Implementation of the genome-informed risk assessment (GIRA) may lead to large disruptions to the health system

The Genome Informed Risk Assessment (GIRA) report from eMERGE has become a standard approach to implement genomic precision medicine at scale. Here, we assess GIRAs utility and impact in a health care system independent of eMERGE, focusing on 9 adult conditions using the Penn Medicine Biobank (PMBB, n=48,279). We find a large number of patients - 50.1% (n=24,185) - were deemed by GIRA as high-risk for at least one of the 9 conditions with 30.4% (n=14,676) due to polygenic and/or monogenic risk. Stratifying by ancestry revealed significant differences in high-risk proportions, with higher rates in African/African American (AFR) (56.6% vs. 50.1%, p=7.43x10-36) and lower rates in East (42.0%) and South Asian (40.0%). Increased high-risk rates were observed in the lowest quartile of social deprivation index, highlighting the influence of environmental factors and access to care on GIRAs utility. GIRA was a good predictor of prevalent cases (in-line with the eMERGE GIRA reported results); incident case prediction was substantially attenuated for 5 of the 9 conditions (e.g., OR of 2.36 vs. HR of 1.31 for atrial fibrillation (AFIB)). We find demographic compositions of high-risk patients differed from the incident cases for some of the conditions; for example, high-risk for AFIB individuals where enriched for European ancestries in contrast with incident AFIB cases that were enriched for AFR ancestries. Overall, our results show the accuracy of GIRA as a biomarker to stratify high-risk patients for precision medicine and highlight implementation challenges in its impact on the health system if implemented at scale.