GWAS summary statistics for UPLC IgG N-glycosylation traits

The majority of proteins undergo post-translational glycosylation, in which complex carbohydrates are attached to the surface of proteins. However, when studying glycoproteins, the glycan component is often neglected. Glycosylation can affect protein structure and function, as is the case with Immunoglobulin G, the most abundant antibody in human blood and an important component of the immune system. Effector functions of IgG require the addition of a glycan moiety and are regulated by the composition of the carbohydrate, thus affecting activity of the immune system. Aberrant glycosylation of IgG has been observed in many diseases, but little is understood about the mechanisms behind these changes. Here we show that the synthesis of the glycan fraction is under control of an interconnected set of genes. We performed the largest genome-wide association study of IgG N-glycosylation to date (N=8,090) and found 27 associated loci (15 novel) that explain up to 22% of variance in glycosylation level. We developed a data-driven network approach to propose how these genes form a functional network regulating glycosylation of IgG. From this network we confirmed in-vitro that the transcription factor IKZF1 regulates the expression of glycosyltransferase FUT8, resulting in increased levels of fucosylated glycans. We also found strong in-silico evidence that RUNX1 and RUNX3 transcription factors, together with SMARCB1 chromatin remodelling protein, regulate expression of glycosyltransferase MGAT3. We showed that glycosylation variants supporting this network are pleiotropic with inflammatory and autoimmune diseases, suggesting how variants with an effect on both IgG glycosylation levels and disease risk could influence glycosyltransferases and result in aberrant IgG glycosylation profiles observed in these diseases.

Klaric, Lucija; Tsepilov, Yakov A; Aulchenko, Yurii S; Lauc, Gordan; Hayward, Caroline. (2018). GWAS summary statistics for UPLC IgG N-glycosylation traits, [dataset]. MRC Human Genetics Unit. Institute of Genetics and Molecular Medicine. University of Edinburgh. https://doi.org/10.7488/ds/2481.