Development of a clinical polygenic risk score assay and reporting workflow

The first report from the prospective GenoVA Study provides preliminary insights into the development of a polygenic risk score assay in a clinical setting and discusses the challenges of generating, interpreting and reporting results. Implementation of polygenic risk scores (PRS) may improve disease prevention and management but poses several challenges: the construction of clinically valid assays, interpretation for individual patients, and the development of clinical workflows and resources to support their use in patient care. For the ongoing Veterans Affairs Genomic Medicine at Veterans Affairs (GenoVA) Study we developed a clinical genotype array-based assay for six published PRS. We used data from 36,423 Mass General Brigham Biobank participants and adjustment for population structure to replicate known PRS-disease associations and published PRS thresholds for a disease odds ratio (OR) of 2 (ranging from 1.75 (95% CI: 1.57-1.95) for type 2 diabetes to 2.38 (95% CI: 2.07-2.73) for breast cancer). After confirming the high performance and robustness of the pipeline for use as a clinical assay for individual patients, we analyzed the first 227 prospective samples from the GenoVA Study and found that the frequency of PRS corresponding to published OR > 2 ranged from 13/227 (5.7%) for colorectal cancer to 23/150 (15.3%) for prostate cancer. In addition to the PRS laboratory report, we developed physician- and patient-oriented informational materials to support decision-making about PRS results. Our work illustrates the generalizable development of a clinical PRS assay for multiple conditions and the technical, reporting and clinical workflow challenges for implementing PRS information in the clinic.

Automated summary

The first report from the GenoVA Study provides insights into the development of a clinical polygenic risk score assay and discusses the challenges of implementing and reporting the results. The study developed a clinical genotype array-based assay for multiple conditions and analyzed prospective samples to determine the frequency of high-risk polygenic risk scores. The research highlights the importance of developing resources and workflows for using polygenic risk score information in patient care.