Human Molecular Genetics, 2000, Vol. 9, No. 15 2241-2250
© 2000 Oxford University Press
Genetic dissection of a rat model for rheumatoid arthritis: significant gender influences on autosomal modifier loci
Inflammatory Joint Diseases Section, Arthritis and Rheumatism Branch, National Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, 9000 Rockville Pike, Building 10, Room 9N240, Bethesda, MD 20892-1820, USA and 1Research Service Veterans Affairs Medical Center and Department of Medicine/Rheumatology, University of Utah, Salt Lake City, UT, USA
Received 8 May 2000; Revised and Accepted 20 July 2000.
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ABSTRACT |
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Rheumatoid arthritis (RA) is a common, chronic, autoimmune, inflammatory disease that is influenced by genetic factors including gender. Many studies suggest that the genetic risk for RA is determined by the MHC, in particular class II alleles with a ‘shared epitope’ (SE), and multiple non-MHC loci. Other studies indicate that RA and other autoimmune diseases, in particular insulin-dependent diabetes mellitus (IDDM) and autoimmune thyroid disease (ATD), share genetic risk factors. Rat collagen-induced arthritis (CIA) is an experimental model with many features that resemble RA. The spontaneous diabetes-resistant bio-breeding rat, BB(DR), is of interest because it is susceptible to experimentally induced CIA, IDDM and ATD, and it has an SE in its MHC class II allele. To explore the genetics of CIA, including potential gender influences and the genetic relationships between CIA and other autoimmune diseases, we conducted a genome-wide scan for CIA regulatory loci in the F2 progeny of BB(DR) and CIA-resistant BN rats. We identified 10 quantitative trait loci (QTLs), including 5 new ones (Cia15, Cia16*, Cia17, Cia18* and Cia19 on chromosomes 9, 10, 18 and two on the X chromosome, respectively), that regulated CIA severity. We also identified four QTLs, including two new ones (Ciaa4* and Ciaa5* on chromosomes 4 and 5, respectively), that regulated autoantibody titer to rat type II collagen. Many of these loci appeared to be gender influenced, and most co-localized with several other autoimmune trait loci. Our data support the view that multiple autoimmune diseases may share genetic risk factors, and suggest that many of these loci are gender influenced.
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Rheumatoid arthritis (RA) is a common, chronic, autoimmune, inflammatory disease that affects the small joints of the hands and feet. The prevalence of RA is
1% in Caucasian populations, and the female-to-male ratio is 3–4:1 (1). This female-to-male disparity is most pronounced in the childbearing years (2,3). The risk of RA onset in women increases steadily until it reaches a peak around the perimenopause/menopause years. RA is uncommon in men under the age of 45 years, but risk increases in older age groups and approaches the risk of RA onset in females (2). Moreover, a number of hormonal abnormalities, such as estrogen and androgen deficiencies, are present in RA patients and may be involved in regulating onset and severity of RA (4). These data suggest that factors regulating female versus male susceptibility differences may be mechanistically linked to hormonal regulation, aging and reproductive function. Although environmental factors, gender, age and reproductive status clearly influence RA, numerous studies demonstrate that genetic factors also have an important influence on an individual’s susceptibility to RA (5). Familial clustering of RA cases is relatively common, in particular when the proband is severely affected (6,7). Twin studies also support the hypothesis of genetic involvement in RA, as monozygotic twins have a significantly higher risk of developing RA than do dizygotic twins (8,9). Many studies suggest that at least some of the genetic risk for RA can be explained on the basis of a ‘shared epitope’ (SE) in various class II HLA DR molecules (5,10). Despite this strong association, it is clear that multiple other genes are also involved in RA, as recent genome scan analyses provide evidence for multiple non-MHC susceptibility loci on many chromosomes (11,12).
Evidence also exists suggesting that RA may share one or more genetic risk factors with other autoimmune diseases. Familial clustering of several autoimmune diseases is frequently evident in families of RA probands. For example, the prevalence of insulin-dependent diabetes mellitus (IDDM) and autoimmune thyroid disease (ATD; includes Grave’s disease and Hashimoto’s thyroiditis) is significantly higher in the first degree relatives of RA probands than it is in the general population (7). Furthermore, a recent study which compared the linkage results from 21 previously published genome-wide scans, in a search for loci contributing to susceptibility to autoimmune disorders, suggested that several clinically distinct autoimmune diseases, in humans and in animals, may be controlled by a common set of susceptibility loci (13).
