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Breast cancer risk in patients with polycystic ovary syndrome: a Mendelian randomization analysis

  • Epidemiology
  • Published:
Breast Cancer Research and Treatment Aims and scope Submit manuscript

Abstract

Purpose

The association between polycystic ovary syndrome (PCOS) and breast cancer remains inconclusive. Conventional observational studies are susceptible to inverse causality and potential confounders. With a Mendelian randomization (MR) approach, we aimed to investigate the causal relationship between genetically predicted PCOS and breast cancer risk.

Methods

Our study included 11 PCOS-associated single nucleotide polymorphisms as instrumental variables identified by the latest genome-wide association study. Individual-level genetic summary data of participants were obtained from the Breast Cancer Association Consortium, with a total of 122,977 cases and 105,974 controls. The inverse-variance weighted method was applied to estimate the causality between genetically predicted PCOS and breast cancer risk. To further evaluate the pleiotropy, the weighted median and MR-Egger regression methods were implemented as well.

Results

Our study demonstrated that genetically predicted PCOS was causally associated with an increased risk of overall breast cancer (odds ratio (OR) = 1.07; 95% confidence interval (CI) 1.02–1.12, p = 0.005). The subgroup analyses according to immunohistochemical type further illustrated that genetically predicted PCOS was associated with an increased risk of estrogen receptor (ER)-positive breast cancer (OR = 1.09; 95% CI 1.03–1.15, p = 0.002), while no causality was observed for ER-negative breast cancer (OR = 1.02; 95% CI 0.96–1.09, p = 0.463). In addition, no pleiotropy was found in our study.

Conclusions

Our findings indicated that PCOS was likely to be a causal factor in the development of ER-positive breast cancer, providing a better understanding for the etiology of breast cancer and the prevention of breast cancer.

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Abbreviations

AR:

Androgen receptor

BCAC:

Breast Cancer Association Consortium

GIANT:

Genetic Investigation of Anthropometric Traits

MRC-IEU:

Medical Research Council Integrative Epidemiology Unit

CIs:

Confidence intervals

BMI:

Body mass index

ER:

Estrogen receptor

GWASs:

Genome-wide association studies

IVs:

Instrumental variables

IVF:

In vitro fertilization

IVW:

Inverse-variance weighted

LD:

Linkage disequilibrium

NIH:

National Institutes of Health

MR:

Mendelian randomization

OCs:

Oral contraceptives

ORs:

Odds ratios

PCOS:

Polycystic ovary syndrome

SNPs:

Single nucleotide polymorphisms

References

  1. Sirmans SM, Pate KA (2013) Epidemiology, diagnosis, and management of polycystic ovary syndrome. Clin Epidemiol. https://doi.org/10.2147/CLEP.S37559

    Article  PubMed  PubMed Central  Google Scholar 

  2. Azziz R et al (2016) Polycystic ovary syndrome. Nat Rev 2:16057

    Google Scholar 

  3. Christ JP, Gunning MN, Fauser BCJM (2017) Implications of the 2014 androgen excess and polycystic ovary syndrome society guidelines on polycystic ovarian morphology for polycystic ovary syndrome diagnosis. Reprod Biomed 35(4):480–483

    Article  CAS  Google Scholar 

  4. Lansdown AJ et al (2019) Regional cerebral activation accompanies sympathoexcitation in women with polycystic ovary syndrome. J Clin Endocrinol Metab 104(9):3614–3623

    Article  Google Scholar 

  5. Shafiee MN et al (2013) Reviewing the molecular mechanisms which increase endometrial cancer (EC) risk in women with polycystic ovarian syndrome (PCOS): time for paradigm shift? Gynecol Oncol 131(2):489–492

    Article  CAS  Google Scholar 

  6. Flint MS et al (2007) Induction of DNA damage, alteration of DNA repair and transcriptional activation by stress hormones. Psychoneuroendocrinology 32(5):470–479

    Article  CAS  Google Scholar 

  7. Wild S et al (2000) Long-term consequences of polycystic ovary syndrome: results of a 31 year follow-up study. Hum Fertil 3(2):101–105

