Data-driven multivariate population subgrouping via lipoprotein phenotypes versus apolipoprotein B in the risk assessment of coronary heart disease

This study presents a novel application of an artificial intelligence algorithm, self-organizing maps (SOM), to define subgroups based on detailed lipoprotein profiles in large population-based cohort.

Four SOM-based subgroups of individuals with distinct lipoprotein profiles and CHD risk were identified and compared those to univariate subgrouping by apolipoprotein B quartiles. Results suggest that the majority of lipoprotein mediated CHD risk is explained by apolipoprotein B-containing lipoprotein particles.