Dataset Information

Loci associated with N-glycosylation of human immunoglobulin G show pleiotropy with autoimmune diseases and haematological cancers.

ABSTRACT: Glycosylation of immunoglobulin G (IgG) influences IgG effector function by modulating binding to Fc receptors. To identify genetic loci associated with IgG glycosylation, we quantitated N-linked IgG glycans using two approaches. After isolating IgG from human plasma, we performed 77 quantitative measurements of N-glycosylation using ultra-performance liquid chromatography (UPLC) in 2,247 individuals from four European discovery populations. In parallel, we measured IgG N-glycans using MALDI-TOF mass spectrometry (MS) in a replication cohort of 1,848 Europeans. Meta-analysis of genome-wide association study (GWAS) results identified 9 genome-wide significant loci (P<2.27 × 10(-9)) in the discovery analysis and two of the same loci (B4GALT1 and MGAT3) in the replication cohort. Four loci contained genes encoding glycosyltransferases (ST6GAL1, B4GALT1, FUT8, and MGAT3), while the remaining 5 contained genes that have not been previously implicated in protein glycosylation (IKZF1, IL6ST-ANKRD55, ABCF2-SMARCD3, SUV420H1, and SMARCB1-DERL3). However, most of them have been strongly associated with autoimmune and inflammatory conditions (e.g., systemic lupus erythematosus, rheumatoid arthritis, ulcerative colitis, Crohn's disease, diabetes type 1, multiple sclerosis, Graves' disease, celiac disease, nodular sclerosis) and/or haematological cancers (acute lymphoblastic leukaemia, Hodgkin lymphoma, and multiple myeloma). Follow-up functional experiments in haplodeficient Ikzf1 knock-out mice showed the same general pattern of changes in IgG glycosylation as identified in the meta-analysis. As IKZF1 was associated with multiple IgG N-glycan traits, we explored biomarker potential of affected N-glycans in 101 cases with SLE and 183 matched controls and demonstrated substantial discriminative power in a ROC-curve analysis (area under the curve = 0.842). Our study shows that it is possible to identify new loci that control glycosylation of a single plasma protein using GWAS. The results may also provide an explanation for the reported pleiotropy and antagonistic effects of loci involved in autoimmune diseases and haematological cancer.

SUBMITTER: Lauc G

PROVIDER: S-EPMC3561084 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Loci associated with N-glycosylation of human immunoglobulin G show pleiotropy with autoimmune diseases and haematological cancers.

Lauc Gordan G Huffman Jennifer E JE Pučić Maja M Zgaga Lina L Adamczyk Barbara B Mužinić Ana A Novokmet Mislav M Polašek Ozren O Gornik Olga O Krištić Jasminka J Keser Toma T Vitart Veronique V Scheijen Blanca B Uh Hae-Won HW Molokhia Mariam M Patrick Alan Leslie AL McKeigue Paul P Kolčić Ivana I Lukić Ivan Krešimir IK Swann Olivia O van Leeuwen Frank N FN Ruhaak L Renee LR Houwing-Duistermaat Jeanine J JJ Slagboom P Eline PE Beekman Marian M de Craen Anton J M AJ Deelder André M AM Zeng Qiang Q Wang Wei W Hastie Nicholas D ND Gyllensten Ulf U Wilson James F JF Wuhrer Manfred M Wright Alan F AF Rudd Pauline M PM Hayward Caroline C Aulchenko Yurii Y Campbell Harry H Rudan Igor I

PLoS genetics 20130131 1

Glycosylation of immunoglobulin G (IgG) influences IgG effector function by modulating binding to Fc receptors. To identify genetic loci associated with IgG glycosylation, we quantitated N-linked IgG glycans using two approaches. After isolating IgG from human plasma, we performed 77 quantitative measurements of N-glycosylation using ultra-performance liquid chromatography (UPLC) in 2,247 individuals from four European discovery populations. In parallel, we measured IgG N-glycans using MALDI-TOF ...[more]

PMID: 23382691

Similar Datasets

Project description:ImportanceRecent genome-wide association studies (GWAS) and pathway analyses supported long-standing observations of an association between immune-mediated diseases and Parkinson disease (PD). The post-GWAS era provides an opportunity for cross-phenotype analyses between different complex phenotypes.ObjectivesTo test the hypothesis that there are common genetic risk variants conveying risk of both PD and autoimmune diseases (ie, pleiotropy) and to identify new shared genetic variants and their pathways by applying a novel statistical framework in a genome-wide approach.Design, setting, and participantsUsing the conjunction false discovery rate method, this study analyzed GWAS data from a selection of archetypal autoimmune diseases among 138 511 individuals of European ancestry and systemically investigated pleiotropy between PD and type 1 diabetes, Crohn disease, ulcerative colitis, rheumatoid arthritis, celiac disease, psoriasis, and multiple sclerosis. NeuroX data (6927 PD cases and 6108 controls) were used for replication. The study investigated the biological correlation between the top loci through protein-protein interaction and changes in the gene expression and methylation levels. The dates of the analysis were June 10, 2015, to March 4, 2017.Main outcomes and measuresThe primary outcome was a list of novel loci and their pathways involved in PD and autoimmune diseases.ResultsGenome-wide conjunctional analysis identified 17 novel loci at false discovery rate less than 0.05 with overlap between PD and autoimmune diseases, including known PD loci adjacent to GAK, HLA-DRB5, LRRK2, and MAPT for rheumatoid arthritis, ulcerative colitis and Crohn disease. Replication confirmed the involvement of HLA, LRRK2, MAPT, TRIM10, and SETD1A in PD. Among the novel genes discovered, WNT3, KANSL1, CRHR1, BOLA2, and GUCY1A3 are within a protein-protein interaction network with known PD genes. A subset of novel loci was significantly associated with changes in methylation or expression levels of adjacent genes.Conclusions and relevanceThe study findings provide novel mechanistic insights into PD and autoimmune diseases and identify a common genetic pathway between these phenotypes. The results may have implications for future therapeutic trials involving anti-inflammatory agents.

