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. 2025 Oct;10(10):101298.
doi: 10.1016/j.jacbts.2025.04.012. Epub 2025 Jul 30.

Novel Method for Predicting Lp(a) From Genomic Testing Identifies ASCVD Risk Across a Diverse Cohort

Natalie Telis  1 , Hang Dai  2 , Ashley Waring  3 , David Kann  4 , Dana Wyman  2 , Simon White  2 , Basil Khuder  2 , Francisco Tanudjaja  2 , Alexandre Bolze  2 , Matthew E Levy  2 , Cassie Hajek  2 , Lisa M McEwen  2 , Douglas Stoller  3 , Christopher N Chapman  4 , C Anwar A Chahal  5 , Daniel P Judge  6 , Douglas A Olson  7 , Joseph J Grzymski  8 , Nicole L Washington  2 , William Lee  2 , Elizabeth T Cirulli  2 , Shishi Luo  2 , Kelly Schiabor Barrett  2
Affiliations

Novel Method for Predicting Lp(a) From Genomic Testing Identifies ASCVD Risk Across a Diverse Cohort

Natalie Telis et al. JACC Basic Transl Sci. 2025 Oct.

Abstract

Lipoprotein(a) (Lp[a]) is a genetic and often unmeasured contributor to atherosclerotic cardiovascular disease (ASCVD) risk. In this study, Lp(a) was estimated from exome data by quantifying Kringle IV subtype 2 repeats alongside a single-nucleotide variant-based genetic risk score. This method was applied to a diverse cohort (N = 76,147) from the Helix Research Network. The method better identified individuals with high Lp(a) levels, especially among individuals not genetically similar to Europeans. High genetic risk for high Lp(a) level was correlated with earlier and more frequent ASCVD diagnoses. Those with high genetic Lp(a) were more likely to have ASCVD without traditional risk factors present.

Keywords: cardiovascular disease; clinical genetics; genomics; lipoprotein(a).

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Conflict of interest statement

Funding Support and Author Disclosures Funding was provided to the Healthy Nevada Project by the Renown Institute for Health Innovation and the Renown Health Foundation. The Healthy Nevada Project receives funding from Gilead Sciences, outside the scope of this research. Funding was provided to the myGenetics program by HealthPartners. Drs Barrett, Cirulli, Bolze, Telis, Lee, Luo, and Washington and Mr Khuder are employees of Helix. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.

Figures

None
Graphical abstract
Figure 1
Figure 1
GRS and KIV-2 Each Contribute Independently to Predicting Lp(a) Levels (A) Schematic representation of bioinformatic process for Kringle IV (KIV) subtype 2 copy number estimate (CNE) and calculation of the LPA genetic risk score (GRS). (B) Proportion of individuals in each category with lipoprotein(a) (Lp[a]) >120 nmol/L, divided by membership in either the European (EUR) or non-EUR cohort. From left to right, “high GRS” is a GRS >120 nmol/L (as the GRS is in units of predicted Lp[a]), “low KIV-2” denotes a normalized KIV-2 <0.8 SDs from the mean, and “high GRS or low KIV-2” indicates that a patient was included for either reason. Although some individuals with high GRS may have nonrisk KIV-2, and vice versa, “low PRS or high KIV-2” are individuals with neither genetic risk factor. SNV = single-nucleotide variant.
Figure 2
Figure 2
Elevated Combined Genetic Risk for High Lp(a) Is Associated With Increased Phenotype Incidence After Adjusting for Age, Sex, Body Mass Index, and Population of Origin (A) Cumulative fraction of individuals with coronary artery disease, divided by their Lp(a) combined genetic risk group (high, average, or low). (B) Cox proportional HRs and 95% CIs for high vs average and high vs low combined genetic risk for high Lp(a) groups across statistical significant phenotypes in the unified cohort, as well as these estimations in subcohorts separated by genetic similarity (EUR or non-EUR cohorts). HRN = Helix Research Network; MACE = major adverse cardiovascular events; other abbreviations as in Figure 1.
Figure 3
Figure 3
Proportion of Individuals at Low Canonical Risk With Disease Diagnoses The proportion of individuals in each lipoprotein(a) (Lp[a]) genetic risk group receiving a diagnosis (Dx). These individuals are all restricted to age <55 years (men) or <65 years (women), body mass index (BMI) <30 kg/m2, and either no low-density lipoprotein (LDL) measurement or a low measurement, to include only individuals with no canonical risk factors for cardiovascular disease (hypertension [HTN], type 2 diabetes [T2D], or smoking). CAD = coronary artery disease; MI = myocardial infarction; NA = not available.
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