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The Journal of Immunology, 2003, 170: 2283-2292.
Copyright © 2003 by The American Association of Immunologists

Combined Autoimmune Models of Arthritis Reveal Shared and Independent Qualitative (Binary) and Quantitative Trait Loci 1

Vyacheslav A. Adarichev*, Juan C. Valdez2,*, Tamás Bárdos3,*, Alison Finnegan{dagger},{ddagger}, Katalin Mikecz*,{ddagger} and Tibor T. Glant4,*,{dagger}

* Section of Biochemistry and Molecular Biology, Departments of Orthopedic Surgery and Biochemistry, {dagger} Section of Rheumatology, Department of Internal Medicine, and {ddagger} Department of Immunology/Microbiology, Rush University at Rush-Presbyterian-St. Luke’s Medical Center, Chicago, IL 60612


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
Collagen-induced arthritis (CIA) and proteoglycan-induced arthritis (PGIA) are murine models for rheumatoid arthritis both in terms of their pathology and genetics. Using the F2 hybrids of the CIA-susceptible, but PGIA-resistant DBA/1 mice, and the CIA-resistant, but PGIA-susceptible BALB/c mice, our goals were to 1) identify both model-specific and shared loci that confer disease susceptibility, 2) determine whether any pathophysiological parameters could be used as markers that distinguish between nonarthritic and arthritic mice, and 3) analyze whether any immune subtraits showed colocalization with arthritis-related loci. To identify chromosomal loci, we performed a genome scan on 939 F2 hybrid mice. For pathophysiological analyses, we measured pro- and anti-inflammatory cytokines (IL-1, IL-6, TNF-{alpha}, IFN-{gamma}, IL-4, IL-10, IL-12), Ag-specific T cell proliferation and IL-2 production, serum IgG1 and IgG2 levels of both auto- and heteroantibodies, and soluble CD44. In addition to multiple CIA- and PGIA-related loci identified in previous studies, we have identified nine new CIA- and eight new PGIA-linked loci. Comprehensive statistical analysis demonstrated that IL-2 production, T cell proliferation, and IFN-{gamma} levels differed significantly between arthritic and nonarthritic animals in both CIA and PGIA populations. High levels of TNF-{alpha}, IFN-{gamma}, IL-2, and Ab production were detected in F2 hybrids with CIA, whereas T cell proliferation, IL-2 and IFN-{gamma} production, and a shift to IgG2a isotype were more characteristic of PGIA. Quantitative trait loci analysis demonstrated colocalization of numerous immune subtraits with arthritis-related traits. Quantitative trait loci on chromosomes 5, 10, 17, 18, and X were found to control arthritis in both models.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
To investigate loci associated with rheumatoid arthritis (RA),5 numerous studies have used animal models which have the advantage of a controlled environment and known genetic background. To date, disease-associated loci were identified in animal models for arthritis, induced by immunization with adjuvant (1), oil (2), pristane (3), bacterial wall components (4), type II collagen (5, 6, 7, 8, 9, 10), and proteoglycan (11, 12, 13). Together, these studies have identified a large number of loci associated with clinical symptoms of arthritis, thus illustrating the underlying complexity of autoimmune diseases. Many of these quantitative trait loci (QTL) are colocalized to homologous chromosomal regions in different models and in different species suggesting common genetic components (4, 14, 15, 16). Presumably, certain genes associated with these loci will correspond to genes involved in RA susceptibility (17, 18, 19). Furthermore, many of these loci have been colocalized with loci uncovered in other autoimmune models or diseases (14, 15, 16), suggesting a shared or common genetic pathway in autoimmune diseases.

Although these studies have helped define the genetic relatedness and similarities of the available autoimmune models, none have successfully narrowed the genetic interval of any QTL to the point where positional cloning can be used. Thus, the central problem of the identification of the disease-responsible genes remains. The use of different genetic crosses, increasingly dense genetic maps and congenic strains, as well as the completion of the human and mouse genome projects, will likely make these goals a reality.

