Positive predictive value highlights four novel candidates for actionable genetic screening from analysis of 220,000 clinicogenomic records

Abstract

Purpose: To identify conditions that are candidates for population genetic screening based on population prevalence, penetrance of rare variants, and actionability. Methods: We analyzed exome and medical record data from >220,000 participants across two large population health cohorts with different demographics. We performed a gene-based collapsing analysis of rare variants to identify genes significantly associated with disease status. Results: We identify 74 statistically significant gene–disease associations across 27 genes. Seven of these conditions have a positive predictive value (PPV) of at least 30% in both cohorts. Three are already used in population screening programs (BRCA1, BRCA2, LDLR), and we also identify four new candidates for population screening: GCK with diabetes mellitus, HBB with β-thalassemia minor and intermedia, PKD1 with cystic kidney disease, and MIP with cataracts. Importantly, the associations are actionable in that early genetic screening of each of these conditions is expected to improve outcomes. Conclusion: We identify seven genetic conditions where rare variation appears appropriate to assess in population screening, four of which are not yet used in screening programs. The addition of GCK, HBB, PKD1, and MIP rare variants into genetic screening programs would reach an additional 0.21% of participants with actionable disease risk, depending on the population.