NIH researchers are developing guidelines for reporting polygenic risk scores

Scientists and healthcare providers are beginning to use a new method for assessing a person’s legacy risk for diseases such as Type 2 diabetes, coronary heart disease and breast cancer, which into a measured polygenic risk score. The score provides an estimate of a person’s risk for specific diseases, based on their DNA changes associated with those diseases.

Despite the increase in studies using polygenic risk scores, researchers have observed inconsistencies in how such scores are measured and reported. These differences threaten to undermine the acceptance of polygenic risk scores in clinical care.

To address this issue, the research teams, funded specifically by the National Human Genome Research Institute (NHGRI), have published a 22-topic framework in the journal Nature that indicates the minimum amount of polygenic risk score information that scientists should include in their study. This framework – created by the NHGRI Genome Resource Compound Disease Working Group (ClinGen) and the Polygenic Score Catalog (PGS), an open database of polygenic risk scores – will help improve the validity, transparency and reproducibility of risk scores polygenic. NHGRI is part of the National Institutes of Health.

To measure a person’s polygenic risk score, researchers study DNA changes in more than 6 billion places in the human genome.

“A real challenge is that the research community has not adopted universal best practices for reporting polygenic risk scores,” said Erin Ramos, Ph.D., program director for ClinGen, deputy director of the NHGRI Division of Genomic Medicine and co-author of the paper. “With the field growing so rapidly, we need to put standards in place so that we can properly assess these scores and find out which ones are ready for use in care. clinical. “

This framework builds on another best practice model called the Genetic Risk Prediction Studies (GRIPS) report, published by an international working group in 2011. GRIPS focused on models that included a smaller set of genomic changes and gene scores. However, genetic risk prediction models have evolved rapidly since then, and are based on a much larger set of genomic changes and more complex approaches. Also, researchers have not fully adopted the GRIPS framework.

“There is a renewed emphasis on reporting standards by ClinGen and the Polygenic Score Catalog comes at a crucial time for polygenic risk scores,” said Genevieve Wojcik, Ph.D., MHS, assistant professor of epidemiology at the Johns School of Public Health Hopkins Bloomberg, Baltimore, and corresponding author of the paper. “It specifies the minimum information that should be described in a research paper for defining a polygenic risk score, reproducing results and ultimately translating the information into clinical care.”

Some of the new reporting framework materials include details of the study population and the basis for selecting that population.

“If we want to give these scores to people all over the world, the studies need to explain who they are studying and why, in the clearest possible way,” said Katrina Goddard, Ph.D. ., director of Translational and Applied Genomics at the Kaiser Permanente Center for Health Research, Portland, Oregon, who was also a co-author of the paper. “Without that clarity and reproducibility, efforts may fail to weaken the use of polygenic risk scores. “

The new framework suggests that scientists should explain the statistical methods they used to develop and determine the polygenic risk scores. Without a consistent method of reporting polygenic risk scores, it is almost impossible to compare the usefulness of the scores for assessing disease risk in humans. Under the new guidance, researchers should also consider potential limitations of these scores and how clinicians should use the scores in patient care.

“If researchers can follow these guidelines, it will be easier to assess published polygenic risk scores and determine which ones are most appropriate for the clinical setting,” said Michael Inouye, Ph.D. ., director of the Cambridge Baker Systems Genomics Systems Initiative. , UK, and co-senior author of the paper. “For diseases such as breast cancer and many more, we will be able to carefully place patients in different risk areas and provide beneficial screening strategies and treatments. In reality, in the future, we will detect risk early enough to fight the disease effectively. “

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ClinGen is funded by NHGRI. This effort was led by Stanford University, the award site of the ClinGen consortium. The PGS Catalog is funded by the EMBL European Institute of Biology, Cambridge University, Baker Institute of Heart and Diabetes and Health Data Research, UK