The approach used in this study makes use of a single F1 intercross that permits simultaneous analysis of two genetically distinct murine models of RA: collagen-induced arthritis (CIA) and proteoglycan (aggrecan)-induced arthritis (PGIA). CIA is an autoimmune model that can be generated in rats (20), mice (21), and monkeys (22). PGIA is an autoimmune murine model with 100% incidence in the BALB/c mouse strain (23, 24, 25, 26). DBA/1 (H-2q) mice are susceptible to CIA but resistant to PGIA, whereas BALB/c mice (H-2d) are susceptible to PGIA, and resistant to CIA. To gain insight into the mechanisms of how the major clinical (disease susceptibility, severity, and onset of arthritis) and immunological traits (Ag-specific T and B cell responses and cytokine production) are influenced in this special combination of genetic background, we have generated a unique intercross of BALB/c and DBA/1 parent strains, and the F1 and F2 hybrids were immunized for either CIA or PGIA. The combination of two arthritis models using F2 hybrids of the susceptible parental strains provides an avenue for testing the hypothesis that QTL identified in one model may also be involved in a second model. Presumably, some QTL will be model-specific, while others will be shared between different models. It is our hypothesis that loci shared between different models are more likely to involve genetic pathways that are also shared in RA, and perhaps autoimmune diseases in general.

Our aims in this study were multifold. First, we wanted to evaluate the F1 and F2 hybrids of this novel cross in terms of arthritis incidence and severity. We have hypothesized that, while BALB/c mice are resistant to CIA and DBA/1 mice resistant to PGIA, there may be genetic components from each background that contribute to susceptibility in the disease model from which that particular mouse strain is resistant. Secondly, we wanted to test a wide range of pathophysiological and immunological markers to determine whether any of these parameters could be used as phenotypic markers associated with disease susceptibility or severity. Finally, we sought to determine whether QTL controlling clinical symptoms, or any of the pathophysiological parameters, would colocalize with QTL previously identified (7, 8, 11, 12) and, if so, how these traits modify the clinical picture of the original model.


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Animals, Ags, and immunization

BALB/c female mice (Kingston colony K51; Charles River Breeding Laboratories, Wilmington, MA) were mated with DBA/1 males (The Jackson Laboratory, Bar Harbor, ME), and the resulting F1 offspring were intercrossed to generate F2 hybrids (n = 939). Parent BALB/c females were selected to achieve 100% incidence of PGIA in the parental line (26) and DBA/1 males to the highest incidence for CIA (27). Notably, BALB/c mice were absolutely resistant to CIA, and the DBA/1 strain was previously found to be resistant to PGIA (26). Mice were immunized by the standard immunization protocols. For CIA (26), 100 µg of human and 100 µg of bovine type II collagen were emulsified in CFA and injected into the proximal tail. A second injection (same dose and adjuvant) was given i.p. on day 21. Mice that did not develop arthritis within 3 wk of the second collagen injection were boosted with a third injection (equally divided i.p. and into the proximal tail) and sacrificed 6 wk later. For PGIA (26), 100 µg of Ag (measured as proteoglycan core protein) was emulsified with adjuvant and injected i.p. on days 0, 7, 28, and 49. The first and fourth injections were given in CFA (Difco, Detroit, MI), whereas the second and third boosters contained Ag in IFA (Difco). Mice that did not develop arthritis within 5 wk after the fourth injection were boosted and sacrificed 4 wk later. These extra Ag injections (third in CIA and fifth in PGIA) were given in both models to provoke CIA or PGIA in all, but possibly less susceptible, F2 hybrid mice.

Assessment of quantitative and qualitative arthritis traits

Arthritis was assessed daily and the inflammation of each paw was scored from 0 to 4 of each animal. Thus the maximum score might be 16, when all four paws were maximally inflamed in one animal. Earlier we have used this scoring system, but designated as a cumulative (0–16) acute arthritis score of each animal (12, 25, 26). However, this clinical score includes two basic traits for arthritis: susceptibility to the disease (qualitative trait) and severity of inflammation (quantitative trait). The first phenotype is a binary/qualitative trait, i.e., has only two values: either "1" for positive (arthritis-susceptible) or "0" for nonarthritic (resistant) animals. The other component of the arthritis score is the disease severity or magnitude of inflammation. Therefore, we separated quantitative (severity) traits from the qualitative (binary) traits to dissect the disease phenomenology. The severity score of arthritis is the same as the traditional "acute" arthritis score (24, 25, 26, 28, 29), but applies only to positive mice, thus ranging from 1 to 16.

