Lipoprotein(a) metabolomic and proteomic features and atherosclerotic cardiovascular disease in young, healthy adults

Abstract

Background: Elevated lipoprotein (a) [Lp(a)] is associated with a higher risk of atherosclerotic cardiovascular disease (ASCVD) events. Although Lp(a) is a genetically determined risk factor, the metabolomic and proteomic features that may mediate or be associated with this risk are unknown. Methods: In young, healthy Coronary Artery Risk Development in Young Adults (CARDIA) participants, we defined the relationships between year 7 (Y7) Lp(a) and metabolomic (n=563)/proteomic (n=184) features, derived quantitative Lp(a)-omic scores from these features, and related these quantitative scores to ASCVD phenotypes. Results: CARDIA participants had a mean age of 32 years at Y7 in this study and a median follow-up of 27.1 years. In the overall cohort (n=3920), Y7 Lp(a) levels were associated prospectively with ASCVD phenotypes at year 25 (Y25), including hs-CRP, coronary artery calcification (CAC), and incident CHD. In the subcohort (n=2290) that had measurements of Lp(a), proteomics, and metabolomics, Y7 Lp(a) levels were associated with distinct proteomic and metabolomic features indicative of immune responses, lipoprotein metabolism, atherogenesis, and arginine/steroid biosynthesis. Using machine learning approaches, Lp(a) metabolomic, proteomic, and transomic quantitative scores were derived. The Y7 Lp(a) transomic score was more strongly associated with Y25 incident CAC (standardized beta; = 0.29, p=0.04), hs-CRP (standardized beta = 0.18, p =0.0008), and incident any CHD (standardized beta = 0.51, p = 0.05), than the Y7 Lp(a) concentration itself (no significant associations). Conclusions: To our knowledge, this is the first study to identify relationships between Lp(a) and associated metabolomic/proteomic features in young, healthy adults and joint associations with ASCVD phenotypes. The multi-omics approaches employed here provide insight into the pathobiology of Lp(a)-driven ASCVD and enable more nuanced mechanistic risk assessment compared with Lp(a) concentrations alone.