Heterogeneity, incomplete penetrance and environmental influences complicate the genetic dissection of RA and its relationships to IDDM, ATD and other autoimmune diseases in humans. Experimental animal models have the potential to markedly accelerate the identification and functional characterization of autoimmune disease regulatory loci. Rat models of inflammatory arthritis are particularly useful because large numbers of progeny can be generated from inbred strains that differ in their susceptibility to various forms of experimentally induced arthritis, including collagen-induced arthritis [CIA (14–19)], adjuvant-induced arthritis [AIA (15,19)], oil-induced arthritis [OIA (19,20)] and pristane-induced arthritis [PIA (19,21)].
Experimental animal models also provide a potential opportunity to more incisively dissect the inter-relationships of RA, IDDM, ATD and other autoimmune diseases. The spontaneous diabetes-resistant bio-breeding [BB(DR)] rat is particularly well suited for this effort. Although BB(DR) rats are resistant to both spontaneous IDDM and spontaneous ATD, they are susceptible to experimentally induced IDDM and ATD (22). The BB(DR) rat is also highly susceptible to CIA, and it has an SE in its HLA DR ß homolog, RT1.Dß (23). Thus, BB(DR) rats provide a model in which the inter-relationships of CIA, IDDM and ATD may be dissected, and support the view that multiple autoimmune diseases may share genetic risk factors. Interestingly, the first genetic linkage study of experimentally induced IDDM in the BB(DR) rat was only recently reported (24), and linkage studies of CIA and ATD have not yet been reported for the BB(DR) rat.
To explore the genetics of CIA in BB(DR) rats, including potential gender influences and the genetic relationships among CIA and other autoimmune diseases, we conducted a genome-wide scan for CIA regulatory loci in the F2 progeny of BB(DR) and CIA-resistant BN rats. Here, we report the identification of 10 quantitative trait loci (QTLs) that regulate CIA severity, including five that have not been previously identified, and four QTLs that regulate CIA autoantibody production against native rat type II collagen, including two that have not been identified previously, in [BB(DR) x BN]F2 rats. The majority of the QTLs identified in this cross, including two MHC-linked QTLs, appeared to be gender influenced, and most of the loci detected in our study showed linkage conservation with one or more loci that regulate other forms of autoimmune disease in humans.
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RESULTS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Phenotypic expression of CIA
As shown in Table 1, BB(DR) rats were highly susceptible to CIA, displaying severe polyarticular arthritis with high maximum arthritis score (MAS) and high IgG autoantibody titers to native rat type II collagen (AU-RII). BN rats were resistant to CIA, displaying no swelling (MAS = 0) and very low AU-RII. All F1 rats were susceptible with intermediate scores for both MAS and AU-RII (Table 1). F2 rats showed decreased incidence and increased range for both MAS and AU-RII compared with the F1 progeny (Table 1). There were no significant differences relating to strain parentage detected in the F1 or the F2 progeny for either MAS or AU-RII (data not shown); therefore, analyses of the combined data are shown (Table 1).
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There were no significant differences between females and males for MAS or AU-RII in either parental group or in the F1 progeny, irrespective of the direction of the cross (Table 1; data not shown). Significant differences between females and males were, however, detected in the F2 progeny, with females showing higher scores than males for both MAS and AU-RII (Table 1). The difference in AU-RII between female and male F2 progeny was observed irrespective of the direction of the cross (data not shown); however, the difference in MAS between female and male F2 progeny was observed only in animals whose paternal grandmother was BB(DR) (data not shown).
The F2 animals were also evaluated for correlation between MAS and AU-RII. MAS and AU-RII were weakly correlated with females showing a slightly higher correlation between the two traits than males (r2 = 0.37 in females and males combined, 0.44 in females alone, 0.33 in males alone).
