Systematic approach demonstrates enrichment of multiple interactions between non-HLA risk variants and HLA-DRB1 risk alleles in rheumatoid arthritis

Identification of epistatic SNP combinations in rheumatoid arthritis using LAMPLINK and Japanese cohorts

Genome-wide association studies have enabled the identification of important genetic factors in many trait studies. However, only a fraction of the heritability can be explained by known genetic factors, even in the most common diseases. Genetic loci combinations, or epistatic contributions expressed by combinations of single nucleotide polymorphisms (SNPs), have been argued to be one of the critical factors explaining some of the missing heritability, especially in oligogenic/polygenic diseases. Rheumatoid arthritis (RA) is a complex disease with more than 100 reported SNP associations, as well as various HLA haplotypes and amino acids; however, many associations between RA and inter-chromosomal SNP combinations are unknown. To discover novel associations of epistatic interactions with high odds ratios in RA, we applied the LAMPLINK method, a systematic enumerative procedure for identifying high-order SNP combinations, to a Japanese RA cohort (discovery cohort; 4024 patients with RA and 7731 controls). We validated the identified associations in a different Japanese cohort (validation cohort; 810 RA patients and 6303 controls). In this study, we identified 90 significant genetic associations in the discovery cohort. Among these, 74 (82.2%) associations were replicated in the validation cohort, and eight combinations were inter-chromosomal, all of which comprised rs7765379 or rs35265698 located in the HLA region. These two SNPs exhibited strong correlations with valine at amino acid position 11 in HLA-DRB1 (HLA-DRB1-11-Val). Finally, we discovered that rs9624 showed an association with RA through an epistatic interaction with HLA-DRB1-11-Val. Overall, LAMPLINK showed high reliability for identifying epistatic genetic contributions hidden in complex traits.

Genetics of rheumatoid arthritis

Rheumatoid arthritis (RA) is an inflammatory autoimmune disease involving symmetric joints and is generally characterized by persistent pain, tenderness, and destruction of joints. The vast majority of RA patients produce autoantibodies, and immune cell involvement in disease development is well recognized, as is the contribution of other types of cells in synovial tissue, like fibroblasts. It is known that there are major genetic associations with the HLA locus, while multiple non-HLA genetic variants display relatively low risk of RA. Both HLA and non-HLA associations suggest that the profiles of genetic associations for autoantibody-positive vs. autoantibody-negative RA are different. Several alleles of HLA-DRB1 are associated with high risk for autoantibody-positive RA, with the strongest risk characterized by valine at position 11 of the protein sequence (HLA-DRB1*04 and *10 alleles). There is a strong protective effect for the risk of autoantibody-positive RA associated with HLA-DRB1*13 alleles. Although major genetic associations have been known for several years, understanding of the specific mechanisms in the development of increased risk of RA for these variations is work in progress. Current studies focus on the binding of immune receptors involved in recognition of putative peptides in activation of T cells, as well as investigation of cell signaling mechanisms. At least a part of RA risk could be explained by gene-gene and gene-environment interactions. There are currently more than 150 candidate loci with polymorphisms that associate with RA, mainly related to seropositive disease, and new discoveries are anticipated in the future from investigation of diverse human populations. This new research will help create a strong foundation for the continuing process of integrating genetic, epigenetic, transcriptomic, and proteomic data in studies of RA.

Impact of Posttranslational Modification in Pathogenesis of Rheumatoid Arthritis: Focusing on Citrullination, Carbamylation, and Acetylation

Rheumatoid arthritis (RA) is caused by prolonged periodic interactions between genetic, environmental, and immunologic factors. Posttranslational modifications (PTMs) such as citrullination, carbamylation, and acetylation are correlated with the pathogenesis of RA. PTM and cell death mechanisms such as apoptosis, autophagy, NETosis, leukotoxic hypercitrullination (LTH), and necrosis are related to each other and induce autoantigenicity. Certain microbial infections, such as those caused by Porphyromonasgingivalis, Aggregatibacter actinomycetemcomitans, and Prevotella copri, can induce autoantigens in RA. Anti-modified protein antibodies (AMPA) containing anti-citrullinated protein/peptide antibodies (ACPAs), anti-carbamylated protein (anti-CarP) antibodies, and anti-acetylated protein antibodies (AAPAs) play a role in pathogenesis as well as in prediction, diagnosis, and prognosis. Interestingly, smoking is correlated with both PTMs and AMPAs in the development of RA. However, there is lack of evidence that smoking induces the generation of AMPAs.

