Calcified Tissue International

, Volume 101, Issue 5, pp 489–500 | Cite as

Enhanced Identification of Potential Pleiotropic Genetic Variants for Bone Mineral Density and Breast Cancer

  • Cheng Peng
  • Hui-Ling Lou
  • Feng Liu
  • Jie Shen
  • Xu Lin
  • Chun-Ping Zeng
  • Ji-Rong Long
  • Kuan-Jui Su
  • Lan Zhang
  • Jonathan Greenbaum
  • Wei-Feng Deng
  • Yu-Mei Li
  • Hong-Wen Deng
Original Research


Epidemiological and clinical evidences have shown that bone mineral density (BMD) has a close relationship with breast cancer (BC). They might potentially have a shared genetic basis. By incorporating information about these pleiotropic effects, we may be able to explore more of the traits’ total heritability. We applied a recently developed conditional false discovery rate (cFDR) method to the summary statistics from two independent GWASs to identify the potential pleiotropic genetic variants for BMD and BC. By jointly analyzing two large independent GWASs of BMD and BC, we found strong pleiotropic enrichment between them and identified 102 single-nucleotide polymorphisms (SNPs) in BMD and 192 SNPs in BC with cFDR < 0.05, including 230 SNPs that might have been overlooked by the standard GWAS analysis. cFDR-significant genes were enriched in GO terms and KEGG pathways which were crucial to bone metabolism and/or BC pathology (adjP < 0.05). Some cFDR-significant genes were partially validated in the gene expressional validation assay. Strong interactions were found between proteins produced by cFDR-significant genes in the context of biological mechanism of bone metabolism and/or BC etiology. Totally, we identified 7 pleiotropic SNPs that were associated with both BMD and BC (conjunction cFDR < 0.05); CCDC170, ESR1, RANKL, CPED1, and MEOX1 might play important roles in the pleiotropy of BMD and BC. Our study highlighted the significant pleiotropy between BMD and BC and shed novel insight into trait-specific as well as the potentially shared genetic architecture for both BMD and BC.


Bone mineral density (BMD) Breast cancer Pleiotropy Genome wide association study (GWAS) 



Hong-Wen Deng was partially supported by Grants from the National Institutes of Health [R01AR057049, R01AR059781, D43TW009107, P20 GM109036, R01MH107354, R01MH104680, R01GM109068], the Edward G. Schlieder Endowment fund to Tulane University. The GWAS datasets for BMD were obtained from GEFOS at We acknowledge GEFOS-seq Consortium, AOGC Consortium, and The UK10 K Consortium for their GWAS summary statistics posted online, and we also acknowledge Wei Zheng for providing the BC GWAS data. Chun-Ping Zeng was partially supported by Medical Research Fund of Guangdong Province, Guangdong, China (A2017575). Cheng Peng was partially supported by Guangzhou Planned Project of Science and Technology, Guangzhou, China [201704020105] and Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People’s Hospital during this study.

Author’s Contribution

Hong-Wen Deng conceived and initiated the development of this study, is responsible for general development and design of the study, and contributed to critical revisions and finalization of the manuscript, and he is guarantor. Cheng Peng contributed to the acquisition and analysis of the data and drafted the manuscript. Xu Lin, Chun-Ping Zeng, and Kuan-Jui Su contributed to data analysis. Ji-Rong Long contributed to the data acquisition. Lan Zhang, Jonathan Greenbaum, Yu-Mei Li, and Wei-Feng Deng contributed to critical revisions. Feng Liu, Hui-Ling Lou, and Jie Shen contributed to the general study design and development. All authors have given approval to the final version of the manuscript. All authors agree to be accountable for the work and ensure that any questions relating to the accuracy and integrity of the paper are investigated and properly resolved.

Compliance with Ethical Standards

Conflict of interest

Cheng Peng, Hui-Ling Lou, Feng Liu, Jie Shen, Xu Lin, Chun-Ping Zeng, Ji-Rong Long, Kuan-Jui Su, Lan Zhang, Jonathan Greenbaum, Wei-Feng Deng, Yu-Mei Li, and Hong-Wen Deng declare that they have no conflicts of interest.

Human and Animal Rights and Informed Consent

No human participants or animals were involved in this empirical study. We only analyzed the existing data published on public websites.

Supplementary material

223_2017_308_MOESM1_ESM.docx (2.9 mb)
Supplementary material 1 (DOCX 2929 kb)


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Copyright information

© Springer Science+Business Media, LLC 2017

Authors and Affiliations

  • Cheng Peng
    • 1
  • Hui-Ling Lou
    • 1
  • Feng Liu
    • 1
  • Jie Shen
    • 2
  • Xu Lin
    • 2
  • Chun-Ping Zeng
    • 3
  • Ji-Rong Long
    • 4
  • Kuan-Jui Su
    • 5
  • Lan Zhang
    • 5
  • Jonathan Greenbaum
    • 5
  • Wei-Feng Deng
    • 6
  • Yu-Mei Li
    • 7
  • Hong-Wen Deng
    • 2
    • 5
  1. 1.Department of Geriatrics, National Key Clinical Specialty, Guangzhou First People’s HospitalGuangzhou Medical UniversityGuangzhouPeople’s Republic of China
  2. 2.Department of Endocrinology and MetabolismThe Third Affiliated Hospital of Southern Medical UniversityGuangzhouPeople’s Republic of China
  3. 3.Department of Endocrinology and MetabolismAffiliated Nanhai Hospital of Southern Medical UniversityGuangzhouPeople’s Republic of China
  4. 4.Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer CenterVanderbilt University School of MedicineNashvilleUSA
  5. 5.Department of Global Statistics and Data Science, School of Public Health and Tropical Medicine, Center for Bioinformatics and GenomicsTulane UniversityNew OrleansUSA
  6. 6.Hunan University of MedicineHuaihuaPeople’s Republic of China
  7. 7.School of Mathematics and Computational ScienceHuaihua UniversityHuaihuaPeople’s Republic of China

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