As arthritic animals exhibited a wide range of individual variability along the experimental period, we made the arthritis or severity score as uniform as was possible. Animals were scored daily after the second collagen or third proteoglycan injections and the highest arthritis/severity score, whenever it reached during the experimental period, was applied for that particular animal. In this scoring system we diagnosed primarily the acute inflammation (score 1–4/paw), but an ankylotized joint (e.g., the ankle or knee), where the ankylosis indicated massive cartilage deterioration and synovial tissue proliferation (histologically) was scored as 4. In addition, a special onset score (0–5) was established for this study to create a range of values weighted to those animals that quickly developed arthritis. As the latent (prearthritic) period is significantly different in the two models (21, 23, 26, 27), the "maximum onset score" of 5 was given at different time points in CIA and PGIA. A maximum score of 5 was given for all animals that developed CIA on day 21 or earlier, whereas score 5 was used for mice having PGIA on day 49 or earlier. A minimum onset score 0 was given to mice that did not develop arthritis for the whole period of immunization and monitoring (by days 70–78 for CIA and days 99–100 for PGIA). Intermediate onset score values from 5 to 0 were given using linear time adjustments, i.e., if an animal developed the disease 1 wk later than the other one, the onset score was 0.7 lower. All clinically questionable joints/paws (score <1.5–2.0) were scored by histology as described (12).

Measurement of Abs and T cell response

Abs to the immunizing human and mouse (self) cartilage proteoglycans or type II collagen were determined by ELISA (12, 25, 30). Maxisorp 96-well plates (Nunc, Hanover Park, IL) were coated with either chondroitinase ABC-digested human (for heteroantibodies) or native mouse (for autoantibodies) cartilage proteoglycans (0.1 µg of Ag protein per well of each). Similarly, 0.1 µg of bovine, human, or mouse cartilage-derived type II collagen was coated in 100 µl of coating buffer as described (26). Proteoglycan- and collagen-specific Abs were determined in serial dilutions of immune sera (1/500 to 1/62,500) using peroxidase-conjugated goat anti-mouse IgGAM (for total Abs), and anti-IgG1 or anti-IgG2a (for Th2- and Th1-supported isotypes, respectively) second Abs (Zymed Laboratories, San Francisco, CA). Serum Ab levels were expressed in arbitrary units. These units were calculated in each case as a ratio of the serum dilution of the experimental sample relative to the dilution of the standard (pooled sera of arthritic BALB/c or DBA/1 mice) at the median of the maximum and minimum absorbance levels measured on the same plate (12).

Ag-specific T cell responses (IL-2 production and T cell proliferation) were measured in quadruplicate samples of spleen cells (3 x 105 cells/well) cultured in the presence of 100 µg of proteoglycan or collagen protein per milliliter. IL-2 was measured in supernatants harvested on day 2 by the proliferation of the IL-2-dependent CTLL-2 cell line. Ag-specific T cell proliferation was assessed on day 5 by the incorporation of 3[H]thymidine (25, 31). In both cases, the Ag-specific response was expressed as stimulation index which is a ratio of incorporated 3[H]thymidine (cpm) in Ag-stimulated cultures relative to cpm in nonstimulated cultures (25, 26).

Ag-specific IFN-{gamma} and IL-4 production by T cells were determined in identical culture conditions as described for T cell proliferation in 4-day-old conditioned medium (2.5 x 106 mononuclear cells/ml) using capture ELISAs from R&D Systems (Minneapolis, MN). Serum IL-1 level was determined by bioassay using D10S cells as described (12). Soluble CD44 (sCD44) was determined by a capture ELISA developed in our laboratory (32). Serum TNF-{alpha}, IL-6, IL-10, and IL-12 levels were determined by capture ELISAs (R&D Systems or BD PharMingen, San Diego, CA).

Genome screening

DNA was extracted from the mouse tail using standard methods as described (11, 33). Genomic DNA was isolated from 939 F2 hybrids and subjected to an exhaustive genome-wide screening using 135 simple sequence length polymorphic (SSLP) markers (MWG Biotec, High Point, NC). SSLP analysis was performed using PCR of genomic DNA and gel electrophoresis of PCR products in MetaPhore agarose (BioWhittaker Molecular Applications, Rockland, ME) as described (11). Genomic markers were designed to cover all autosomes and X chromosomes with average spacing of 10.7 cM. Genetic linkage maps of the SSLP markers were constructed with Map Manager QTX version 13 (Roswell Park Cancer Institute; http://mapmgr.roswellpark.org/mmQTX.html) using the Kozambi mapping function (34). SSLP markers identified containing unlikely recombination events were reanalyzed. The chromosomal linkage maps and marker positions were ultimately confirmed using The Jackson Laboratory Web resource (http://www.informatics.jax.org/) and Celera Discovery system (http://www.celera.com/). Linkage of potential QTL to SSLP marker polymorphisms and {chi}2 statistics for trait-marker association was determined with Map Manager QTX version 13 using a free regression model (13, 34). For selection of QTL in the intercross, a logarithm of the odds (LOD) score value of 2.8 was used as a cut-off for suggestive linkage and a LOD score value of 4.3 was used as the threshold for significant linkage (35).