Tuning Monocytes and Macrophages for Personalized Therapy and Diagnostic Challenge in Rheumatoid Arthritis

Monocytes/macrophages play a central role in chronic inflammatory disorders, including rheumatoid arthritis (RA). Activation of these cells results in the production of various mediators responsible for inflammation and RA pathogenesis. On the other hand, the depletion of macrophages using specific antibodies or chemical agents can prevent their synovial tissue infiltration and subsequently attenuates inflammation. Their plasticity is a major feature that helps the switch from a pro-inflammatory phenotype (M1) to an anti-inflammatory state (M2). Therefore, understanding the precise strategy targeting pro-inflammatory monocytes/macrophages should be a powerful way of inhibiting chronic inflammation and bone erosion. In this review, we demonstrate potential consequences of different epigenetic regulations on inflammatory cytokines production by monocytes. In addition, we present unique profiles of monocytes/macrophages contributing to identification of new biomarkers of disease activity or predicting treatment response in RA. We also outline novel approaches of tuning monocytes/macrophages by biologic drugs, small molecules or by other therapeutic modalities to reduce arthritis. Finally, the importance of cellular heterogeneity of monocytes/macrophages is highlighted by single-cell technologies, which leads to the design of cell-specific therapeutic protocols for personalized medicine in RA in the future.

Interaction of HLA Class II rs9272219 and TMPO rs17028450 (Arg690Cys) Variants Affects Neuromyelitis Optica Spectrum Disorder Susceptibility in an Admixed Mexican Population

Neuromyelitis Optica Spectrum Disorder (NMOSD) is a demyelinating autoimmune disease of the central nervous system, more prevalent in individuals of non-European ancestry. Few studies have analyzed genetic risk factors in NMOSD, and HLA class II gene variation has been associated NMOSD risk in various populations including Mexicans. Thymopoietin (TMPO) has not been tested as a candidate gene for NMOSD or other autoimmune disease, however, experimental evidence suggests this gene may be involved in negative selection of autoreactive T cells and autoimmunity. We thus investigated whether the missense TMPO variant rs17028450 (Arg630Cys, frequent in Latin America) is associated with NMOSD, and whether this variant shows an interaction with HLA-class II rs9272219, previously associated with NMOSD risk. A total of 119 Mexican NMOSD patients, 1208 controls and 357 Native Mexican individuals were included. The HLA rs9272219 “T” risk allele frequency ranged from 21 to 68%, while the rs17028450 “T” minor allele frequency was as high as 18% in Native Mexican groups. Both rs9272219 and rs17028450 were significantly associated with NMOSD risk under additive models (OR = 2.48; p = 8 × 10^–10 and OR = 1.59; p = 0.0075, respectively), and a significant interaction between both variants was identified with logistic regression models (p = 0.048). Individuals bearing both risk alleles had an estimated 3.9-fold increased risk of NMOSD. To our knowledge, this is the first study reporting an association of TMPO gene variation with an autoimmune disorder and the interaction of specific susceptibility gene variants, that may contribute to the genetic architecture of NMOSD in admixed Latin American populations.

Past infections are associated with low levels of anti-citrullinated protein autoantibodies in rheumatoid arthritis

Background : Rheumatoid arthritis (RA), an autoimmune disease of unknown etiology, is believed to occur as the result of actions of genetic and environmental factors. In this study, we examined the relation of past histories about infectious diseases with the levels anti-citrullinated protein autoantibodies (ACPA) in RA. Methods : Results of a questionnaire about histories of infectious diseases were obtained from 85 patients with RA, and were analyzed. Results : Significantly lower level of ACPA was detected in patients with the history of tonsillitis, otitis media or urinary cystitis than in those without it. There was no difference in the level of ACPA in RA patients between with and without cold / influenza, rubella, chickenpox, herpes labialis or herpes zoster. When RA patients were divided into two groups, high-level and low-level ACPA, multiple logistic regression analysis revealed that the history of otitis media was a significantly independent factor for the low level of ACPA. There was no significant relation between the level of rheumatoid factor and histories of infectious diseases. Conclusion : This study clarified that the past history of otitis media is associated with the low level of ACPA in RA. J. Med. Invest. 67 : 182-188, February, 2020.

