A new genomic method predicting Lp(a) from exome data flags high-risk individuals better than prior tools, especially outside European ancestry, 76,147-person study finds (JACC Basic Transl Sci 2025)

This study developed a method to estimate Lp(a) from exome sequencing data by combining Kringle IV subtype 2 repeat quantification with a single-nucleotide-variant genetic risk score, applying it to a diverse cohort of 76,147 individuals from the Helix Research Network. The method identified individuals with high Lp(a) levels more accurately than prior approaches, with the improvement most pronounced among individuals not genetically similar to Europeans, a population historically underserved by Lp(a) genetic tools. High genetic risk for elevated Lp(a) correlated with earlier and more frequent ASCVD diagnoses, and individuals with high genetic Lp(a) risk were more likely to develop ASCVD in the absence of traditional risk factors. This genomic approach offers a route to flagging Lp(a)-driven risk from existing exome data without a dedicated Lp(a) blood test, with particular value for populations where current tools underperform.