A Breast Cancer Polygenic Risk Score Is Feasible for Risk Stratification in the Norwegian Population

Area of Science:

• Genetics and Genomics
• Cancer Epidemiology
• Biostatistics

Background:

• Genome-wide association studies (GWAS) have identified numerous single nucleotide polymorphisms (SNPs) associated with breast cancer (BC).
• Polygenic Risk Score (PRS) models are emerging as valuable tools for BC risk stratification.
• The clinical utility of PRS requires validation in diverse populations, including Norway.

Purpose of the Study:

• To evaluate the performance and clinical utility of established PRS models for breast cancer risk prediction in a Norwegian population.
• To assess the association between PRS and BC age of onset and lifetime risk.

Main Methods:

• Utilized a Norwegian dataset comprising 1053 BC cases and 7094 controls.
• Calculated PRS values using four distinct PRS models.
• Evaluated model performance using Area Under the Curve (AUC) and Odds Ratio (OR); assessed age of onset and lifetime risk using Cox regression and the iCare tool.

Main Results:

• The optimal PRS model, incorporating 3820 SNPs, achieved an AUC of 0.625 and an OR of 1.567 per standard deviation increase.
• Elevated PRS values significantly correlated with increased BC risk (Hazard Ratio = 1.494 per SD increase).
• Individuals in the highest PRS decile exhibited at least double the risk of developing BC compared to those with a median PRS, consistent with findings in UK and Estonian cohorts.

Conclusions:

• Validated PRS models demonstrate comparable accuracy in the Norwegian population to that observed in UK and Estonian cohorts.
• PRS is a meaningful predictor of BC age of onset and lifetime risk.
• Integration of PRS into BC screening strategies in Norway is recommended, mirroring successful implementation in Estonia.