IgG <i>N-</i>glycans are associated with prevalent and incident complications of type 2 diabetes

Memarian, Elham; Heijmans, Ralph; Slieker, Roderick C.; Sierra, Adriana; Gornik, Olga; Beulens, Joline; Elders, Petra J. M.; Pascual, Julio; Sijbrands, Eric; Lauc, Gordan; Dotz, Viktoria; Barrios, Clara; Hart, Leen M. ‘t; Wuhrer, Manfred; Hoek, Mandy van

doi:10.1101/2022.03.15.22272417

Cited by 2 publications

(2 citation statements)

References 36 publications

(61 reference statements)

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“…In line, IgG-GP14 and IgG-GP18 were previously found to be cross-sectionally inversely associated with dyslipidemia in comparison to healthy controls, 48 and also associated with lower incidence and progression of complications of diabetes. 50…”

Section: Discussionmentioning

confidence: 99%

N-Glycosylation Profiles of Immunoglobulin G and Future Cardiovascular Events

Hoshi,

Plavša,

Liu

et al. 2024

Circulation Research

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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 LASSO-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.

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Section: Discussionmentioning

confidence: 99%

N-Glycosylation Profiles of Immunoglobulin G and Future Cardiovascular Events

Hoshi,

Plavša,

Liu

et al. 2024

Circulation Research

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“…recently, the rather strong glycomic signatures of cardiovascular conditions and metabolic disorders received more attention. 37,94,95 Obviously, there are pathological commonalities between different disease groups, with inflammatory responses being associated with various types of autoimmune and infectious diseases and cancers, but also metabolic and cardiovascular diseases. Interestingly, in terms of the TBNG signature, T2D sides with PC and to a lesser extent with CRC regarding sialylation features.…”

Section: Metabolic Disease Signature: T2dmentioning

confidence: 99%

The Human Blood N-Glycome: Unraveling Disease Glycosylation Patterns

Pongracz,

Mayboroda,

Wuhrer

2024

JACS Au

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Most of the proteins in the circulation are Nglycosylated, shaping together the total blood N-glycome (TBNG). Glycosylation is known to affect protein function, stability, and clearance. The TBNG is influenced by genetic, environmental, and metabolic factors, in part epigenetically imprinted, and responds to a variety of bioactive signals including cytokines and hormones. Accordingly, physiological and pathological events are reflected in distinct TBNG signatures. Here, we assess the specificity of the emerging disease-associated TBNG signatures with respect to a number of key glycosylation motifs including antennarity, linkagespecific sialylation, fucosylation, as well as expression of complex, hybrid-type and oligomannosidic N-glycans, and show perplexing complexity of the glycomic dimension of the studied diseases. Perspectives are given regarding the protein-and site-specific analysis of N-glycosylation, and the dissection of underlying regulatory layers and functional roles of blood protein N-glycosylation.

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IgG N-glycans are associated with prevalent and incident complications of type 2 diabetes

Cited by 2 publications

References 36 publications

N-Glycosylation Profiles of Immunoglobulin G and Future Cardiovascular Events

N-Glycosylation Profiles of Immunoglobulin G and Future Cardiovascular Events

The Human Blood N-Glycome: Unraveling Disease Glycosylation Patterns

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