Effects of selenium on coronary artery disease, type 2 diabetes and their risk factors: a Mendelian randomization study (original) (raw)

• Rayman MP. Selenium and human health. Lancet. 2012;379:1256–68. https://doi.org/10.1016/S0140-6736(11)61452-9
  Article CAS PubMed Google Scholar
• Rees K, Hartley L, Day C, Flowers N, Clarke A, Stranges S. Selenium supplementation for the primary prevention of cardiovascular disease. Cochrane Database Syst Rev. 2013. https://doi.org/10.1002/14651858.CD009671.pub2.
• Vinceti M, Filippini T, Del Giovane C, Dennert G, Zwahlen M, Brinkman M et al. Selenium for preventing cancer. Cochrane Database Syst Rev. 2018. https://doi.org/10.1002/14651858.CD005195.pub4.
• Ju W, Li X, Li Z, Wu GR, Fu XF, Yang XM, et al. The effect of selenium supplementation on coronary heart disease: A systematic review and meta-analysis of randomized controlled trials. J Trace Elem Med Biol. 2017;44:8–16. https://doi.org/10.1016/j.jtemb.2017.04.009
  Article CAS PubMed Google Scholar
• Zhang X, Liu C, Guo J, Song Y. Selenium status and cardiovascular diseases: meta-analysis of prospective observational studies and randomized controlled trials. Eur J Clin Nutr. 2015;70:162–9.
• Flores-Mateo G, Nanas-Acien A, Pastor-Barriuso R, Guallar E. Selenium and coronary heart disease: a meta-analysis. Am J Clin Nutr. 2006;84:762–73. https://doi.org/10.1093/ajcn/84.4.762
  Article CAS PubMed Google Scholar
• Vinceti M, Filippini T, Rothman K. Selenium exposure and the risk of type 2 diabetes: a systematic review and meta-analysis. Eur J Epidemiol. 2018;33:789–810. https://doi.org/10.1007/s10654-018-0422-8
  Article PubMed Google Scholar
• Kim J, Chung HS, Choi M-K, Roh YK, Yoo HJ, Park JH, et al. Association between serum selenium level and the presence of diabetes mellitus: a meta-analysis of observational studies. Diabetes Metab J. 2019;43:e1.
  Article Google Scholar
• Kohler LN, Foote J, Kelley CP, Florea A, Shelly C, Chow HHS, et al. Selenium and type 2 diabetes: systematic review. Nutrients. 2018;10:1924. https://doi.org/10.3390/nu10121924
  Article CAS PubMed Central Google Scholar
• Wang X-L, Yang T-B, Wei J, Lei G-H, Zeng C. Association between serum selenium level and type 2 diabetes mellitus: a non-linear dose–response meta-analysis of observational studies. Nutr J. 2016;15:48. https://doi.org/10.1186/s12937-016-0169-6
  Article CAS PubMed PubMed Central Google Scholar
• Lawlor DA, Harbord RM, Sterne JAC, Timpson N, Davey Smith G. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008;27:1133–63. https://doi.org/10.1002/sim.3034
  Article PubMed Google Scholar
• Yarmolinsky J, Bonilla C, Haycock PC, Langdon RJQ, Lotta LA, Langenberg C, et al. Circulating Selenium and Prostate Cancer Risk: A Mendelian Randomization Analysis. JNCI: J Natl Cancer Inst. 2018;110:1035–8. https://doi.org/10.17863/CAM.27700
  Article PubMed PubMed Central Google Scholar
• Cornelis MC, Fornage M, Foy M, Xun P, Gladyshev VN, Morris S, et al. Genome-wide association study of selenium concentrations. Hum Mol Genet. 2015;24:1469–77. https://doi.org/10.1093/hmg/ddu546
  Article CAS PubMed Google Scholar
• Evans DM, Zhu G, Dy V, Heath AC, Madden PAF, Kemp JP, et al. Genome-wide association study identifies loci affecting blood copper, selenium and zinc. Hum Mol Genet. 2013;22:3998–4006. https://doi.org/10.1093/hmg/ddt239
  Article CAS PubMed PubMed Central Google Scholar
• Nelson CP, Goel A, Butterworth AS, Kanoni S, Webb TR, Marouli E, et al. Association analyses based on false discovery rate implicate new loci for coronary artery disease. Nat Genet. 2017;49**:**1385–91.
