Rethinking ‘good cholesterol’ for cardiovascular risk stratification

Cardiovascular diseases (CVDs), and particularly atherosclerotic CVD (ASCVD), are the leading cause of death globally. Estimating individual risk of developing CVD is essential to determine the most appropriate management. This estimation includes demographic, clinical and biological parameters, which must be simple and easily accessible for physicians, especially in the primary-prevention setting which represents the vast majority of situations. The relationship between serum high-density lipoprotein cholesterol (HDL-C) and ASCVD events is well known, and it actually follows a U-shaped curve independently of other traditional cardiovascular risk markers. Guidelines on the primary prevention of CVD have long included serum HDL-C in the prediction models for cardiovascular risk, in a direct or indirect manner through non-HDL-C. New simple tools for cardiovascular risk stratification are needed because current prediction models have well-established limitations under certain conditions. For instance, both the Pooled Cohort Equations score and SCORE2 charts underestimate cardiovascular risk in individuals with socioeconomic disadvantage. Focusing on HDL antiatherogenic functions instead or in addition to HDL-C is a promising way to substantially improve cardiovascular risk stratification. HDLs have multiple antiatherogenic properties, such as the capacity to remove cholesterol from vascular cells and to prevent the recruitment of inflammatory cells into the arterial wall. They are complex multimolecular particles, and their antiatherogenic properties are related to their content in both proteins and lipids. It seems conceptually more clinically relevant to focus on HDL antiatherogenic functions for cardiovascular risk assessment rather than on just the cholesterol concentration in HDL particles, which does not mirror the complex pathophysiology of HDLs.