Physical activity and risks of breast and colorectal cancer: a Mendelian randomisation analysis

Nikos Papadimitriou, Niki Dimou, Konstantinos K Tsilidis, Barbara Banbury, Richard M Martin, Sarah J Lewis, Nabila Kazmi, Timothy M Robinson, Demetrius Albanes, Krasimira Aleksandrova, Sonja I Berndt, D Timothy Bishop, Hermann Brenner, Daniel D Buchanan, Bas Bueno-de-Mesquita, Peter T Campbell, Sergi Castellví-Bel, Andrew T Chan, Jenny Chang-Claude, Merete Ellingjord-Dale, Jane C Figueiredo, Steven J Gallinger, Graham G Giles, Edward Giovannucci, Stephen B Gruber, Andrea Gsur, Jochen Hampe, Heather Hampel, Sophia Harlid, Tabitha A Harrison, Michael Hoffmeister, John L Hopper, Li Hsu, José María Huerta, Jeroen R Huyghe, Mark A Jenkins, Temitope O Keku, Tilman Kühn, Carlo La Vecchia, Loic Le Marchand, Christopher I Li, Li Li, Annika Lindblom, Noralane M Lindor, Brigid Lynch, Sanford D Markowitz, Giovanna Masala, Anne M May, Roger Milne, Evelyn Monninkhof, Lorena Moreno, Victor Moreno, Polly A Newcomb, Kenneth Offit, Vittorio Perduca, Paul D P Pharoah, Elizabeth A Platz, John D Potter, Gad Rennert, Elio Riboli, Maria-Jose Sánchez, Stephanie L Schmit, Robert E Schoen, Gianluca Severi, Sabina Sieri, Martha L Slattery, Mingyang Song, Catherine M Tangen, Stephen N Thibodeau, Ruth C Travis, Antonia Trichopoulou, Cornelia M Ulrich, Franzel J B van Duijnhoven, Bethany Van Guelpen, Pavel Vodicka, Emily White, Alicja Wolk, Michael O Woods, Anna H Wu, Ulrike Peters, Marc J Gunter, Neil Murphy, Nikos Papadimitriou, Niki Dimou, Konstantinos K Tsilidis, Barbara Banbury, Richard M Martin, Sarah J Lewis, Nabila Kazmi, Timothy M Robinson, Demetrius Albanes, Krasimira Aleksandrova, Sonja I Berndt, D Timothy Bishop, Hermann Brenner, Daniel D Buchanan, Bas Bueno-de-Mesquita, Peter T Campbell, Sergi Castellví-Bel, Andrew T Chan, Jenny Chang-Claude, Merete Ellingjord-Dale, Jane C Figueiredo, Steven J Gallinger, Graham G Giles, Edward Giovannucci, Stephen B Gruber, Andrea Gsur, Jochen Hampe, Heather Hampel, Sophia Harlid, Tabitha A Harrison, Michael Hoffmeister, John L Hopper, Li Hsu, José María Huerta, Jeroen R Huyghe, Mark A Jenkins, Temitope O Keku, Tilman Kühn, Carlo La Vecchia, Loic Le Marchand, Christopher I Li, Li Li, Annika Lindblom, Noralane M Lindor, Brigid Lynch, Sanford D Markowitz, Giovanna Masala, Anne M May, Roger Milne, Evelyn Monninkhof, Lorena Moreno, Victor Moreno, Polly A Newcomb, Kenneth Offit, Vittorio Perduca, Paul D P Pharoah, Elizabeth A Platz, John D Potter, Gad Rennert, Elio Riboli, Maria-Jose Sánchez, Stephanie L Schmit, Robert E Schoen, Gianluca Severi, Sabina Sieri, Martha L Slattery, Mingyang Song, Catherine M Tangen, Stephen N Thibodeau, Ruth C Travis, Antonia Trichopoulou, Cornelia M Ulrich, Franzel J B van Duijnhoven, Bethany Van Guelpen, Pavel Vodicka, Emily White, Alicja Wolk, Michael O Woods, Anna H Wu, Ulrike Peters, Marc J Gunter, Neil Murphy

Abstract

Physical activity has been associated with lower risks of breast and colorectal cancer in epidemiological studies; however, it is unknown if these associations are causal or confounded. In two-sample Mendelian randomisation analyses, using summary genetic data from the UK Biobank and GWA consortia, we found that a one standard deviation increment in average acceleration was associated with lower risks of breast cancer (odds ratio [OR]: 0.51, 95% confidence interval [CI]: 0.27 to 0.98, P-value = 0.04) and colorectal cancer (OR: 0.66, 95% CI: 0.48 to 0.90, P-value = 0.01). We found similar magnitude inverse associations for estrogen positive (ER+ve) breast cancer and for colon cancer. Our results support a potentially causal relationship between higher physical activity levels and lower risks of breast cancer and colorectal cancer. Based on these data, the promotion of physical activity is probably an effective strategy in the primary prevention of these commonly diagnosed cancers.