• Nikpay M, Goel A, Won H-H, 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;47:1121–30. https://doi.org/10.1038/ng.3396
  Article CAS PubMed PubMed Central Google Scholar
• Willer C, Schmidt E, Sengupta S, Peloso G, Gustafsson S, Kanoni S, et al. Discovery and refinement of loci associated with lipid levels. Nat Genet. 2013;45:1274–83. https://doi.org/10.1038/ng.2797
  Article CAS PubMed PubMed Central Google Scholar
• Mahajan A, Taliun D, Thurner M, Robertson NR, Torres JM, Rayner NW, et al. Fine-mapping type 2 diabetes loci to single-variant resolution using high-density imputation and islet-specific epigenome maps. Nat Genet. 2018;50:1505–13. https://doi.org/10.1038/s41588-018-0241-6
  Article CAS PubMed PubMed Central Google Scholar
• Wheeler E, Leong A, Liu CT, Hivert MF, Strawbridge RJ, Podmore C, et al. Impact of common genetic determinants of Hemoglobin A1c on type 2 diabetes risk and diagnosis in ancestrally diverse populations: A transethnic genome-wide meta-analysis. PLoS Med. 2017;14:e1002383. https://doi.org/10.17863/CAM.13618
  Article PubMed PubMed Central Google Scholar
• Manning AK, Hivert M-F, Scott RA, Grimsby JL, Bouatia-Naji N, Chen H et al. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat Genet. 2012;44:659.
• 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;42:105–16.
• Hemani G, Zheng J, Elsworth B, Wade KH, Haberland V, Baird D, et al. The MR-Base platform supports systematic causal inference across the human phenome. eLife. 2018;7:e34408 https://doi.org/10.7554/eLife.34408
  Article PubMed PubMed Central Google Scholar
• Burgess S, Zuber V, Valdes-Marquez E, Sun BB, Hopewell JC. Mendelian randomization with fine-mapped genetic data: choosing from large numbers of correlated instrumental variables. Genet Epidemiol. 2017;41:714–25. https://doi.org/10.1002/gepi.22077
  Article PubMed PubMed Central Google Scholar
• Greco MFD, Minelli C, Sheehan NA, Thompson JR. Detecting pleiotropy in Mendelian randomisation studies with summary data and a continuous outcome. Stat Med. 2015;34:2926–40. https://doi.org/10.1002/sim.6522
  Article Google Scholar
• Burgess S, Thompson S. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32:377–89. https://doi.org/10.1007/s10654-017-0255-x
  Article PubMed PubMed Central Google Scholar
• Burgess S, Thompson SG. Bias in causal estimates from Mendelian randomization studies with weak instruments. Stat Med. 2011;30:1312–23. https://doi.org/10.1002/sim.4197
  Article PubMed Google Scholar
• Freeman G, Cowling BJ, Schooling CM. Power and sample size calculations for Mendelian randomization studies using one genetic instrument. Int J Epidemiol. 2013;42:1157–63. https://doi.org/10.1093/ije/dyt110
  Article PubMed Google Scholar
• Rayman MP, Stranges S. Epidemiology of selenium and type 2 diabetes: Can we make sense of it? Free Radic Biol Med. 2013;65:1557–64. https://doi.org/10.1016/j.freeradbiomed.2013.04.003
  Article CAS PubMed Google Scholar
• Slotnick MJ, Nriagu JO. Validity of human nails as a biomarker of arsenic and selenium exposure: a review. Environ Res. 2006;102:125–39. https://doi.org/10.1016/j.envres.2005.12.001
  Article CAS PubMed Google Scholar
• Vinceti M, Filippini T, Wise LA. Environmental Selenium and Human Health: an Update. Curr Environ Health Rep. 2018;5:464–85. https://doi.org/10.1007/s40572-018-0213-0. e-pub ahead of print 2018/10/04
  Article PubMed Google Scholar
• Willer CJ, Li Y, Abecasis GR. METAL: fast and efficient meta-analysis of genomewide association scans. Bioinformatics. 2010;26:2190–1. https://doi.org/10.1093/bioinformatics/btq340
  Article CAS PubMed PubMed Central Google Scholar
• Bowden J, Davey Smith G, Haycock PC, Burgess S. Consistent estimation in mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol. 2016;40:304–14. https://doi.org/10.1002/gepi.21965
  Article PubMed PubMed Central Google Scholar
• Verbanck M, Chen C-Y, Neale B, Do R. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50:693–8. https://doi.org/10.1038/s41588-018-0099-7
  Article CAS PubMed PubMed Central Google Scholar
• R Core Team. R: a language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2018.
