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The largest genome-wide association study for breast cancer in Taiwanese Han population

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

Abstract

Purpose

Breast cancer is a molecularly heterogeneous disease, and multiple genetic variants contribute to its development and prognosis. Most of previous genome-wide association studies (GWASs) and polygenic risk scores (PRSs) analyses focused on studying breast cancers of Caucasian populations, which may not be applicable to other population. Therefore, we conducted the largest breast cancer cohort of Taiwanese population to fill in the knowledge gap.

Methods

A total of 152,534 Participants recruited by China Medical University Hospital between 2003 and 2019 were filtered by several patient selection criteria and GWAS quality control steps, resulting in the inclusion of 2496 cases and 9984 controls for this study. We then conducted GWAS for all breast cancers and PRS analyses for all breast cancers and the four breast cancer subtypes, including luminal A, luminal B, basal-like, and HER2-enriched.

Results

The GWAS analyses identified 113 SNPs, 50 of which were novel. The PRS models for all breast cancers and the luminal A subtype showed positively correlated trends between the PRS and the risk of developing breast cancer. The odds ratios (95% confidence intervals) for the groups with the highest PRS in all breast cancers and the luminal A subtype were 5.33 (3.79–7.66) and 3.55 (2.13–6.14), respectively.

Conclusion

In summary, we explored the association of genetic variants with breast cancer in the largest Taiwanese cohort and developed two PRS models that can predict the risk of developing any breast cancer and the luminal A subtype in Taiwanese women.

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Data availability

The dataset supporting the conclusions of this article is available in the China Medical Hospital repository. Anyone who is interested in accessing the data must contact China Medical Hospital thorough the corresponding author Dr. Tsai.

Code availability

Codes for data preprocessing and analysis in this study are available online at https://github.com/ychsu2014/Taiwan_2496_breast_cancers for review.

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Acknowledgements

We appreciate the iHi Clinical Research and iHi Genomics Platform from the Big Data Center of China Medical University Hospital for the data exploration, administrative, and statistical analytic support.

Funding

This work was partly supported by National Science and Technology Council, Taiwan (MOST-106-2314-B-002-134-MY2, MOST-108-2314-B-002-103-MY2, and MOST-109-2314-B-002-151-MY3) and Population Health and Welfare Research Center from Featured Areas Research Center Program within the framework of the Higher Education Sprout Project by the Ministry of Education (MOE) in Taiwan (grant number NTU-112L9004).

Author information

Author notes

  1. Yu-Ching Hsu and Hung-Lin Chen contributed equally as the co-first authors.

Authors and Affiliations

  1. Bioinformatics Program, Taiwan International Graduate Program, National Taiwan University, Taipei, Taiwan

    Yu-Ching Hsu

  2. Bioinformatics Program, Institute of Statistical Science, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan

    Yu-Ching Hsu

  3. Institute of Health Data Analytics and Statistics, Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan

    Yu-Ching Hsu & Tzu-Pin Lu

  4. Big Data Center, China Medical University Hospital, Taichung, Taiwan

    Hung-Lin Chen, Chi-Fung Cheng, Pei-Shan Chen, Che-Chen Lin, Hsiu-Yin Chiang & Chin-Chi Kuo

  5. Center for Translational Genomic Research, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan

    Amrita Chattopadhyay

  6. Million-Person Precision Medicine Initiative, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan

    Ting-Yuan Liu

  7. Division of Breast Surgery, Department of Surgery, China Medical University Hospital, Taichung, Taiwan

    Chi-Hao Huang

  8. Division of Nephrology, Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan

    Chin-Chi Kuo

  9. Department of Medical Research, China Medical University Hospital, Taichung, Taiwan

    Chin-Chi Kuo

  10. Bioinformatics and Biostatistics Core, Center of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan

    Eric Y. Chuang

  11. Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan

    Eric Y. Chuang

  12. Biomedical Technology and Device Research Laboratories, Industrial Technology Research Institute, Hsinchu, Taiwan

    Eric Y. Chuang

  13. Genetic Center, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan

    Fuu-Jen Tsai

Authors
  1. Yu-Ching Hsu
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  2. Hung-Lin Chen
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  3. Chi-Fung Cheng
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Contributions

YH: data analysis, data visualization, manuscript writing, manuscript revision; HC: data curation, data analysis, manuscript revision; CC: data curation, data analysis, manuscript revision; AC: data analysis, manuscript revision; PC: data curation; CL: data curation; HC: data curation; TYL: data curation; CK: data curation, data analysis, project design, project supervision, administrative support, manuscript revision; EYC: project supervision, administrative support; TPL: data analysis, manuscript writing, manuscript revision, project design, project supervision, administrative support; FT: data curation, project supervision, administrative support. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Tzu-Pin Lu or Fuu-Jen Tsai.

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Competing interests

The authors have no relevant financial or non-financial interests to disclose.

Ethical approval

The study was approved by the Big Data Center of CMUH and the Research Ethical Committee/Institutional Review Board (REC/IRB) of China Medical University Hospital (CMUH105-REC3-068, CMUH107-REC3-058, CMUH110-REC1-100, and CMUH110-REC2-145). All methods were performed in accordance with the relevant guidelines and regulations of REC/IRB.

Consent to participate

Informed consent was obtained from all individual participants included in the study.

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The authors affirm that human research participants provided informed consent for publication of all the figures and tables in this manuscript.

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Hsu, YC., Chen, HL., Cheng, CF. et al. The largest genome-wide association study for breast cancer in Taiwanese Han population. Breast Cancer Res Treat 203, 291–306 (2024). https://doi.org/10.1007/s10549-023-07133-5

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