GLYC-A 

 

 * Glyc-A (Glycoprotein Acetylation) is associated with chronic inflammation and predicts long term risk of severe infection.

Atherosclerosis. 2018 Jul 26;277:1-6. doi: 10.1016/j.atherosclerosis.2018.07.029. [Epub ahead of print]

Effects of regular endurance exercise on GlycA: Combined analysis of 14 exercise interventions.

Abstract

BACKGROUND AND AIMS:

GlycA is a relatively new biomarker for inflammation as well as cardiometabolic disease risk. However, the effect of exercise on GlycA is largely unknown. Therefore, the purpose of this study was to examine the effects of regular exercise on the inflammatory marker GlycA across seven studies and 14 exercise interventions.

METHODS:

Nuclear magnetic resonance spectroscopy, specifically signal amplitudes originating from the N-acetyl methyl group protons of the N-acetylglucosamine residues on the glycan branches of glycoproteins, was used to quantify GlycA concentrations. GlycA was measured before and after completion of an exercise intervention in 1568 individuals across seven studies and 14 exercise interventions. Random effects inverse variance weighting models were used to pool effects across interventions.

RESULTS:

Combined analysis of unadjusted data showed that regular exercise significantly (p = 2 × 10-6) reduced plasma GlycA(-8.26 ± 1.8 μmol/L). This reduction remained significant (-9.12 ± 1.9 μmol/L, p = 1.22 × 10-6) following adjustment for age, sex, race, baseline BMI, and baseline GlycA. Changes in GlycA were correlated with changes in traditional inflammatory markers, C-reactive protein, interleukin-6, and fibrinogen, however, these correlations were relatively weak (range r: 0.21-0.38, p < 0.0001).

CONCLUSIONS:

Regular exercise significantly reduced plasma GlycA across 14 different exercise interventions despite differences in exercise programs and study populations. The current study provides a greater understanding of the use of exercise as a potential therapy for the reduction of systemic inflammation. Further research is needed to understand the mechanisms behind the exercise-related reductions in GlycA.

Anatol J Cardiol. 2018 Sep;20(3):152-158. doi: 10.14744/AnatolJCardiol.2018.01058.

Increased glycoprotein acetylation is associated with high cardiac event rates: Analysis using coronary computed tomography angiography.

An LLiu QFeng HBai XDang YLi CYang ZLi J1.

Author information

Abstract

OBJECTIVE:

Glycoprotein acetylation (GlycA), an emerging inflammatory biomarker, has been used as an indicator of cardiovascular disease. Our research aimed to evaluate the correlation between GlycA and coronary artery disease (CAD) using coronary computed tomography angiography (CCTA).

METHODS:

In the present study, a total of 342 patients were enrolled, and each of them underwent CCTA. The correlation between GlycAand major adverse cardiac events (MACE) was detected via Cox's proportional hazards models. Based on differences in the GlycA level, patients were categorized into three groups (T1, T2, and T3).

RESULTS:

Compared with the group with the lowest GlycA level (T1), the group with the highest GlycA level (T3) exhibited stronger atherosclerotic pressure involving the extent of atherosclerotic plaque and risk of obstructive CAD. In addition, the patients in the T3 group had a greater chance of experiencing MACE and higher all-cause mortality than those in the T1 group. Among patients without CAD who underwent CCTA, those with high GlycA levels experienced elevated atherosclerotic stress and heightened risk of MACE compared with those with low GlycA levels.

CONCLUSION:

These results suggest that serum GlycA is significantly associated with the long-term clinical results of patients with no known CAD undergoing CCTA. The risks of death and experiencing MACE increase among patients with high GlycA levels.

J Transl Med. 2017 Oct 27;15(1):219. doi: 10.1186/s12967-017-1321-6.

GlycA, a novel biomarker of systemic inflammation and cardiovascular disease risk.

BACKGROUND:

GlycA is a novel spectroscopic marker of systemic inflammation with low intra-individual variability and other attributes favoring its clinical use in patients with chronic inflammatory and autoimmune diseases. GlycA is unique in its composite nature, reflecting both increased glycan complexity and circulating acute phase protein levels during local and systemic inflammation. Recent studies of GlycAfrom cross-sectional, observational and interventional studies have been highly informative, demonstrating that GlycA is elevated in acute and chronic inflammation, predicts death in healthy individuals and is associated with disease severity in patients with chronic inflammatory diseases such as rheumatoid arthritis, psoriasis and lupus. Moreover, following treatment with biological therapy in psoriasis, reduction in skin disease severity was accompanied by a decrease in GlycA levels and improvement in vascular inflammation.

