Working…
ClinicalTrials.gov
ClinicalTrials.gov Menu

Vitamin D-related Genes and Metabolic Disorders

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details.
 
ClinicalTrials.gov Identifier: NCT03279432
Recruitment Status : Completed
First Posted : September 12, 2017
Last Update Posted : September 12, 2017
Sponsor:
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 *

*   Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
 
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
Removed Location Countries  
 
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