Polygenic determinants of global atherosclerotic plaque burden and progression assessed by 3D vascular ultrasound in young patients with early coronary artery disease

Introduction The rising incidence of early coronary artery disease (eCAD) events, and their recurrence despite medical management, represents a major public health concern, driven by heterogeneous and poorly understood mechanisms. Genetic burden, particularly polygenic risk, is becoming a key determinant of eCAD beyond cardiovascular risk factors (CVRF). However, the relationship between genetic susceptibility, atherosclerotic burden at presentation and its progression remains unexplored. Purpose To investigate the genetic determinants of global atherosclerosis plaque burden (GPB) and its progression in patients with eCAD, using genome-wide association studies (GWAS) and polygenic risk scores (PRS). Methods A cohort of 190 eCAD patients (<60yo) was consecutively and prospectively recruited. GPB, the sum of plaque volumes in bilateral carotid and femoral arteries measured by 3D vascular ultrasound (3DVUS), was assessed at baseline and its change (ΔGPB) evaluated after ~3 years of follow-up. CVRFs and blood biomarkers (lipid, inflammatory, immunological, coagulation) were assessed. GWAS were conducted using the FarmCPU model, adjusted for relevant covariates, to identify SNPs significantly associated with the phenotypes (P<10-5), which were then included in multivariate GLM models with other clinical variables, to assess the association with both GBP and ΔGPB. PRS were calculated using PRSice-2 and their prediction ability evaluated by incorporating them in the multivariate models. The potential biological implication of the genetic variants was also assessed via functional enrichment analysis. Results GWAS identified multiple SNPs independently associated with both GPB and ΔGPB, with no SNPs shared between them, indicating distinct genetic determinants of plaque burden and progression. Incorporating these genetic variants into multivariate models markedly improved the prediction of GPB and ΔGPB (R² increased from 0.26 to 0.52, and from 0.15 to 0.63, respectively; P<10⁻³). PRS showed improved risk stratification, with GPB and ΔGPB increasing across PRS-defined risk categories (low, intermediate and high), with significantly higher plaque burden and progression in individuals in the highest PRS category (Figure 1A). For GPB, enriched terms included molecular functions related to cell adhesion, protein binding, and ion transport activity, suggesting roles in intercellular communication and structural regulation. In contrast, genes associated with ΔGPB were enriched for protein binding and transcriptional regulation functions, with biological processes cantered around cell differentiation, development, and nervous system formation (Figure 1B). Conclusion Polygenic risk influences both baseline atherosclerotic burden and its progression in young eCAD patients via distinct genetic determinants. Integrating PRS with 3DVUS and clinical data improves risk stratification, supporting a precision-based approach to secondary prevention in eCAD.