CONCLUSIONS:

Collectively, these findings suggest GlycA is a marker that tracks systemic inflammation and subclinical vascular inflammation. However, larger prospective studies and randomized trials are necessary in order to assess the impact of novel therapies on GlycA in patients with chronic inflammatory conditions, which may be concomitant with cardiovascular benefits.

Cell Syst. 2015 Oct 28;1(4):293-301. doi: 10.1016/j.cels.2015.09.007. Epub 2015 Oct 22.

The Biomarker GlycA Is Associated with Chronic Inflammation and Predicts Long-Term Risk of Severe Infection.

Highlights

  • GlycA is a biomarker for chronic inflammation, neutrophil activity, and risk of future severe infection.

  • Elevated GlycA was stable within individuals for up to a decade.

  • GlycA marked the levels of myriad inflammatory cytokines in circulation.

  • A gene network enriched for neutrophil functions was associated with GlycA.

  • GlycA strongly predicted future risk of hospitalization and death from infection.

Summary

  • The biomarker glycoprotein acetylation (GlycA) has been shown to predict risk of cardiovascular disease and all-cause mortality. Here, we characterize biological processes associated with GlycA by leveraging population-based omics data and health records from >10,000 individuals.

  • Our analyses show that GlycA levels are chronic within individuals for up to a decade. In apparently healthy individuals, elevated GlycA corresponded to elevation of myriad inflammatory cytokines, as well as a gene coexpression network indicative of increased neutrophil activity, suggesting that individuals with high GlycA may be in a state of chronic inflammatory response.

  • Accordingly, analysis of infection-related hospitalization and death records showed that increased GlycA increased long-term risk of severe non-localized and respiratory infections, particularly septicaemia and pneumonia.

  • In total, our work demonstrates that GlycA is a biomarker for chronic inflammation, neutrophil activity, and risk of future severe infection. It also illustrates the utility of leveraging multi-layered omics data and health records to elucidate the molecular and cellular processes associated with biomarkers.

J Am Heart Assoc. 2016 Jul 13;5(7). pii: e003822. doi: 10.1161/JAHA.116.003822.

Circulating N-Linked Glycoprotein Side-Chain Biomarker, Rosuvastatin Therapy, and Incident Cardiovascular Disease: An Analysis From the JUPITER Trial.

Akinkuolie AO1, Glynn RJ2, Padmanabhan L1, Ridker PM3, Mora S4.

Author information

  • 1Center for Lipid Metabolomics, Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.

  • 2Center for Lipid Metabolomics, Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA Department of Biostatistics, Harvard School of Public Health, Boston, MA.

  • 3Center for Lipid Metabolomics, Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.

  • 4Center for Lipid Metabolomics, Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA Division of Cardiovascular Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA smora@partners.org.

Abstract

BACKGROUND:

GlycA, a novel protein glycan biomarker of N-acetyl side chains of acute-phase proteins, was recently associated with incident cardiovascular disease (CVD) in healthy women. Whether GlycA predicts CVD events in the setting of statin therapy in men and women without CVD but with evidence of chronic inflammation is unknown.

METHODS AND RESULTS:

In the Justfication for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER) trial (NCT00239681), participants with low-density lipoprotein cholesterol <130 mg/dL and high-sensitivity C-reactive protein (hsCRP) ≥2 mg/L were randomized to rosuvastatin 20 mg/day or placebo. GlycA was quantified by nuclear magnetic resonance spectroscopy in 12 527 before randomization and 10 039 participants at 1 year. A total of 310 first primary CVD events occurred during maximum follow-up of 5.0 years (median, 1.9). GlycA changed minimally after 1 year on study treatment: 6.8% and 4.7% decrease in the rosuvastatin and placebo groups, respectively. Overall, baseline GlycA levels were associated with increased risk of CVD: multivariable-adjusted hazard ratio (HR) per SD increment, 1.20 (95% CI, 1.08-1.34; P=0.0006). After additionally adjusting for hsCRP, this was slightly attenuated (HR, 1.18; 95% CI, 1.04-1.35; P=0.01). On-treatment GlycA levels were also associated with CVD; corresponding multivariable-adjusted HRs per SD before and after additionally adjusting for hsCRP: 1.27 (95% CI, 1.13-1.42; P<0.0001) and 1.24 (95% CI, 1.07-1.44; P=0.004), respectively. Tests for heterogeneity by treatment arm were not significant (P for interaction, >0.20).

CONCLUSION:

In the JUPITER trial, increased levels of GlycA were associated with an increased risk of CVD events independent of traditional risk factors and hsCRP.

