Journal Article

Genomic platform specific polygenic risk scores impact breast cancer risk stratification

Hartman, Mikael, Li, Zheng, Khng, Alexis Jiaying, Dorajoo, Rajkumar, Ho, Peh Joo, Chong, Dawn Qingqing, Goy, Pierre-Alexis Vincent, Goh, Liuh Ling, Li, Jingmei, Lo, Elaine, Bertin, Nicolas, Kamila, Kayla Aisha, Tan, Iain Bee Huat, Wee, Hwee Lin, Tan, Joanna Hui Juan, Ho, Weang Kee

2025

Overview

Background At present, there is no consensus on which genotyping platform should serve as the standard for clinical polygenic risk score (PRS) implementation. Previous studies have compared the overall performance and concordance of different genotyping and sequencing technologies; however, these analyses have generally averaged the results over the whole genome. We evaluated differences in a 313-variant breast cancer PRS (PRS 313 ) across genomic platforms and their impact on risk stratification. Methods We compare PRS 313 derived from genotyping arrays (Global Screening Array [GSA], OncoArray-500K [OncoArray], Global Diversity Array [GDA], custom Axiom_PrecipV1 array [ThermoFisher]) and low-coverage genome sequencing (lc-WGS) in 2 cell lines and 92 individuals. Probes are designed for all variants on ThermoFisher (success rate: 259/313). Sanger sequencing profiles indels. Concordance of high-risk classification (PRS 313 scoresum > 0.6) across platforms is assessed using Kappa statistics. Results In saliva samples, indel concordance with Sanger sequencing varies widely (Kappa: 0.007-1.000). PRS 313 -ThermoFisher is predictable from other platforms using linear models, despite systematic differences. Greater agreement is observed between arrays with high imputation overlap (e.g., GDA ~ GSA slope=0.986). Agreement in high-risk classification before mean correction is moderate (Fleiss’s Kappa=0.552) and improves after mean correction (Kappa=0.650). Arrays with similar designs show higher agreement before mean correction (Kappa=0.745). Mean correction narrows high-risk proportions from 4-45% to 15-21%. Overall, 26 of 92 samples are classified as high risk on at least one platform, but only 7 are high risk across all. When restricting to identical variants across all platforms for PRS 313 calculation, the corresponding number of high-risk individuals are 24 and 11. Conclusion Our findings demonstrate that platform-specific variability can influence PRS 313 estimates to potentially reclassify individuals around clinically relevant thresholds. Plain Language Summary This study looks at how different DNA sequencing methods can affect estimates of genetic risk for breast cancer. DNA sequencing is a process that determines the exact order of the building blocks (nucleotides) in a person’s genes. Different sequencing technologies and platforms may read this information slightly differently, leading to variations in the data even when analyzing the same individual. These differences can be important because they might change a person’s estimated risk for breast cancer, especially if the risk score is close to a level where doctors would take action. To study this, we analyzed a previously validated breast cancer risk model based on 313 genetic variants, called a polygenic risk score (PRS). A PRS combines the effects of many small genetic differences across the genome to estimate a person’s overall risk for developing a disease, rather than focusing on a single high-risk gene. We found that the estimated risk could shift depending on the sequencing platform used, revealing systematic biases in how people are classified into risk groups. We also identified concerns with certain types of genetic changes, called insertions and deletions (indels), which are sometimes inconsistently detected across platforms and could affect the reliability of the risk score. Ho et al. investigate the impact of choice of sequencing platform on identification of specific variants for breast cancer risk stratification. Platform-specific variability is found to influence PRS313 estimates, potentially reclassifying individuals around clinically relevant thresholds.

• Publisher: Nature Publishing Group UK,Springer Nature B.V,Nature Portfolio
• Subject: 45/23 / 692/53/2423 / 692/700/459/1748 / Accuracy / Arrays / Breast cancer / Genomes / Medical screening / Medicine / Medicine & Public Health