Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Original Article
  • Published:

Nutrigenomics

Genetically predicted milk consumption and bone health, ischemic heart disease and type 2 diabetes: a Mendelian randomization study

European Journal of Clinical Nutrition volume 71, pages 1008–1012 (2017)Cite this article

Subjects

Abstract

Background/objectives:

Milk provides protein and micronutrients, and is recommended by some dietary guidelines, particularly for bone health. Meta-analysis of small randomized controlled trials suggests that milk may increase bone mineral density, but they are very heterogeneous. No randomized controlled trial has assessed the effects of milk on major chronic diseases. Previous Mendelian randomization studies of milk did not consider bone health, found no effects on ischemic heart disease (IHD) or type 2 diabetes (T2D) but higher body mass index. Using larger genetic studies, we estimated the effects of milk on osteoporosis, IHD, T2D, adiposity, lipids and glycemic traits.

Subjects/methods:

Instrumental variable analysis based on a genetic variant endowing lactase persistence (rs4988235 (MCM6)) was used to obtain estimates for osteoporosis (GEFOS), IHD (CARDIoGRAMplusC4D), T2D (DIAGRAM), adiposity (GIANT), lipids (GLGC) and glycaemic traits (MAGIC). Eye color was a negative control for IHD, as it mirrors the distribution of lactase persistence and IHD in Western Europe.

Results:

Genetically predicted adult milk consumption was not clearly associated with bone mineral density, IHD (odds ratio (OR): 1.03 per s.d., 95% confidence interval (CI): 0.95–1.12) and or T2D (OR: 0.92, 95% CI: 0.83–1.02) but was associated with higher log-transformed fasting insulin (0.05, 95% CI: 0.02–0.07) and body mass index (0.06, 95% CI: 0.03–0.09). Genetically predicted eye color was not associated with IHD.

Conclusions:

The lack of association of genetically predicted milk consumption with bone health, IHD or T2D suggests few beneficial effects but is more consistent with milk promoting adiposity.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Similar content being viewed by others

References

  1. Weaver CM . How sound is the science behind the dietary recommendations for dairy? Am J Clin Nutr 2014; 99: 1217s–1222s.

    Article  CAS  Google Scholar 

  2. O'Sullivan TA, Hafekost K, Mitrou F, Lawrence D . Food sources of saturated fat and the association with mortality: a meta-analysis. Am J Public Health 2013; 103: e31–e42.

    Article  Google Scholar 

  3. Tai V, Leung W, Grey A, Reid IR, Bolland MJ . Calcium intake and bone mineral density: systematic review and meta-analysis. BMJ 2015; 351: h4183.

    Article  Google Scholar 

  4. Wang L, Manson JE, Song Y, Sesso HD . Systematic review: vitamin D and calcium supplementation in prevention of cardiovascular events. Ann Intern Med 2010; 152: 315–323.

    Article  Google Scholar 

  5. Benatar JR, Sidhu K, Stewart RA . Effects of high and low fat dairy food on cardio-metabolic risk factors: a meta-analysis of randomized studies. PLoS One 2013; 8: e76480.

    Article  CAS  Google Scholar 

  6. Alexander DD, Bylsma LC, Vargas AJ, Cohen SS, Doucette A, Mohamed M et al. Dairy consumption and CVD: a systematic review and meta-analysis. Br J Nutr 2016; 115: 737–750.

    Article  CAS  Google Scholar 

  7. Gijsbers L, Ding EL, Malik VS, de Goede J, Geleijnse JM, Soedamah-Muthu SS . Consumption of dairy foods and diabetes incidence: a dose-response meta-analysis of observational studies. Am J Clin Nutr 2016; 103: 1111–1124.

    Article  CAS  Google Scholar 

  8. Bergholdt HK, Nordestgaard BG, Varbo A, Ellervik C . Milk intake is not associated with ischaemic heart disease in observational or Mendelian randomization analyses in 98529 Danish adults. Int J Epidemiol 2015; 44: 587–603.