MHC effects on CIA expression
In crosses involving DA rats, the genotype of markers within the MHC has been shown to have a significant effect on CIA expression (14,15,18). In our analysis of [BB(DR) x BN]F2 rats, animals homozygous for the BN allele at D20Wox3 (a marker for TNF-
which is located within the class III region of the rat MHC) showed only mild, if any, disease. Animals either homozygous or heterozygous for the BB(DR) allele at D20Wox3 showed substantially higher MAS (Fig. 1A) and AU-RII (Fig. 1B) compared with BN homozygotes. A comparison of scores between D20Wox3 genotype groups revealed that BB/BB > BB/BN > BN/BN for MAS, and BB/BB = BB/BN > BN/BN for AU-RII (Table 2). When scores were compared in females or males alone, the same pattern was observed (data not shown).
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QTL analysis of chromosome 20 revealed a highly significant MHC-linked severity QTL [maximum LOD score (MLS) = 9.4], as well as a highly significant MHC-linked autoantibody QTL (MLS = 39.9), both of which peaked at D20Wox3 (Table 2). This result further confirms previously identified linkage in analyses of (DA x F344)F2 and (DA x BN)F2 rats to the MHC for both CIA severity [Cia1 (14,15,18)] and CIA autoantibody [Ciaa1 (18,25)]. In this analysis of [BB(DR) x BN]F2 rats, the score-enhancing alleles for both Cia1 and Ciaa1 were contributed by the BB(DR) parent. Cia1 segregated with an additive mode of inheritance, and Ciaa1 segregated with a dominant mode of inheritance (Table 2). These modes of inheritance are consistent with phenotype data shown in Figure 1.
When QTL analysis was performed for females or males alone, Cia1 was similar in both females and males (data not shown). Sex-segregated analyses of Ciaa1, however, resulted in considerably different LOD scores between females (LOD = 27.9) and males (LOD = 14.2). A comparison of the median scores of females and males for each D20Wox3 genotype group revealed that females had marginally higher MAS than males in BB/BB and BB/BN animals, but there was no difference in MAS between females and males in the BN/BN group (Fig. 1A; Table 2). For AU-RII, females had significantly higher scores than males in all genotype groups, but particularly in BB/BB and BB/BN animals (Fig. 1B; Table 2).
Non-MHC effects on CIA expression
Because F2 animals that were homozygous for the BN allele at D20Wox3 showed minimal or no disease, we chose to focus our genome scan for non-MHC QTLs on F2 animals that were homozygous or heterozygous for the BB(DR) allele at D20Wox3. The resulting population, the BB(DR) TNF-subset population, contained 434 animals with a median MAS of 21 (range: 0–69) and a median AU-RII of 28 (range: 0–53). The females in the BB(DR) TNF-subset population (n = 230) had higher AU-RII than did the males (n = 204; P < 0.001), irrespective of the direction of the cross (data not shown). There was no statistically significant difference in this population between females and males for MAS, irrespective of the direction of the cross (data not shown). The correlation between MAS and AU-RII was less strong in the BB(DR) TNF-subset population than it was in the complete F2 population, and males showed slightly higher correlation between the two traits than did females (r = 0.11 in females and males combined, 0.08 in females alone, 0.12 in males alone).
In the preliminary scan for autosomal non-MHC CIA regulatory loci, QTL analysis in populations of females alone and males alone produced remarkably different log-likelihood plots for individual chromosomes (Fig. 2A and B). For each chromosome that showed evidence (LOD > 1.5) of either a severity or an autoantibody QTL, additional animals were genotyped until an MLS was reached. The log-likelihood plots for each QTL with an MLS of >2.8 (suggestive) are shown in Figure 2A and B. Additionally, the mode of inheritance, peak marker and 2 LOD support interval are shown in Table 2. Results of a Kruskal–Wallis one-way analysis of variance (ANOVA) are also shown in Table 2.
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From analysis of the female plus male F2 population, two significant and three suggestive QTLs regulating CIA severity were identified on chromosomes 1, 4, 8, 9 and 10 (Fig. 2A; Table 2). The QTLs on chromosomes 1, 4 and 8 overlapped with Cia2 (14), Cia13 (18) and Cia6 (14), previously identified in other crosses. The QTLs on chromosomes 9 and 10 are new and were named Cia15 and Cia16*, respectively (an asterisk denotes a new QTL with suggestive, but not significant, linkage). Sex-segregated log-likelihood plots suggested that both Cia13 and Cia15 regulated arthritis severity more strongly in females than in males, and that Cia2, Cia6 and Cia16* regulated disease more strongly in males than in females (Fig. 2A). For Cia2 and Cia6, the MLS was higher in males alone than in females plus males (Fig. 2A). For these five QTLs, comparisons of median scores revealed significant differences between females and males at their peak markers (Table 2).
