide scan data of approximately 7000 Chinese women. Int J Obes (Lond). 2012 Sep;36(9):1252-5. doi: 10.1038/ijo.2011.246. Epub 2011 Dec 13.
• Zemel MB. Role of dietary calcium and dairy products in modulating adiposity. Lipids. 2003 Feb;38(2):139-46. Review.
• Kato S. The function of vitamin D receptor in vitamin D action. J Biochem. 2000 May;127(5):717-22. Review.
• Wood RJ. Vitamin D and adipogenesis: new molecular insights. Nutr Rev. 2008 Jan;66(1):40-6. doi: 10.1111/j.1753-4887.2007.00004.x. Review.
• Grundberg E, Brändström H, Ribom EL, Ljunggren O, Mallmin H, Kindmark A. Genetic variation in the human vitamin D receptor is associated with muscle strength, fat mass and body weight in Swedish women. Eur J Endocrinol. 2004 Mar;150(3):323-8.
• Filus A, Trzmiel A, Kuliczkowska-Płaksej J, Tworowska U, Jedrzejuk D, Milewicz A, Medraś M. Relationship between vitamin D receptor BsmI and FokI polymorphisms and anthropometric and biochemical parameters describing metabolic syndrome. Aging Male. 2008 Sep;11(3):134-9. doi: 10.1080/13685530802273426.
• Oh JY, Barrett-Connor E. Association between vitamin D receptor polymorphism and type 2 diabetes or metabolic syndrome in community-dwelling older adults: the Rancho Bernardo Study. Metabolism. 2002 Mar;51(3):356-9.
• Ortlepp JR, Lauscher J, Hoffmann R, Hanrath P, Joost HG. The vitamin D receptor gene variant is associated with the prevalence of type 2 diabetes mellitus and coronary artery disease. Diabet Med. 2001 Oct;18(10):842-5.
• Ortlepp JR, Metrikat J, Albrecht M, von Korff A, Hanrath P, Hoffmann R. The vitamin D receptor gene variant and physical activity predicts fasting glucose levels in healthy young men. Diabet Med. 2003 Jun;20(6):451-4.
• Speer G, Cseh K, Winkler G, Vargha P, Braun E, Takács I, Lakatos P. Vitamin D and estrogen receptor gene polymorphisms in type 2 diabetes mellitus and in android type obesity. Eur J Endocrinol. 2001 Apr;144(4):385-9.
• Ye WZ, Reis AF, Dubois-Laforgue D, Bellanné-Chantelot C, Timsit J, Velho G. Vitamin D receptor gene polymorphisms are associated with obesity in type 2 diabetic subjects with early age of onset. Eur J Endocrinol. 2001 Aug;145(2):181-6.
• Gu JM, Xiao WJ, He JW, Zhang H, Hu WW, Hu YQ, Li M, Liu YJ, Fu WZ, Yu JB, Gao G, Yue H, Ke YH, Zhang ZL. Association between VDR and ESR1 gene polymorphisms with bone and obesity phenotypes in Chinese male nuclear families. Acta Pharmacol Sin. 2009 Dec;30(12):1634-42. doi: 10.1038/aps.2009.169.
• Gressner OA, Lahme B, Gressner AM. Gc-globulin (vitamin D binding protein) is synthesized and secreted by hepatocytes and internalized by hepatic stellate cells through Ca(2+)-dependent interaction with the megalin/gp330 receptor. Clin Chim Acta. 2008 Apr;390(1-2):28-37. doi: 10.1016/j.cca.2007.12.011. Epub 2007 Dec 23.
• Liu W, Yu WR, Carling T, Juhlin C, Rastad J, Ridefelt P, Akerström G, Hellman P. Regulation of gp330/megalin expression by vitamins A and D. Eur J Clin Invest. 1998 Feb;28(2):100-7.
• Dietrich MO, Spuch C, Antequera D, Rodal I, de Yébenes JG, Molina JA, Bermejo F, Carro E. Megalin mediates the transport of leptin across the blood-CSF barrier. Neurobiol Aging. 2008 Jun;29(6):902-12. Epub 2007 Feb 26.
• Lisi S, Segnani C, Mattii L, Botta R, Marcocci C, Dolfi A, McCluskey RT, Pinchera A, Bernardini N, Marinò M. Thyroid dysfunction in megalin deficient mice. Mol Cell Endocrinol. 2005 May 31;236(1-2):43-7.
• Beydoun MA, Beydoun HA, Shroff MR, Kitner-Triolo MH, Zonderman AB. Serum leptin, thyroxine and thyroid-stimulating hormone levels interact to affect cognitive function among US adults: evidence from a large representative survey. Neurobiol Aging. 2012 Aug;33(8):1730-43. doi: 10.1016/j.neurobiolaging.2011.05.008. Epub 2011 Jul 16.
• Ding EL, Mehta S, Fawzi WW, Giovannucci EL. Interaction of estrogen therapy with calcium and vitamin D supplementation on colorectal cancer risk: reanalysis of Women's Health Initiative randomized trial. Int J Cancer. 2008 Apr 15;122(8):1690-4.

Recruitment Information

• Recruitment Status: Completed
• Actual Enrollment (submitted: September 11, 2017): 1021
• Original Actual Enrollment: Same as current
• Actual Study Completion Date: July 7, 2013
• Actual Primary Completion Date: July 7, 2013 (Final data collection date for primary outcome measure)

Eligibility Criteria

Inclusion Criteria:

1. 3,720 baseline participants (mean±SD age(y) of 48.3±9.4, 45.3% men, and 59.1% African-American),
2. Genetic data were available on 1,024 African-American participants.
3. Incomplete covariate data reduced the sample to n=769, while additional exclusions lead to a sample size ranging between 574 and 598 participants, with 539 having complete data on all baseline and follow-up outcome measures (cross-sectional part of the analysis).
4. In the longitudinal analysis, metabolic disturbance-free at baseline participants were selected for each outcome. Sample sizes ranged from n=246 (central obesity-free) to n=466 (hyperglycemia-free).
5. There were n=294 MetS-free individuals at baseline.

Exclusion Criteria:

1. Whites in HANDLS, since they did not have any genetic data collected.
2. All African-Americans in HANDLS without genetic data collected.
3. All African-Americans in HANDLS with genetic data collected, who had incomplete data on key outcome variables and/or basic covariates of interest.

Sex/Gender

• Sexes Eligible for Study: All

• Ages: 30 Years to 64 Years (Adult)
• Accepts Healthy Volunteers: Yes
• Contacts: Contact information is only displayed when the study is recruiting subjects
• Listed Location Countries: Not Provided

Administrative Information

• NCT Number: NCT03279432
• Other Study ID Numbers: NIA
• Has Data Monitoring Committee: No

U.S. FDA-regulated Product

• Studies a U.S. FDA-regulated Drug Product: No
• Studies a U.S. FDA-regulated Device Product: No

IPD Sharing Statement

• Plan to Share IPD: No

• Responsible Party: May Ahmad Baydoun, National Institute on Aging (NIA)
• Study Sponsor: National Institute on Aging (NIA)
• Collaborators: Not Provided

Investigators

• Principal Investigator: Alan B Zonderman, PhD; National Institute on Aging (NIA)
• Principal Investigator: Michele K Evans, MD; National Institute on Aging (NIA)

• PRS Account: National Institute on Aging (NIA)
• Verification Date: September 2017