AI Article Synopsis

  • Polygenic risk scores (PRSs), derived from genome-wide association studies (GWASs), can enhance breast cancer risk evaluation but are primarily based on European populations.
  • This study analyzed the effectiveness of European-based PRS models in identifying breast cancer risk among Ashkenazi Jewish women in Israel using data from two cohorts.
  • Results indicated that these PRS models successfully identified Ashkenazi Jewish women at high risk for breast cancer, suggesting they could improve risk assessment in this group.

Article Abstract

Background: Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women.

Methods: We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel.

Results: In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28).

Conclusions: Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10715538PMC
http://dx.doi.org/10.1136/jmg-2023-109185DOI Listing

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