A Novel Protein Glycan-Derived Inflammation Biomarker Independently Predicts Cardiovascular Disease and Modifies the Association of HDL Subclasses with Mortality.


Journal Article

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.

Full Text

Duke Authors

Cited Authors

  • McGarrah, RW; Kelly, JP; Craig, DM; Haynes, C; Jessee, RC; Huffman, KM; Kraus, WE; Shah, SH

Published Date

  • January 2017

Published In

Volume / Issue

  • 63 / 1

Start / End Page

  • 288 - 296

PubMed ID

  • 27811210

Pubmed Central ID

  • 27811210

Electronic International Standard Serial Number (EISSN)

  • 1530-8561

Digital Object Identifier (DOI)

  • 10.1373/clinchem.2016.261636


  • eng

Conference Location

  • England