ArticleScientific reports2024
Polygenic risk score-based prediction of breast cancer risk in Taiwanese women with dense breast using a retrospective cohort study.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed, 5 citations in OpenAlex.
- Are polygenic scores for psychiatric and substance use outcomes "ready" for clinical application? Current state and next steps.Psychiatric genetics · 2026Review
- Preimplantation genetic testing for polygenic diseases: A novel paradigm in embryo selection.Biochemistry and biophysics reports · 2026Review
- Circulating tumor cells (CTCs) enumeration and machine-learning based diagnostic biomarkers for breast cancer detection.BMC cancer · 2026Article
- Decoding Breast Cancer: Emerging Molecular Biomarkers and Novel Therapeutic Targets for Precision Medicine.International journal of molecular sciences · 2025Review
- Predictive capabilities of polygenic scores in an East-Asian population-based cohort: the Singapore Chinese health study.Communications biology · 2025Article
- Identifying breast cancer risk factors and evaluating biennial mammography screening efficacy using big data analysis in Taiwan.Scientific reports · 2025Article
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Authors and funding
5 authors at 5 institutions in 1 country.
Funding
Abstract
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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