The Intermountain heart collaborative study Differential Association of High-Density Lipoprotein Particle Subclasses and GlycA, a Novel Inflammatory Marker, in Predicting Cardiac Death Among Patients Undergoing Angiography The Intermountain heart collaborative study • Joseph B. Muhlestein*† • Heidi T. may* • Deborah A. winegar ‡ • Jeffrey rollo* • margery a. connelly ‡ • james d. otvos* • Jeffrey L. Anderson *† *Intermountain Medical Center, Salt Lake City, UT †University of Utah, Salt Lake City, UT ‡LipoScience, Laboratory Corporation of America ® Holdings, Raleigh, NC No Conflicts of interests to disclose BACKGROUND HDL particle (HDL-P) concentrations are comprised of particles that vary in size and composition, and potentially, in cardiovascular risk prediction. Previous studies have demonstrated that the greatest cardiovascular protective effect from HDL-P appears to come from small HDL-P. Inflammation has been long associated with cardiovascular risk. We have previously reported that a recently identified novel marker of cardiovascular risk, GlycA, is an excellent predictor of cardiovascular risk. Inflammation is known to modulate HDL function. Whether increased inflammation alters associations of HDL subclasses with cardiovascular risk requires further study. STUDY OBJECTIVE Evaluate the association and interaction between various HDL sub-particles, the inflammatory marker GlycA, and future cardiovascular risk. METHOD A total of 2,848 consecutive patients of the angiography registry of the Intermountain Heart Study were evaluated. Patients were included if they underwent angiography for CAD determination, received a lipid panel as part of their clinical care, and had lipoprotein particle measurements determined by NMR spectroscopy (LipoScience, Inc., Raleigh, NC). Multivariable Cox hazard regression was utilized to determine the association of GlycA and HDL-P subclasses with cardiac death. Cardiac death was determined by the State of Utah death certificates. Covariables included in the multivariable models include age, sex, diabetes, hypertension, hyperlipidemia, smoking, HF, renal failure, prior MI, prior stroke, presentation (reason for angiography), discharge statin, discharge antiplatelet, discharge digoxin, discharge ACEI, heparin use prior to or during angiography, and lipoproteins. Hazard ratios (HR) are presented as per standard deviation (SD) increment. RESULTS Median levels (µmol/L) of small, medium, and large HDL-P were 2.9, 8.1, and 15.4, respectively. The median level of GlycA was 337.5 µm/L. Table 1. Baseline characteristics stratified by cardiac death FIGURE 1. MULTIVARIABLE HR (PRESENTED AS PER SD) FOR GLYCA AND THE HDL-P SUBCLASSES TO CARDIAC DEATH. THE MODEL INCLUDED GLYCA, THE HDL-P SUBCLASSES, BASELINE RISK FACTORS, CLINICAL CHARACTERISTICS, AND MEDICATIONS. Characteristics No Cardiac Death (n=2465) Cardiac Death (n=384) p-value Age (years) 62.3±11.9 70.1±11.3 <0.0001 Sex (male) 66.1% 63.7% 0.38 Hypertension 65.2% 74.5% Hyperlipidemia 65.0% 66.4% 0.59 Diabetes 24.0% 35.9% Family history 46.3% 41.4% 0.07 Smoking 16.9% 16.1% 0.72 Heart failure 12.9% 34.9% Renal failure 1.4% 4.2% Prior MI 12.7% 17.2% 0.02 Prior stroke 3.3% 5.2% 0.06 Presentation Stable angina 58.6% 58.9% Unstable angina 32.1% 27.6% MI 9.3% 13.5% CAD 47.7% Discharge statin 43.6% 53.6% Discharge antiplatelet 40.2% 40.6% 0.86 Discharge digoxin 2.8% 9.1% Discharge ACEI 27.0% 31.0% 0.11 Heparin use 37.7% 38.8% 0.69 Total cholesterol 173.8±41.1 166.0±42.6 0.001 LDL-C 102.3±35.3 95.4±33.5 HDL-C 41.0±12.9 40.4±14.8 0.39 Triglycerides 153.3±78.6 150.8±73.2 0.57 Model Variables Hazard Ratio, p-value Parsimonious MV model (age, heart failure, renal failure, atrial fibrillation, depression history, beta-blocker use, anti-diabetic use, digoxin use Model chi-square: 437.0 GlycA + small HDL-P +medium HDL-P + large HDL-P + MV Model chi-square: 479.3 GlycA 1.24, p<0.0001 Small HDL-P 0.81, p=0.001 Medium HDL-P 0.83, p=0.004 Large HDL-P 1.08, p=0.11 GlycA + small HDL-P +medium HDL-P + large HDL-P + (GlycA*small HDL-P) + (GlycA*medium HDL-P) + (GlycA*large HDL-P) MV Model chi-square: 486.1 1.34, p<0.0001 0.74, p<0.0001 0.84, p=0.01 1.06, p=0.28 GlycA*Small HDL-P 1.13, p=0.01 GlycA*Medium HDL-P 0.94, p=0.26 GlycA*Large HDL-P 1.00, p=1.00 GlycA + small HDL-P + medium HDL-P + (GlycA*small HDL-P) + MV Model chi-square: 481.2 1.36, p<0.0001 0.73, p<0.0001 0.82, p=0.003 Small HDL-P*GlycA 1.16, p<0.0001 TABLE 2. ASSOCIATION OF HDL-P SUBCLASSES AND GLYCA WITH CARDIAC DEATH. HAZARD RATIOS (HR) ARE PRESENTED AS PER STANDARD DEVIATION (SD) INCREMENT AND MODEL CHI-SQUARES ARE SHOWN (MEAN LENGTH OF FOLLOW-UP: 7.1±2.8 YEARS). MULTIVARIABLE (MV) MODELS ARE ADJUSTED BY BASELINE RISK FACTORS, CLINICAL CHARACTERISTICS, AND MEDICATIONS. CONCLUSION This study found that the inflammation biomarker, GlycA, and both small- and medium-size HDL particles are independent predictors of cardiac death. The observed interaction of GlycA with small HDL-P indicates that the protection afforded by high levels of small HDL-P is lessened in patients with elevated systemic inflammation. This interaction between systemic inflammation and the protective effect of HDL particles deserves further study.