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Open Access 01-11-2018 | Original paper

Mendelian randomization does not support serum calcium in prostate cancer risk

Authors: James Yarmolinsky, Katie Berryman, Ryan Langdon, Carolina Bonilla, George Davey Smith, Richard M. Martin, Sarah J. Lewis, PRACTICAL consortium

Published in: Cancer Causes & Control | Issue 11/2018

Abstract

Purpose

Observational studies suggest that dietary and serum calcium are risk factors for prostate cancer. However, such studies suffer from residual confounding (due to unmeasured or imprecisely measured confounders), undermining causal inference. Mendelian randomization uses randomly assigned (hence unconfounded and pre-disease onset) germline genetic variation to proxy for phenotypes and strengthen causal inference in observational studies. We tested the hypothesis that serum calcium is associated with an increased risk of overall and advanced prostate cancer.

Methods

A genetic instrument was constructed using five single-nucleotide polymorphisms robustly associated with serum calcium in a genome-wide association study (n ≤ 61,079). This instrument was then used to test the effect of a 0.5 mg/dL increase (1 standard deviation, SD) in serum calcium on risk of prostate cancer in 72,729 men in the PRACTICAL (Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome) Consortium (44,825 cases, 27,904 controls) and risk of advanced prostate cancer in 33,498 men (6,263 cases, 27,235 controls).

Results

We found weak evidence for a protective effect of serum calcium on prostate cancer risk (odds ratio [OR] per 0.5 mg/dL increase in calcium: 0.83, 95% CI 0.63–1.08; p = 0.12). We did not find strong evidence for an effect of serum calcium on advanced prostate cancer (OR per 0.5 mg/dL increase in calcium: 0.98, 95% CI 0.57–1.70; p = 0.93).

Conclusions

Our Mendelian randomization analysis does not support the hypothesis that serum calcium increases risk of overall or advanced prostate cancer.

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Global Burden of Disease Cancer Collaboration (2015) et al The global burden of cancer 2013. JAMA Oncol 1(4):505–527CrossRef

Gann PH (2002) Risk factors for prostate cancer. Rev Urol 4(Suppl 5):S3–S10

Center MM et al (2012) International variation in prostate cancer incidence and mortality rates. Eur Urol 61(6):1079–1092CrossRef

Wong MC et al (2016) Global incidence and mortality for prostate cancer: analysis of temporal patterns and trends in 36 countries. Eur Urol 70(5):862–874CrossRef

Haenszel W, Kurihara M (1968) Studies of Japanese migrants. I. Mortality from cancer and other diseases among Japanese in the United States. J Natl Cancer Inst 40(1):43–68PubMed

McCredie M, Williams S, Coates M (1999) Cancer mortality in East and Southeast Asian migrants to New South Wales, Australia, 1975–1995. Br J Cancer 79(7–8):1277–1282CrossRef

Thomas DB, Karagas MR (1996) Migrant studies. In: Schottenfeld D, Fraumeni JF (eds) Cancer epidemiology and prevention, Oxford University Press, New York, pp 236–254

Butler LM et al (2010) Calcium intake increases risk of prostate cancer among Singapore Chinese. Cancer Res 70(12):4941–4948CrossRef

Gao X, LaValley MP, Tucker KL (2005) Prospective studies of dairy product and calcium intakes and prostate cancer risk: a meta-analysis. J Natl Cancer Inst 97(23):1768–1777CrossRef

10.

Tseng M et al (2005) Dairy, calcium, and vitamin D intakes and prostate cancer risk in the National Health and nutrition examination epidemiologic follow-up study cohort. Am J Clin Nutr 81(5):1147–1154CrossRef

11.

Aune D et al (2015) Dairy products, calcium, and prostate cancer risk: a systematic review and meta-analysis of cohort studies. Am J Clin Nutr 101(1):87–117CrossRef

12.

Chan JM et al (1998) Dairy products, calcium, phosphorous, vitamin D, and risk of prostate cancer (Sweden). Cancer Causes Control 9(6):559–566CrossRef

13.

Giovannucci E et al (2006) A prospective study of calcium intake and incident and fatal prostate cancer. Cancer Epidemiol Biomark Prev 15(2):203–210CrossRef

14.

Giovannucci E et al (1998) Calcium and fructose intake in relation to risk of prostate cancer. Cancer Res 58(3):442–447PubMed

15.

