Causal Relationship between Obesity and Vitamin D Status: Bi-Directional Mendelian Randomization Analysis of Multiple Cohorts

Genetic Investigation of Anthropometric Traits-GIANT Consortium, Karani S Vimaleswaran, Diane J Berry, Chen Lu, Emmi Tikkanen, Stefan Pilz, Linda T Hiraki, Jason D Cooper, Zari Dastani, Rui Li, Denise K Houston, Andrew R Wood, Karl Michaëlsson, Liesbeth Vandenput, Lina Zgaga, Laura M Yerges-Armstrong, Mark I McCarthy, Josée Dupuis, Marika Kaakinen, Marcus E KleberKaren Jameson, Nigel Arden, Olli Raitakari, Jorma Viikari, Kurt K Lohman, Luigi Ferrucci, Håkan Melhus, Erik Ingelsson, Liisa Byberg, Lars Lind, Mattias Lorentzon, Veikko Salomaa, Harry Campbell, Malcolm Dunlop, Braxton D Mitchell, Karl-Heinz Herzig, Anneli Pouta, Anna-Liisa Hartikainen, Elizabeth A Streeten, Evropi Theodoratou, Antti Jula, Nicholas J Wareham, Claes Ohlsson, Timothy M Frayling, Stephen B Kritchevsky, Timothy D Spector, J Brent Richards, Terho Lehtimäki, Willem H Ouwehand, Peter Kraft, Cyrus Cooper

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

Background: Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional Mendelian randomization (MR) analysis. Methods and Findings: We used information from 21 adult cohorts (up to 42,024 participants) with 12 BMI-related SNPs (combined in an allelic score) to produce an instrument for BMI and four SNPs associated with 25(OH)D (combined in two allelic scores, separately for genes encoding its synthesis or metabolism) as an instrument for vitamin D. Regression estimates for the IVs (allele scores) were generated within-study and pooled by meta-analysis to generate summary effects. Associations between vitamin D scores and BMI were confirmed in the Genetic Investigation of Anthropometric Traits (GIANT) consortium (n = 123,864). Each 1 kg/m higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10). The BMI allele score was associated both with BMI (p = 6.30×10) and 25(OH)D (-0.06% [95% CI -0.10 to -0.02], p = 0.004) in the cohorts that underwent meta-analysis. The two vitamin D allele scores were strongly associated with 25(OH)D (p≤8.07×10 for both scores) but not with BMI (synthesis score, p = 0.88; metabolism score, p = 0.08) in the meta-analysis. A 10% higher genetically instrumented BMI was associated with 4.2% lower 25(OH)D concentrations (IV ratio: -4.2 [95% CI -7.1 to -1.3], p = 0.005). No association was seen for genetically instrumented 25(OH)D with BMI, a finding that was confirmed using data from the GIANT consortium (p≥0.57 for both vitamin D scores). Conclusions: On the basis of a bi-directional genetic approach that limits confounding, our study suggests that a higher BMI leads to lower 25(OH)D, while any effects of lower 25(OH)D increasing BMI are likely to be small. Population level interventions to reduce BMI are expected to decrease the prevalence of vitamin D deficiency. Please see later in the article for the Editors' Summary.
Original languageEnglish
Article numbere1001383
Pages (from-to)e1001383
Number of pages13
JournalPLoS Medicine
Volume10
Issue number2
DOIs
Publication statusPublished - 2013

Keywords / Materials (for Non-textual outputs)

  • Adult
  • Aged
  • Aged, 80 and over
  • Biological Markers
  • Body Mass Index
  • Europe
  • European Continental Ancestry Group
  • Evidence-Based Medicine
  • Female
  • Genetic Predisposition to Disease
  • Humans
  • Linear Models
  • Male
  • Mendelian Randomization Analysis
  • Middle Aged
  • Multivariate Analysis
  • North America
  • Obesity
  • Phenotype
  • Polymorphism, Single Nucleotide
  • Risk Assessment
  • Risk Factors
  • Vitamin D
  • Vitamin D Deficiency

Fingerprint

Dive into the research topics of 'Causal Relationship between Obesity and Vitamin D Status: Bi-Directional Mendelian Randomization Analysis of Multiple Cohorts'. Together they form a unique fingerprint.

Cite this