ApoA-I not superior to HDL-c to predict coronary heart disease
Association of High-Density Lipoprotein-Cholesterol Versus Apolipoprotein A-I With Risk of Coronary Heart Disease: The European Prospective Investigation Into Cancer-Norfolk Prospective Population Study, the Atherosclerosis Risk in Communities Study, and the Women’s Health Study
Van Capelleveen JC, Bochem AE, Boekholdt M, et al. - JAHA 2017, Epub ahead of printBackground
As mendelian studies cannot show a causal association between HDL-c levels and coronary heart disease (CHD) [1] and pharmacological HDL-c stimulation lacks prove of effect in humans [2-4], the hypothesis had been raised that HDL-c may not have a causal protective effect against atherosclerosis development itself and other parameters that reflect the physical structure and role of HDL may serve as a more relevant predictor of CHD risk.
For example, apolipoprotein A-I (apoA-I), which is the major constituent of HDL particles. However, prospective studies in which the association of apoA-I and HDL-c with CHD risk has been investigated, show conflicting data [5,6]. This may be due to the complex relationship between the two parameters, that is hard to dissect in conventional regression models.
Therefore, a new approach had been used in this study, in which HDL-c and apoA-I levels were categorized into quartiles in a 4x4 fashion. Subsequently, the association of apoA-I levels with CHD risk as well as with CHD risk factors, was assessed within the four HDL-c quartiles, and vice versa. This was done using a subset of the large European Prospective investigation into Cancer (EPIC) Norfolk cohort (United Kingdom, n=17,661) and a validation was executed with a subset of the Atherosclerosis Risk in Communities (ARIC) cohort (n=15,494) and Women’s Health Study (WHS, n=27,552). Risk factors: age, male sex, BMI, HbA1c, non-HDL-c, triglycerides, ApoB, systolic blood pressure (SBP), c-reactive protein (CRP), metabolic syndrome and alcohol intake.
Main results
- 12.6% of the EPIC-Norfolk cohort experienced CHD.
- HR for CHD events highest versus lowest HDL-c quartile was 0.34 (95% CI 0.30-0.39, P trend <0.001). Fully adjusted, this was 0.69 (95% CI 0.59-0.80, P trend <0.001).
- HR for CHD events highest versus lowest apoA-I quartile was 0.55 (95% CI 0.49-0.62, P trend <0.001). Fully adjusted, this was 0.75 (95% CI 0.66-0.86, P trend <0.001).
- In almost half of the patients, HDL-c quartile and apoA-I quartile were discordant.
- Within each apoA-I quartile, higher HDL-c levels were associated with lower CHD risk. In contrast, within each HDL-c quartile, we did not find a consistent association between apoA-I and CHD risk. However, a trend towards increased CHD risk with higher apoA-I levels was observed in the middle HDL-c quartiles.
- HDL-c levels within apo-I quartiles were inversely associated with CHD risk factors (all P<0.001). However, opposite was true for apoA-I levels within HDL-c quartiles: positive association with age, female sex, BMI, HbA1c, non-HDL-c, triglycerides, apoB, SBP and CRP (all P<0.001).
- Validation with the ARIC study (19.3% CHD events) showed comparable results regarding CHD risk. Significant trends were seen for the majority of HDL-c and apoA-I quartiles for risk factors: male percentage, BMI, non-HDL-c, triglyceride, ApoB, SBP and metabolic syndrome.
- Validation with the WHS study were done with tertiles because of the low number of CHD events (3.9%). Also here, similar results were obtained.
Conclusion
In the EPIC-Norfolk cohort, HDL-c and apoA-I were strongly and inversely associated with CHD risk. However, these associations were not interchangeable as apoA-I levels did not show a similar trend within HDL-c quartiles, while vice versa, this was. Therefore, apoA-I levels do not offer predictive information over and above HDL-c. In contrast, an unexpected trend was even observed towards increased risk in some apoA-I quartiles. This was supported by a positive association of apoA-I levels with CHD risk factors within all HDL-c quartiles. All observations were confirmed in two independent cohorts, suggesting biological relevant associations.