Glycans are an essential structural component of Immunoglobulin G (IgG) that modulate its structure and function. However, regulatory mechanisms behind this complex posttranslational modification are not well known. Previous genome-wide association studies (GWAS) identified 29 genomic regions involved in regulation of IgG glycosylation, but only a few were functionally validated. One of the key functional features of IgG glycosylation is the addition of galactose (galactosylation). We performed GWAS of IgG galactosylation (N=13,705) and identified 16 significantly associated loci, indicating that IgG galactosylation is regulated by a complex network of genes that extends beyond the galactosyltransferase enzyme that adds galactose to IgG glycans. Gene prioritization identified 37 candidate genes. Using a recently developed CRISPR/dCas9 system we manipulated gene expression of candidate genes in thein vitroIgG expression system. Up- and downregulation of three genes,EEF1A1,MANBAandTNFRSF13B, changed the IgG glycome composition, which confirmed that these three genes are involved in IgG galactosylation in this in vitro expression system.

Human plasma transferrin (Tf) N-glycosylation has been mostly studied as a marker for congenital disorders of glycosylation, alcohol abuse, and hepatocellular carcinoma. However, inter-individual variability of Tf N-glycosylation is not known, mainly due to technical limitations of Tf isolation in large-scale studies. Here, we present a highly specific robust high-throughput approach for Tf purification from human blood plasma and detailed characterization of Tf N-glycosylation on the level of released glycans by ultra-high-performance liquid chromatography based on hydrophilic interactions and fluorescence detection (HILIC-UHPLC-FLD), exoglycosidase sequencing, and matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS). We perform a large-scale comparative study of Tf and immunoglobulin G (IgG) N-glycosylation analysis in two human populations and demonstrate that Tf N-glycosylation is associated with age and sex, along with multiple biochemical and physiological traits. Observed association patterns differ compared to the IgG N-glycome corroborating tissue-specific N-glycosylation and specific N-glycans’ role in their distinct physiological functions.

It is often difficult to be certain which genes underlie the effects seen in association studies. However, variants that disrupt the protein, such as predicted loss of function (pLoF) and missense variants, provide a shortcut to identify genes with a clear biological link to the phenotype of interest. Glycosylation is one of the most common post-translationalmodifications of proteins, and an important biomarker of both disease and its progression. Here, we utilised the power of genetic isolates, gene-based aggregation tests and intermediate phenotypes to assess the effect of rare (MAF<5%) pLoF and missense variants from whole exome sequencing on the N-glycome of plasma transferrin (N=1907) and immunoglobulin G (N=4912), and their effect on diseases. We identified significant gene-based associations for transferrin glycosylation at 5 genes (p<8.06x10-8) and for IgG glycan traits at 4 genes (p<1.19x10-7). Associations in three of these genes (FUT8, MGAT3 and RFXAP) are driven by multiple rare variants simultaneously contributing to protein glycosylation. Association at ST6GAL1, with a 300-fold up-drifted variant in the Orkney Islands, was detectable by a single-point exome-wide association analysis. Glycome-associated aggregate associations are located in genes already known to have a biological link to protein glycosylation (FUT6, FUT8 for transferrin; FUT8, MGAT3 and ST6GAL1 for IgG) but also in genes which have not been previously reported (e.g. RFXAP for IgG). To assess the potential impact of rare variants associated with glycosylation on other traits, we queried public repositories of gene-based tests, discovering a potential connection between transferrin glycosylation, MSR1, galectin-3, insulin-like growth factor 1 and diabetes. However, the exact mechanism behind these connections requires further elucidation.