Understanding interactions between risk factors, and assessing the utility of the additive and multiplicative models through simulations

Understanding the genetic background of complex diseases requires the expansion of studies beyond univariate associations. Therefore, it is important to use interaction assessments of risk factors in order to discover whether, and how genetic risk variants act together on disease development. The principle of interaction analysis is to explore the magnitude of the combined effect of risk factors on disease causation. In this study, we use simulations to investigate different scenarios of causation to show how the magnitude of the effect of two risk factors interact. We mainly focus on the two most commonly used interaction models, the additive and multiplicative risk scales, since there is often confusion regarding their use and interpretation. Our results show that the combined effect is multiplicative when two risk factors are involved in the same chain of events, an interaction called synergism. Synergism is often described as a deviation from additivity, which is a broader term. Our results also confirm that it is often relevant to estimate additive effect relationships, because they correspond to independent risk factors at low disease prevalence. Importantly, we evaluate the threshold of more than two required risk factors for disease causation, called the multifactorial threshold model. We found a simple mathematical relationship (square root) between the threshold and an additive-to-multiplicative linear effect scale (AMLES), where 0 corresponds to an additive effect and 1 to a multiplicative. We propose AMLES as a metric that could be used to test different effects relationships at the same time, given that it can simultaneously reveal additive, multiplicative and intermediate risk effects relationships. Finally, the utility of our simulation study was demonstrated using real data by analyzing and interpreting gene-gene interaction odds ratios from a rheumatoid arthritis case-control cohort.

Etiologies of Rheumatoid Arthritis: Update on Mucosal, Genetic, and Cellular Pathogenesis

Purpose of Review

Over the last few years, the scientific community has made significant progress in understanding the etiology of rheumatoid arthritis (RA). In this review, we summarize those key findings and trends.

Recent Findings

New data strongly implicates respiratory exposures, obesity, diet and microbiome, genetics, and their interactions in the etiology of RA. Furthermore, anti-posttranslationally modified protein antibodies (AMPAs) and abnormal glycosylation may be additional biomarkers for RA. Finally, functional genomics techniques implicate loss of certain macrophage populations and proliferation of synovial fibroblasts in RA.

Summary

These findings support the notion that RA originates at mucosal sites, augmented by genetic predisposition, and mediated by certain cell types including macrophages and fibroblasts. Weight loss, physical activity, and diet are additional modifiable factors beyond smoking cessation that can reduce risk of RA. Future epidemiologic and translational studies leveraging multi-omics approaches will help map the precise sequence of events in RA pathogenesis.

Association of PTPN22-C1858T Polymorphism With Susceptibility to Mycobacterium tuberculosis and Mycobacterium leprae Infection: A Meta-Analysis

It was previously published that single-nucleotide polymorphism rs2476601 (PTPN22 [protein tyrosine phosphatase non-receptor type 22]-C1858T) might be related to increased sensibility to Mycobacterium tuberculosis and M. leprae infection. However, the results were inconclusive despite a high degree of similarity between both parameters. Herein, we carried out this meta-analysis to systematically summarize and articulate the correlation between PTPN22-C1858T polymorphism and mycobacterial infection. The susceptibility of PTPN22-C1858T carriers with autoimmune conditions receiving immunosuppressive therapy to M. tuberculosis and M. leprae infection was determined. A systematic retrieval of studies on relevance of PTPN22-C1858T polymorphism to susceptibility of M. tuberculosis or M. leprae infection was performed in Chinese National Knowledge Infrastructure, PubMed and Embase databases. We regarded Odds ratios (ORs) and 95% confidence intervals (CIs) as the determined effect size. Finally, four and two case-control studies on tuberculosis and leprosy, respectively, were included. In all genetic models, without indicated association between PTPN22-C1858T polymorphism and tuberculosis’s susceptibility. [C versus T: OR = 0.22 (95% CI: 0.09–0.50, P_H = 0.887); CT versus CC: OR = 0.21 (95% CI: 0.09–0.49, P_H = 0.889); TT+CT versus CC: OR = 0.21 (95% CI: 0.09–0.49, P_H = 0.889)]. A significantly increased risk of leprosy was perceived in patients with the PTPN22-C1858T polymorphism [C versus T: OR = 2.82 (95% CI: 1.02–7.81, P_H = 0.108)]. While the PTPN22-C1858T polymorphism is irrelevant to higher susceptibility to the infection of M. tuberculosis in Caucasians and Asians, it is relevant to increased susceptibility to the infection of M. leprae. However, the results of M. leprae are supposed to interpreted with prudence owing to the limited quantity of studies and heterogeneity. Further well-designed studies with sufficient populations are required to verify our conclusions.

