Loci associated with N-glycosylation of human IgG are not associated with rheumatoid arthritis: a Mendelian randomisation study

Unravelling the genetic causality of immunoglobulin G N-glycans in ischemic stroke

BACKGROUND

Evidence suggests that immunoglobulin G (IgG) N-glycosylation is associated with ischemic stroke (IS). However, the causality of IgG N-glycosylation for IS remains unknown.

METHODS

Two-sample Mendelian randomization (MR) analyses were performed to investigate the potential causal effects of genetically determined IgG N-glycans on IS using publicly available summarized genetic data from East Asian and European populations. Genetic instruments were used as proxies for IgG N-glycan traits. IgG N-glycans were analysed using ultra-performance liquid chromatography. Four complementary MR methods were performed, including the inverse variance weighted method (IVW), MR‒Egger, weighted median and penalized weighted median. Furthermore, to further test the robustness of the results, MR based on Bayesian model averaging (MR-BMA) was then applied to select and prioritize IgG N-glycan traits as risk factors for IS.

RESULTS

After correcting for multiple testing, in two-sample MR analyses, genetically predicted IgG N-glycans were unrelated to IS in both East Asian and European populations, and the results remained consistent and robust in the sensitivity analysis. Moreover, MR-BMA also showed consistent results in both East Asian and European populations.

CONCLUSIONS

Contrary to observational studies, the study did not provide enough genetic evidence to support the causal associations of genetically predicted IgG N-glycan traits and IS, suggesting that N-glycosylation of IgG might not directly involve in the pathogenesis of IS.

Genome-Wide Mapping of Plasma IgG N-Glycan Quantitative Trait Loci Identifies a Potentially Causal Association between IgG N-Glycans and Rheumatoid Arthritis

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 ratio_GP4 = 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.

Promising role of polymeric nanoparticles in the treatment of rheumatoid arthritis

Rheumatoid arthritis (RA) is a chronic inflammatory illness caused by an autoimmune disorder of synovial membrane resulting in synovial membrane dysfunction. The available treatment particularly focuses on inhibiting macrophage proliferation and reducing the generation of pro-inflammatory cytokines. However, therapeutic success of current treatment options at targeted site is limited; therefore, development of promising therapeutic strategy is the need of time that may provide better targeted delivery of drug with added safety. In development of precision medicine to manage RA, nanotechnology is a viable option to be considered. Recent research using nanoparticles for the treatment of RA, particularly polymeric nanoparticles, has been discussed in this article. Using polymeric nanoparticles as a therapeutic method has shown considerable promise of enhancing treatment success over standard medications used in routine. It is exclusively evident that the viability of using nanoparticles is mainly owed due to their biocompatibility, chemical stability, controlled drug release, and selective drug delivery to inflamed tissues in RA model animals. The current analysis focuses on the critical design characteristics of RA-targeted nanotechnology-based strategies in quest of better therapeutic strategies for RA, and to identify leading polymer as the most effective medications in RA therapy.

Investigation of the causal relationships between human IgG N-glycosylation and twelve common diseases associated with changes in the IgG N-glycome

Changes in the N-glycosylation of immunoglobulin G (IgG) are often observed in pathological states, such as autoimmune, inflammatory, neurodegenerative, cardiovascular diseases and some types of cancer. However, in most cases it is not clear if the disease onset causes these changes, or if the changes in IgG N-glycosylation are among the risk factors for the diseases. The aim of this study was to investigate the casual relationships between IgG N-glycosylation traits and 12 diseases, in which the alterations of IgG N-glycome were previously reported, using Two Sample Mendelian Randomization (MR) approach. We have performed Two Sample MR using publicly available summary statistics of genome-wide association studies of IgG N-glycosylation and disease risks. Our results indicate positive causal effect of systemic lupus erythematosus (SLE) on the abundance of N-glycans with bisecting N-acetylglucosamine in the total IgG N-glycome. Therefore, we suggest regarding this IgG glycosylation trait as a biomarker of SLE. We also emphasize the need for more powerful GWAS studies of IgG N-glycosylation to further elucidate the causal effect of IgG N-glycome on the diseases.

