Title: Who to sequence? Data-driven triage for targeted genetic testing
Abstract: Genetic testing for pathogenic variants can enable early diagnosis, guide preventive care, and inform cascade testing of at-risk relatives. However, it is not routinely conducted at scale because of cost, limited genetics workforce capacity, uncertain yield in unselected populations, and persistent disparities in access. Beyond family history, which is often incomplete or inaccurately captured, can we use data already embedded in health systems to better identify who is most likely to benefit from targeted sequencing?
In this talk, I will present two complementary, data-driven approaches to triage for genetic testing. First, we leverage routinely collected electronic health record data to develop clinical scores that quantify testing priority. I will highlight applications in glucose-6-phosphate dehydrogenase deficiency and alpha-1 antitrypsin deficiency, demonstrating how structured diagnoses, laboratory values, and medication histories can enrich for individuals with a higher likelihood of carrying pathogenic variants.
Second, we evaluate the use of common variant-based polygenic risk scores, which are relatively inexpensive to obtain, as a scalable pre-screen to prioritize sequencing for CDC Tier 1 conditions, including hereditary breast and ovarian cancer syndrome, lynch syndrome, and familial hypercholesterolemia.
Together, these approaches highlight the promise of precision triage frameworks that could improve diagnostic yield, focus resources where they are most likely to have impact, and expand access to genomic medicine. While further validation, implementation research, and careful attention to equity are needed, data-driven prioritization offers a path toward more strategic and scalable integration of genetic testing into routine care.