Clin Chem. 2016 Jul;62(7):1020-31. doi: 10.1373/clinchem.2016.255828. Epub 2016 May 12.

Comparison of the Predictive Value of GlycA and Other Biomarkers of Inflammation for Total Death, Incident Cardiovascular Events, Noncardiovascular and Noncancer Inflammatory-Related Events, and Total Cancer Events.

Duprez DA1, Otvos J2, Sanchez OA3, Mackey RH4, Tracy R5, Jacobs DR Jr6.

Author information

  • 1Cardiovascular Division, School of Medicine, University of Minnesota, Minneapolis, MN; dupre007@umn.edu.

  • 2LabCorp, Raleigh, NC;

  • 3Department of Internal Medicine, Division of Nephrology, School of Medicine, University of Minnesota, Minneapolis, MN;

  • 4University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA;

  • 5Department of Pathology & Laboratory Medicine, and Biochemistry, University of Vermont College of Medicine, Colchester, VT;

  • 6Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN.

Abstract

BACKGROUND:

GlycA is a biomarker that reflects integrated concentrations and glycosylation states of several acute-phase proteins. We studied the association of GlycA and inflammatory biomarkers with future death and disease.

METHODS:

A total of 6523 men and women in the Multi-Ethnic Study of Atherosclerosis who were free of overt cardiovascular disease (CVD) and in generally good health had a baseline blood sample taken. We assayed high-sensitivity C-reactive protein (hsCRP), interleukin-6 (IL-6), and d-dimer. A spectral deconvolution algorithm was used to quantify GlycA signal amplitudes from automated nuclear magnetic resonance (NMR) LipoProfile® test spectra. Median follow-up was 12.1 years. Among 4 primary outcomes, CVD events were adjudicated, death was by death certificate, and chronic inflammatory-related severe hospitalization and death (ChrIRD) and total cancer were classified using International Classification of Diseases (ICD) codes. We used Poisson regression to study baseline GlycA, hsCRP, IL-6, and d-dimer in relation to total death, CVD, ChrIRD, and total cancer.

RESULTS:

Relative risk per SD of GlycA, IL-6, and d-dimer for total death (n = 915); for total CVD (n = 922); and for ChrIRD (n = 1324) ranged from 1.05 to 1.20, independently of covariates. In contrast, prediction from hsCRP was statistically explained by adjustment for other inflammatory variables. Only GlycA was predictive for total cancer (n = 663). Women had 7% higher values of all inflammatory biomarkers than men and had a significantly lower GlycA prediction coefficient than men in predicting total cancer.

CONCLUSIONS:

The composite biomarker GlycA derived from NMR is associated with risk for total death, CVD, ChrIRD, and total cancer after adjustment for hsCRP, IL-6, and d-dimer. IL-6 and d-dimer contribute information independently of GlycA.

Cell Syst. 2015 Oct 28;1(4):293-301. doi: 10.1016/j.cels.2015.09.007. Epub 2015 Oct 22.

The Biomarker GlycA Is Associated with Chronic Inflammation and Predicts Long-Term Risk of Severe Infection.

Ritchie SC1, Würtz P2, Nath AP3, Abraham G1, Havulinna AS4, Fearnley LG1, Sarin AP5, Kangas AJ2, Soininen P6, Aalto K7, Seppälä I8, Raitoharju E8, Salmi M9, Maksimow M9, Männistö S10, Kähönen M11, Juonala M12, Ripatti S13, Lehtimäki T8, Jalkanen S7, Perola M4, Raitakari O14, Salomaa V10, Ala-Korpela M15, Kettunen J16, Inouye M17.

Author information

1Centre for Systems Genomics, School of BioSciences, The University of Melbourne, Parkville, 3010 Victoria, Australia; Department of Pathology, The University of Melbourne, Parkville, 3010 Victoria, Australia.

2Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu 90014, Finland.

3Centre for Systems Genomics, School of BioSciences, The University of Melbourne, Parkville, 3010 Victoria, Australia; Department of Microbiology and Immunology, The University of Melbourne, Parkville, 3010 Victoria, Australia.

4National Institute for Health and Welfare, Helsinki 00271, Finland; Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland.

5Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland.

6Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu 90014, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio 70211, Finland.

7MediCity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland.

8Department of Clinical Chemistry, Fimlab Laboratories, School of Medicine, University of Tampere, Tampere 33520, Finland.

9National Institute for Health and Welfare, Helsinki 00271, Finland; MediCity Research Laboratory, Department of Medical Microbiology and Immunology, University of Turku, Turku 20520, Finland.

