Oops, you're using an old version of your browser so some of the features on this page may not be displaying properly.

MINIMAL Requirements: Google Chrome 24+Mozilla Firefox 20+Internet Explorer 11Opera 15–18Apple Safari 7SeaMonkey 2.15-2.23

e-Poster Display Session

11P - Genetically predicted bipolar disorder is causally associated with increased risk of breast cancer: A Mendelian randomization analysis

Date

22 Nov 2020

Session

e-Poster Display Session

Topics

Tumour Site

Breast Cancer

Presenters

Haoxin Peng

Citation

Annals of Oncology (2020) 31 (suppl_6): S1241-S1254. 10.1016/annonc/annonc351

Authors

H. Peng, X. Wu, C. Li, W. Liang, J. He

Author affiliations

  • The First Affiliated Hospital Of Guangzhou Medical University, Guangzhou, China., Department of Thoracic Oncology and Surgery, China State Key Laboratory of Respiratory Disease & National Clinical Research Center for Respiratory Disease, 510000 - Guangzhou/CN

Resources

Login to get immediate access to this content.

If you do not have an ESMO account, please create one for free.

Abstract 11P

Background

Epidemiologic findings suggested that bipolar disorder (BD) may be associated with increased risk of breast cancer. However, there are few studies that comprehensively evaluate their correlation and the causal effect remains unknown. With a Mendelian randomization (MR) approach, we were able to investigate the causal relationship between genetically predicted BD and breast cancer risk.

Methods

Utilizing 6 BD-related single nucleotide polymorphisms as instrumental variables identified by the latest genome-wide association studies, we investigated the correlation between genetically predicted BD and breast cancer risk using summary statistics from the Breast Cancer Association Consortium, with a total of 122 977 cases and 105 974 controls. Study-specific estimates were summarized using inverse-variance-weighted (IVW) method. To further evaluate the pleiotropy, the weighted median and the MR-Egger regression method were implemented. Subgroup analyses according to different immunohistochemical type of breast cancer were also conducted.

Results

MR analyses demonstrated that genetically predicted BD was causally associated with an increased risk of breast cancer (OR = 1.058; 95% CI 1.023-1.093, p < 0.001). When results were examined by immunohistochemical type, a strong association was observed between genetically predicted BD and estrogen receptor-positive (ER) breast cancer (OR = 1.048, 95%CI 1.008-1.090 p = 0.0177) rather than ER-negative breast cancer (OR = 1.026, 95%CI 0.975-1.081 p = 0.3231). Additionally, the results demonstrated the absence of the horizontal pleiotropy. Table: 11P

Mendelian randomization estimates of the associations between bipolar disorder and risk of breast cancer overall and immunohistochemical types

Outcome IVW method MR-Egger Weighted median method
OR (95% CI) P-value OR (95% CI) P-value OR (95% CI) P-value
Breast cancer overall 1.058 (1.023, 1.093) 0.0009 1.032 (0.969, 1.099) 0.3858 1.044 (1.006, 1.083) 0.0239
ER-positive breast cancer 1.048 (1.008, 1.090) 0.0177 1.004 (0.942, 1.070) 0.9118 1.030 (0.998, 1.074) 0.1622
ER-negative breast cancer 1.026 (0.975, 1.081) 0.3231 1.085 (0.986, 1.195) 0.1713 1.041 (0.978, 1.109) 0.2063

Conclusions

Our findings provide evidence for a causal relationship between genetically predicted BD and increased breast cancer risk, overall and among specific immunohistochemical type. Further studies are warranted to investigate the underlying mechanism.

Clinical trial identification

Editorial acknowledgement

Legal entity responsible for the study

Haoxin Peng.

Funding

China National Science Foundation (Grant No. 81871893); Key Project of Guangzhou Scientific Research Project (Grant No. 201804020030); Cultivation of Guangdong College Students' Scientific and Technological Innovation (“Climbing Program” Special Funds) (Grant No. pdjh2020a0480).

Disclosure

All authors have declared no conflicts of interest.

This site uses cookies. Some of these cookies are essential, while others help us improve your experience by providing insights into how the site is being used.

For more detailed information on the cookies we use, please check our Privacy Policy.

Customise settings
  • Necessary cookies enable core functionality. The website cannot function properly without these cookies, and you can only disable them by changing your browser preferences.