Allen NE et al (2008) Animal foods, protein, calcium and prostate cancer risk: the European Prospective Investigation into Cancer and Nutrition. Br J Cancer 98(9):1574–1581CrossRef

16.

Park SY et al (2007) Calcium, vitamin D, and dairy product intake and prostate cancer risk: the Multiethnic Cohort Study. Am J Epidemiol 166(11):1259–1269CrossRef

17.

Peacock M (2010) Calcium metabolism in health and disease. Clin J Am Soc Nephrol 5(Suppl 1):S23–S30CrossRef

18.

Schwartz GG (2009) Is serum calcium a biomarker of fatal prostate cancer? Future Oncol 5(5):577–580CrossRef

19.

Konety BR et al (1996) The role of vitamin D in normal prostate growth and differentiation. Cell Growth Differ 7(11):1563–1570PubMed

20.

Schwartz GG et al (1995) 1,25-Dihydroxy-16-ene-23-yne-vitamin D3 and prostate cancer cell proliferation in vivo. Urology 46(3):365–369CrossRef

21.

Schwartz GG et al (1997) 1 alpha,25-Dihydroxyvitamin D (calcitriol) inhibits the invasiveness of human prostate cancer cells. Cancer Epidemiol Biomark Prev 6(9):727–732

22.

Giovannucci E (1998) Dietary influences of 1,25(OH)2 vitamin D in relation to prostate cancer: a hypothesis. Cancer Causes Control 9(6):567–582CrossRef

23.

Skinner HG, Schwartz GG (2008) Serum calcium and incident and fatal prostate cancer in the National Health and Nutrition Examination Survey. Cancer Epidemiol Biomark Prev 17(9):2302–2305CrossRef

24.

Van Hemelrijck M et al (2012) Serum calcium and incident and fatal prostate cancer in the Swedish AMORIS study. Cancer Causes Control 23(8):1349–1358CrossRef

25.

Brandstedt J et al, Vitamin D (2016) PTH, and calcium in relation to survival following prostate cancer. Cancer Causes Control 27(5):669–677CrossRef

26.

Schwartz GG, Skinner HG (2012) A prospective study of total and ionized serum calcium and time to fatal prostate cancer. Cancer Epidemiol Biomark Prev 21(10):1768–1773CrossRef

27.

Skinner HG, Schwartz GG (2009) A prospective study of total and ionized serum calcium and fatal prostate cancer. Cancer Epidemiol Biomark Prev 18(2):575–578CrossRef

28.

Brandstedt J et al, Vitamin D (2012) PTH, and calcium and the risk of prostate cancer: a prospective nested case-control study. Cancer Causes Control 23(8):1377–1385CrossRef

29.

Halthur C et al (2009) Serum calcium and the risk of prostate cancer. Cancer Causes Control 20(7):1205–1214CrossRef

30.

Smith GD, Ebrahim S (2001) Epidemiology–is it time to call it a day? Int J Epidemiol 30(1):1–11CrossRef

31.

Lawlor DA et al (2004) Those confounded vitamins: what can we learn from the differences between observational versus randomised trial evidence? Lancet 363(9422):1724–1727CrossRef

32.

Davey Smith G, Ebrahim S (2003) ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol 32(1):1–22CrossRef

33.

Yarmolinsky J et al (2018) Causal inference in cancer epidemiology: what is the role of mendelian randomization? Cancer Epidemiol Biomark Prev 27(9):995–1010CrossRef

34.

O’Seaghdha CM et al (2013) Meta-analysis of genome-wide association studies identifies six new Loci for serum calcium concentrations. PLoS Genet 9(9):e1003796CrossRef

35.

Schumacher FR et al (2018) Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci. Nat Genet 50(7):928–936CrossRef

36.

Pierce BL, Burgess S (2013) Efficient design for Mendelian randomization studies: subsample and 2-sample instrumental variable estimators. Am J Epidemiol 178(7):1177–1184CrossRef

37.

Amos CI et al (2017) The OncoArray Consortium: a network for understanding the genetic architecture of common cancers. Cancer Epidemiol Biomark Prev 26(1):126–135CrossRef

38.

1000 Genomes Project Consortium (2015) et al A global reference for human genetic variation. Nature 526(7571):68–74CrossRef

39.

1000 Genomes Project Consortium (2010) et al A map of human genome variation from population-scale sequencing. Nature 467(7319):1061–1073CrossRef

40.

