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


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/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) 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≤8.07×10−57 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


Vyšlo v časopise: Causal Relationship between Obesity and Vitamin D Status: Bi-Directional Mendelian Randomization Analysis of Multiple Cohorts. PLoS Med 10(2): e32767. doi:10.1371/journal.pmed.1001383
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pmed.1001383

Souhrn

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/m2 higher BMI was associated with 1.15% lower 25(OH)D (p = 6.52×10−27). The BMI allele score was associated both with BMI (p = 6.30×10−62) 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≤8.07×10−57 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


Zdroje

1. BaskinML, ArdJ, FranklinF, AllisonDB (2005) Prevalence of obesity in the United States. Obes Rev 6: 5–7.

2. OgdenCL, CarrollMD, CurtinLR, LambMM, FlegalKM (2010) Prevalence of high body mass index in US children and adolescents, 2007–2008. JAMA 303: 242–249.

3. BerghoferA, PischonT, ReinholdT, ApovianCM, SharmaAM, et al. (2008) Obesity prevalence from a European perspective: a systematic review. BMC Public Health 8: 200.

4. ZhengW, McLerranDF, RollandB, ZhangX, InoueM, et al. (2011) Association between body-mass index and risk of death in more than 1 million Asians. N Engl J Med 364: 719–729.

5. FlegalKM, CarrollMD, KitBK, OgdenCL (2012) Prevalence of obesity and trends in the distribution of body mass index among US adults, 1999–2010. JAMA 307: 491–497.

6. VimaleswaranKS, LoosRJ (2010) Progress in the genetics of common obesity and type 2 diabetes. Expert Rev Mol Med 12: e7.

7. GindeAA, LiuMC, CamargoCAJr (2009) Demographic differences and trends of vitamin D insufficiency in the US population, 1988–2004. Arch Intern Med 169: 626–632.

8. Lanham-NewSA, ButtrissJL, MilesLM, AshwellM, BerryJL, et al. (2011) Proceedings of the Rank Forum on vitamin D. Br J Nutr 105: 144–156.

9. HyppönenE, PowerC (2007) Hypovitaminosis D in British adults at age 45 y: nationwide cohort study of dietary and lifestyle predictors. Am J Clin Nutr 85: 860–868.

10. EarthmanCP, BeckmanLM, MasodkarK, SibleySD (2012) The link between obesity and low circulating 25-hydroxyvitamin D concentrations: considerations and implications. Int J Obes (Lond) 36: 387–396.

11. ShiH, NormanAW, OkamuraWH, SenA, ZemelMB (2001) 1alpha,25-Dihydroxyvitamin D3 modulates human adipocyte metabolism via nongenomic action. Faseb J 15: 2751–2753.

12. FassinaG, MaragnoI, DorigoP, ContessaAR (1969) Effect of vitamin D2 on hormone-stimulated lipolysis in vitro. Eur J Pharmacol 5: 286–290.

13. SneveM, FigenschauY, JordeR (2008) Supplementation with cholecalciferol does not result in weight reduction in overweight and obese subjects. Eur J Endocrinol 159: 675–684.

14. ZittermannA, FrischS, BertholdHK, GottingC, KuhnJ, et al. (2009) Vitamin D supplementation enhances the beneficial effects of weight loss on cardiovascular disease risk markers. Am J Clin Nutr 89: 1321–1327.

15. SalehpourA, ShidfarF, HosseinpanahF, VafaM, RazaghiM, et al. (2012) Vitamin D3 and the risk of CVD in overweight and obese women: a randomised controlled trial. Br J Nutr 1–8.

16. SoaresMJ, MurhadiLL, KurpadAV, Chan She Ping-DelfosWL, PiersLS (2012) Mechanistic roles for calcium and vitamin D in the regulation of body weight. Obes Rev 13: 592–605.

17. FossYJ (2009) Vitamin D deficiency is the cause of common obesity. Med Hypotheses 72: 314–321.

18. WortsmanJ, MatsuokaLY, ChenTC, LuZ, HolickMF (2000) Decreased bioavailability of vitamin D in obesity. Am J Clin Nutr 72: 690–693.

19. Davey SmithG, EbrahimS (2003) ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol 32: 1–22.

20. LawlorDA, HarbordRM, SterneJA, TimpsonN, Davey SmithG (2008) Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med 27: 1133–1163.

21. Davey SmithG (2011) Random allocation in observational data: how small but robust effects could facilitate hypothesis-free causal inference. Epidemiology 22: 460–463; discussion 467–468.

22. PalmerTM, LawlorDA, HarbordRM, SheehanNA, TobiasJH, et al. (2012) Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res 21: 223–242.

23. SpeliotesEK, WillerCJ, BerndtSI, MondaKL, ThorleifssonG, et al. (2010) Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index. Nat Genet 42: 937–948.

24. LiS, ZhaoJH, LuanJ, LubenRN, RodwellSA, et al. (2010) Cumulative effects and predictive value of common obesity-susceptibility variants identified by genome-wide association studies. Am J Clin Nutr 91: 184–190.

