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.

  • Article
  • Published:

Epidemiology

Assessing the role of cortisol in cancer: a wide-ranged Mendelian randomisation study

British Journal of Cancer volume 125, pages 1025–1029 (2021)Cite this article

Subjects

Abstract

Background

Cortisol’s immunosuppressive, obesogenic, and hyperglycaemic effects suggest that it may play a role in cancer development. However, whether cortisol increases cancer risk is not known. We investigated the potential causal association between plasma cortisol and risk of overall and common site-specific cancers using Mendelian randomisation.

Methods

Three genetic variants associated with morning plasma cortisol levels at the genome-wide significance level (P < 5 × 10−8) in the Cortisol Network consortium were used as genetic instruments. Summary-level genome-wide association study data for the cancer outcomes were obtained from large-scale cancer consortia, the UK Biobank, and the FinnGen consortium. Two-sample Mendelian randomisation analyses were performed using the fixed-effects inverse-variance weighted method. Estimates across data sources were combined using meta-analysis.

Results

A standard deviation increase in genetically predicted plasma cortisol was associated with increased risk of endometrial cancer (odds ratio 1.50, 95% confidence interval 1.13–1.99; P = 0.005). There was no significant association between genetically predicted plasma cortisol and risk of other common site-specific cancers, including breast, ovarian, prostate, colorectal, lung, or malignant skin cancer, or overall cancer.

Conclusions

These results indicate that elevated plasma cortisol levels may increase the risk of endometrial cancer but not other cancers. The mechanism by which this occurs remains to be investigated.

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

Fig. 1: A directed acyclic graph representing the MR framework, with the present MR study as an example.
Fig. 2: Associations of genetically predicted plasma cortisol with risk of overall and common site-specific cancers.

Similar content being viewed by others

Data availability

All data used in this study are publicly available summary-level data, with the relevant studies cited.

References

  1. Katsu Y, Iguchi T. Cortisol. In: Takei Y, Ando H & Tsutsui K, editors. Handbook of hormones. Oxford, UK: Academic Press; 2016.

  2. Antonova L, Aronson K, Mueller CR. Stress and breast cancer: from epidemiology to molecular biology. Breast Cancer Res. 2011;13:208.

    Article  Google Scholar 

  3. Coutinho AE, Chapman KE. The anti-inflammatory and immunosuppressive effects of glucocorticoids, recent developments and mechanistic insights. Mol Cell Endocrinol. 2011;335:2–13.

    Article  CAS  Google Scholar 

  4. Avgerinos KI, Spyrou N, Mantzoros CS, Dalamaga M. Obesity and cancer risk: emerging biological mechanisms and perspectives. Metabolism. 2019;92:121–35.

    Article  CAS  Google Scholar 

  5. van der Valk ES, Savas M, van Rossum EFC. Stress and obesity: are there more susceptible individuals? Curr Obes Rep. 2018;7:193–203.

    Article  Google Scholar 

  6. Nead KT, Sharp SJ, Thompson DJ, Painter JN, Savage DB, Semple RK, et al. Evidence of a causal association between insulinemia and endometrial cancer: a Mendelian randomization analysis. J Natl Cancer Inst. 2015;107:djv178.

    Article  Google Scholar 

  7. Kruk J, Aboul-Enein BH, Bernstein J, Gronostaj M. Psychological stress and cellular aging in cancer: a meta-analysis. Oxid Med Cell Longev. 2019;2019:1270397.

    Article  Google Scholar 

  8. Shin KJ, Lee YJ, Yang YR, Park S, Suh PG, Follo MY, et al. Molecular mechanisms underlying psychological stress and cancer. Curr Pharm Des. 2016;22:2389–402.

    Article  CAS  Google Scholar 

  9. Yang T, Qiao Y, Xiang S, Li W, Gan Y, Chen Y. Work stress and the risk of cancer: a meta-analysis of observational studies. Int J Cancer. 2019;144:2390–400.

    Article  CAS  Google Scholar 

  10. Bahri N, Fathi Najafi T, Homaei Shandiz F, Tohidinik HR, Khajavi A. The relation between stressful life events and breast cancer: a systematic review and meta-analysis of cohort studies. Breast Cancer Res Treat. 2019;176:53–61.