    Article  Google Scholar 

  8. Shen CC et al (2015) A nationwide population-based retrospective cohort study of the risk of uterine, ovarian and breast cancer in women with polycystic ovary syndrome. Oncologist 20(1):45–49

    Article  Google Scholar 

  9. Baron JA et al (2001) Metabolic disorders and breast cancer risk (United States). Cancer Causes Control 12(10):875–880

    Article  CAS  Google Scholar 

  10. Kim J et al (2016) Polycystic ovarian syndrome (PCOS), related symptoms/sequelae, and breast cancer risk in a population-based case-control study. Cancer Causes Control 27(3):403–414

    Article  Google Scholar 

  11. Yin W et al (2019) Association between polycystic ovary syndrome and cancer risk. JAMA Oncology 5(1):106–107

    Article  Google Scholar 

  12. Anderson KE et al (1997) Association of Stein-Leventhal syndrome with the incidence of postmenopausal breast carcinoma in a large prospective study of women in Iowa. Cancer 79(3):494–499

    Article  CAS  Google Scholar 

  13. Gottschau M et al (2015) Risk of cancer among women with polycystic ovary syndrome: a Danish cohort study. Gynecol Oncol 136(1):99–103

    Article  Google Scholar 

  14. Brinton LA et al (2010) Cancer risk among infertile women with androgen excess or menstrual disorders (including polycystic ovary syndrome). Fertil Steril 94(5):1787–1792

    Article  Google Scholar 

  15. Ding DC et al (2018) Association between polycystic ovarian syndrome and endometrial, ovarian, and breast cancer: a population-based cohort study in Taiwan. Medicine (Baltimore) 97(39):e12608

    Article  Google Scholar 

  16. Talamini R et al (1997) Frequency of poly cystic ovary syndrome in patients with premenopausal breast cancer. Br J Cancer 75(11):1699–1703

    Article  CAS  Google Scholar 

  17. Ghasemi N, Mortazavizadeh MR, Khorasani Gerdekoohi A (2010) Frequency of poly cystic ovary syndrome in patients with premenopausal breast cancer. Int J Reprod Biomed 8(2):86

    Google Scholar 

  18. Shobeiri F, Jenabi E (2016) The association between polycystic ovary syndrome and breast cancer: a meta-analysis. Obstet Gynecol Sci 59(5):367–372

    Article  Google Scholar 

  19. Carvalho MJ et al (2019) Controversial association between polycystic ovary syndrome and breast cancer. Eur J Obstet Gynecol Reprod Biol 243:125–132

    Article  CAS  Google Scholar 

  20. Key TJ et al (2011) Circulating sex hormones and breast cancer risk factors in postmenopausal women: reanalysis of 13 studies. Br J Cancer 105(5):709–722

    Article  CAS  Google Scholar 

  21. Lawlor DA et al (2008) Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med 27(8):1133–1163

    Article  Google Scholar 

  22. Shi Y et al (2012) Genome-wide association study identifies eight new risk loci for polycystic ovary syndrome. Nat Genet 44(9):1020–1025

    Article  CAS  Google Scholar 

  23. Chen ZJ et al (2011) Genome-wide association study identifies susceptibility loci for polycystic ovary syndrome on chromosome 2p16.3, 2p21 and 9q33.3. Nat Genet 43(1):55–59

    Article  Google Scholar 

  24. 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):543–552

    Article  Google Scholar 

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

    Article  Google Scholar 

  26. Harris HR et al (2019) Association between genetically predicted polycystic ovary syndrome and ovarian cancer: a Mendelian randomization study. Int J Epidemiol 48(3):822–830

    Article  Google Scholar 

  27. Day F et al (2018) Large-scale genome-wide meta-analysis of polycystic ovary syndrome suggests shared genetic architecture for different diagnosis criteria. PLoS Genet 14(12):e1007813

    Article  Google Scholar 

  28. Hemani G et al (2018) The MR-Base platform supports systematic causal inference across the human phenome. eLife 7:e34408

    Article  Google Scholar 

  29. About BCAC – The Breast Cancer Association Consortium. Centre for Cancer Genetic Epidemiology> https://bcac.ccge.medschl.cam.ac.uk/. Accessed 28 Mar 2020

