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Published on: January 28, 2020
A Novel Protein Glycan-Derived Inflammation Biomarker Independently Predicts Cardiovascular Disease and Modifies the
Robert W McGarrah1,2, Jacob P Kelly3,2,4, Damian M Craig2
1Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC; robert.mcgarrah@dm.duke.edu.
Insights
Systemic inflammation, measured by GlycA, and HDL subclasses interact to predict mortality risk in secondary prevention patients. Combining these biomarkers improves clinical risk assessment for adverse events.
Area of Science:
- Cardiovascular Medicine
- Biomarker Discovery
- Inflammation Research
Background:
- Systemic inflammation may negatively affect High-Density Lipoprotein (HDL) function.
- GlycA, a novel biomarker for enzymatically glycosylated acute phase proteins, offers a measure of systemic inflammation.
Purpose of the Study:
- To assess the predictive performance of GlycA and HDL subclasses for adverse events.
- To investigate potential interactions between GlycA and HDL subclasses in a secondary prevention cohort.
Main Methods:
- Proton nuclear magnetic resonance spectroscopy was used to measure GlycA and HDL subclasses in 7617 individuals from the CATHGEN biorepository.
- Retrospective observational study design in a secondary prevention population.
Main Results:
- GlycA correlated with coronary artery disease presence and extent, and all-cause, cardiovascular, and noncardiovascular mortality.
- GlycA and smaller HDL subclasses demonstrated independent, opposing effects on mortality prediction; smaller HDL subclasses were protective.
- An interaction was observed where higher GlycA attenuated the protective effect of smaller HDL subclasses on mortality.
Conclusions:
- Systemic inflammation (GlycA) and HDL subclasses interact, influencing clinical outcomes.
- These biomarkers can enhance the precision of clinical risk assessment in secondary prevention populations.
Background:
Evidence suggests that systemic inflammation may adversely impact HDL function. In this study we sought to evaluate the independent and incremental predictive performance of GlycA-a novel serum inflammatory biomarker that is an aggregate measure of enzymatically glycosylated acute phase proteins-and HDL subclasses on adverse events in a retrospective observational study of a secondary prevention population and to understand a priori defined potential interactions between GlycA and HDL subclasses.
Methods:
GlycA and HDL subclasses were measured using proton nuclear magnetic resonance spectroscopy in 7617 individuals in the CATHGEN (CATHeterization GENetics) cardiac catheterization biorepository.
Results:
GlycA was associated with presence [odds ratio (OR) 1.07 (1.02-1.13), P = 0.01] and extent [OR 1.08 (1.03, 1.12) P < 0.0005] of coronary artery disease and with all-cause mortality [hazard ratio (HR) 1.34 (1.29-1.39), P < 0.0001], cardiovascular mortality [1.37 (1.30-1.45), P < 0.0001] and noncardiovascular mortality [1.46 (1.39-1.54) P < 0.0001] in models adjusted for 10 cardiovascular risk factors. GlycA and smaller HDL subclasses had independent but opposite effects on mortality risk prediction, with smaller HDL subclasses being protective [HR 0.69 (0.66-0.72), P < 0.0001]. There was an interaction between GlycA and smaller HDL subclasses-increasing GlycA concentrations attenuated the inverse association of smaller HDL subclasses with mortality. Adding GlycA and smaller HDL subclasses into the GRACE (Global Registry of Acute Coronary Events) and Framingham Heart Study Risk Scores improved mortality risk prediction, discrimination and reclassification.
Conclusions:
These findings highlight the interaction of systemic inflammation and HDL with clinical outcomes and may increase precision for clinical risk assessment in secondary prevention populations.
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