    Article  Google Scholar 

  9. Smith CE, Coltell O, Sorli JV, Estruch R, Martinez-Gonzalez MA, Salas-Salvado J et al. Associations of the MCM6-rs3754686 proxy for milk intake in Mediterranean and American populations with cardiovascular biomarkers, disease and mortality: Mendelian randomization. Sci Rep 2016; 6: 33188.

    Article  CAS  Google Scholar 

  10. Bergholdt HK, Nordestgaard BG, Ellervik C . Milk intake is not associated with low risk of diabetes or overweight-obesity: a Mendelian randomization study in 97811 Danish individuals. Am J Clin Nutr 2015; 102: 487–496.

    Article  CAS  Google Scholar 

  11. Lamri A, Poli A, Emery N, Bellili N, Velho G, Lantieri O et al. The lactase persistence genotype is associated with body mass index and dairy consumption in the D.E.S.I.R. study. Metabolism 2013; 62: 1323–1329.

    Article  CAS  Google Scholar 

  12. Hartwig FP, Horta BL, Smith GD, de Mola CL, Victora CG . Association of lactase persistence genotype with milk consumption, obesity and blood pressure: a Mendelian randomization study in the 1982 Pelotas (Brazil) birth cohort, with a systematic review and meta-analysis. Int J Epidemiol 2016; 45: 1573–1587.

    Article  Google Scholar 

  13. Muehlhoff E, Bennett A, McMahon D (eds). Milk and Dairy Products in Human Nutrition. Food and agriculture organization of the United Nations: Rome, Italy, 2013. Available at http://www.fao.org/docrep/018/i3396e/i3396e.pdf.

    Google Scholar 

  14. Dave D, Doytch N, Kelly IR . Nutrient intake: a cross-national analysis of trends and economic correlates. Soc Sci Med 2016; 158: 158–167.

    Article  Google Scholar 

  15. Mattar R, de Campos Mazo DF, Carrilho FJ . Lactose intolerance: diagnosis, genetic, and clinical factors. Clin Exp Gastroenterol 2012; 5: 113–121.

    Article  CAS  Google Scholar 

  16. Nichols M, Townsend N, Scarborough P, Rayner M . Trends in age-specific coronary heart disease mortality in the European Union over three decades: 1980-2009. Eur Heart J 2013; 34: 3017–3027.

    Article  Google Scholar 

  17. Walsh S, Wollstein A, Liu F, Chakravarthy U, Rahu M, Seland JH et al. DNA-based eye colour prediction across Europe with the IrisPlex system. Forensic Sci Int Genet 2012; 6: 330–340.

    Article  CAS  Google Scholar 

  18. Troelsen JT . Adult-type hypolactasia and regulation of lactase expression. Biochim Biophys Acta 2005; 1723: 19–32.

    Article  CAS  Google Scholar 

  19. Lehtimaki T, Hutri-Kahonen N, Kahonen M, Hemminki J, Mikkila V, Laaksonen M et al. Adult-type hypolactasia is not a predisposing factor for the early functional and structural changes of atherosclerosis: the Cardiovascular Risk in Young Finns Study. Clin Sci (Lond) 2008; 115: 265–271.

    Article  Google Scholar 

  20. Almon R, Alvarez-Leon EE, Serra-Majem L . Association of the European lactase persistence variant (LCT-13910 C>T polymorphism) with obesity in the Canary Islands. PLoS One 2012; 7: e43978.

    Article  CAS  Google Scholar 

  21. Almon R, Nilsson TK, Sjostrom M, Engfeldt P . Lactase persistence and milk consumption are associated with body height in Swedish preadolescents and adolescents. Food Nutr Res 2011; 55: 7253.

    Article  Google Scholar 

  22. Lerchbaum E, Giuliani A, Gruber HJ, Pieber TR, Obermayer-Pietsch B . Adult-type hypolactasia and calcium intake in polycystic ovary syndrome. Clin Endocrinol (Oxf) 2012; 77: 834–843.

    Article  CAS  Google Scholar 

  23. Eriksson N, Macpherson JM, Tung JY, Hon LS, Naughton B, Saxonov S et al. Web-based, participant-driven studies yield novel genetic associations for common traits. PLoS Genet 2010; 6: e1000993.