Hemani G et al (2018) The MR-Base platform supports systematic causal inference across the human phenome. eLife 7:e34408CrossRef

41.

Albanes D et al (2009) Serum insulin, glucose, indices of insulin resistance, and risk of prostate cancer. J Natl Cancer Inst 101(18):1272–1279CrossRef

42.

Gong Z et al (2006) Obesity, diabetes, and risk of prostate cancer: results from the prostate cancer prevention trial. Cancer Epidemiol Biomark Prev 15(10):1977–1983CrossRef

43.

Jess T et al (2013) Cancer risk in inflammatory bowel disease according to patient phenotype and treatment: a Danish population-based cohort study. Am J Gastroenterol 108(12):1869–1876CrossRef

44.

Kok DE et al (2011) Blood lipid levels and prostate cancer risk; a cohort study. Prostate Cancer Prostatic Dis 14(4):340–345CrossRef

45.

Shin SY et al (2014) An atlas of genetic influences on human blood metabolites. Nat Genet 46(6):543–550CrossRef

46.

Burgess S, Thompson SG, Collaboration CCG (2011) Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol 40(3):755–764CrossRef

47.

Burgess S (2014) Sample size and power calculations in Mendelian randomization with a single instrumental variable and a binary outcome. Int J Epidemiol 43(3):922–929CrossRef

48.

Burgess S et al (2015) Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. Eur J Epidemiol 30(7):543–552CrossRef

49.

Higgins JP et al (2003) Measuring inconsistency in meta-analyses. BMJ 327(7414):557–560CrossRef

50.

Bowden J, Smith GD, Burgess S (2015) Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int J Epidemiol 44(2):512–525CrossRef

51.

Bowden J et al (2016) Consistent estimation in mendelian randomization with some invalid instruments using a weighted median estimator. Genet Epidemiol 40(4):304–314CrossRef

52.

Bowden J et al (2016) Assessing the suitability of summary data for two-sample Mendelian randomization analyses using MR-Egger regression: the role of the I2 statistic. Int J Epidemiol 45(6):1961–1974

53.

Pierce BL, Ahsan H, Vanderweele TJ (2011) Power and instrument strength requirements for Mendelian randomization studies using multiple genetic variants. Int J Epidemiol 40(3):740–752CrossRef

54.

Liao J et al (2006) Extracellular calcium as a candidate mediator of prostate cancer skeletal metastasis. Cancer Res 66(18):9065–9073CrossRef

55.

Ritchie CK et al (1997) Effects of the calciotrophic peptides calcitonin and parathyroid hormone on prostate cancer growth and chemotaxis. Prostate 30(3):183–187CrossRef

56.

Harrison S et al (2017) Does milk intake promote prostate cancer initiation or progression via effects on insulin-like growth factors (IGFs)? A systematic review and meta-analysis. Cancer Causes Control 28(6):497–528CrossRef

57.

Roddam AW et al (2008) Insulin-like growth factors, their binding proteins, and prostate cancer risk: analysis of individual patient data from 12 prospective studies. Ann Intern Med 149(7):461–471CrossRef

58.

Bristow SM et al (2013) Calcium supplements and cancer risk: a meta-analysis of randomised controlled trials. Br J Nutr 110(8):1384–1393CrossRef

59.

Sanson-Fisher RW et al (2007) Limitations of the randomized controlled trial in evaluating population-based health interventions. Am J Prev Med 33(2):155–161CrossRef

60.

Etzioni R et al (1998) Asymptomatic incidence and duration of prostate cancer. Am J Epidemiol 148(8):775–785CrossRef

61.

Schatzkin A et al (2009) Mendelian randomization: how it can–and cannot–help confirm causal relations between nutrition and cancer. Cancer Prev Res 2(2):104–113CrossRef

Title: Mendelian randomization does not support serum calcium in prostate cancer risk
Authors: James Yarmolinsky
Katie Berryman
Ryan Langdon
Carolina Bonilla
George Davey Smith
Richard M. Martin
Sarah J. Lewis
PRACTICAL consortium
Publication date: 01-11-2018
Publisher: Springer International Publishing
Published in: Cancer Causes & Control / Issue 11/2018
Print ISSN: 0957-5243
Electronic ISSN: 1573-7225
DOI: https://doi.org/10.1007/s10552-018-1081-5

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