A big data approach to examine the association of high density lipoprotein cholesterol and mortality: lessons for future investigations

It has been a long-held understanding that higher levels of high density lipoprotein cholesterol (HDL-C)—colloquially referred to as the good cholesterol—are associated with reduced risk of cardiovascular events and death. The seminal observations were made in a 1988 report of 2,748 individuals from the Framingham Heart Study (1) where after 12 years of follow up, the researchers reported that compared to the highest quintile of HDL-C, the lowest quintile had increased risk of death from coronary heart disease in both men and women. The fundamental assumption of the analytic strategies undertaken by the Framingham investigators, which we later learned was not valid, was that the relationship between HDL-C and risk of death is linear where low levels of HDL-C are associated with increased risk, and higher levels are associated with reduced risk of death from coronary heart disease. Decades later, and thanks to the power of big data, our understanding has evolved as we have come to appreciate that the association between HDL-C and risk of death is not linear. The implicit assumption of linearity and comparison of risk in high HDL-C vis-à-vis low HDL-C groups (e.g., quintile 5 vs. quintile 1 in the Framingham studies), when the risk relationship might not be linear and risk may be increased at both ends of the HDL-C values spectrum, might obscure the presence of an association where one exists (2).