The genetics of rheumatoid arthritis

RA is a chronic systemic inflammatory disease that primarily affects the small joints of the hands and feet, and results in a mean reduction in life expectancy of 3-10 years. RA is a multigene disorder with a substantial genetic component and a heritability estimate of 60%. Large-scale Genome-Wide Association Studies (GWAS) and meta-analyses have revealed common disease-associated variants in the population that may contribute cumulatively to RA pathogenesis. This review identifies the most significant genetic variants associated with RA susceptibility to date, with particular focus on the contribution of the HLA class II genes across different ethnic groups. Also discussed are the potential applications of pharmacogenomics to RA management by identifying polymorphisms associated with variation in treatment response or toxicity. The use of genetic variants to guide treatment strategy has the potential to not only reduce National Health Service costs, but also drastically improve patient experience and quality of life.

A sequencing study of CTLA4 in Pakistani rheumatoid arthritis cases

Rheumatoid arthritis (RA) is a multifactorial autoimmune disease. The interaction of genetic and environmental factors is likely necessary for RA. Among potential genetic factors, many major histocompatibility complex (MHC) and non-MHC variants may be involved in RA susceptibility. CTLA4 is involved in the regulation of T-cell response during an immune reaction, and multiple CTLA4 single nucleotide polymorphisms (SNPs) have been associated with numerous autoimmune diseases, including RA. To our knowledge, the genetic association of CTLA4 with RA risk has not been examined previously in the Pakistani population. In this study, we sequenced the entire CTLA4 gene and flanking regions in 95 Pakistani RA cases followed the screening of identified variants in Study 1 sample consisting of 350 RA cases and controls. Four common significant variants identified in Study 1 sample were further examined in a larger Study 2 replication sample comprising 1,678 independent RA cases and controls. We report significant associations of three variants from the combined analysis: rs3087243 (OR = 1.26, p = 4.47E-03), rs5742909 (OR = 1.78, p = 4.60E-03), and rs11571319 (OR = 1.48, p = 6.64E-03); the latter is a novel association in the Pakistani sample.

Comparison of methods to construct a genetic risk score for prediction of rheumatoid arthritis in the population-based Nord-Trøndelag Health Study, Norway

Objectives

To evaluate selection methods among published single-nucleotide polymorphisms (SNPs) associated with RA to construct predictive genetic risk scores (GRSs) in a population-based setting.

Methods

The Nord-Trøndelag Health (HUNT) Study is a prospective cohort study among the whole adult population of northern Trøndelag, Norway. Participants in HUNT2 (1995–1997) and HUNT3 (2006–2008) were included (489 RA cases, 61 584 controls). The initial SNP selection from relevant genome-wide studies included 269 SNPs from 30 studies. Following different selection criteria, SNPs were weighted by published odds ratios. The sum of each person’s carriage of all weighted susceptibility variants was calculated for each GRS.

Results

The best-fitting risk score included 27 SNPs [weighted genetic risk score 27 (wGRS27)] and was identified using P-value selection criterion ≤5 × 10−8, the largest possible SNP selection without high linkage disequilibrium (r2 < 0.8), and lasso regression to select for positive coefficients. In a logistic regression model adjusted for gender, age and ever smoking, wGRS27 was associated with RA [odds ratio 1.86 (95% CI 1.71, 2.04) for each s.d. increase, P < 0.001]. The AUC was 0.76 (95% CI 0.74, 0.78). The positive and negative predictive values were 1.6% and 99.7%, respectively, and the positive predictive value was not improved in sensitivity analyses subselecting participants to illustrate settings with increased RA prevalences. Other schemes selected more SNPs but resulted in GRSs with lower predictive ability.

