<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT03279432</url>
  </required_header>
  <id_info>
    <org_study_id>NIA</org_study_id>
    <nct_id>NCT03279432</nct_id>
  </id_info>
  <brief_title>Vitamin D-related Genes and Metabolic Disorders</brief_title>
  <official_title>Vitamin D Receptor and Megalin Gene Polymorphisms and Their Association With Obesity, Central Obesity and the Metabolic Syndrome</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>National Institute on Aging (NIA)</agency>
      <agency_class>NIH</agency_class>
    </lead_sponsor>
  </sponsors>
  <source>National Institute on Aging (NIA)</source>
  <oversight_info>
    <has_dmc>No</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      The link between metabolic disturbances and vitamin D receptor (VDR) and MEGALIN (or LRP2)&#xD;
      gene polymorphisms remains unclear, particularly among African-American adults. The&#xD;
      associations of single nucleotide polymorphisms (SNPs) for VDR [rs1544410(BsmI:G/A),&#xD;
      rs7975232(ApaI:A/C), rs731236(TaqI:G/A)] and MEGALIN [rs3755166:G/A,rs2075252:C/T,&#xD;
      rs2228171:C/T] genes with incident and prevalent metabolic disturbances, including obesity,&#xD;
      central obesity and metabolic syndrome (MetS) were evaluated.&#xD;
&#xD;
      From 1,024 African-Americans participating in the Healthy Aging in Neighborhoods of Diversity&#xD;
      across the Life Span (HANDLS, Baltimore, MD, 2004-2013) study, 539 subjects were selected who&#xD;
      had complete genetic data as well as covariates selected for metabolic outcomes at two&#xD;
      consecutive examinations (visits 1 and 2) with a mean follow-up time of 4.64±0.93y. Haplotype&#xD;
      (HAP) analyses generated polymorphism groups that were linked to incident and prevalent&#xD;
      metabolic disturbances.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      Adiposity, especially central adiposity, is a key component of the metabolic syndrome (MetS),&#xD;
      which is accompanied by hyperglycemia, elevated blood pressure, lower HDL cholesterol and&#xD;
      hypertriglyceridemia.(Ford, et al., 2003,Grundy, 1999)_ENREF_4 MetS increases the risk of&#xD;
      type 2 diabetes (T2D) and cardiovascular disease by 1.7- and 5-folds, respectively.(Alberti,&#xD;
      et al., 2009,Ford, et al., 2003,Galassi, et al., 2006) MetS is heritable and polygenic.(Maes,&#xD;
      et al., 1997) Genetic variability contributes to 16%-85% of changes in Body Mass Index&#xD;
      (BMI)(Yang, et al., 2007) and 37%-81% in waist circumference (WC) (e.g.(Ochs-Balcom, et al.,&#xD;
      2011)). MetS is a major public health concern, increasing all-cause mortality rates,&#xD;
      disability and health care costs.(Appels and Vandenbroucke, 2006,Bender, et al.,&#xD;
      2006,Colditz, 1999,Doig, 2004,Ferrucci and Alley, 2007,Hill, et al., 2004,Solomon and Manson,&#xD;
      1997,Stevens, 2000,Wolf and Colditz, 1998) Obesity is implicated in the etiology of vitamin D&#xD;
      deficiency. Serum 25-hydroxyvitamin D [25(OH)D] concentration correlates inversely with&#xD;
      adiposity.(Beydoun, et al., 2010,Dorjgochoo, et al., 2012) Conversely, vitamin D3 may play a&#xD;
      role in obesity by modulating intracellular calcium homeostasis, because higher intracellular&#xD;
      calcium triggers lipogenesis and suppresses lipolysis.(Zemel, 2003) Many organs express&#xD;
      vitamin D receptor (VDR), a part of the nuclear hormone receptor super-family. The&#xD;
      VDR-1,25(OH)2D3 complex modulates transcription of vitamin D responsive genes(Kato, 2000) and&#xD;
      influences adipocyte differentiation both in vitro and in vivo.(Wood, 2008) Epidemiological&#xD;
      studies have shown associations of VDR gene polymorphisms with adiposity and related&#xD;
      metabolic disorders.(Filus, et al., 2008,Grundberg, et al., 2004,Gu, et al.,&#xD;
      2009,Ochs-Balcom, et al., 2011,Oh and Barrett-Connor, 2002,Ortlepp, et al., 2001,Ortlepp, et&#xD;
      al., 2003,Speer, et al., 2001,Ye, et al., 2001) However, studies specifically examining&#xD;
      adiposity outcomes either had small sample sizes (&lt;400), (e.g.(Filus, et al., 2008,Grundberg,&#xD;
      et al., 2004,Speer, et al., 2001)) or were restricted to one sex, (e.g. (Grundberg, et al.,&#xD;
      2004,Ochs-Balcom, et al., 2011)) but more importantly were all cross-sectional or&#xD;
      case-control by design.(Filus, et al., 2008,Grundberg, et al., 2004,Gu, et al.,&#xD;
      2009,Ochs-Balcom, et al., 2011,Oh and Barrett-Connor, 2002,Ortlepp, et al., 2001,Ortlepp, et&#xD;
      al., 2003,Speer, et al., 2001,Ye, et al., 2001) MEGALIN (aka low-density lipoprotein&#xD;