Statistical analysis

Statistical analysis was performed using the statistical software package SPSS version 10.0.5 (SPSS, Chicago, IL). Clinical traits, including binary, severity, and onset scores of arthritis, and basic immune parameters (Abs and T cell proliferation) demonstrated nonparametric distributions in F2 hybrid population. Therefore, we used the nonparametric Mann-Whitney U test to analyze differences between subgroups. The Spearman’s correlation coefficient was used to evaluate biases between traits. For statistical analysis of parametric data, the two-sample Student’s t test was used. The significance level was set at p < 0.05.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
Characterization of CIA and PGIA in BALB/c and DBA/1 parent strains and in their F1 and F2 hybrids

To investigate the genetics of both CIA and PGIA in BALB/c and DBA/1 mice, we initiated a set of experiments using BALB/c x DBA/1 F1 hybrids (n = 94) and BALB/c x DBA/1 F2 hybrids (n = 939). All mice were immunized with type II collagen or cartilage proteoglycan by the same standard protocol as described above and scored for the clinical appearance of arthritis. As has been reported previously (5), CIA has 100% penetrance in the F1 generation. Indeed, all 49 F1 hybrid mice developed CIA with an average severity score of 6.3 ± 3.4 (mean ± SD). In contrast, PGIA has never been found in the F1 generation of susceptible and resistant strains of mice (11, 24, 36). Hence, we were surprised to find that 41% of the females (20 arthritic of 49 immunized F1 hybrid mice) were positive for arthritis with an average severity score of 5.3 ± 2.7 (Table I and Fig. 1).


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  		Table I. Incidence and severity of arthritis in a combined model of CIA and PGIA

 


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  		FIGURE 1. Onset of arthritis during the course of immunization (A and B), and the severity score (C) in parent strains and their F1 and F2 hybrids with CIA or PGIA. Each paw was individually scored from 0 to 4 resulting in a possible maximum score per animal of 16 (26 ), and then the percent of arthritis score (from 0 to 16) is shown in a weekly scale (A and B). For comparison of various groups, scores measured 3 days after the onset are summarized and shown. The incidence and severity of each group are listed in Table I. Arrows indicate the time of Ag injection. C, Summary of the severity score in parent strains and their hybrids.

 
The BALB/c x DBA/1 F2 hybrids tested for CIA (38.9% positive for CIA; 209 of 537) had an average severity score of 8.6 ± 3.5, which was much higher than the severity scores measured in the parental DBA/1 strain (3.3 ± 2.1; Table I). Many of these F2 hybrids with CIA developed severe arthritis, which has never been observed in any of the parental strains for either CIA or PGIA (Fig. 2). Clearly, F2 hybrids of BALB/c x DBA/1 intercross inherited certain genes from the BALB/c background, which made CIA significantly more severe (Fig. 1C). In contrast, the BALB/c x DBA/1 F2 hybrids tested for PGIA (31.6% positive for PGIA; 127 of 402) had an average severity score of 4.4 ± 2.6, which was significantly lower than the severity scores measured in the parental BALB/c strain (8.2 ± 4.0; Table I). Thus, F2 hybrids with PGIA lost some genes, which were involved in disease severity in BALB/c parents. When males and females were analyzed separately, no significant differences in clinical scores (susceptibility, onset, or severity) between sexes were detected within the groups immunized for CIA or PGIA (Table I).



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  		FIGURE 2. Clinical appearance (insets) and histopathology of ankle joints 3 days after the onset of arthritis. A "resistant" (A) and a highly susceptible (D) (paw score = 4) F2 hybrid (BALB/c x DBA/1 cross) immunized with type II collagen. B, An F1 hybrid with CIA (score = 2); C, an F2 hybrid with PGIA (score = 4). Although the onset frequently was delayed in PGIA and severity was higher in F2 hybrids with CIA (Table I; Fig. 1), the inflammatory cell reaction, cartilage, and bone erosions (i.e., the overall histopathological pictures) were highly comparable in all arthritic animals.

 
Clinical traits of CIA and PGIA in F2 hybrid mice of BALB/c and DBA/1 intercross

We have hypothesized that the susceptibility to disease and arthritis severity are governed by different sets of genes. In earlier studies (11, 12), we have used an "acute" and/or "cumulative" arthritis score as a single trait, which was applied to both arthritic and nonarthritic mice with a scale from 0 to 16. However, this cumulative acute arthritis score contained a mixture of several clinical traits, thus we further dissected it into three scores: susceptibility to arthritis (binary), onset of the disease (onset), and severity of inflammation (severity). Although separation of clinical traits did not create biases among all traits, this step seemed to be a necessary procedure for correct calculations and linkage analysis of genes that might control the different features of arthritis. Indeed, differences between the three clinical traits (binary, onset, and severity) and their linkage to different mCia and Pgia loci clearly indicated the necessity of this approach. The binary (qualitative) trait (susceptibility) is insensitive to the degree of inflammation and takes only two values: either "1" or "0". Disease severity is a separate quantitative trait varying from 1 to 16, and by definition is determined for arthritic mice only (Fig. 1C). An additional phenotype of the disease, which is possibly independent of both the binary trait and severity, is the disease onset that reflects the speed of disease progression (Fig. 1, A and B).