Similarly, one significant and one suggestive QTL regulating autoantibody titer were identified on chromosomes 4 and 9 (Fig. 2B; Table 2). The QTL on chromosome 9 overlapped with Ciaa3, which was identified in a (DA x BN)F2 cross (18). The autoantibody QTL on chromosome 4 has not been previously identified; therefore, we named it Ciaa4*. The log-likelihood plots suggested that both Ciaa3 and Ciaa4* regulated autoantibody titer to rat type II collagen more strongly in females than in males (Fig. 2B). For both QTLs, significant differences between females and males were detected in all genotype groups (Table 2), but this may represent a gender influence independent of genotype.
There was little evidence of CIA-regulatory QTLs on chromosomes 2, 5 and 18 in analyses of the combined female plus male F2 data set. When analyses were conducted in females alone, however, a suggestive severity QTL on chromosome 2, a suggestive antibody QTL on chromosome 5 and a significant severity QTL on chromosome 18 were identified (Fig. 2A and B; Table 2). The suggestive autoantibody QTL on chromosome 5 and the significant severity QTL on chromosome 18 have not been identified previously. Thus, we named them Ciaa5* and Cia17, respectively. The QTL on chromosome 2 overlapped the previously identified QTL Cia7 (16) and was not given a new name. Sex-segregated log-likelihood plots suggested that Cia7, Ciaa5* and Cia17 regulated disease expression in females, but not in males (Fig. 2A and B). Comparisons between the median scores of females and males confirmed these gender influences (Table 2).
A suggestive severity QTL was identified near the centromere, and a significant severity QTL was identified near the telomere of the X chromosome (Fig. 2C; Table 2). CIA linkage to the rat X chromosome has not been reported previously; thus, we designated these loci Cia18* and Cia19, respectively.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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To explore the genetics of CIA, including potential gender influences, and the genetic relationships among CIA and other autoimmune diseases, we conducted a genome-wide scan for CIA regulatory loci in [BB(DR) x BN]F2 rats. BB(DR) rats provide an opportunity to address the genetics of CIA and the genetic relationships between CIA and other autoimmune diseases, because BB(DR) rats are susceptible to experimentally induced CIA, IDDM and ATD (23,26). This is an important observation because, in humans, IDDM, ATD and RA have been shown to cluster in families (7), and it has been suggested that IDDM, ATD and RA may share several genetic risk factors (13).
BN rats also provide an opportunity to investigate further the genetic relationships among multiple autoimmune diseases because they have a unique autoimmune disease susceptibility profile. BN rats are highly resistant to most autoimmune diseases (19,27), but they are highly susceptible to a few specific antibody-mediated autoimmune diseases (28–31). Thus, although they are resistant to CIA, BN rats may harbor alleles that enhance certain types of autoimmune disease expression, but these alleles are likely neutralized by powerful resistance loci in many autoimmune disease models.
In this analysis of [BB(DR) x BN]F2 rats, we identified 10 QTLs that regulated CIA severity and four QTLs that regulated CIA autoantibody production against native rat type II collagen. Two CIA severity loci were identified on the X chromosome, and many of the autosomal loci identified here appeared to be gender influenced. Furthermore, most of these CIA regulatory loci co-localized with loci that regulate RA and/or other autoimmune diseases in humans, thus supporting the view that multiple autoimmune diseases may share genetic risk factors.
As expected, the disease-enhancing alleles were contributed by the BB(DR) parent for the majority of the QTLs identified in this cross. For three of the severity QTLs (Cia2, Cia7 and Cia13) and two of the autoantibody QTLs (Ciaa4* and Ciaa5*), however, the disease-enhancing alleles were contributed by the BN parent. In a previous analysis of (DA x F344)F2 rats, we showed that for a CIA severity QTL on chromosome 1, Cia2, the disease-enhancing allele was contributed by the CIA-resistant F344 parent (14). Thus, BN rats, as well as other CIA-resistant strains, do indeed harbor alleles that enhance CIA, but these alleles are likely neutralized by other powerful autoimmune resistance loci in the genetic background.
