N-Glycosylation Profiles of Immunoglobulin G and Future Cardiovascular Events

Author:

Hoshi Rosangela A.123ORCID,Plavša Branimir4ORCID,Liu Yanyan13,Trbojević-Akmačić Irena5ORCID,Glynn Robert J.3,Ridker Paul M.23,Cummings Richard D.6,Gudelj Ivan57,Lauc Gordan45ORCID,Demler Olga V.138ORCID,Mora Samia123ORCID

Affiliation:

1. Center for Lipid Metabolomics (R.A.H, Y.L., O.V.D., S.M.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA.

2. Division of Cardiovascular Medicine (R.A.H., P.M.R., S.M.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA.

3. Division of Preventive Medicine (R.A.H., Y.L., R.J.G., P.M.R., O.V.D., S.M.), Brigham and Women’s Hospital, Harvard Medical School, Boston, MA.

4. University of Zagreb Faculty of Pharmacy and Biochemistry, Zagreb, Croatia (B.P., G.L.).

5. Genos Glycoscience Research Laboratory, Zagreb, Croatia (I.T.-A., I.G., G.L.).

6. Department of Surgery, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA (R.D.C.).

7. Department of Biotechnology, University of Rijeka, Croatia (I.G.).

8. Computer Science Department, ETH Zurich, Switzerland (O.V.D.)

Abstract

BACKGROUND: Posttranslational glycosylation of IgG can modulate its inflammatory capacity through structural variations. We examined the association of baseline IgG N-glycans and an IgG glycan score with incident cardiovascular disease (CVD). METHODS: IgG N-glycans were measured in 2 nested CVD case-control studies: JUPITER (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin; NCT00239681; primary prevention; discovery; Npairs=162); and TNT trial (Treating to New Targets; NCT00327691; secondary prevention; validation; Npairs=397). Using conditional logistic regression, we investigated the association of future CVD with baseline IgG N-glycans and a glycan score adjusting for clinical risk factors (statin treatment, age, sex, race, lipids, hypertension, and smoking) in JUPITER. Significant associations were validated in TNT, using a similar model further adjusted for diabetes. Using least absolute shrinkage and selection operator regression, an IgG glycan score was derived in JUPITER as a linear combination of selected IgG N-glycans. RESULTS: Six IgG N-glycans were associated with CVD in both studies: an agalactosylated glycan (IgG-GP4) was positively associated, while 3 digalactosylated glycans (IgG glycan peaks 12, 13, 14) and 2 monosialylated glycans (IgG glycan peaks 18, 20) were negatively associated with CVD after multiple testing correction (overall false discovery rate <0.05). Four selected IgG N-glycans comprised the IgG glycan score, which was associated with CVD in JUPITER (adjusted hazard ratio per glycan score SD, 2.08 [95% CI, 1.52–2.84]) and validated in TNT (adjusted hazard ratio per SD, 1.20 [95% CI, 1.03–1.39]). The area under the curve changed from 0.693 for the model without the score to 0.728 with the score in JUPITER (PLRT=1.1×10 −6 ) and from 0.635 to 0.637 in TNT (PLRT=0.017). CONCLUSIONS: An IgG N-glycan profile was associated with incident CVD in 2 populations (primary and secondary prevention), involving an agalactosylated glycan associated with increased risk of CVD, while several digalactosylated and sialylated IgG glycans associated with decreased risk. An IgG glycan score was positively associated with future CVD.

Publisher

Ovid Technologies (Wolters Kluwer Health)

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