Dissection of the genetic complexity of arthritis using animal models

Copy number variation of the gene NCF1 is associated with rheumatoid arthritis

AIMS

The aim of this study was to investigate genetic variants in the gene neutrophil cytosolic factor 1 (NCF1) for association with rheumatoid arthritis (RA). In rodent models, a single-nucleotide polymorphism (SNP) in Ncf1 has been shown to be a major locus regulating severity of arthritis. Ncf1 encodes one of five subunits of the NADPH oxidase complex. In humans the genomic structure of NCF1 is complex, excluding it from genome-wide association screens and complicating genetic analysis. In addition to copy number variation of NCF1, there are also two nonfunctional pseudogenes, nearly identical in sequence to NCF1. We have characterized copy number variation and SNPs in NCF1, and investigated these variants for association with RA.

RESULTS

We find that RA patients are less likely to have an increased copy number of NCF1, 7.6%, compared with 11.6% in controls; p=0.037. We also show that the T-allele of NCF1-339 (rs13447) is expressed in NCF1 and significantly reduces reactive oxygen species production.

INNOVATION

This is the first finding of genetic association of NCF1 with RA. The detailed characterization of genetic variants in NCF1 also helps elucidate the complexity of the NCF1 gene.

CONCLUSION

These data suggest that an increased copy number of NCF1 can be protective against developing RA and add support to previous findings of a role of NCF1 and the phagocyte NADPH oxidase complex in RA pathogenesis.

High-resolution mapping of a complex disease, a model for rheumatoid arthritis, using heterogeneous stock mice

Resolving the genetic basis of complex diseases like rheumatoid arthritis will require knowledge of the corresponding diseases in experimental animals to enable translational functional studies. Mapping of quantitative trait loci in mouse models of arthritis, such as collagen-induced arthritis (CIA), using F(2) crosses has been successful, but can resolve loci only to large chromosomal regions. Using an inbred-outbred cross design, we identified and fine-mapped CIA loci on a genome-wide scale. Heterogeneous stock mice were first intercrossed with an inbred strain, B10.Q, to introduce an arthritis permitting MHCII haplotype. Homozygous H2(q) mice were then selected to set up an F(3) generation with fixed major histocompatibility complex that was used for arthritis experiments. We identified 26 loci, 18 of which are novel, controlling arthritis traits such as incidence of disease, severity and time of onset and fine-mapped a number of previously mapped loci.

DA rats from two colonies differ genetically and in their arthritis susceptibility

The arthritis-susceptible DA rat is one of the most commonly used rat strains for genetic linkage analysis and is instrumental for the identification of many genetic loci. Even though DA rats were kept as inbred lines at different institutes and suppliers, it became obvious that the various breeding stocks differed genetically. To be able to compare the results from different linkage studies it is very import to verify the genetic background of the substrains used in those studies. We performed a genetic and phenotypic analysis of two DA substrains, DA/ZtmRhd and DA/OlaHsd, and found several genetic differences. One of the allelic differences between the DA/ZtmRhd and the DA/OlaHsd strain was located at rat chromosome 3, a 17-Mb large fragment, including the peak marker of a previously identified quantitative trait locus (QTL) for collagen-induced arthritis, Cia11. In addition, the substrains exhibited a significant difference in the susceptibility to pristane-induced arthritis (PIA) and disease severity of collagen-induced arthritis and PIA. However, by generating and testing a congenic line, we could demonstrate that phenotypic differences were not due to the contaminating fragment on chromosome 3. Nevertheless, we conclude that DA substrains show distinct genetic differences and caution should be taken when comparing arthritis data from different DA substrains.

Congenic strains displaying similar clinical phenotype of arthritis represent different immunologic models of inflammation

Proteoglycan (PG)-induced arthritis (PGIA) is an autoimmune inflammatory disease controlled by multiple genes in the murine genome. BALB/c x DBA/2 congenic strains carrying four major PGIA chromosome loci were immunized, and positions of loci on chromosomes 3, 7, 8 and 19 (loci Pgia26, Pgia21, Pgia4 and Pgia12, respectively) were confirmed. Each congenic strain exhibited a different pattern of regulation of clinical and immunologic features of PGIA, and these features were significantly influenced by gender. Locus Pgia26 delayed PGIA onset in males and females, and the effect was associated with a lower rate of antigen-induced lymphocyte proliferation and lower production of interferon-gamma (IFN-gamma), tumor necrosis factor-alpha (TNF-alpha) and interleukin-4 (IL-4). Pgia12 similarly delayed onset in males, but the effect was achieved by elevated proliferation of PG-specific lymphocytes and enhanced production of IFN-gamma and IL-4. The effect of the Pgia21 locus was arthritis-suppressive in females but PGIA-permissive in congenic males. These opposite effects are attributed to two-fold higher serum autoantibody and IL-6 levels in males than in females. Our study supports the idea that each congenic strain represents a different immunologic subtype of PGIA, providing an explanation for the complex etiology and various clinical phenotypes of rheumatoid arthritis.