Conflict of interest statement

Where authors are identified as personnel of the International Agency for Research on Cancer/World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organization. The authors declare no competing interests.

Figures

Fig. 1. Mendelian randomisation analysis for individual…
Fig. 1. Mendelian randomisation analysis for individual SNPs associated with accelerometer-measured physical activity in relation to breast cancer risk using the genetic instrument from the GWAS by Doherty et al..
The x axis corresponds to a log OR per one unit increase in the physical activity based on the average acceleration (milligravities). The Mendelian randomisation (MR) result corresponds to a random effects model due to heterogeneity across the genetic instruments. logOR = log odds ratio (black filled circle). 95% CI = 95% confidence interval (black line). SNP single nucleotide polymorphism.
Fig. 2. Mendelian randomisation analysis for individual…
Fig. 2. Mendelian randomisation analysis for individual SNPs associated with accelerometer-measured physical activity in relation to colorectal cancer risk (overall, colon, rectal) using the genetic instrument from the GWAS by Doherty et al..
The x axis corresponds to a log OR per one unit increase in the physical activity based on the average acceleration (milli-gravities). The Mendelian randomisation (MR) result corresponds to a random effects model due to heterogeneity across the genetic instruments. logOR = log odds ratio (black filled circle). 95% CI = 95% confidence interval (black line). SNP single nucleotide polymorphism.

