Clinical trial NCT03279432: 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
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Metabolic Syndrome
Obesity
Central Obesity
Keywords: VDR, MEGALIN, haplotypes, obesity, metabolic syndrome
Lead sponsor: National Institute on Aging (NIA)
Sponsor class: NIH
First posted: 2017-09-12
Enrollment: 1021
Sex: ALL
Minimum age (years): 30
Maximum age (years): 64
Standard ages: ADULT
Accepts healthy volunteers: yes
Observational model: COHORT
Time perspective: PROSPECTIVE
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).

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.

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.

Primary outcomes:
measure: Obesity
timeFrame: 2004-2013
measure: Central Obesity
timeFrame: 2004-2013
measure: Metabolic Syndrome
timeFrame: 2004-2013
Secondary outcomes:
Other outcomes:
Locations:
Study officials:
affiliation: National Institute on Aging (NIA)
name: Alan B Zonderman, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: National Institute on Aging (NIA)
name: Michele K Evans, MD
role: PRINCIPAL_INVESTIGATOR
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