    Article  Google Scholar 

  24. Zheng HF, Forgetta V, Hsu YH, Estrada K, Rosello-Diez A, Leo PJ et al. Whole-genome sequencing identifies EN1 as a determinant of bone density and fracture. Nature 2015; 526: 112–117.

    Article  CAS  Google Scholar 

  25. Estrada K, Styrkarsdottir U, Evangelou E, Hsu YH, Duncan EL, Ntzani EE et al. Genome-wide meta-analysis identifies 56 bone mineral density loci and reveals 14 loci associated with risk of fracture. Nat Genet 2012; 44: 491–501.

    Article  CAS  Google Scholar 

  26. Deloukas P, Kanoni S, Willenborg C, Farrall M, Assimes TL, Thompson JR et al. Large-scale association analysis identifies new risk loci for coronary artery disease. Nat Genet 2013; 45: 25–33.

    Article  CAS  Google Scholar 

  27. Schunkert H, Konig IR, Kathiresan S, Reilly MP, Assimes TL, Holm H et al. Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease. Nat Genet 2011; 43: 333–338.

    Article  CAS  Google Scholar 

  28. Nikpay M, Goel A, Won HH, Hall LM, Willenborg C, Kanoni S et al. A comprehensive 1000 genomes-based genome-wide association meta-analysis of coronary artery disease. Nat Genet 2015; 47: 1121–1130.

    Article  CAS  Google Scholar 

  29. Morris AP, Voight BF, Teslovich TM, Ferreira T, Segre AV, Steinthorsdottir V et al. Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nat Genet 2012; 44: 981–990.

    Article  CAS  Google Scholar 

  30. Locke AE, Kahali B, Berndt SI, Justice AE, Pers TH, Day FR et al. Genetic studies of body mass index yield new insights for obesity biology. Nature 2015; 518: 197–206.

    Article  CAS  Google Scholar 

  31. Shungin D, Winkler TW, Croteau-Chonka DC, Ferreira T, Locke AE, Magi R et al. New genetic loci link adipose and insulin biology to body fat distribution. Nature 2015; 518: 187–196.

    Article  CAS  Google Scholar 

  32. Willer CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S et al. Discovery and refinement of loci associated with lipid levels. Nat Genet 2013; 45: 1274–1283.

    Article  CAS  Google Scholar 

  33. Soranzo N, Sanna S, Wheeler E, Gieger C, Radke D, Dupuis J et al. Common variants at 10 genomic loci influence hemoglobin A(1)(C) levels via glycemic and nonglycemic pathways. Diabetes 2010; 59: 3229–3239.

    Article  CAS  Google Scholar 

  34. Scott RA, Lagou V, Welch RP, Wheeler E, Montasser ME, Luan J et al. Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways. Nat Genet 2012; 44: 991–1005.

    Article  CAS  Google Scholar 

  35. Dupuis J, Langenberg C, Prokopenko I, Saxena R, Soranzo N, Jackson AU et al. New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk. Nat Genet 2010; 42: 105–116.

    Article  CAS  Google Scholar 

  36. Burgess S, Thompson SG . Mendelian Randomization Methods for Using Genetic Variants in Causal Estimation, 1st edn. CRC Press: Bocs Raton, USA, 2015.

    Book  Google Scholar 

  37. Lin DY, Sullivan PF . Meta-analysis of genome-wide association studies with overlapping subjects. Am J Hum Genet 2009; 85: 862–872.

    Article  CAS  Google Scholar 

  38. Pontiroli AE, Miele L, Morabito A . Increase of body weight during the first year of intensive insulin treatment in type 2 diabetes: systematic review and meta-analysis. Diabetes Obes Metab 2011; 13: 1008–1019.

    Article  CAS  Google Scholar 

  39. Wu C, DeWan A, Hoh J, Wang Z . A comparison of association methods correcting for population stratification in case-control studies. Ann Hum Genet 2011; 75: 418–427.

