Nonlinearity of the inverse relationship between high-density lipoprotein (HDL) cholesterol and incident cardiovascular risk: Is it time to revisit the "HDL hypothesis"?

Abstract

Background: Low levels of high-density lipoprotein cholesterol (HDL-C) are clearly associated with atherosclerotic cardiovascular disease (ASCVD), but the risk curve is not well defined, especially at very high and low HDL-C levels. Current proportional hazards prediction models assume inverse linearity of effect, which may not accurately represent risk at these levels.

Sources of material: Clinical inattention to risk associated with low HDL-C may derive from randomized controlled trials (RCTs) aimed at raising HDL-C, though most failed to reduce ASCVD events when combined with statin-based therapy. However, these prior trials enrolled patients with HDL-C levels largely in the 35-45 mg/dL range.

Abstract of findings: Mounting post hoc evidence from RCTsß as well as new genetic and observational data suggests that very low HDL-C (less than 30 or 35 mg/dL) may signal a further increase in incident cardiovascular events. Moreover, when HDL-C exceeds 90 mg/dL, monotonic reduction of ASCVD risk appears to reverse. Because a pervasively agnostic view of the importance of both very low and high levels of HDL-C now exists, consideration should be given to incorporating nonlinear effects of HDL-C into future risk prediction models such that very low HDL-C and/or very high HDL-C levels could be considered as new risk-enhancing factors to promote more optimal risk stratification.

Conclusion: When revision of the U.S. Cholesterol Guideline recommences, consideration should be directed to whether HDL-associated risk matches the assumptions of current statistical models. Thus, it may be both timely and opportune to revisit the "HDL Hypothesis" based on evolving scientific evidence.