Genome scans identified both model-specific and common QTL. In both models, the major locus for disease susceptibility was localized over the MHC region on chromosome 17 (Fig. 3). The effect of the MHC locus on clinical traits (except severity) was much more prominent in CIA than in PGIA (LOD score 21 in CIA and 6.0 in PGIA; Fig. 3). Other QTL on chromosomes 3, 5, 10, 19, and X in CIA (Fig. 3), while they were highly significant, have never reached the level of the MHC effect. In the model of PGIA, two major QTL were found on chromosome 17, one within the MHC locus and another one in the telomeric region (Fig. 3). Additional significant QTL of clinical traits were identified on chromosome 5, 6, 9, and 18. Most of the QTL identified were model-specific, and only the MHC locus on chromosome 17 seemed to be a common genetic component for both murine models of arthritis.



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  		FIGURE 3. LOD score plots for individual chromosomes containing putative QTL controlling arthritis (black line), onset of the disease (green), arthritis susceptibility (blue), and severity (red). QTL identified in this study are indicated by asterisks (*). The description of these clinical scores of arthritis are in Materials and Methods. The length of each chromosome is adjusted to the same size, albeit the centimorgan length of each chromosome varies. Genetic maps were constructed using Map Manager QTX. The positions of SSLP markers used for genotyping are indicated on the x-axis of each panel with vertical sticks. The LOD score for the free regression model is given on the y-axis. Significance is set by the suggestive LOD score of 2.8 and is indicated by the horizontal dotted line on each panel. For clarity, linkage with arthritis score, onset, and binary/susceptibility traits were analyzed for the total F2 population, but the severity of the disease was calculated for arthritic mice only. In most cases, the arthritis score showed colocalization with either susceptibility or onset of the disease, but severity QTL showed distinct localization. As the penetrance of QTL was frequently affected by mouse gender, the population (males and/or females) is shown on each panel. Immunological (pathophysiological) traits linked to either CIA or PGIA are listed in Tables III and IV.

 
The nonparametric Spearman’s correlation coefficient {rho} was applied to test biases between traits in PGIA and CIA mice populations. Each correlation coefficient was characterized with significance of correlation, and the p value was set to 0.05 level. As expected, an early onset tightly correlated with the arthritis score and binary trait ({rho} 0.92–0.98) in both models (not shown), whereas the onset of arthritis demonstrated a significant positive correlation ({rho} 0.24) with severity only in PGIA (Fig. 4).



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  		FIGURE 4. Distribution of the acute score (A and B) and correlations between onset and severity (C and D). Arthritis score is the score counting each animal individually from 0 (nonarthritic, i.e., negative) to a maximum score of 16. The severity represents only arthritic mice (with one single score between 1 and 16), and the onset score indicates the how early the arthritis development was (5 was the earliest and 0 was the negative). The significance (p) and the correlation coefficient ({rho}S) are given on the top of C and D.

 
Immune and pathophysiological markers in F2 hybrid mice with or without CIA or PGIA

All animals of BALB/c x DBA/1 F2 population were immunized either with type II collagen or proteoglycan, and ~39% of the entire F2 population was susceptible to CIA and only 32% was susceptible to PGIA (Table I). Although the majority of animals did not develop arthritis, all mice were positive for Ag-specific T cell responses and both auto and heteroantibodies, and pro- and anti-inflammatory cytokines were equally well-measured in both arthritic and arthritis resistant mice (Table II).


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  		Table II. Comparison of immune responses and pathophysiological markers in F2 hybrid mice of BALB/c x DBA/1 intercrossa

 
To reveal major immunological traits linked to arthritis in any of the two models, we compared arthritic and nonarthritic animals of the F2 population. Many of the parameters differed significantly between diseased and normal animals either in CIA or PGIA models. As summarized in Table II, only the Ag-specific T cell responses (T cell proliferation, IL-2, and IFN-{gamma} production) and serum levels of TNF-{alpha} and IL-12 were significantly different between the arthritic and nonarthritic animals in both CIA and PGIA, while other differences appeared to be model-specific. In the CIA model, serum levels of IL-6 and Abs (both against mouse and human type II collagen) were significantly higher in arthritic, than in nonarthritic, mice (Table II). In contrast, the ratio of IgG1 to IgG2a, and the Ag-induced IL-4 production, were significantly less in mice with PGIA than those remaining asymptomatic; both parameters reflecting a shift of Th1/Th2 balance to the Th1 direction in, or during the development of, arthritis (30, 37).