  30. VanderWeele TJ et al (2014) Methodological challenges in mendelian randomization. Epidemiology 25(3):427–435

    Article  Google Scholar 

  31. Bowden J et al (2017) A framework for the investigation of pleiotropy in two-sample summary data Mendelian randomization. Stat Med 36(11):1783–1802

    Article  Google Scholar 

  32. Dimitrakakis C, Bondy C (2009) Androgens and the breast. Breast Cancer Res 11(5):212

    Article  Google Scholar 

  33. Berrino F et al (2005) Serum testosterone levels and breast cancer recurrence. Int J Cancer 113(3):499–502

    Article  CAS  Google Scholar 

  34. Schmitt M et al (2001) Dehydroepiandrosterone stimulates proliferation and gene expression in MCF-7 cells after conversion to estradiol. Mol Cell Endocrinol 173:1–2

    Article  CAS  Google Scholar 

  35. Ortmann J et al (2002) Testosterone and 5 alpha-dihydrotestosterone inhibit in vitro growth of human breast cancer cell lines. Gynecol Endocrinol 16(2):113–120

    Article  CAS  Google Scholar 

  36. Farhat GN et al (2011) Sex hormone levels and risks of estrogen receptor-negative and estrogen receptor-positive breast cancers. J Natl Cancer Inst 103(7):562–570

    Article  CAS  Google Scholar 

  37. Cummings SR et al (2005) Sex hormones, risk factors, and risk of estrogen receptor-positive breast cancer in older women: a long-term prospective study. Cancer Epidemiol Biomark Prev 14(5):1047–1051

    Article  CAS  Google Scholar 

  38. Haendler B, Cleve A (2012) Recent developments in antiandrogens and selective handrogen receptor modulators. Mol Cell Endocrinol 352(1–2):79–91

    Article  CAS  Google Scholar 

  39. Lin H-Y et al (2009) Androgen-induced human breast cancer cell proliferation is mediated by discrete mechanisms in estrogen receptor-alpha-positive and -negative breast cancer cells. J Steroid Biochem Mol Biol 113(3–5):182–188

    Article  CAS  Google Scholar 

  40. Clark NM et al (2014) Prevalence of polycystic ovary syndrome phenotypes using updated criteria for polycystic ovarian morphology: an assessment of over 100 consecutive women self-reporting features of polycystic ovary syndrome. Reprod Sci 21(8):1034–1043

    Article  Google Scholar 

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Acknowledgements

The authors acknowledge the efforts of the consortia in providing high-quality GWAS resources for researchers. Data and material are available from corresponding GWAS consortium. The authors also thank Ms. Lindsey Hamblin for helping to edit the manuscript.

Funding

This study was supported by the National Key R&D Program of China [2016YFC0905400]; China National Science Foundation [81871893, 81501996]; Key Project of Guangzhou Scientific Research Project [201804020030]; High-level university construction project of Guangzhou Medical University [20182737, 201721007, 201715907, 2017160107]; IVATS National key R&D Program [2017YFC0907903, 2017YFC0112704]; and Application, industrialization, and generalization of surgical incision protector [2011B090400589].

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Author notes

  1. Yaokai Wen, Xiangrong Wu, and Haoxin Peng have contributed equally to this work.

Authors and Affiliations

  1. Department of Thoracic Surgery and Oncology, The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, 510120, China

    Yaokai Wen, Xiangrong Wu, Haoxin Peng, Caichen Li, Yu Jiang, Zixuan Su, Hengrui Liang, Jun Liu, Jianxing He & Wenhua Liang

  2. Nanshan School, Guangzhou Medical University, Jingxiu Road, Panyu District, Guangzhou, 511436, China

    Yaokai Wen, Xiangrong Wu, Haoxin Peng, Yu Jiang & Zixuan Su

Authors
  1. Yaokai Wen
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Correspondence to Jianxing He or Wenhua Liang.

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Wen, Y., Wu, X., Peng, H. et al. Breast cancer risk in patients with polycystic ovary syndrome: a Mendelian randomization analysis. Breast Cancer Res Treat 185, 799–806 (2021). https://doi.org/10.1007/s10549-020-05973-z

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  • DOI: https://doi.org/10.1007/s10549-020-05973-z

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