• Xiang S, Dai Z, Man C, Fan Y. Circulating selenium and cardiovascular or all-cause mortality in the general population: a meta-analysis. Biol Trace Elem Res. 2020;195:55–62. https://doi.org/10.1007/s12011-019-01847-8
  Article CAS PubMed Google Scholar
• Rayman MP, Stranges S, Griffin BA, Pastor-Barriuso R, Guallar E. Effect of supplementation with high-selenium yeast on plasma lipids: a randomized trial. Ann Intern Med. 2011;154:656–65. https://doi.org/10.7326/0003-4819-154-10-201105170-00005
  Article PubMed Google Scholar
• Jacobs ET, Lance P, Mandarino LJ, Ellis NA, Chow HHS, Foote J, et al. Selenium supplementation and insulin resistance in a randomized, clinical trial. BMJ Open Diabetes Res Care. 2019;7:e000613. https://doi.org/10.1136/bmjdrc-2018-000613
  Article PubMed PubMed Central Google Scholar
• Junxi L, Shiu Lun Au Y, Shi Lin L, Gabriel ML, Schooling CM. Liver enzymes and risk of ischemic heart disease and type 2 diabetes mellitus: a Mendelian Randomization Study. Sci Rep. 2016;6:38813. https://doi.org/10.1038/srep38813
  Article CAS Google Scholar
• Zhao J, Schooling C. Effect of linoleic acid on ischemic heart disease and its risk factors: a Mendelian randomization study. BMC Med. 2019;17:61. https://doi.org/10.1186/s12916-019-1293-x
  Article PubMed PubMed Central Google Scholar
• Sattar N, Taskinen M-R. Statins are diabetogenic – Myth or reality? Atherosclerosis. 2012;13:1–10. https://doi.org/10.1016/j.atherosclerosissup.2012.06.001
  Article CAS PubMed Google Scholar
• Fall T, Xie W, Poon W, Yaghootkar H, Mägi R, Knowles JW, et al. Using genetic variants to assess the relationship between circulating lipids and type 2 diabetes. Diabetes. 2015;64:2676–84. https://doi.org/10.2337/db14-1710
  Article CAS PubMed Google Scholar
• Swerdlow DI, Preiss D, Kuchenbaecker KB, Holmes MV, Engmann JEL, Shah T, et al. HMG-coenzyme a reductase inhibition, type 2 diabetes, and bodyweight: evidence from genetic analysis and randomised trials. Lancet. 2015;385:351–61. https://doi.org/10.1016/S0140-6736(14)61183-1
  Article CAS PubMed PubMed Central Google Scholar
• Axsom K, Berger J, Schwartzbard A. Statins and diabetes: the good, the bad, and the unknown. Curr Atheroscler Rep. 2013;15:1–7. https://doi.org/10.1007/s11883-012-0299-z
  Article CAS Google Scholar
• White J, Swerdlow DI, Preiss D, Fairhurst-Hunter Z, Keating BJ, Asselbergs FW, et al. Association of lipid fractions with risks for coronary artery disease and diabetes. JAMA Cardiol. 2016;1:692–9. https://doi.org/10.1001/jamacardio.2016.1884
  Article PubMed PubMed Central Google Scholar
• Ference BA, Robinson JG, Brook RD, Catapano AL, Chapman MJ, Neff DR, et al. Variation in PCSK9 and HMGCR and risk of cardiovascular disease and diabetes. N. Engl J Med. 2016;375:2144–53. https://doi.org/10.1056/NEJMoa1604304
  Article CAS PubMed Google Scholar
• Lotta LA, Sharp SJ, Burgess S, Perry JRB, Stewart ID, Willems SM, et al. Association between low-density lipoprotein cholesterol–lowering genetic variants and risk of type 2 diabetes: a meta-analysis. JAMA. 2016;316:1383–91. https://doi.org/10.1001/jama.2016.14568
  Article CAS PubMed PubMed Central Google Scholar
