Population-Level Genomic Surveillance for Early Detection of Polygenic Risk in Primary Care Practice
Keywords:
polygenic risk score, genomic surveillance, primary care, population health, EHR integration, implementation science, health equityAbstract
Population-level genomic surveillance using polygenic risk scores (PRS) can identify individuals at substantially elevated risk for common diseases before symptoms emerge. We outline a primary-care–anchored framework for early detection and risk management using PRS, demonstrate a workflow for electronic health record (EHR) integration, and present a simulated implementation dataset from a 20,000-person program. In the simulation, 4.9% screened above the ≥95th percentile PRS threshold, with a positive predictive value (PPV) of 17.6% for a composite 10-year cardiometabolic outcome. Number needed to screen (NNS) to identify one high-PRS individual was 20; assuming a 40% relative risk reduction among high-PRS patients adherent to preventive therapy, the number needed to treat (NNT) within the high-PRS stratum was 14. We discuss operational considerations (population outreach, confirmatory workflows, equity), governance (reporting standards, consent, data protection), and health-system outcomes (referrals completed, treatment initiation).
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