      receptor-related protein-2 [LRP-2]), is the endocytic vitamin D-binding protein receptor&#xD;
      which allows vitamin D entry into cells and whose expression is directly regulated by both&#xD;
      vitamin D (Gressner, et al., 2008)) and vitamin A.(Liu, et al., 1998) MEGALIN may influences&#xD;
      obesity by mediating leptin transport through the blood-brain barrier and modulating leptin&#xD;
      signaling,(Dietrich, et al., 2008) or by facilitating transcytosis of its precursor hormone&#xD;
      thyroglobulin.(Lisi, et al., 2005) Collectively, leptin and thyroid hormones affect adiposity&#xD;
      through energy metabolism regulation.(Beydoun, et al., 2011) MEGALIN acting also as the&#xD;
      receptor for sex-hormone binding globulin (SHBG) may play a role in the interaction between&#xD;
      estrogen, vitamin D and intracellular calcium in adipocytes, resulting in sex-specific&#xD;
      effects of MEGALIN polymorphisms on obesity phenotypes.(Ding, et al., 2008) In this study, it&#xD;
      is hypothesized that selected polymorphisms in VDR and MEGALIN genes have sex-specific&#xD;
      associations with several key metabolic disturbances in a longitudinal study of&#xD;
      African-American urban adults.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">August 18, 2004</start_date>
  <completion_date type="Actual">July 7, 2013</completion_date>
  <primary_completion_date type="Actual">July 7, 2013</primary_completion_date>
  <study_type>Observational</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <observational_model>Cohort</observational_model>
    <time_perspective>Prospective</time_perspective>
  </study_design_info>
  <primary_outcome>
    <measure>Obesity</measure>
    <time_frame>2004-2013</time_frame>
    <description>Obesity was defined as BMI≥30 kg/m2.</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Central Obesity</measure>
    <time_frame>2004-2013</time_frame>
    <description>Central obesity was defined based on waist circumference (WC) ≥ 102 cm or 40 inches (men), ≥ 88 cm or 35 inches (women)</description>
  </primary_outcome>
  <primary_outcome>
    <measure>Metabolic Syndrome</measure>
    <time_frame>2004-2013</time_frame>
    <description>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&lt;40 mg/dL (male), &lt;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).</description>
  </primary_outcome>
  <enrollment type="Actual">1021</enrollment>
  <condition>Metabolic Syndrome</condition>
  <condition>Obesity</condition>
  <condition>Central Obesity</condition>
  <biospec_retention>Samples With DNA</biospec_retention>
  <biospec_descr>
    <textblock>
      Study participants were genotyped to 907,763 single nucleotide polymorphisms (SNPs) using the&#xD;
      Illumina 1M and 1M-Duo genotyping arrays. Sample quality control inclusion criteria were: (1)&#xD;
      concordance between self-reported sex and X-chromosome estimated sex; (2) sample call rate&#xD;
      &gt;95%, (3) concordance between self-reported African ancestry and ancestry estimated using&#xD;
      genotyped SNPs, and (4) proportional sharing of genotypes &lt; 15% between samples, excluding&#xD;
      close relatives from the final sample. SNPs in HANDLS were selected when the following&#xD;
      criteria were met: (1) Hardy-Weinberg equilibrium p-value (HWE P &gt;10-7); (2) Missing by&#xD;
      haplotype P &gt; 10-7; (3) Minor allele frequency&gt;0.01, and (4) SNP call rate &gt;95%. Quality&#xD;
      control and data management for each genotype was conducted using PLINKv1.06.&#xD;
    </textblock>
  </biospec_descr>
  <eligibility>
    <study_pop>
      <textblock>
        Of the 3,720 baseline participants (mean±SD age(y) of 48.3±9.4, 45.3% men, and 59.1%&#xD;
        African-American), genetic data were available on 1,024 African-American participants.&#xD;
        Incomplete covariate data reduced the sample to n=769, while additional exclusions lead to&#xD;
        a sample size ranging between 574 and 598 participants, with 539 having complete data on&#xD;
        all baseline and follow-up outcome measures (cross-sectional part of the analysis). In the&#xD;
        longitudinal analysis, metabolic disturbance-free at baseline participants were selected&#xD;
        for each outcome. Sample sizes ranged from n=246 (central obesity-free) to n=466&#xD;
        (hyperglycemia-free). There were n=294 MetS-free individuals at baseline (Figure 1).&#xD;
      </textblock>
    </study_pop>
    <sampling_method>Probability Sample</sampling_method>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          1. 3,720 baseline participants (mean±SD age(y) of 48.3±9.4, 45.3% men, and 59.1%&#xD;
