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. 2024 Mar;134(5):e3-e14.
doi: 10.1161/CIRCRESAHA.123.323623. Epub 2024 Feb 13.

N-Glycosylation Profiles of Immunoglobulin G and Future Cardiovascular Events

Rosangela A Hoshi  1   2   3 , Branimir Plavša  4 , Yanyan Liu  1   3 , Irena Trbojević-Akmačić  5 , Robert J Glynn  3 , Paul M Ridker  2   3 , Richard D Cummings  6 , Ivan Gudelj  5   7 , Gordan Lauc  4   5 , Olga V Demler #  1   3   8 , Samia Mora #  1   2   3
Affiliations

N-Glycosylation Profiles of Immunoglobulin G and Future Cardiovascular Events

Rosangela A Hoshi et al. Circ Res. 2024 Mar.

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.

Keywords: cardiovascular diseases; glycosylation; immunoglobulin G; inflammation; risk factors.

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Conflict of interest statement

Disclosures R.A. Hoshi, G. Lauc, O.V. Demler, S. Mora, and B. Plavša are co-inventors on a patent application for a Method for prediction of future cardiovascular disease risk via analysis of IgG glycome assigned to GENOS d.o.o. and the Brigham and Women’s Hospital Inc. O.V. Demler received support from Kowa, not related to the current work. S. Mora has served as consultant to Pfizer for work outside the current study. G. Lauc is the founder and chief executive officer of Genos Ltd, a private research organization that specializes in high-throughput glycomics analysis and has several patents in this field. I. Trbojević-Akmačić and Ivan Gudelj are employees of Genos Ltd. P.M. Ridker received past investigator-initiated research grant support from AstraZeneca to conduct the JUPITER (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin) and has current investigator-initiated research grant support from Novartis, Novo Nordisk, Kowa, Amarin, Pfizer, Esperion, National Heart, Lung, and Blood Institute, Bristol Myers Squibb, and Operation Warp Speed; served as a consultant to Novartis, Flame, Agepha, Ardelyx, AstraZeneca, Janssen, Civi Biopharm, Glaxo Smith Kline, Socar, Novo Nordisk, Health Outlook, Montai Health, Eli Lilly, New Amsterdam, Boehringer-Ingelheim, RTI, Cytokinetics, Horizon Therapeutics, and Cardio Therapeutics; has minority shareholder equity positions in Uppton, Bitteroot Bio, and Angiowave; received nonmonetary research support from the Pfizer Bristol Myers Squibb Alliance and from Quidel Inc. to conduct federally funded COVID-19 research; and receives compensation for service on the Peter Munk Advisory Board (University of Toronto), the Leducq Foundation, Paris France, and the Baim Institute (Boston, MA). The other authors report no conflicts.

Figures

Figure 1.
Figure 1.. IgG-GPs 4, 12, 13, 14, 18, 20 were significantly associated with CVD in both JUPITER and TNT.
The graph displays conditional logistic regression HRs and 95%CIs for CVD events per SD increment in each IgG-GP. Significant results for model 2 in JUPITER (adjusted for age, statin randomization, race, LDL-C, HDL-C, smoking, hypertension) and validated in TNT (the same covariates as in JUPITER plus diabetes) are highlighted in dark turquoise and orange, respectively. The top panel shows the most abundant IgG N-glycan structure in each GP. Analyses were adjusted for multiple comparisons at the two-stage overall FDR level of 0.05 (FDR < 0.2 in each stage).
Figure 2.
Figure 2.. Derived IgG N-glycosylation traits agalactosylation, digalactosylation, asialylation, and monosialylation were significantly associated with CVD in both JUPITER and TNT.
Left panel: Conditional logistic regression HRs and 95%CIs for CVD risk per SD increment in derived IgG N-glycosylation traits. Significant results for model 2 in JUPITER (adjusted for age, statin randomization, race, LDL-C, HDL-C, smoking, hypertension) and validated in TNT (the same covariates as in JUPITER plus diabetes) are highlighted in dark turquoise and orange, respectively. Analyses were adjusted for multiple comparisons at the two-stage overall FDR level of 0.05 (FDR < 0.2 in each stage). *Borderline significant (FDR = 0.20). Right panel: Table for each derived IgG N-glycosylation trait calculation. Total GP: sum of all IgG-GPs.
Figure 3.
Figure 3.. LASSO regression selected 7 IgG-GPs out of which 4 were significantly associated with CVD and comprised the IgG glycan score.
Flowchart for JUPITER IgG-GPs selection for the IgG glycan score. *Adjusted for age, statin randomization, race, LDL-C, HDL-C, smoking, and hypertension. ** The IgG glycan score was a linear combination of these 4 IgG-GPs using the β-coefficients from an adjusted model controlled for age and intervention arm, defined as: −0.595*IgG-GP9 −0.272*IgG-GP12 +0.218*IgG-GP19 −0.264*IgG-GP20.
See this image and copyright information in PMC

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