Genome-wide linkage analysis of clinical and immunological traits in F2 hybrids of BALB/c x DBA/1 intercross

The results of linkage analysis for clinical and immunological traits are summarized in Tables III and IV. A number of these QTL were identified in other studies (7, 8, 9, 11, 12, 13) and we maintained the original QTL number for a given chromosome region, even if our QTL represented linkage with a new trait. As summarized in Table III for CIA and in Table IV for PGIA, using the genetic cross of BALB/c x DBA/1, we have identified four new QTL of clinical traits in CIA (mCia10-mCia13) and three new QTL of PGIA (Pgia18-Pgia20). In addition to the earlier studies (7, 8, 9, 11, 12, 13) and in results summarized in Fig. 3, we identified five additional new QTL in CIA and five new QTL in PGIA. Many of these new immune- or cytokine-associated QTL shared the same chromosome region with clinical QTL (Fig. 3), either in the same or the other model. Taking linkage analysis data together, we identified nine new QTL (mCia10-mCia18) for mouse CIA, and eight new Pgia QTL (Pgia18-Pgia25), and the summary of these arthritis and immune QTL are presented in Fig. 3, Table III, and Table IV.


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  		Table III. Summary of QTL in F2 hybrid (BALB/c x DBA/1) mice immunized with type II collagen for CIAa

 

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  		Table IV. Summary of QTL in F2 hybrid (BALB/c x DBA/1) mice immunized with cartilage proteoglycan for PGIAa

 
Correlation between clinical traits of arthritis and pathophysiological markers in F2 hybrids of BALB/c x DBA/1 intercross

In an effort to identify critical immune parameters that may play a role either in CIA or PGIA, or have an effect on one or both models, statistical comparisons were made between the major overall clinical scores of arthritis (from 0 to 16) or the subtraits of severity (scores from 1 to 16), onset (scores from 0 to 5), and susceptibility (either score 0 or 1), and the immune response/inflammation-related parameters (Table V). Clinical traits of arthritis demonstrated biases with certain immune response parameters, a pattern that was specific for each animal model. Ag-specific T cell responses (proliferation and IL-2 production) demonstrated significant correlation with arthritis in both models, but the correlation was positive in CIA ({rho} 0.19 to 0.37) and negative in PGIA ({rho} from -0.18 to -0.45). Similarly, Ag-induced IFN-{gamma} production showed significant correlations with the overall arthritis score in both models ({rho} 0.21–0.25; Table V). Serum Ab levels (both hetero- and autoantibodies) were specific immune markers for CIA, but not for PGIA. On the list of serum markers tested (Table II), only IL-6 showed correlation with severity ({rho} 0.33), and TNF-{alpha} with arthritis scores ({rho} 0.22), both in CIA only (Table V).


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  		Table V. Spearman’s correlation coefficients for clinical and immunological traits in F2 hybrid mice with CIA or with PGIAa

 

   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
We report in this study the first time that two separate autoimmune models have been "combined" through a single genetic cross. We were taking the advantage of a single cross in an identical environmental condition to compare the genetics of these two (CIA and PGIA) most frequently used murine models of RA. We immunized F2 hybrids of two parent strains, which are susceptible for either CIA or PGIA, but not vice versa. Although DBA/1 mice are highly susceptible for CIA, this strain is completely resistant to proteoglycan immunization (26). In contrast, 100% of the BALB/c females respond with arthritis to the immunization with human cartilage proteoglycan, and while they do respond well to collagen immunization, they are completely resistant to CIA. The incidence, onset, and severity of the disease were distinct in these two models. The inheritance in arthritis susceptibility was also different. F1 hybrids of DBA/1 x resistant strain intercrosses develop CIA in a high percentage, but PGIA does not affect F1 hybrids of BALB/c parents (11, 28, 36). In contrast, 41% of F1 mice of BALB/c x DBA/1 intercross developed PGIA (Fig. 1 and Table I). This penetrance of the disease (PGIA) in F1 generation was highly unexpected, and evidently certain genes from DBA/1 parents overruled the recessive inheritance in F1 hybrids. Although the different MHC haplotype (H-2d in BALB/c and H-2q in DBA/1) might modify the disease susceptibility in F1 hybrids, the susceptibility in F2 hybrids did not correlate with the presence or absence of the H-2q allele (13).