             African-American),&#xD;
&#xD;
          2. Genetic data were available on 1,024 African-American participants.&#xD;
&#xD;
          3. Incomplete covariate data reduced the sample to n=769, while additional exclusions&#xD;
             lead to a sample size ranging between 574 and 598 participants, with 539 having&#xD;
             complete data on all baseline and follow-up outcome measures (cross-sectional part of&#xD;
             the analysis).&#xD;
&#xD;
          4. In the longitudinal analysis, metabolic disturbance-free at baseline participants were&#xD;
             selected for each outcome. Sample sizes ranged from n=246 (central obesity-free) to&#xD;
             n=466 (hyperglycemia-free).&#xD;
&#xD;
          5. There were n=294 MetS-free individuals at baseline.&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          1. Whites in HANDLS, since they did not have any genetic data collected.&#xD;
&#xD;
          2. All African-Americans in HANDLS without genetic data collected.&#xD;
&#xD;
          3. All African-Americans in HANDLS with genetic data collected, who had incomplete data&#xD;
             on key outcome variables and/or basic covariates of interest.&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>30 Years</minimum_age>
    <maximum_age>64 Years</maximum_age>
    <healthy_volunteers>Accepts Healthy Volunteers</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Alan B Zonderman, PhD</last_name>
    <role>Principal Investigator</role>
    <affiliation>National Institute on Aging (NIA)</affiliation>
  </overall_official>
  <overall_official>
    <last_name>Michele K Evans, MD</last_name>
    <role>Principal Investigator</role>
    <affiliation>National Institute on Aging (NIA)</affiliation>
  </overall_official>
  <link>
    <url>http://handls.nih.gov</url>
    <description>Related Info</description>
  </link>
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  <verification_date>September 2017</verification_date>
  <study_first_submitted>September 8, 2017</study_first_submitted>
  <study_first_submitted_qc>September 11, 2017</study_first_submitted_qc>
  <study_first_posted type="Actual">September 12, 2017</study_first_posted>
  <last_update_submitted>September 11, 2017</last_update_submitted>
  <last_update_submitted_qc>September 11, 2017</last_update_submitted_qc>
  <last_update_posted type="Actual">September 12, 2017</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>National Institute on Aging (NIA)</investigator_affiliation>
    <investigator_full_name>May Ahmad Baydoun</investigator_full_name>
    <investigator_title>Staff Scientist</investigator_title>
  </responsible_party>
  <keyword>VDR, MEGALIN, haplotypes, obesity, metabolic syndrome</keyword>
  <condition_browse>
    <!-- CAUTION:  The following MeSH terms are assigned with an imperfect algorithm            -->
    <mesh_term>Obesity</mesh_term>
    <mesh_term>Metabolic Syndrome</mesh_term>
    <mesh_term>Obesity, Abdominal</mesh_term>
    <mesh_term>Syndrome</mesh_term>
  </condition_browse>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT03279432
org study id: NIA
nct id: NCT03279432
lead sponsor: 
has dmc: No
is fda regulated drug: No
is fda regulated device: No
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.
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.
observational model: Cohort
time perspective: Prospective
measure: Obesity
time frame: 2004-2013
description: Obesity was defined as BMI≥30 kg/m2.
measure: Central Obesity
time frame: 2004-2013
description: Central obesity was defined based on waist circumference (WC) ≥ 102 cm or 40 inches (men), ≥ 88 cm or 35 inches (women)
measure: Metabolic Syndrome
time frame: 2004-2013
description: 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).
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.
study pop: 
sampling method: Probability Sample
criteria: 
gender: All
minimum age: 30 Years
maximum age: 64 Years
healthy volunteers: Accepts Healthy Volunteers
last name: Alan B Zonderman, PhD
role: Principal Investigator
affiliation: National Institute on Aging (NIA)
last name: Michele K Evans, MD
role: Principal Investigator
affiliation: National Institute on Aging (NIA)
url: http://handls.nih.gov
description: Related Info
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responsible party type: Principal Investigator
investigator affiliation: National Institute on Aging (NIA)
investigator full name: May Ahmad Baydoun
investigator title: Staff Scientist
mesh term: Obesity
mesh term: Metabolic Syndrome
mesh term: Obesity, Abdominal
mesh term: Syndrome
sharing ipd: No