    Article  Google Scholar 

  11. Bolton JL, Hayward C, Direk N, Lewis JG, Hammond GL, Hill LA, et al. Genome wide association identifies common variants at the SERPINA6/SERPINA1 locus influencing plasma cortisol and corticosteroid binding globulin. PLoS Genet. 2014;10:e1004474.

    Article  Google Scholar 

  12. Broad Institute of MIT and Harvard. The Genotype-Tissue Expression (GTEx) portal. 2021. https://gtexportal.org/home/. Accessed 12 Feb 2021.

  13. Michailidou K, Lindstrom S, Dennis J, Beesley J, Hui S, Kar S, et al. Association analysis identifies 65 new breast cancer risk loci. Nature. 2017;551:92–4.

    Article  Google Scholar 

  14. O’Mara TA, Glubb DM, Amant F, Annibali D, Ashton K, Attia J, et al. Identification of nine new susceptibility loci for endometrial cancer. Nat Commun. 2018;9:3166.

    Article  Google Scholar 

  15. Phelan CM, Kuchenbaecker KB, Tyrer JP, Kar SP, Lawrenson K, Winham SJ, et al. Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer. Nat Genet. 2017;49:680–91.

    Article  CAS  Google Scholar 

  16. Schumacher FR, Al Olama AA, Berndt SI, Benlloch S, Ahmed M, Saunders EJ, et al. Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci. Nat Genet. 2018;50:928–36.

    Article  CAS  Google Scholar 

  17. Wang Y, McKay JD, Rafnar T, Wang Z, Timofeeva MN, Broderick P, et al. Rare variants of large effect in BRCA2 and CHEK2 affect risk of lung cancer. Nat Genet. 2014;46:736–41.

    Article  CAS  Google Scholar 

  18. FinnGen consortium. FinnGen Documentation of R4 release, 2020. https://finngen.gitbook.io/documentation/. Accessed 10 Dec 2020.

  19. Fry A, Littlejohns TJ, Sudlow C, Doherty N, Adamska L, Sprosen T, et al. Comparison of sociodemographic and health-related characteristics of UK Biobank participants with those of the general population. Am J Epidemiol. 2017;186:1026–34.

    Article  Google Scholar 

  20. Astle WJ, Elding H, Jiang T, Allen D, Ruklisa D, Mann AL, et al. The allelic landscape of human blood cell trait variation and links to common complex disease. Cell. 2016;167:1415.e19–29.e19.

    Article  Google Scholar 

  21. Marchini J, Howie B. Genotype imputation for genome-wide association studies. Nat Rev Genet. 2010;11:499–511.

    Article  CAS  Google Scholar 

  22. Brion MJ, Shakhbazov K, Visscher PM. Calculating statistical power in Mendelian randomization studies. Int J Epidemiol. 2013;42:1497–501.

    Article  Google Scholar 

  23. Yavorska OO, Burgess S. MendelianRandomization: an R package for performing Mendelian randomization analyses using summarized data. Int J Epidemiol. 2017;46:1734–9.

    Article  Google Scholar 

  24. Pulit SL, Stoneman C, Morris AP, Wood AR, Glastonbury CA, Tyrrell J, et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum Mol Genet. 2019;28:166–74.

    Article  CAS  Google Scholar 

  25. 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.

    Article  CAS  Google Scholar 

  26. Neale Laboratory. GWAS round 2 of the UK Biobank. Results shared 1st August 2018. 2018. http://www.nealelab.is/uk-biobank. Accessed 5 May 2021.

  27. Rodriguez AC, Blanchard Z, Maurer KA, Gertz J. Estrogen signaling in endometrial cancer: a key oncogenic pathway with several open questions. Horm Cancer. 2019;10:51–63.

    Article  CAS  Google Scholar 

  28. Ruth KS, Day FR, Tyrrell J, Thompson DJ, Wood AR, Mahajan A, et al. Using human genetics to understand the disease impacts of testosterone in men and women. Nat Med. 2020;26:252–8.

    Article  CAS  Google Scholar 

  29. Dupuis CC, Storr HL, Perry LA, Ho JT, Ahmed L, Ong KK, et al. Abnormal puberty in paediatric Cushing’s disease: relationship with adrenal androgen, sex hormone binding globulin and gonadotrophin concentrations. Clin Endocrinol. 2007;66:838–43.