Causal risk and protective factors in rheumatoid arthritis: A genetic update

The characterization of risk and protective factors in complex diseases such as rheumatoid arthritis (RA) has evolved from epidemiological studies, which test association, to the use of Mendelian randomization approaches, which test direct relationships. Indeed, direct associations with the mucosal origin of RA are retrieved with periodontal disease (Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans predominantly), interstitial lung involvement, tobacco smoking and air pollutants. Next, factors directly associated with an acquired immune response include genetic factors (HLA DRB1, PTPN22), capacity to produce anti-modified protein antibodies (AMPA), and relatives with a history of autoimmune diseases. Finally, factors can be also classified according to their direct capacity to interfere with the IL-6/CRP/sIL-IL6R proinflammatory pathway as risk factor (body fat, cardiometabolic factors, type 2 diabetes, depressive syndrome) or either as protective factors by controlling of sIL-6R levels (higher education level, and intelligence). Although some co-founders have been characterized (e.g. vitamin D, physical activity, cancer) the direct association with sex-discrepancy, pregnancy, and infections among other factors remains to be better explored.

Modifiable environmental exposure and risk of rheumatoid arthritis-current evidence from genetic studies

Rheumatoid arthritis (RA) is a multifactorial chronic autoimmune disease, which involves a complex interplay of environmental triggers and genetic components in its etiology. It has been shown that genetics only explain about half of the liability to develop RA, leaving a large room for non-genetic factors. Indeed, several environmental exposures including smoking, drinking, obesity, and dietary patterns (and more) have been identified to be associated with RA risk, yet the observational nature of conventional epidemiological investigation hampers causal inference, as the validity of results could be plagued by measurement error, confounding, and/or reverse causality. Mendelian randomization (MR) is a novel statistical approach that uses genetic variants as instrumental variables (IV) to make causal inferences from observational data. The current genetic discoveries in the many heritable and modifiable human complex traits have provided an exceptional opportunity to evaluate a putative causal relationship between exposure and outcome in the absence of high-quality experimental or intervention studies, through a MR design. In the current review, we detail the contribution of MR studies hitherto conducted for modifiable environmental exposures with the risk of RA to understand the role of these factors in RA pathogenesis. We start with a brief introduction of each study, follow by a summarization of shortcomings and conclude by highlighting future directions. The application of MR design in the field of rheumatology remains limited. Only a few MR studies have examined the causal roles of vitamin D, cigarette smoking, alcohol consumption, coffee consumption, and levels of education in RA, where, no consistent evidence for a causal relationship has been found. Most studies lacked sensitivity analyses to verify MR model assumptions and to guarantee the validity of results. Almost all studies are likely to bias the strength of association towards a null value, since they used IVs from earlier GWAS(s) of exposures with a small sample size (i.e., few genetic markers). As the magnitudes of GWAS expand rapidly, additional trait-associated loci have been discovered. Incorporating these loci would greatly improve the strength of genetic instruments, as well as both the accuracy and precision of MR estimates. To conclude, there is a need for an update and a huge space for improvement of future MR studies in RA.

Current Understanding of an Emerging Role of HLA-DRB1 Gene in Rheumatoid Arthritis-From Research to Clinical Practice

Rheumatoid arthritis (RA) is an autoimmune disease with an unclear pathogenic mechanism. However, it has been proven that the key underlying risk factor is a genetic predisposition. Association studies of the HLA-DRB1 gene clearly indicate its importance in RA morbidity. This review presents the current state of knowledge on the impact of HLA-DRB1 gene, functioning both as a component of the patient’s genome and as an environmental risk factor. The impact of known HLA-DRB1 risk variants on the specific structure of the polymorphic HLA-DR molecule, and epitope binding affinity, is presented. The issues of the potential influence of HLA-DRB1 on the occurrence of non-articular disease manifestations and response to treatment are also discussed. A deeper understanding of the role of the HLA-DRB1 gene is essential to explore the complex nature of RA, which is a result of multiple contributing factors, including genetic, epigenetic and environmental factors. It also creates new opportunities to develop modern and personalized forms of therapy.

Comparative study for haplotype block partitioning methods - Evidence from chromosome 6 of the North American Rheumatoid Arthritis Consortium (NARAC) dataset

