Genome-wide mapping of plasma IgG N-glycan quantitative trait loci identifies a potentially causal association between IgG N-glycans and rheumatoid arthritis

Document Type

Journal Article

Publication Title

Journal of immunology

Volume

208

Issue

11

First Page

2508

Last Page

2514

PubMed ID

35545292

Publisher

American Association of Immunologists

School

Centre for Precision Health / School of Medical and Health Sciences

RAS ID

52021

Funders

National Nature Science Foundation of China NFSC; 81872682 and 81773527 / China-Australian Collaborative Grant NSFC 81561128020-NHMRC APP1112767 / China Scholarship Council (CSC) CSC 201908110339

Grant Number

NHMRC Number : APP1112767

Grant Link

http://purl.org/au-research/grants/nhmrc/1112767

Comments

Liu, D., Dong, J., Zhang, J., Xu, X., Tian, Q., Meng, X., ... & Wang, Y. (2022). Genome-Wide Mapping of Plasma IgG N-Glycan Quantitative Trait Loci Identifies a Potentially Causal Association between IgG N-Glycans and Rheumatoid Arthritis. The Journal of Immunology, 208(11), 2508-2514. https://doi.org/10.4049/jimmunol.2100080

Abstract

Observational studies highlight associations of IgG N-glycosylation with rheumatoid arthritis (RA); however, the causality between these conditions remains to be determined. Standard and multivariable two-sample Mendelian randomization (MR) analyses integrating a summary genome-wide association study for RA and IgG N-glycan quantitative trait loci (IgG N-glycan-QTL) data were performed to explore the potentially causal associations of IgG N-glycosylation with RA. After correcting for multiple testing (p < 2 × 10-3), the standard MR analysis based on the inverse-variance weighted method showed a significant association of genetically instrumented IgG N-glycan (GP4) with RA (odds ratioGP4 = 0.906, 95% confidence interval = 0.857-0.958, p = 5.246 × 10-4). In addition, we identified seven significant associations of genetically instrumented IgG N-glycans with RA by multivariable MR analysis (p < 2 × 10-3). Results were broadly consistent in sensitivity analyses using MR_Lasso, MR_weighted median, MR_Egger regression, and leave-one-out analysis with different instruments (all p values <0.05). There was limited evidence of pleiotropy bias (all p values > 0.05). In conclusion, our MR analysis incorporating genome-wide association studies and IgG N-glycan-QTL data revealed that IgG N-glycans were potentially causally associated with RA. Our findings shed light on the role of IgG N-glycosylation in the development of RA. Future studies are needed to validate our findings and to explore the underlying physiological mechanisms in the etiology of RA.

DOI

10.4049/jimmunol.2100080

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