Evidence exists suggesting that MHC alleles strongly influence the pathogenesis of CIA (14,15,18,19), and these alleles may be responsible for neutralizing CIA susceptibility loci in CIA-resistant rats. Highly significant linkage to the MHC has been demonstrated not only for CIA, but for several other forms of experimental arthritis (15,19–21) as well. Moreover, in humans, MHC subgroups of HLA-DR1, HLA-DR4 and HLA-DR10 molecules, primarily those with an SE, are associated with RA (5,10), and MHC associations have been noted for several other autoimmune diseases (32–40). In our analysis of [BB(DR) x BN]F2 rats, we found that the MHC strongly influenced both MAS and AU-RII, and we confirmed linkage to the MHC for both severity (Cia1) and autoantibody (Ciaa1) with highly significant LOD scores.
The role of the MHC in RA pathogenesis has been suspected to be gender influenced (41). A recent study showed that, among HLA molecules with an SE, DR1 is increased among male RA patients, whereas DR4 and DR10 are preferentially associated with female RA patients (42). In our analysis of [BB(DR) x BN]F2 rats, Cia1 appeared to be gender influenced, with females tending to exhibit higher scores than males. The susceptibility sequence of HLA-DR10 (RRRAA) is the same as that of RT1.Dß, the HLA DRß homolog in BB(DR) (23). Thus, our data appear to be consistent with the human data, and provide support for the hypothesis that the RRRAA sequence enhances autoimmune inflammatory arthritis to a greater extent in females than in males. Furthermore, these data suggest that other MHC alleles, in the context of their relationship to autoimmune disease susceptibility, may also be gender influenced.
Several non-MHC gender-influenced autosomal regulatory QTLs were also identified in our analysis of [BB(DR) x BN]F2 rats. Interestingly, some of these QTLs, Cia2 on chromosome 1, Cia7 on chromosome 2, Ciaa5* on chromosome 5, Cia6 on chromosome 8 and Cia17 on chromosome 18, exhibited a higher LOD score in the single-gender analysis than in the analysis of females and males combined. Furthermore, gender-segregated QTL analysis revealed multiple peaks in a single QTL region for chromosomes 1, 4, 8 and 9. Though methodological limitations of QTL analysis prevent us from resolving two closely linked regulatory loci as two distinct QTLs, a recent congenic study suggests that multiple gender-influenced loci may contribute to a single QTL in analyses of females and males combined (43).
In addition to these gender-influenced autosomal non-MHC CIA regulatory QTLs, two CIA severity QTLs (Cia18* and Cia19) were discovered on the X chromosome. In the F2 population, females had significantly higher scores than males for both MAS and AU-RII, suggesting possible X-linked QTLs. When these differences were analyzed with respect to the direction of the cross, the difference in MAS was evident only in animals with a parental grandmother that was BB(DR). This is consistent with the BB(DR) recessive mode of inheritance of Cia19 because females homozygous for BB(DR) alleles on the X chromosome can only be produced from crosses involving a BB(DR) X/BN Y male.
As mentioned previously, most of the CIA regulatory QTLs detected in this study co-localized with one or more loci that regulate RA and/or other autoimmune diseases, including IDDM and ATD, in humans (Table 3). Among the QTLs detected for the first time in this study, Cia17 on chromosome 18 as well as Cia18* and Cia19 on the X chromosome are of particular interest. For each of these QTLs, extensive co-localization with other autoimmune trait loci was identified in several species [Cia17: rats (44,45), mice (46–48), humans (11,32,39,49–51); Cia18*: rats (44,52,53), mice (47,54), humans (11,32,34,40,55); Cia19: rats (44,52), mice (54), humans (11,12,34,56,57)]. Moreover, for Cia17, Cia18* and Cia19, the disease-enhancing alleles were contributed by the BB(DR) parent; thus, these QTLs are potential autoimmune regulators, contributing to CIA and possibly to IDDM and ATD as well.