Haplotype-based methods compete with “one-SNP-at-a-time” approaches on being preferred for association studies. Chromosome 6 contains most of the known genetic biomarkers for rheumatoid arthritis (RA) disease. Therefore, chromosome 6 serves as a benchmark for the haplotype methods testing. The aim of this study is to test the North American Rheumatoid Arthritis Consortium (NARAC) dataset to find out if haplotype block methods or single-locus approaches alone can sufficiently provide the significant single nucleotide polymorphisms (SNPs) associated with RA. In addition, could we be satisfied with only one method of the haplotype block methods for partitioning chromosome 6 of the NARAC dataset? In the NARAC dataset, chromosome 6 comprises 35,574 SNPs for 2,062 individuals (868 cases, 1,194 controls). Individual SNP approach and three haplotype block methods were applied to the NARAC dataset to identify the RA biomarkers. We employed three haplotype partitioning methods which are confidence interval test (CIT), four gamete test (FGT), and solid spine of linkage disequilibrium (SSLD). P-values after stringent Bonferroni correction for multiple testing were measured to assess the strength of association between the genetic variants and RA susceptibility. Moreover, the block size (in base pairs (bp) and number of SNPs included), number of blocks, percentage of uncovered SNPs by the block method, percentage of significant blocks from the total number of blocks, number of significant haplotypes and SNPs were used to compare among the three haplotype block methods. Individual SNP, CIT, FGT, and SSLD methods detected 432, 1,086, 1,099, and 1,322 associated SNPs, respectively. Each method identified significant SNPs that were not detected by any other method (Individual SNP: 12, FGT: 37, CIT: 55, and SSLD: 189 SNPs). 916 SNPs were discovered by all the three haplotype block methods. 367 SNPs were discovered by the haplotype block methods and the individual SNP approach. The P-values of these 367 SNPs were lower than those of the SNPs uniquely detected by only one method. The 367 SNPs detected by all the methods represent promising candidates for RA susceptibility. They should be further investigated for the European population. A hybrid technique including the four methods should be applied to detect the significant SNPs associated with RA for chromosome 6 of the NARAC dataset. Moreover, SSLD method may be preferred for its favored benefits in case of selecting only one method.

Inflammatory Stress Causes N-Glycan Processing Deficiency in Ocular Autoimmune Disease

High levels of proinflammatory cytokines have been associated with a loss of tissue function in ocular autoimmune diseases, but the basis for this relationship remains poorly understood. Here we investigate a new role for tumor necrosis factor α in promoting N-glycan-processing deficiency at the surface of the eye through inhibition of N-acetylglucosaminyltransferase expression in the Golgi. Using mass spectrometry, complex-type biantennary oligosaccharides were identified as major N-glycan structures in differentiated human corneal epithelial cells. Remarkably, significant differences were detected between the efficacies of cytokines in regulating the expression of glycogenes involved in the biosynthesis of N-glycans. Tumor necrosis factor α but not IL-1β had a profound effect in suppressing the expression of enzymes involved in the Golgi branching pathway, including N-acetylglucosaminyltransferases 1 and 2, which are required for the formation of biantennary structures. This decrease in gene expression was correlated with a reduction in enzymatic activity and impaired N-glycan branching. Moreover, patients with ocular mucous membrane pemphigoid were characterized by marginal N-acetylglucosaminyltransferase expression and decreased N-glycan branching in the conjunctiva. Together, these data indicate that proinflammatory cytokines differentially influence the expression of N-glycan-processing enzymes in the Golgi and set the stage for future studies to explore the pathophysiology of ocular autoimmune diseases.

Low galactosylation of IgG associates with higher risk for future diagnosis of rheumatoid arthritis during 10 years of follow-up

Antibodies are known to have an important role in the development of rheumatoid arthritis (RA), one of the most prevalent chronic inflammatory diseases which primarily involves the joints. Most RA patients develop autoantibodies against immunoglobulin G (IgG) and changes in IgG glycosylation have been associated with RA. We undertook this study to determine whether altered IgG glycosylation precedes the disease diagnosis. We studied IgG glycosylation in RA in two prospective cohorts (N = 14,749) by measuring 28 IgG glycan traits in 179 subjects who developed RA within 10-years follow-up and 358 matched controls. Ultra-performance liquid chromatography method based on hydrophilic interactions (HILIC-UPLC) was used to analyse IgG glycans. Future RA diagnosis associated with traits related to lower galactosylation and sialylation of IgG when comparing the cases to the matched controls. In RA cases, these traits did not correlate with the time between being recruited to the study and being diagnosed with RA (median time 4.31 years). The difference in IgG glycosylation was relatively stable and present years before diagnosis. This indicates that long-acting factors affecting IgG glycome composition are among the underlying mechanisms of RA and that decreased galactosylation is a pre-existing risk factor involved in the disease development.

Insight into rheumatological cause and effect through the use of Mendelian randomization

Establishing causality of risk factors is important to determine the pathogenetic mechanisms underlying rheumatic diseases, and can facilitate the design of interventions to improve care for affected patients. The presence of unmeasured confounders, as well as reverse causation, is a challenge to the assignment of causality in observational studies. Alleles for genetic variants are randomly inherited at meiosis. Mendelian randomization analysis uses these genetic variants to test whether a particular risk factor is causal for a disease outcome. In this Review of the Mendelian randomization technique, we discuss published results and potential applications in rheumatology, as well as the general clinical utility and limitations of the approach.