25. LoosRJ, LindgrenCM, LiS, WheelerE, ZhaoJH, et al. (2008) Common variants near MC4R are associated with fat mass, weight and risk of obesity. Nat Genet 40: 768–775.

26. ThorleifssonG, WaltersGB, GudbjartssonDF, SteinthorsdottirV, SulemP, et al. (2009) Genome-wide association yields new sequence variants at seven loci that associate with measures of obesity. Nat Genet 41: 18–24.

27. WangTJ, ZhangF, RichardsJB, KestenbaumB, van MeursJB, et al. (2010) Common genetic determinants of vitamin D insufficiency: a genome-wide association study. Lancet 376: 180–188.

28. ZhengJ, LiY, AbecasisGR, ScheetP (2011) A comparison of approaches to account for uncertainty in analysis of imputed genotypes. Genet Epidemiol 35: 102–110.

29. ColeTJ (2000) Sympercents: symmetric percentage differences on the 100 log(e) scale simplify the presentation of log transformed data. Stat Med 19: 3109–3125.

30. LinX, SongK, LimN, YuanX, JohnsonT, et al. (2009) Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score–the CoLaus Study. Diabetologia 52: 600–608.

31. PierceBL, AhsanH, VanderweeleTJ (2011) Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J Epidemiol 40: 740–752.

32. BerryDJ, VimaleswaranKS, WhittakerJC, HingoraniAD, HypponenE (2012) Evaluation of genetic markers as instruments for mendelian randomization studies on vitamin D. PLoS One 7: e37465 doi:10.1371/journal.pone.0037465.

33. ChunRF, LauridsenAL, SuonL, ZellaLA, PikeJW, et al. (2010) Vitamin D-binding protein directs monocyte responses to 25-hydroxy- and 1,25-dihydroxyvitamin D. J Clin Endocrinol Metab 95: 3368–3376.

34. Rice JA (1995) Expected values. Mathematical statistics and data analysis. 2nd edition. Pacific Grove (California): Duxbury Press.

35. EhretGB, MunroePB, RiceKM, BochudM, JohnsonAD, et al. (2011) Genetic variants in novel pathways influence blood pressure and cardiovascular disease risk. Nature 478: 103–109.

36. ThomasDC, LawlorDA, ThompsonJR (2007) Re: Estimation of bias in nongenetic observational studies using “Mendelian triangulation” by Bautista et al. Ann Epidemiol 17: 511–513.

37. WhiteIR (2009) Multivariate random-effects meta-analysis. The Stata Journal 9: 40–56.

38. Borenstein M (2009) Introduction to meta-analysis. Chichester: John Wiley & Sons. xxviii.

39. StataCorp (2011). Stata Statistical Software: Release 12: College Station (Texas): StataCorp LP.

40. JordeR, SneveM, EmausN, FigenschauY, GrimnesG (2010) Cross-sectional and longitudinal relation between serum 25-hydroxyvitamin D and body mass index: the Tromso study. Eur J Nutr 49: 401–407.

41. LeeP, GreenfieldJR, SeibelMJ, EismanJA (2009) Center JR (2009) Adequacy of vitamin D replacement in severe deficiency is dependent on body mass index. Am J Med 122: 1056–1060.

42. BassettDRJr, PucherJ, BuehlerR, ThompsonDL, CrouterSE (2008) Walking, cycling, and obesity rates in Europe, North America, and Australia. J Phys Act Health 5: 795–814.

43. DorjgochooT, ShiJ, GaoYT, LongJ, DelahantyR, et al. (2012) Genetic variants in vitamin D metabolism-related genes and body mass index: analysis of genome-wide scan data of approximately 7000 Chinese women. Int J Obes (Lond) 36: 1252–1255.

44. DrincicAT, ArmasLA, Van DiestEE, HeaneyRP (2012) Volumetric dilution, rather than sequestration best explains the low vitamin D status of obesity. Obesity (Silver Spring) 20: 1444–1448.

45. BellNH, EpsteinS, GreeneA, SharyJ, OexmannMJ, et al. (1985) Evidence for alteration of the vitamin D-endocrine system in obese subjects. J Clin Invest 76: 370–373.

46. HolickMF (2007) Vitamin D deficiency. N Engl J Med 357: 266–281.

47. HyppönenE, BerryD, Cortina-BorjaM, PowerC (2010) 25-Hydroxyvitamin D and pre-clinical alterations in inflammatory and hemostatic markers: a cross sectional analysis in the 1958 British Birth Cohort. PLoS One 5: e10801 doi:10.1371/journal.pone.0010801.

48. BurgessS, ThompsonSG, AndrewsG, SamaniNJ, HallA, et al. (2010) Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables. Stat Med 29: 1298–1311.

49. StaigerD, StockJH (1997) Instrumental variables regression with weak instruments. Econometrica 65: 557–586.

50. HuhSY, GordonCM (2008) Vitamin D deficiency in children and adolescents: epidemiology, impact and treatment. Rev Endocr Metab Disord 9: 161–170.

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PLOS Medicine


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