Conclusion

Constructing a wGRS based on a smaller selection of informative SNPs improved predictive ability. Even with a relatively high AUC, the low PPV illustrates that there was a large overlap in risk variants among RA patients and controls, precluding clinical usefulness.

The evolution in our understanding of the genetics of rheumatoid arthritis and the impact on novel drug discovery

Introduction: Rheumatoid arthritis (RA) is an autoimmune disease that is characterized by chronic inflammation of the joints and affects 1% of the population. Polymorphisms of genes that encode proteins that primarily participate in inflammation may influence RA occurrence or become useful biomarkers for certain types of anti-rheumatic treatment.Areas covered: The authors summarize the recent progress in our understanding of the genetics of RA. In the last few years, multiple variants of genes that are associated with RA risk have been identified. The development of new technologies and the detection of new potential therapeutic targets that contribute to novel drug discovery are also described.Expert opinion: There is still the need to search for new genes which may be a potential target for RA therapy. The challenge is to develop appropriate strategies for achieving insight into the molecular pathways involved in RA pathogenesis. Understanding the genetics, immunogenetics, epigenetics and immunology of RA could help to identify new targets for RA therapy. The development of new technologies has enabled the detection of a number of new genes, particularly genes associated with proinflammatory cytokines and chemokines, B- and T-cell activation pathways, signal transducers and transcriptional activators, which might be potential therapeutic targets in RA.

DNA Damage Response Signals Transduce Stress From Rheumatoid Arthritis Risk Factors Into T Cell Dysfunction

Rheumatoid arthritis (RA) is an autoimmune-mediated disease that is associated with significant cartilage damage and immunosenescence. Despite decades of research, the major signal pathways that initiate RA are still unclear. The DNA damage response (DDR) is a specific and hierarchical network that includes cell cycle checkpoints, DNA repair, and DNA-damage tolerance pathways. Recent studies suggest that this condition is associated with deficits in telomere maintenance and overall genomic instability in the T cells of RA patients. Analysis of the underlying mechanisms has revealed defects in DDR pathways. Particularly, the DNA repair enzyme, ataxia telangiectasia mutated (ATM), is downregulated, which leaves the damaged DNA breaks in RA-associated T cells unrepaired and pushes them to apoptosis, exhausts the T cell pool, and promotes the arthritogenesis effector function of T cells. This review discusses recent advancements and illustrates that risk factors for RA, such as viral infections, environmental events, and genetic risk loci are combat with DDR signals, and the impaired DDR response of RA-associated T cells, in turn, triggers disease-related phenotypes. Therefore, DDR is the dominant signal that converts genetic and environmental stress to RA-related immune dysfunction. Understanding the orchestration of RA pathogenesis by DDR signals would further our current knowledge of RA and provide novel avenues in RA therapy.

Increased Risk of Thyroid Dysfunction Among Patients With Rheumatoid Arthritis

Background: Thyroid dysfunction seems to be common among rheumatoid arthritis (RA) patients, but the risk of thyroid dysfunction in RA has not been well-defined. Methods: We performed a case-control study of 65 RA patients and 550 matched non-RA subjects to assess the risk of thyroid dysfunction among Chinese RA patients. A systematic review and meta-analysis was also conducted to comprehensively define the relationship between RA and thyroid dysfunction. Results: The case-control study indicated that the prevalence of thyroid dysfunction was significantly higher in RA patients than controls (OR = 2.89, P < 0.001). Further subgroup analyses revealed positive correlations of RA with hypothyroidism (OR = 2.28, P = 0.006) and hyperthyroidism (OR = 8.95, P < 0.001). Multivariate logistic regression analysis revealed an independent association between RA and thyroid dysfunction (Adjusted OR = 2.89, 95%CI 1.63-5.12, P < 0.001). Meta-analysis of 15 independent studies also showed an obviously increased risk of thyroid dysfunction among RA patients (RR = 2.86, 95%CI 1.78-4.58, P < 0.001). Further subgroup analysis showed RA could obviously increase risk of hyperthyroidism (RR = 2.73, 95%CI 1.29-5.77, P = 0.043) and hypothyroidism (RR = 2.02, 95%CI 1.49-2.74, P < 0.001). Conclusion: Our study provides strong evidence for the increased risk of thyroid dysfunction among RA patients. Screening of thyroid dysfunction may be recommended for RA patients.