The susceptibility of F1 hybrids in heterozygous BALB/c background can be explained in the view of QTL analysis. The effect of MHC on the PGIA in F2 hybrids is the strongest QTL, i.e., can be considered as a major gene for this autoimmune disease, but is comparable with other QTL on other chromosomes (Table IV). Eventually, as we cannot identify a "super"-dominant gene or loci in PGIA, the whole set of genes is important for the development of this polygenic autoimmune disease (Fig. 3; Table IV). In contrast, in CIA, the effect of a major gene that controls all or many other genes all over the genome is very strong with the result of 100% incidence in F1 hybrids. QTL analysis of F2 hybrids showed that MHC locus on mouse chromosome 17 had an exceptionally high LOD score value of 21, equally significant in both sexes (Fig. 3 and Table III). Other QTL in CIA, while significant, are much smaller and can only modify the disease profile. The overall pattern of disease inheritance traced in parental strains, F1 and F2 hybrids of both arthritis models can be described the best as interaction between the major arthritis gene controlling susceptibility to the disease (either CIA or PGIA) and other genes for disease incidence and severity (13). In this study, using a large number of animals, we aimed to detect not only the effect of the major arthritis gene residing inside MHC locus (Fig. 3), but we also screened the entire genome, and analyzed all possible traits or substraits in all immunized animals.

Perhaps the most important finding from these experiments has been the observation of how strong the contribution of a resistant background can be to disease development. We were astounded by the observation that the CIA profile was faster and much more severe in the F2 hybrids than in the parental DBA/1 strain (Figs. 1C and 2; Table I). This suggests that while the BALB/c strain is resistant to CIA, it contains significant numbers of loci that can contribute to the disease, when placed in the proper background. Interestingly, the reciprocal observation was not true (Table I). This observation supports the hypothesis described above for a dominant gene in CIA controlling susceptibility, and the presence of multiple genes controlling clinical traits in PGIA. The strength of these loci is further illustrated by the suppression of the sex effect in F2 hybrids (Table I), which is typically seen in parent DBA/1 mice immunized for CIA (16) and in BALB/c mice immunized for PGIA (23, 24).

As expected, the linkage analysis identified different localization patterns for the susceptibility, onset, and severity QTL in murine models of arthritis (Fig. 3; Table III and Table IV). Although qualitative/binary trait loci, i.e., the disease susceptibility, were colocalized with the onset of arthritis in most cases, severity QTL exhibited very diverse distributions over the genome, and essentially no linkage with other clinical traits were found (Figs. 3 and 4). Only the telomeric part of chromosome 5 in CIA carried a locus that contributed to all clinical traits analyzed (Fig. 3). Chromosomes 3 and 5 carried major severity QTL in the CIA, and chromosome 9 in the PGIA, model.

Analysis of chromosomal loci that control arthritis conditions and are linked to immunological and/or pathophysiological traits in mice might help to reveal true arthritis loci in different models. Assuming this hypothesis is correct, we calculated linkage for all scored immune response parameters and cytokines, even if no arthritis QTL was identified in the region for the particular model (Tables III and IV). Indeed, while clinical QTL in CIA on chromosome 5 (mCia11) and chromosome 10 (mCia8) did not show any relationships with immune parameters in our CIA population, the same chromosome regions, while not carrying clinical traits for PGIA, interlaced with IL-1 and IL-4 (Pgia16) and T cell responses (Pgia6). QTL on chromosome X (mCia13) is linked to other pathophysiological traits in the CIA model, such as IgG1/IgG2a ratio, sCD44, and IL-2 production, but the same locus also influenced IL-1 and sCD44 production in PGIA (Pgia25).

Taking advantage of the combined model of RA we used in this study, we have analyzed overlapping immune and clinical QTL discovered for each model (Tables III and IV). Only one locus shared high significance in both models: the MHC on chromosome 17 (Pgia17, mCia1). The MHC is exceptionally important carrying the most dominant alleles for susceptibility to insulin-dependent diabetes mellitus, RA, systemic lupus erythematosus, multiple sclerosis in human autoimmune diseases, and their animal models (38, 39). Although the MHC is the most important known genetic predisposition factor for all autoimmune diseases mapped to date in humans or in corresponding animal models, the MHC alone is insufficient for disease induction, and can only partially control the progression of established disease. This seems to be also relevant for autoimmune arthritis models (11, 12, 13), and we are compelled to believe that additional QTL on chromosomes 5, 10, 18, and X are among the most important regions which control arthritis susceptibility, severity, or onset.

Loci on chromosome 5 (Pgia16, mCia10, and mCia11) are also involved in other arthritis models, such as pristane-induced arthritis (3) and CIA severity in rats (10). This region corresponds to the locus in the human genome that was shown to be involved in RA (40, 41) and type I diabetes (42). Genes that are localized in this region (40–80 cM) of mouse chromosome 5 were found to control murine lupus (43) and Lyme disease in mice (44, 45). Locus at 50–69 cM on mouse chromosome 10 (Pgia6, mCia8) was shown to be relevant for RA (38, 41), CIA in rats (9, 46), systemic lupus erythematosus in human patients and lupus-prone mice (38, 47), human type I diabetes (38, 48), and murine experimental autoimmune encephalomyelitis (49). A locus on mouse chromosome 18, around 50 cM (Pgia11, mCia18), corresponds to a QTL which is involved in RA (19, 50), and susceptibility to both murine experimental autoimmune encephalomyelitis (49) and lupus (39, 49, 51). QTL on chromosome X linked to arthritis were demonstrated in this study (Pgia24, Pgia25, mCia13) and in allied conditions of rat (52) and mouse studies (53), and in human patients with RA (19, 41). Chromosome X carries gene(s) linked to numerous immune disorders such as X-linked severe combined immunodeficiency (54), Graves’ disease (55), hyper-IgM syndrome (56), Bruton-type agammaglobulinemia (57, 58), and ichthyosis vulgaris (59). Many of these loci, and some additional QTL are summarized and discussed in Refs.38 and 39 , and the online database of Mendelian inheritance in man (60).

These results helped us to confirm the long-held hypothesis that while different autoimmune models may have model-specific genes, other loci will be shared between different models. Presumably, loci shared between multiple models are more likely to be involved in autoimmune diseases in general. This hypothesis is supported in the literature as many papers have documented clustering of loci in autoimmune disease models (14, 15, 16, 38, 39, 48, 61). Consequently, we believe that this combined model of arthritis provides a powerful tool for the identification and localization of common loci.


   Acknowledgments
 
We thank Drs. Vincent C. Hascall (Cleveland Clinic, Cleveland, OH), Dwight H. Kono (The Scripps Research Institute, La Jolla, CA), Jayne Lesley (The Salk Institute, Richmond, CA), Björn R. Olsen (Harvard Medical School, Boston, MA), Wim van den Berg (University of Nymegen, Nymegen, The Netherlands), and Warren Knudson (Rush University, Chicago, IL) for helpful comments, discussion and criticisms (all are members of the External Advisory Board of the "Autoimmune Arthritis: Genetics and Cellular Mechanisms" program). We thank Dr. Susan Shott (Rush University, Chicago, IL) for helpful statistical advice; Dr. Yefu Li (Harvard Medical School, Boston, MA) for many discussions on the genetics of polygenic traits; Diana Otto for technical help; and Dr. Jeffrey M. Otto (Genaissance Pharmaceuticals, New Haven, CT) for both discussion and valuable technical help. We also thank Dr. Joshua J. Jacobs, Leslie Manion-Patterson, and members of the Department of Orthopedics at Rush University for providing human cartilage samples; and Darci Biesczat, Stiliani Christodoulou, David Gerard, Sonja Velins, and Drs. Csaba Vermes, Raman Chandraskeran, and Ping Tao (all at Rush University) for expert technical assistance.


   Footnotes
 
1 This research has been supported in part by National Institutes of Health Grants AR-40310 and AR-45652 and the Arthritis Foundation (Greater Chicago Chapter). Back

2 Current address: Instituto de Microbilogia, Tucuman, Argentina. Back

3 Current address: Department of Orthopaedic Surgery, University of Pécs, Pécs, Hungary. Back

4 Address correspondence and reprint requests to Dr. Tibor T. Glant, Section of Biochemistry and Molecular Biology, Departments of Biochemistry and Orthopedic Surgery, Rush-Presbyterian-St. Luke’s Medical Center, 1653 West Congress Parkway, Chicago, IL 60612. E-mail address: tglant{at}rush.edu Back

5 Abbreviations used in this paper: RA, rheumatoid arthritis; QTL, quantitative trait loci; CIA, collagen-induced arthritis; PGIA, proteoglycan-induced arthritis; sCD44, soluble CD44; LOD, logarithm of the odds; SSLP, simple sequence length polymorphism. Back

Received for publication July 17, 2002. Accepted for publication December 18, 2002.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

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