Polygenic risk score-based prediction of breast cancer risk in Taiwanese women with dense breast using a retrospective cohort study

被引:0
作者
Chih-Chiang Hung
Sin-Hua Moi
Hsin-I Huang
Tzu-Hung Hsiao
Chi-Cheng Huang
机构
[1] Taichung Veterans General Hospital,Division of Breast Surgery, Department of Surgery
[2] Hung Kuang University,Department of Applied Cosmetology, College of Human Science and Social Innovation
[3] National Chung Hsing University,College of Life Sciences
[4] Kaohsiung Medical University,Graduate Institute of Clinical Medicine, College of Medicine
[5] Kaohsiung Medical University,Research Center for Precision Environmental Medicine
[6] Kaohsiung Medical University,Department of Medical Research, Kaohsiung Medical University Hospital
[7] National Sun Yat-Sen University,Department of Information Management
[8] INC,International Integrated Systems
[9] Taichung Veterans General Hospital,Department of Medical Research
[10] Fu Jen Catholic University,Department of Public Health
[11] National Chung Hsing University,Institute of Genomics and Bioinformatics
[12] Taipei Veterans General Hospital,Division of Breast Surgery, Department of Surgery
[13] National Taiwan University,Institute of Epidemiology and Preventive Medicine, College of Public Health
来源
Scientific Reports | / 14卷
关键词
Breast cancer; Dense breast; Polygenic risk score; Genotyping; Precision screening;
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摘要
Mammographic screening has contributed to a significant reduction in breast cancer mortality. Several studies have highlighted the correlation between breast density, as detected through mammography, and a higher likelihood of developing breast cancer. A polygenic risk score (PRS) is a numerical score that is calculated based on an individual's genetic information. This study aims to explore the potential roles of PRS as candidate markers for breast cancer development and investigate the genetic profiles associated with clinical characteristics in Asian females with dense breasts. This is a retrospective cohort study integrated breast cancer screening, population genotyping, and cancer registry database. The PRSs of the study cohort were estimated using genotyping data of 77 single nucleotide polymorphisms based on the PGS000001 Catalog. A subgroup analysis was conducted for females without breast symptoms. Breast cancer patients constituted a higher proportion of individuals in PRS Q4 (37.8% vs. 24.8% in controls). Among dense breast patients with no symptoms, the high PRS group (Q4) consistently showed a significantly elevated breast cancer risk compared to the low PRS group (Q1–Q3) in both univariate (OR = 2.25, 95% CI 1.43–3.50, P < 0.001) and multivariate analyses (OR: 2.23; 95% CI 1.41–3.48, P < 0.001). The study was extended to predict breast cancer risk using common low-penetrance risk variants in a PRS model, which could be integrated into personalized screening strategies for Taiwanese females with dense breasts without prominent symptoms.
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