    Article  CAS  Google Scholar 

  30. Woods NF, Mitchell ES, Smith-Dijulio K. Cortisol levels during the menopausal transition and early postmenopause: observations from the Seattle Midlife Women’s Health Study. Menopause. 2009;16:708–18.

    Article  Google Scholar 

  31. Grant SD, Pavlatos FC, Forsham PH. Effects of estrogen therapy on cortisol metabolism. J Clin Endocrinol Metab. 1965;25:1057–66.

    Article  CAS  Google Scholar 

  32. Edwards KM, Mills PJ. Effects of estrogen versus estrogen and progesterone on cortisol and interleukin-6. Maturitas. 2008;61:330–3.

    Article  CAS  Google Scholar 

  33. Vahrenkamp JM, Yang C-H, Rodriguez AC, Jarboe EA, Janat-Amsbury MM. Clinical and genomic crosstalk between glucocorticoid receptor and estrogen receptor α in endometrial cancer. Cell Rep. 2018;22:P2995–3005.

    Article  Google Scholar 

  34. Byrne, FL, Martin, AR, Kosasih, M, Caruana, BT, Farrell, R. The role of hyperglycemia in endometrial cancer pathogenesis. Cancers. 2020;12:1191.

Download references

Acknowledgements

The authors would like to thank the investigators of the Breast Cancer Association Consortium (BCAC), Endometrial Cancer Association Consortium (ECAC), Genetic Investigation of ANthropometric Traits (GIANT) consortium, International Lung Cancer Consortium (ILCCO), Meta-Analyses of Glucose and Insulin-related traits consortium (MAGIC), Ovarian Cancer Association Consortium (OCAC), Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium, and the FinnGen consortium for sharing summary-level GWAS data. Analyses of UK Biobank data were performed under application 29202.

Funding

SCL acknowledges research support from the Swedish Research Council (Vetenskapsrådet, 2016-01042 and 2019-00977), the Swedish Research Council for Health, Working Life and Welfare (Forte, 2018-00123), and the Swedish Heart-Lung Foundation (Hjärt-Lungfonden, 20190247). SK is supported by United Kingdom Research and Innovation Future Leaders Fellowship (MR/T043202/1). SB is supported by Sir Henry Dale Fellowship jointly funded by the Wellcome Trust and the Royal Society (204623/Z/16/Z). During the conduction of this study, EA was supported by the EU/EFPIA Innovative Medicines Initiative Joint Undertaking BigData@Heart grant no. 116074 and is currently funded by the British Heart Foundation Programme Grant RG/18/13/33946. This work was supported by core funding from: the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG/13/13/30194; RG/18/13/33946), and the NIHR Cambridge Biomedical Research Centre (BRC-1215-20014)*. This work was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation, and Wellcome. *The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care.

Author information

Authors and Affiliations

  1. Unit of Cardiovascular and Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden

    Susanna C. Larsson

  2. Unit of Medical Epidemiology, Department of Surgical Sciences, Uppsala University, Uppsala, Sweden

    Susanna C. Larsson

  3. BHF Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK

    Wei-Hsuan Lee, Stephen Burgess & Elias Allara

  4. MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK

    Siddhartha Kar

  5. MRC Biostatistics Unit, University of Cambridge, Cambridge, UK

    Stephen Burgess

Authors
  1. Susanna C. Larsson
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wei-Hsuan Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Siddhartha Kar
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Stephen Burgess
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Elias Allara
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

SCL had full access to the data. SCL, SB, and EA designed the study. SCL performed the statistical analyses and created the figure. SCL, W-HL, and EA drafted the manuscript. SCL, W-HL, SK, SB, and EA interpreted the data and edited the manuscript. All authors have given final approval of the version to be published.

Corresponding author

Correspondence to Susanna C. Larsson.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

Ethics approval and consent to participate had been obtained. The present analyses were approved by the Swedish Ethical Review Authority. The study was performed in accordance with the Declaration of Helsinki.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Larsson, S.C., Lee, WH., Kar, S. et al. Assessing the role of cortisol in cancer: a wide-ranged Mendelian randomisation study. Br J Cancer 125, 1025–1029 (2021). https://doi.org/10.1038/s41416-021-01505-8

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41416-021-01505-8

This article is cited by

Search

Advanced search

Quick links