Chong, D. Q. | Search bioRxiv

bioRxiv2025

Polygenic Risk Scores Across Genomic Platforms for Reliable Breast Cancer Risk Stratification

PurposeWe evaluated differences in a 313-variant breast cancer polygenic risk score (PRS313) across genomic platforms and their impact on risk stratification. MethodsWe compared PRS313 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 were designed for all variants on ThermoFisher (success rate: 259/313). Sanger sequencing was performed to profile indels. Concordance of high-risk classification (PRSscore>0.6) across platforms was assessed using Kappa statistics. ResultsPRS313-lc-WGS was identical in the 4 cell line repeats. In saliva samples, indel concordance with Sanger sequencing varied widely (Kappa: 0.007-1.000). PRS313-ThermoFisher was predictable from other platforms using linear models, despite systematic differences. Greater agreement was observed between arrays with high imputation overlap (e.g., GDA[~]GSA slope=0.986). Pre-calibration agreement in high-risk classification was moderate (Fleiss Kappa=0.552) and improved post-calibration (Kappa=0.650). Arrays with similar designs showed higher pre-calibration agreement (Kappa=0.745). Calibration narrowed high-risk proportions from 4-45% to 15-21% -28% were high-risk by any platform, while 8% were high-risk across all five. ConclusionPlatform-specific biases affect PRS interpretation. Calibration enhances consistency in identifying high-risk individuals. STATEMENT OF SIGNIFICANCEThis study compares the performance of a validated 313-variant breast cancer polygenic risk score across platforms, revealing systematic biases in risk stratification and raising concerns about including inconsistent indels in the model.

genetics↗

bioRxiv2021

Heatrich-BS enables efficient CpG enrichment and highly scalable cell-free DNA methylation profiling

Genome wide analysis of cell-free DNA (cfDNA) methylation profile has been shown to be a promising approach for sensitive and specific multi-cancer detection. However, scaling these assays for clinical translation is impractical due to the high cost of whole genome bisulfite sequencing. We showed that the small fraction of GC-rich genome is highly enriched in CpG sites and disproportionately harbored the majority of cancer-specific methylation signature. Here, we report on the simple but effective Heat enrichment of CpG-rich regions for Bisulfite Sequencing (Heatrich-BS) platform that enables focused methylation profiling in these highly informative regions. Our novel method and bioinformatics algorithm enable high accuracy and sensitivity in tumor burden estimation and quantitative monitoring of colorectal patient response to treatment, at much reduced sequencing requirement. Heatrich-BS holds great potential for highly scalable screening and regular monitoring of cancer using liquid biopsy.

genomics↗