• Sabatine MS, Leiter LA, Wiviott SD, Giugliano RP, Deedwania P, De Ferrari GM, et al. Cardiovascular safety and efficacy of the PCSK9 inhibitor evolocumab in patients with and without diabetes and the effect of evolocumab on glycaemia and risk of new-onset diabetes: a prespecified analysis of the FOURIER randomised controlled trial. Lancet Diabetes Endocrinol. 2017;5:941–50. https://doi.org/10.1016/S2213-8587(17)30313-3
  Article CAS PubMed Google Scholar
• Wu H, Shang H, Wu J. Effect of ezetimibe on glycemic control: a systematic review and meta-analysis of randomized controlled trials. Endocrine. 2018;60:229–39. https://doi.org/10.1007/s12020-018-1541-4
  Article CAS PubMed Google Scholar
• Nassir F, Moundras C, Bayle D, Sérougne C, Gueux E, Rock E, et al. Effect of selenium deficiency on hepatic lipid and lipoprotein metabolism in the rat. Br J Nutr. 1997;78:493–500. https://doi.org/10.1079/BJN19970166
  Article CAS PubMed Google Scholar
• McClung JP, Roneker CA, Mu W, Lisk DJ, Langlais P, Liu F, et al. Development of insulin resistance and obesity in mice overexpressing cellular glutathione peroxidase. Proc Natl Acad Sci USA. 2004;101:8852–7. https://doi.org/10.1073/pnas.0308096101
  Article CAS PubMed PubMed Central Google Scholar
• Loh K, Deng H, Fukushima A, Cai X, Boivin B, Galic S, et al. Reactive oxygen species enhance insulin sensitivity. Cell Metab. 2009;10:260–72. https://doi.org/10.1016/j.cmet.2009.08.009
  Article CAS PubMed PubMed Central Google Scholar
• Misu H, Takamura T, Takayama H, Hayashi H, Matsuzawa-Nagata N, Kurita S, et al. A liver-derived secretory protein, Selenoprotein P, causes insulin resistance. Cell Metab. 2010;12:483–95. https://doi.org/10.1016/j.cmet.2010.09.015
  Article CAS PubMed Google Scholar
• Huang T, Ren J, Huang J, Li D. Association of homocysteine with type 2 diabetes: a meta-analysis implementing Mendelian randomization approach. BMC Genom. 2013;14:867. https://doi.org/10.1186/1471-2164-14-867
  Article CAS Google Scholar
• Zhao JV, Schooling CM. Homocysteine-reducing B vitamins and ischemic heart disease: a separate-sample Mendelian randomization analysis. Eur J Clin Nutr. 2017;71:267–73. https://doi.org/10.1038/ejcn.2016.246
  Article CAS PubMed Google Scholar
• Lopez PM, Subramanian SV, Schooling CM. Effect measure modification conceptualized using selection diagrams as mediation by mechanisms of varying population-level relevance. J Clin Epidemiol. 2019;113:123–8. https://doi.org/10.1016/j.jclinepi.2019.05.005
  Article PubMed Google Scholar
• Staley J, Burgess S. Semiparametric methods for estimation of a nonlinear exposure-outcome relationship using instrumental variables with application to Mendelian randomization. 2017;41:341−52.
• Schooling CM, Yeung SL, Freeman G. Mendelian randomization estimates may be inflated. J Am Coll Cardiol. 2013;61:1931. https://doi.org/10.1016/j.jacc.2012.12.049
  Article PubMed Google Scholar
• Jablonska E, Vinceti M. Selenium and human health: witnessing a copernican revolution? J Environ Sci Health, Part C. 2015;33:328–68. https://doi.org/10.1080/10590501.2015.1055163
  Article CAS Google Scholar