    Article  Google Scholar 

  40. Shin SY, Fauman EB, Petersen AK, Krumsiek J, Santos R, Huang J et al. An atlas of genetic influences on human blood metabolites. Nat Genet 2014; 46: 543–550.

    Article  CAS  Google Scholar 

  41. Dungan KM . 1,5-anhydroglucitol (GlycoMark) as a marker of short-term glycemic control and glycemic excursions. Expert Rev Mol Diagn 2008; 8: 9–19.

    Article  CAS  Google Scholar 

  42. Bonder MJ, Kurilshikov A, Tigchelaar EF, Mujagic Z, Imhann F, Vila AV et al. The effect of host genetics on the gut microbiome. Nat Genet 2016; 48: 1407–1412.

    Article  CAS  Google Scholar 

  43. Lomer MC, Parkes GC, Sanderson JD . Review article: lactose intolerance in clinical practice—myths and realities. Aliment Pharmacol Ther 2008; 27: 93–103.

    Article  CAS  Google Scholar 

  44. Zaman MJ, Philipson P, Chen R, Farag A, Shipley M, Marmot MG et al. South Asians and coronary disease: is there discordance between effects on incidence and prognosis? Heart 2013; 99: 729–736.

    Article  Google Scholar 

  45. Myung SK, Ju W, Cho B, Oh SW, Park SM, Koo BK et al. Efficacy of vitamin and antioxidant supplements in prevention of cardiovascular disease: systematic review and meta-analysis of randomised controlled trials. BMJ 2013; 346: f10.

    Article  Google Scholar 

  46. Izumi H, Tsuda M, Sato Y, Kosaka N, Ochiya T, Iwamoto H et al. Bovine milk exosomes contain microRNA and mRNA and are taken up by human macrophages. J Dairy Sci 2015; 98: 2920–2933.

    Article  CAS  Google Scholar 

  47. Nilsson M, Stenberg M, Frid AH, Holst JJ, Bjorck IM . Glycemia and insulinemia in healthy subjects after lactose-equivalent meals of milk and other food proteins: the role of plasma amino acids and incretins. Am J Clin Nutr 2004; 80: 1246–1253.

    Article  CAS  Google Scholar 

  48. Shanik MH, Xu Y, Skrha J, Dankner R, Zick Y, Roth J . Insulin resistance and hyperinsulinemia: is hyperinsulinemia the cart or the horse? Diabetes Care 2008; 31 (Suppl 2), S262–S268.

    Article  CAS  Google Scholar 

  49. Holmes MV, Lange LA, Palmer T, Lanktree MB, North KE, Almoguera B et al. Causal effects of body mass index on cardiometabolic traits and events: a Mendelian randomization analysis. Am J Hum Genet 2014; 94: 198–208.

    Article  CAS  Google Scholar 

  50. World Health Organization Healthy diet Fact Sheet N°394 2015 Available at http://www.who.int/mediacentre/factsheets/fs394/en/ (accessed Sep 2015).

Download references

Acknowledgements

The authors thank GEFOS, CARDIoGRAMplusC4D, DIAGRAM, GIANT, GLGC and MAGIC for access to their data. The authors received no specific funding for this work.

Author information

Authors and Affiliations

  1. School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China

    Q Yang, S L Lin, S L Au Yeung, M K Kwok, L Xu, G M Leung & C M Schooling

  2. School of Public Health and Health Policy, City University of New York, New York, NY, USA

    C M Schooling

Authors
  1. Q Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. S L Lin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. S L Au Yeung
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. M K Kwok
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. L Xu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. G M Leung
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. C M Schooling
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to C M Schooling.

Ethics declarations

Competing interests

The authors declare no conflict of interest.

Additional information

Supplementary Information accompanies this paper on European Journal of Clinical Nutrition website

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, Q., Lin, S., Au Yeung, S. et al. Genetically predicted milk consumption and bone health, ischemic heart disease and type 2 diabetes: a Mendelian randomization study. Eur J Clin Nutr 71, 1008–1012 (2017). https://doi.org/10.1038/ejcn.2017.8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ejcn.2017.8

This article is cited by

Search

Advanced search

Quick links