10National Institute for Health and Welfare, Helsinki 00271, Finland.

11Department of Clinical Physiology, University of Tampere and Tampere University Hospital, FI-33521 Tampere, Finland.

12Department of Medicine, University of Turku and Division of Medicine, Turku University Hospital, FI-20520 Turku, Finland; Murdoch Childrens Research Institute, Parkville, 3052 Victoria, Australia.

13Institute for Molecular Medicine Finland, University of Helsinki, Helsinki 00014, Finland; Department of Public Health, University of Helsinki, Helsinki 00014, Finland.

14Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku 20520, Finland; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku 20520, Finland.

15Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu 90014, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio 70211, Finland; Oulu University Hospital, Oulu 90220, Finland; Computational Medicine, School of Social and Community Medicine, University of Bristol, Bristol BS8 1TH, UK; Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK.

16Computational Medicine, Institute of Health Sciences, University of Oulu, Oulu 90014, Finland; National Institute for Health and Welfare, Helsinki 00271, Finland; NMR Metabolomics Laboratory, School of Pharmacy, University of Eastern Finland, Kuopio 70211, Finland. Electronic address: johannes.kettunen@computationalmedicine.fi.

17Centre for Systems Genomics, School of BioSciences, The University of Melbourne, Parkville, 3010 Victoria, Australia; Department of Pathology, The University of Melbourne, Parkville, 3010 Victoria, Australia; Department of Microbiology and Immunology, The University of Melbourne, Parkville, 3010 Victoria, Australia. Electronic address: minouye@unimelb.edu.au.

 

Abstract

The biomarker glycoprotein acetylation (GlycA) has been shown to predict risk of cardiovascular disease and all-cause mortality. Here, we characterize biological processes associated with GlycA by leveraging population-based omics data and health records from >10,000 individuals. Our analyses show that GlycA levels are chronic within individuals for up to a decade.

  • In apparently healthy individuals, elevated GlycA corresponded to elevation of myriad inflammatory cytokines, as well as a gene coexpression network indicative of increased neutrophil activity, suggesting that individuals with high GlycA may be in a state of chronic inflammatory response.

 

Accordingly, analysis of infection-related hospitalization and death records showed that increased GlycA increased long-term risk of severe non-localized and respiratory infections, particularly septicaemia and pneumonia. In total, our work demonstrates that GlycA is a biomarker for chronic inflammation, neutrophil activity, and risk of future severe infection. It also illustrates the utility of leveraging multi-layered omics data and health records to elucidate the molecular and cellular processes associated with biomarkers.

Clin Biochem. 2015 Aug;48(12):811-4. doi: 10.1016/j.clinbiochem.2015.05.001. Epub 2015 May 11.

GlycA, a biomarker of inflammatory glycoproteins, is more closely related to the leptin/adiponectin ratio than to glucose tolerance status.

OBJECTIVES:

Plasma GlycA is a recently developed biomarker whose nuclear magnetic resonance signal originates from glycosylated acute-phase proteins. The aim of our study was to determine potential relationships between GlycA and adiposity, insulin resistance (HOMA(ir)), high sensitive C-reactive protein (hs-CRP), leptin, adiponectin, and the leptin/adiponectin ratio, and to test whether GlycA is elevated in subjects with impaired fasting glucose (IFG) and type 2 diabetes mellitus (T2DM).

DESIGN AND METHODS:

Plasma GlycA, hs-CRP, leptin, adiponectin, the leptin/adiponectin ratio, and insulin resistance (HOMA(ir)) were measured in 103 fasting subjects (30 with normal fasting glucose, 25 with IFG and 48 with T2DM).

RESULTS:

In all subjects combined, plasma GlycA was correlated positively with body mass index (BMI), HOMA(ir), hs-CRP, leptin and the leptin/adiponectin ratio, and inversely with adiponectin (p < 0.05 to p < 0.001). GlycA did not significantly vary according to glucose tolerance category (p = 0.060). GlycA was related positively to the leptin/adiponectin ratio (p = 0.049), independent of BMI (p = 0.056) and HOMA(ir) (p = 0.50).

CONCLUSIONS:

High plasma GlycA reflects a pro-inflammatory state. Adipose tissue-associated inflammatory processes could contribute to increased circulating levels of glycosylated acute-phase proteins.

Clin Chem. 2015 May;61(5):714-23. doi: 10.1373/clinchem.2014.232918. Epub 2015 Mar 16.

GlycA: A Composite Nuclear Magnetic Resonance Biomarker of Systemic Inflammation.

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.