NEW YORK – In an effort to boost the transparency and reproductivity behind genetic risk prediction tools, investigators from the Clinical Genomics Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, a database supported by centers in Europe and Australia, have proposed a set of reporting guidelines related to polygenic risk scores (PRS).
"Polygenic risk scores (PRS) are becoming a powerful tool in the translation of genomic discovery to the clinic," co-senior and corresponding author Genevieve Wojcik, a statistical geneticist and genetic epidemiology researcher at the Johns Hopkins Bloomberg School of Public Health, explained in an email. "However, the necessary details of what went into the development of these scores is often missing or insufficient to fully understand their potential utility and limitations."
In a paper published in Nature on Wednesday, Wojcik and her colleagues provided a rationale and key points for the National Human Genome Research Institute-funded Polygenic Risk Score Reporting Standards (PRS-RS) framework. They pointed to the importance of making the data behind a given PRS available to other investigators, along with related details on the analytical methods used to bring together risk variant data, which often comes from genome-wide association studies.
The standards "outline what needs to be reported with the publication of any PRS with an emphasis on reproducibility and transparency throughout the development process," Wojcik explained.
Among the 22 specific items in the PRS-RS are recommendations dealing with everything from considerations related to the study type and study population to the particulars behind risk models, data interpretation, and translation, in the hopes of standardizing genetic risk scores and the ways that these predictive tools are developed and validated.
"Drawing upon experts in epidemiology, statistics, disease-specific applications, implementation, and policy, this 22-item reporting framework defines the minimal information needed to interpret and evaluate PRS, especially with respect to downstream clinical applications," the investigators wrote.
The latest guidance grew out of Genetic Risk Prediction Studies (GRIPS) best practices that an international working group proposed a decade ago, though the updated recommendations aimed to address the ever-growing genetic datasets and approaches that have developed since GRIPS, along with challenges around the widespread adoption of standardized PRS methods.
"If researchers can follow these guidelines, it will be more straightforward to evaluate published polygenic risk scores and decide which ones are a good fit for the clinical setting," co-senior author Michael Inouye, director of the Cambridge Baker Systems Genomics Initiative, said in a statement.
"For diseases such as breast cancer and many others, we will be able to responsibly place patients in different risk categories and provide beneficial screening strategies and treatments," Inouye added. "Ideally, in the future, we will detect risk early enough to combat the disease effectively."