Project description:BACKGROUND AND AIMS:Causes of inflammatory bowel diseases are not well understood and the most prominent forms, Crohn's disease (CD) and ulcerative colitis (UC), are sometimes hard to distinguish. Glycosylation of IgG has been associated with CD and UC. IgG Fc-glycosylation affects IgG effector functions. We evaluated changes in IgG Fc-glycosylation associated with UC and CD, as well as with disease characteristics in different patient groups. METHODS:We analyzed 3441 plasma samples obtained from 2 independent cohorts of patients with CD (874 patients from Italy and 391 from the United States) or UC (1056 from Italy and 253 from the US and healthy individuals [controls]; 427 in Italy and 440 from the United States). IgG Fc-glycosylation (tryptic glycopeptides) was analyzed by liquid chromatography coupled to mass spectrometry. We analyzed associations between disease status (UC vs controls, CD vs controls, and UC vs CD) and glycopeptide traits, and associations between clinical characteristics and glycopeptide traits, using a logistic regression model with age and sex included as covariates. RESULTS:Patients with CD or UC had lower levels of IgG galactosylation than controls. For example, the odds ratio (OR) for IgG1 galactosylation in patients with CD was 0.59 (95% confidence interval [CI], 0.51-0.69) and for patients with UC was 0.81 (95% CI, 0.71-0.92). Fucosylation of IgG was increased in patients with CD vs controls (for IgG1: OR, 1.27; 95% CI, 1.12-1.44), but decreased in patients with UC vs controls (for IgG23: OR, 0.72; 95% CI, 0.63-0.82). Decreased galactosylation associated with more severe CD or UC, including the need for surgery in patients with UC vs controls (for IgG1: OR, 0.69; 95% CI, 0.54-0.89) and in patients with CD vs controls (for IgG23: OR, 0.78; 95% CI, 0.66-0.91). CONCLUSIONS:In a retrospective analysis of plasma samples from patients with CD or UC, we associated levels of IgG Fc-glycosylation with disease (compared to controls) and its clinical features. These findings could increase our understanding of mechanisms of CD and UC pathogenesis and be used to develop diagnostics or guide treatment.

Project description:ObjectiveSubtypes of juvenile idiopathic arthritis (JIA) share phenotypic features with other autoimmune disorders. We investigated several genetic variants associated with rheumatoid arthritis (RA) and other autoimmune disorders for association with JIA to test the hypothesis that clinically distinct phenotypes share common genetic susceptibility factors.MethodsCases were 445 children with JIA, and controls were 643 healthy adults. Using the TaqMan assay, subjects were genotyped for 8 single-nucleotide polymorphisms in 7 loci including rs10499194 and rs6920220 in the TNFAIP3 locus, rs6679677 in the RSBN1 locus, rs17696736 in the C12orf30 locus, rs3761847 in the TRAF1/C5 locus, rs2104286 in the IL2RA locus, rs7574865 in the STAT4 locus, and rs2542151 in the PTPN2 locus. Alleles and genotypes were analyzed for association with JIA and JIA subtypes. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated.ResultsThe strongest associations with JIA risk or protection were observed for TNFAIP3 variants rs10499194 (OR 0.74 [95% CI 0.61-0.91], P < 0.004) and rs6920220 (OR 1.30 [95% CI 1.05-1.61], P = 0.015). We also observed associations between JIA and both STAT4 (OR 1.24 [95% CI 1.02-1.51], P = 0.029) and C12orf30 (OR 1.20 [95% CI 1.01-1.43], P = 0.041) variants. The PTPN2 variant rs2542151 deviated from Hardy-Weinberg equilibrium and was excluded from analyses. Variants in IL2RA, TRAF1/C5, and RSBN1 were not associated with JIA. After stratification by JIA subtype, the TNFAIP3 and C12orf30 variants were associated with oligoarticular JIA, while the STAT4 variant was associated primarily with polyarticular JIA.ConclusionWe have demonstrated associations between JIA and variants in the TNFAIP3, STAT4, and C12orf30 regions that have previously shown associations with other autoimmune diseases, including RA and systemic lupus erythematosus. Our results suggest that clinically distinct autoimmune phenotypes share common genetic susceptibility factors.

Project description:BACKGROUND:Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. OBJECTIVES:This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci. METHODS:In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency >5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs. RESULTS:We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p < 1 × 10-4 with a range of other diseases/traits. CONCLUSIONS:We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk.

Dataset Information

Loci associated with N-glycosylation of human immunoglobulin G show pleiotropy with autoimmune diseases and haematological cancers.

Publications

Loci associated with N-glycosylation of human immunoglobulin G show pleiotropy with autoimmune diseases and haematological cancers.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets