GlycA: A Composite Nuclear Magnetic Resonance Biomarker of Systemic Inflammation

Abstract

Abstract BACKGROUND Nuclear magnetic resonance (NMR) spectra of serum obtained under quantitative conditions for lipoprotein particle analyses contain additional signals that could potentially serve as useful clinical biomarkers. One of these signals that we named GlycA originates from a subset of glycan N-acetylglucosamine residues on enzymatically glycosylated acute-phase proteins. We hypothesized that the amplitude of the GlycA signal might provide a unique and convenient measure of systemic inflammation. METHODS We developed a spectral deconvolution algorithm to quantify GlycA signal amplitudes from automated NMR LipoProfile® test spectra and assessed analytic precision and biological variability. Spectra of acute-phase glycoproteins and serum fractions were analyzed to probe the origins of the GlycA signal. GlycA concentrations obtained from archived NMR LipoProfile spectra of baseline plasma from 5537 participants in the Multi-Ethnic Study of Atherosclerosis (MESA) were used to assess associations with demographic and laboratory parameters including measures of inflammation. RESULTS Major acute-phase protein contributors to the serum GlycA signal are α1-acid glycoprotein, haptoglobin, α1-antitrypsin, α1-antichymotrypsin, and transferrin. GlycA concentrations were correlated with high-sensitivity C-reactive protein (hsCRP) (r = 0.56), fibrinogen (r = 0.46), and interleukin-6 (IL-6) (r = 0.35) (all P < 0.0001). Analytic imprecision was low (intra- and interassay CVs 1.9% and 2.6%, respectively) and intraindividual variability, assessed weekly for 5 weeks in 23 healthy volunteers, was 4.3%, lower than for hsCRP (29.2%), cholesterol (5.7%), and triglycerides (18.0%). CONCLUSIONS GlycA is a unique inflammatory biomarker with analytic and clinical attributes that may complement or provide advantages over existing clinical markers of systemic inflammation.