Proteomic analysis of peripheral blood mononuclear cells: selective protein processing observed in patients with rheumatoid arthritis

In a comparative proteome analysis of peripheral blood mononuclear cells (PBMCs), we analyzed 130 two-dimensional gels obtained from 33 healthy control individuals and 32 patients diagnosed with rheumatoid arthritis (RA). We found 16 protein spots that are deregulated in patients with RA and, using peptide mass fingerprinting and Western blot analyses, identified these spots as belonging to 9 distinct proteins. A hierarchical clustering procedure organizes the study subjects into two main clusters based on the expression of these 16 protein spots, one that contains mostly healthy control individuals and the other mostly RA patients. The majority of the proteins differentially expressed in RA patients when compared with healthy controls can be detected as protein fragments in PBMCs obtained from RA patients. This set of deregulated proteins includes several factors that have been shown to be autoantigens in autoimmune diseases.

Mechanisms of disease: Genetic susceptibility and environmental triggers in the development of rheumatoid arthritis

Rheumatoid arthritis (RA) is a complex disease in which environmental agents are thought to interact with genetic factors that influence susceptibility. This interaction triggers immunologic events that eventually result in the clinical signs of arthritis. Knowledge of the chain of etiological events that lead to the development of RA is incomplete. In this review, we describe the experimental approaches that are used to address the issue of gene-environment interactions in the etiology of RA, and discuss relevant examples of such interactions. We focus on how smoking, the best-known environmental risk factor for RA, interacts with HLA-DR shared epitope genes, the main genetic risk factors for RA, and result in a high risk of RA in individuals exposed to both of these risk factors. From these and other related findings, we can begin to define the distinct environmental risk factors (such as smoking) that in certain genetic contexts (for example, the presence of HLA-DR shared epitope alleles) can trigger immune reactions (such as autoantibodies to citrullinated peptides) many years before onset of RA, and consider how these immune reactions might contribute to clinical symptoms in a subset of affected patients. Increased knowledge about these and other events involved in the development of RA should enable the design of new tools for suppressing RA pathogenesis before the onset of disease.

Immunological memory stabilizing autoreactivity

The etiopathologies of autoimmune diseases are complex. A broad variety of cell types and gene products are involved. However, clinical and experimental evidence suggests that the importance of an individual factor changes during the course of the disease. Factors and cell types that induce acute autoreactivity and initiate an autoimmune disease could be distinct from those that drive a chronic course of that disease. Autoreactive immunological memory, in particular B cell and plasma cell memory, contributes to chronicity through several mechanisms. Formation of autoreactive memory B cells leads to an increase in the numbers of autoreactive cells. In comparison to naive B cells, these memory B cells show a decreased threshold for activation. Additionally, a fraction of memory B cells express the chemokine receptor CXCR3, which supports their accumulation within chronically inflamed tissues. This may allow their escape from mechanisms for induction of peripheral tolerance. Within the inflamed tissue, inflammatory cytokines and autoantigens provide activation signals that promote plasma cell differentiation and survival. The autoantibodies produced locally by these plasma cells contribute to the severity of inflammation. Together, an autoreactive loop of autoantibody-induced inflammation is formed. Another integral part of immunological memory are long-lived plasma cells. These cells provide persistent humoral antibody memory. Though not all autoantibodies are produced by long-lived plasma cells, these cells have a special impact on immune pathology. Long-lived plasma cells are relatively resistant to existing therapies of immunosuppression and continuously secrete antibodies, without need for restimulation. Long-lived plasma cells provide titers of autoantibodies even during clinically quiescent phases and after immunosuppression. These persisting autoantibody titers, though often low and not causing acute clinical symptoms, are likely to maintain a low level of chronic inflammation and progressive tissue destruction, which reduces the threshold for another break of immunological tolerance.

Remnant epitopes, autoimmunity and glycosylation

The role of extracellular proteolysis in innate and adaptive immunity and the interplay between cytokines, chemokines and proteinases are gradually becoming recognized as critical factors in autoimmune processes. Many of the involved proteinases, including those of the plasminogen activator and matrix metalloproteinase cascades, and also several cytokines and chemokines, are glycoproteins. The stability, interactions with inhibitors or receptors, and activities of these molecules are fine-controlled by glycosylation. We studied gelatinase B or matrix metalloproteinase-9 (MMP-9) as a glycosylated enzyme involved in autoimmunity. In the joints of rheumatoid arthritis patients, CXC chemokines, such as interleukin-8/CXCL8, recruit and activate neutrophils to secrete prestored neutrophil collagenase/MMP-8 and gelatinase B/MMP-9. Gelatinase B potentiates interleukin-8 at least tenfold and thus enhances neutrophil and lymphocyte influxes to the joints. When cartilage collagen type II is cleaved at a unique site by one of several collagenases (MMP-1, MMP-8 or MMP-13), it becomes a substrate of gelatinase B. Human gelatinase B cleaves the resulting two large collagen fragments into at least 33 peptides of which two have been shown to be immunodominant, i.e., to elicit activation and proliferation of autoimmune T cells. One of these two remnant epitopes contains a glycan which is important for its immunoreactivity. In addition to the role of gelatinase B as a regulator in adaptive immune processes, we have also demonstrated that it destroys interferon-beta, a typical innate immunity effector molecule and therapeutic cytokine in multiple sclerosis. Furthermore, glycosylated interferon-beta, expressed in Chinese hamster ovary cells, was more resistant to this proteolysis than recombinant interferon-beta from bacteria. These data not only prove that glycosylation of proteins is mechanistically important in the pathogenesis of autoimmune diseases, but also show that targeting of glycosylated proteinases or the use of glycosylated cytokines seems also critical for the treatment of autoimmune diseases.

