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Trial record 66 of 123 for:    hypertension "vitamin d"

Vitamin D-related Genes and Metabolic Disorders

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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)

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.


Condition or disease
Metabolic Syndrome Obesity Central Obesity

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.

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Study Type : Observational
Actual Enrollment : 1021 participants
Observational Model: Cohort
Time Perspective: Prospective
Official Title: Vitamin D Receptor and Megalin Gene Polymorphisms and Their Association With Obesity, Central Obesity and the Metabolic Syndrome
Actual Study Start Date : August 18, 2004
Actual Primary Completion Date : July 7, 2013
Actual Study Completion Date : July 7, 2013

Resource links provided by the National Library of Medicine

Drug Information available for: Vitamin D




Primary Outcome Measures :
  1. Obesity [ Time Frame: 2004-2013 ]
    Obesity was defined as BMI≥30 kg/m2.

  2. 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)

  3. 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).


Biospecimen Retention:   Samples With DNA
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.


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Ages Eligible for Study:   30 Years to 64 Years   (Adult)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   Yes
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).
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.

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT03279432


Sponsors and Collaborators
National Institute on Aging (NIA)
Investigators
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Principal Investigator: Alan B Zonderman, PhD National Institute on Aging (NIA)
Principal Investigator: Michele K Evans, MD National Institute on Aging (NIA)

Additional Information:
Publications:
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.

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Responsible Party: May Ahmad Baydoun, Staff Scientist, National Institute on Aging (NIA)
ClinicalTrials.gov Identifier: NCT03279432     History of Changes
Other Study ID Numbers: NIA
First Posted: September 12, 2017    Key Record Dates
Last Update Posted: September 12, 2017
Last Verified: September 2017
Individual Participant Data (IPD) Sharing Statement:
Plan to Share IPD: No

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

Keywords provided by May Ahmad Baydoun, National Institute on Aging (NIA):
VDR, MEGALIN, haplotypes, obesity, metabolic syndrome

Additional relevant MeSH terms:
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Vitamin D
Syndrome
Obesity
Metabolic Syndrome
Obesity, Abdominal
Disease
Pathologic Processes
Overnutrition
Nutrition Disorders
Overweight
Body Weight
Signs and Symptoms
Insulin Resistance
Hyperinsulinism
Glucose Metabolism Disorders
Metabolic Diseases
Vitamins
Micronutrients
Nutrients
Growth Substances
Physiological Effects of Drugs
Bone Density Conservation Agents