Models combining clinical history and polygenic risk scores were developed and validated for 150 diseases and all-cause mortality in 900,000 participants from UK Biobank and FinnGen. Genetic information added most in metabolic, cardiovascular, autoimmune and neurological conditions and little in genitourinary and respiratory disease, with all significant score-by-clinical-risk interactions negative. For atherosclerotic cardiovascular disease, the polygenic score expanded the clinically identified high-risk group by 40%, and the reclassified group had 4.9-fold higher incidence during follow-up than those remaining low-risk.
Why it is interesting: It places the marginal value of genetic prediction precisely where clinical records are least informative, and quantifies the reclassification for cardiovascular disease.