References

    1. Bray F, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA: Cancer J. Clinicians. 2018;68:394–424.
    1. WHO. Global Status Report on Noncommunicable Diseases 2014 (WHO, 2014).
    1. Moore SC, et al. Association of leisure-time physical activity with risk of 26 types of cancer in 1.44 million adults. JAMA Intern. Med. 2016;176:816–825. doi: 10.1001/jamainternmed.2016.1548.
    1. Morris JS, Bradbury KE, Cross AJ, Gunter MJ, Murphy N. Physical activity, sedentary behaviour and colorectal cancer risk in the UK Biobank. Br. J. Cancer. 2018;118:920. doi: 10.1038/bjc.2017.496.
    1. Kyu HH, et al. Physical activity and risk of breast cancer, colon cancer, diabetes, ischemic heart disease, and ischemic stroke events: systematic review and dose-response meta-analysis for the Global Burden of Disease Study 2013. BMJ. 2016;354:i3857. doi: 10.1136/bmj.i3857.
    1. WCRF-AICR. Physical Activity and the Risk of Cancer (World Cancer Research Fund/American Institute for Cancer Research, 2018).
    1. Prince SA, et al. A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review. Int. J. Behav. Nutr. Phys. Act. 2008;5:56. doi: 10.1186/1479-5868-5-56.
    1. Doherty A, et al. Large scale population assessment of physical activity using wrist worn accelerometers: The UK Biobank Study. PLoS ONE. 2017;12:e0169649. doi: 10.1371/journal.pone.0169649.
    1. Davey Smith, G. & Ebrahim, S. ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease? Int. J. Epidemiol.32, 1–22 (2003).
    1. 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;27:1133–1163. doi: 10.1002/sim.3034.
    1. Doherty A, et al. GWAS identifies 14 loci for device-measured physical activity and sleep duration. Nat. Commun. 2018;9:5257. doi: 10.1038/s41467-018-07743-4.
    1. Klimentidis, Y. C. et al. Genome-wide association study of habitual physical activity in over 277,000 UK Biobank participants identifies novel variants and genetic correlations with chronotype and obesity-related traits. bioRxiv10.1101/179317 (2017).
    1. Michailidou K, et al. Association analysis identifies 65 new breast cancer risk loci. Nature. 2017;551:92. doi: 10.1038/nature24284.
    1. Huyghe JR, et al. Discovery of common and rare genetic risk variants for colorectal cancer. Nat. Genet. 2019;51:76–87. doi: 10.1038/s41588-018-0286-6.
    1. WCRF-AICR. Diet, nutrition, physical activity and breast cancer. Continuous Update Project. (2018).
    1. WCRF-AICR. Diet, nutrition, physical activity and colorectal cancer. Continuous Update Project. (2017).
    1. Ballard-Barbash R, et al. Physical activity, weight control, and breast cancer risk and survival: clinical trial rationale and design considerations. JNCI: J. Natl Cancer Inst. 2009;101:630–643. doi: 10.1093/jnci/djp068.
    1. Friedenreich CM, Shaw E, Neilson HK, Brenner DR. Epidemiology and biology of physical activity and cancer recurrence. J. Mol. Med. 2017;95:1029–1041. doi: 10.1007/s00109-017-1558-9.
    1. Hildebrand, M., Van Hees, V. T., Hansen, B. H. & Ekelund, U. L. F. Age group comparability of raw accelerometer output from wrist- and hip-worn monitors. Medi. Sci. Sports Exercise46, 1816–1824 (2014).
    1. UK-Biobank. UK Biobank Data Showcase
    1. Ulrich CM, Himbert C, Holowatyj AN, Hursting SD. Energy balance and gastrointestinal cancer: risk, interventions, outcomes and mechanisms. Nat. Rev. Gastroenterol. Hepatol. 2018;15:683–698. doi: 10.1038/s41575-018-0053-2.
    1. Hojman P, Gehl J, Christensen JF, Pedersen BK. Molecular mechanisms linking exercise to cancer prevention and treatment. Cell Metab. 2018;27:10–21. doi: 10.1016/j.cmet.2017.09.015.
    1. Bowers, L. W., Rossi, E. L., O’Flanagan, C. H., deGraffenried, L. A. & Hursting, S. D. The role of the insulin/igf system in cancer: lessons learned from clinical trials and the energy balance-cancer link. Frontiers in Endocrinology6, 10.3389/fendo.2015.00077 (2015).
    1. Pollak M. Insulin and insulin-like growth factor signalling in neoplasia. Nat. Rev. Cancer. 2008;8:915. doi: 10.1038/nrc2536.
    1. Shu X, et al. Associations of obesity and circulating insulin and glucose with breast cancer risk: a Mendelian randomization analysis. Int. J. Epidemiol. 2018;48:795–806. doi: 10.1093/ije/dyy201.
    1. Murphy N, et al. A nested case–control study of metabolically defined body size phenotypes and risk of colorectal cancer in the European Prospective Investigation into Cancer and Nutrition (EPIC) PLoS Med. 2016;13:e1001988. doi: 10.1371/journal.pmed.1001988.
    1. The Endogenous H, Breast Cancer Collaborative G. Insulin-like growth factor 1 (IGF1), IGF binding protein 3 (IGFBP3), and breast cancer risk: pooled individual data analysis of 17 prospective studies. Lancet Oncol. 2010;11:530–542. doi: 10.1016/S1470-2045(10)70095-4.
    1. McTiernan A, et al. Effect of exercise on serum estrogens in postmenopausal women: a 12-month randomized clinical trial. Cancer Res. 2004;64:2923–2928. doi: 10.1158/0008-5472.CAN-03-3393.
