Abstract
The aim of this study was to assess the power of the polygenic risk score (PRS) in estimating the overall genetic risk of women carrying germline BRCA1 pathogenic variants (PVs) c.4035del or c.5266dup to develop breast (BC) or ovarian cancer (OC) due to additional genetic variations. In this study, PRSs previously developed from two joint models using summary statistics of age-at-onset (BayesW model) and case–control data (BayesRR-RC model) from a genome-wide association analysis (GWAS) were applied to 406 germline BRCA1 PV (c.4035del or c.5266dup) carriers affected by BC or OC, compared with unaffected individuals. A binomial logistic regression model was used to assess the association of PRS with BC or OC development risk. We observed that the best-fitting BayesW PRS model effectively predicted the individual’s BC risk (OR = 1.37; 95% CI = 1.03–1.81, p = 0.02905 with AUC = 0.759). However, none of the applied PRS models was a good predictor of OC risk. The best-fitted PRS model (BayesW) contributed to assessing the risk of developing BC for germline BRCA1 PV (c.4035del or c.5266dup) carriers and may facilitate more precise and timely patient stratification and decision-making to improve the current BC treatment or even prevention strategies.
Original language | English |
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Article number | 2957 |
Journal | Cancers |
Volume | 15 |
Issue number | 11 |
DOIs | |
Publication status | Published - Jan 2023 |
Keywords*
- BRCA1 pathogenic variant carriers
- breast cancer
- ovarian cancer
- polygenic risk score (PRS)
Field of Science*
- 3.2 Clinical medicine
Publication Type*
- 1.1. Scientific article indexed in Web of Science and/or Scopus database
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Dive into the research topics of 'Polygenic Risk Score Predicts Modified Risk in BRCA1 Pathogenic Variant c.4035del and c.5266dup Carriers in Breast Cancer Patients'. Together they form a unique fingerprint.Datasets
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GWAS summary statistics of PhD Thesis "Identifying Genetic Factors Associated with Breast or Ovarian Cancer Risk in BRCA1 Pathogenic Variant Carriers"
Berga-Švītiņa, E. (Creator), Maksimenko, J. (Creator), Miklaševičs, E. (Creator), Mägi, R. (Creator) & Vilne, B. (Creator), Riga Stradins University, 17 Sept 2024
DOI: 10.48510/FK2/TEJ5PK, https://doi.org/10.48510/FK2/TEJ5PK
Dataset