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The largest genome-wide association study for breast cancer in Taiwanese Han population.
Hsu, Yu-Ching; Chen, Hung-Lin; Cheng, Chi-Fung; Chattopadhyay, Amrita; Chen, Pei-Shan; Lin, Che-Chen; Chiang, Hsiu-Yin; Liu, Ting-Yuan; Huang, Chi-Hao; Kuo, Chin-Chi; Chuang, Eric Y; Lu, Tzu-Pin; Tsai, Fuu-Jen.
Afiliación
  • Hsu YC; Bioinformatics Program, Taiwan International Graduate Program, National Taiwan University, Taipei, Taiwan.
  • Chen HL; Bioinformatics Program, Institute of Statistical Science, Taiwan International Graduate Program, Academia Sinica, Taipei, Taiwan.
  • Cheng CF; Institute of Health Data Analytics and Statistics, Department of Public Health, College of Public Health, National Taiwan University, Taipei, Taiwan.
  • Chattopadhyay A; Big Data Center, China Medical University Hospital, Taichung, Taiwan.
  • Chen PS; Big Data Center, China Medical University Hospital, Taichung, Taiwan.
  • Lin CC; Center for Translational Genomic Research, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan.
  • Chiang HY; Big Data Center, China Medical University Hospital, Taichung, Taiwan.
  • Liu TY; Big Data Center, China Medical University Hospital, Taichung, Taiwan.
  • Huang CH; Big Data Center, China Medical University Hospital, Taichung, Taiwan.
  • Kuo CC; Million-Person Precision Medicine Initiative, Department of Medical Research, China Medical University Hospital, Taichung, Taiwan.
  • Chuang EY; Division of Breast Surgery, Department of Surgery, China Medical University Hospital, Taichung, Taiwan.
  • Lu TP; Big Data Center, China Medical University Hospital, Taichung, Taiwan.
  • Tsai FJ; Division of Nephrology, Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan.
Breast Cancer Res Treat ; 203(2): 291-306, 2024 Jan.
Article en En | MEDLINE | ID: mdl-37851288
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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Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Estudio de Asociación del Genoma Completo Límite: Female / Humans Idioma: En Revista: Breast Cancer Res Treat Año: 2024 Tipo del documento: Article País de afiliación: Taiwán

Texto completo: 1 Bases de datos: MEDLINE Asunto principal: Neoplasias de la Mama / Estudio de Asociación del Genoma Completo Límite: Female / Humans Idioma: En Revista: Breast Cancer Res Treat Año: 2024 Tipo del documento: Article País de afiliación: Taiwán