Variation in IL-1beta gene expression is a major determinant of genetic differences in arthritis aggressivity in mice

In humans and in animal models, susceptibility to arthritis is under complex genetic control, reflecting influences on the immunological processes that initiate autoimmunity and on subsequent inflammatory mechanisms in the joints. The effector phases are conveniently modeled by the K/BxN serum transfer system, a robust model well suited for genetic analysis where arthritis is initiated by pathogenic Ig. Here, we mapped the genetic loci distinguishing the high-responder BALB/c vs. low-responder SJL strains. After computational modeling of potential breeding schemes, we adapted a stepwise selective breeding strategy, with a whole-genome scan performed on a limited number of animals. Several genomic regions proved significantly associated with high sensitivity to arthritis. One of these regions, on distal chr2, was centered on the interleukin 1 gene family. Quantitation of transcripts of the Il1a and Il1b candidate genes revealed a 10-fold greater induction of Il1b mRNA in BALB/c than in SJL splenocytes after injection of LPS, whereas Il1a showed much less difference. The differential activity of the Il1b gene was associated with a particular sequence haplotype of noncoding polymorphisms. The BALB/c haplotype was found in 75% of wild-derived strains but was rare among conventional inbred strains (4/33 tested, one of which is DBA/1, the prototype arthritis-susceptible strain) and was associated with vigorous Il1b responses in a panel of inbred strains. Inbred strains carrying this allele were far more responsive to serum-transferred arthritis, confirming its broad importance in controlling arthritis severity.

Modeling human arthritic diseases in nonhuman primates

Models of rheumatoid arthritis (RA) in laboratory animals are important tools for research into pathogenic mechanisms and the development of effective, safe therapies. Rodent models (rats and mice) have provided important information about the pathogenic mechanisms. However, the evolutionary distance between rodents and humans hampers the translation of scientific principles into effective therapies. The impact of the genetic distance between the species is especially seen with treatments based on biological molecules, which are usually species-specific. The outbred nature and the closer anatomical, genetic, microbiological, physiological, and immunological similarity of nonhuman primates to humans may help to bridge the wide gap between inbred rodent strain models and the heterogeneous RA patient population. Here we review clinical, immunological and pathological aspects of the rhesus monkey model of collagen-induced arthritis, which has emerged as a reproducible model of human RA in nonhuman primates.

A web tool for finding gene candidates associated with experimentally induced arthritis in the rat

Rat models are frequently used for finding genes contributing to the arthritis phenotype. In most studies, however, limitations in the number of animals result in a low resolution. As a result, the linkage between the autoimmune experimental arthritis phenotype and the genomic region, that is, the quantitative trait locus, can cover several hundred genes. The purpose of this work was to facilitate the search for candidate genes in such regions by introducing a web tool called Candidate Gene Capture (CGC) that takes advantage of free text data on gene function. The CGC tool was developed by combining genomic regions in the rat, associated with the autoimmune experimental arthritis phenotype, with rat/human gene homology data, and with descriptions of phenotypic gene effects and selected keywords. Each keyword was assigned a value, which was used for ranking genes based on their description of phenotypic gene effects. The application was implemented as a web-based tool and made public at . The CGC application ranks gene candidates for 37 rat genomic regions associated with autoimmune experimental arthritis phenotypes. To evaluate the CGC tool, the gene ranking in four regions was compared with an independent manual evaluation. In these sample tests, there was a full agreement between the manual ranking and the CGC ranking for the four highest-ranked genes in each test, except for one single gene. This indicates that the CGC tool creates a ranking very similar to that made by human inspection. The exceptional gene, which was ranked as a gene candidate by the CGC tool but not in the manual evaluation, was found to be closely associated with rheumatoid arthritis in additional literature studies. Genes ranked by the CGC tools as less likely gene candidates, as well as genes ranked low, were generally rated in a similar manner to those done manually. Thus, to find genes contributing to experimentally induced arthritis, we consider the CGC application to be a helpful tool in facilitating the evaluation of large amounts of textual information.