    1. Liedtke S, et al. Physical activity and endogenous sex hormones in postmenopausal women: to what extent are observed associations confounded or modified by BMI? Cancer Causes Control. 2011;22:81–89. doi: 10.1007/s10552-010-9677-4.
    1. Bertone-Johnson ER, Tworoger SS, Hankinson SE. Recreational physical activity and steroid hormone levels in postmenopausal women. Am. J. Epidemiol. 2009;170:1095–1104. doi: 10.1093/aje/kwp254.
    1. Endogenous Hormones and Breast Cancer Collaborative Group. Sex hormones and risk of breast cancer in premenopausal women: a collaborative reanalysis of individual participant data from seven prospective studies. Lancet Oncol. 2013;14:1009–1019. doi: 10.1016/S1470-2045(13)70301-2.
    1. The Endogenous Hormones Breast Cancer Collaborative Group. Endogenous sex hormones and breast cancer in postmenopausal women: reanalysis of nine prospective studies. JNCI: J. Natl Cancer Inst. 2002;94:606–616. doi: 10.1093/jnci/94.8.606.
    1. Friedenreich CM, Neilson HK, Lynch BM. State of the epidemiological evidence on physical activity and cancer prevention. Eur. J. Cancer. 2010;46:2593–2604. doi: 10.1016/j.ejca.2010.07.028.
    1. Zhang Xiaojie, Ashcraft Kathleen A., Betof Warner Allison, Nair Smita K., Dewhirst Mark W. Can Exercise-Induced Modulation of the Tumor Physiologic Microenvironment Improve Antitumor Immunity? Cancer Research. 2019;79(10):2447–2456. doi: 10.1158/0008-5472.CAN-18-2468.
    1. McTiernan A. Mechanisms linking physical activity with cancer. Nat. Rev. Cancer. 2008;8:205–211. doi: 10.1038/nrc2325.
    1. Woods JA, Vieira VJ, Keylock KT. Exercise, inflammation, and innate immunity. Neurologic Clin. 2006;24:585–599. doi: 10.1016/j.ncl.2006.03.008.
    1. Helmink BA, Khan MAW, Hermann A, Gopalakrishnan V, Wargo JA. The microbiome, cancer, and cancer therapy. Nat. Med. 2019;25:377–388. doi: 10.1038/s41591-019-0377-7.
    1. Fernandez DM, Clemente JC, Giannarelli C. Physical activity, immune system, and the microbiome in cardiovascular disease. Front Physiol. 2018;9:763–763. doi: 10.3389/fphys.2018.00763.
    1. Allen JM, et al. Exercise alters gut microbiota composition and function in lean and obese humans. Med. Sci. sports Exerc. 2018;50:747–757. doi: 10.1249/MSS.0000000000001495.
    1. Choi KW, et al. Assessment of bidirectional relationships between physical activity and depression among adults: a 2-sample Mendelian randomization study. JAMA. Psychiatry. 2019;76:399–408.
    1. Michailidou K, et al. Large-scale genotyping identifies 41 new loci associated with breast cancer risk. Nat. Genet. 2013;45:353. doi: 10.1038/ng.2563.
    1. Brion M-JA, Shakhbazov K, Visscher PM. Calculating statistical power in Mendelian randomization studies. Int. J. Epidemiol. 2013;42:1497–1501. doi: 10.1093/ije/dyt179.
    1. Higgins JPT, Thompson SG, Deeks JJ, Altman DG. Measuring inconsistency in meta-analyses. BMJ. 2003;327:557–560. doi: 10.1136/bmj.327.7414.557.
    1. 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;40:304–314. doi: 10.1002/gepi.21965.
    1. Burgess S, Thompson SG, Collaboration CCG. Avoiding bias from weak instruments in Mendelian randomization studies. Int. J. Epidemiol. 2011;40:755–764. doi: 10.1093/ije/dyr036.
    1. Shim H, et al. A multivariate genome-wide association analysis of 10 LDL subfractions, and their response to statin treatment, in 1868 caucasians. PLoS ONE. 2015;10:e0120758. doi: 10.1371/journal.pone.0120758.
    1. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B (Methodol.) 1995;57:289–300.
    1. Bowden Jack, Del Greco M Fabiola, Minelli Cosetta, Davey Smith George, Sheehan Nuala, Thompson John. A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Statistics in Medicine. 2017;36(11):1783–1802. doi: 10.1002/sim.7221.
    1. Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. Int. J. Epidemiol. 2015;44:512–525. doi: 10.1093/ije/dyv080.
    1. Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur. J. Epidemiol. 2017;32:377–389. doi: 10.1007/s10654-017-0255-x.
    1. 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;50:693–698. doi: 10.1038/s41588-018-0099-7.
    1. Burgess S, Thompson SG. Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects. Am. J. Epidemiol. 2015;181:251–260. doi: 10.1093/aje/kwu283.
    1. Locke AE, et al. Genetic studies of body mass index yield new insights for obesity biology. Nature. 2015;518:197–206. doi: 10.1038/nature14177.
    1. Yavorska OO, Burgess S. MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data. Int. J. Epidemiol. 2017;46:1734–1739. doi: 10.1093/ije/dyx034.
    1. Hemani G, et al. The MR-Base platform supports systematic causal inference across the human phenome. eLife. 2018;7:e34408. doi: 10.7554/eLife.34408.

Source: PubMed

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