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In summary, we have provided further evidence that the MHC, and numerous non-MHC loci regulate CIA severity and autoantibody production in [BB(DR) x BN]F2 rats. Our data also support the view that multiple autoimmune diseases in rats, mice and humans share numerous genetic risk factors, and suggest that many, if not most, of these loci are gender influenced. Furthermore, our data suggest that the development of gender-specific therapies directed at biochemical pathways common to multiple related autoimmune diseases may be possible. Further analysis in rat models of autoimmune diseases, especially studies using congenic BB(DR) and BN rat strains, should facilitate evaluation of these hypotheses.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONRESULTSDISCUSSIONMATERIALS AND METHODSREFERENCES |
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Rats
Specific pathogen-free BB(DR)/Wor [BB(DR)] rats were obtained from Biomedical Research Models (Worchester, MA) and BN/SsNHsd (BN) rats from Harlan Sprague–Dawley (Indianapolis, IN). The generation of F2 progeny, induction and evaluation of CIA have been described previously (14–18).
Genotype analysis
Genotypes were determined by PCR amplification of polymorphic DNA fragments containing simple sequence repeats as described (58–60). Primer sequences and amplification protocols are available at the ARB Rat Genetic Database (http://www.nih.gov/niams/scientific/ratgbase/index.htm ). Primers were obtained from Research Genetics (Huntsville, AL), Genosys Biotechnologies (The Woodlands, TX), or synthesized by Lofstrand Laboratories (Gaithersburg, MD). The genetic map was constructed with the computer program MAPMAKER/EXP version 3.0b (61,62).
Analysis of chromosome 20 and the MHC
All F2 animals (n = 588) were evaluated for MHC genotype using D20Wox3 (a marker for TNF- which is located within the class III region of the MHC). Non-parametric analyses of MAS and AU-RII were conducted by comparing the scores of animals in each of the three possible genotype groups using a Kruskal–Wallis one-way ANOVA on ranks followed by Dunn’s method for multiple comparisons. Females and males from the phenotypic extremes (based on MAS) of the population were genotyped for several additional makers along chromosome 20. LOD scores for severity (MAS as trait) and autoantibody (AU-RII as trait) were calculated with MAPMAKER/QTL version 1.1b (63) in populations of females and males (n = 588, 64 genotyped), females alone (n = 308, 32 genotyped) and males alone (n = 280, 32 genotyped). In accordance with accepted linkage criteria, a LOD score of >4.3 was considered significant, and a LOD score between 2.8 and 4.3 was considered suggestive for linkage (64). Although MAPMAKER/QTL assumes normally distributed data, recent reports suggest that there are no significant differences between analyses from normalized data and analyses from non-normalized data (16,65). We, however, performed QTL analysis on both non-transformed data and data transformed via the arcsine square root transformation. No differences were detected between analyses of the non-transformed and transformed data; thus, results from the non-transformed data are shown.
Analysis of non-MHC genomic regions
Because animals homozygous for the BN allele at D20Wox3 displayed only mild, if any, disease, only animals homozygous or heterozygous for the BB(DR) allele at D20Wox3 [BB(DR) TNF-subset population; n = 434] were included in the genome scan for non-MHC QTLs. QTL analysis of the X chromosome is complicated by the fact that males are hemizygous for all X-linked loci. For this reason, we conducted our X chromosome analyses in females only and constructed a linkage map using an F2 method of analysis (66). As a preliminary scan, 60 females and 60 males from the phenotypic extremes (based on MAS) were genotyped at 187 autosomal markers and 60 females were genotyped at seven markers along the X chromosome with an average spacing of <15 cM across the genome. LOD scores were calculated as described for chromosome 20. For any marker which flanked an interval with a LOD score of >1.5 for either severity or autoantibody, additional animals were genotyped and LOD scores were recalculated. We continued to evaluate increasingly large data sets for each region until an MLS was reached. Once a QTL was identified, all animals in the BB(DR) TNF-subset population were genotyped at the peak marker of the QTL and non-parametric analyses for MAS or AU-RII were conducted as described for the MHC.
Statistical evaluation of gender influences
For each of the autosomal QTLs identified, the entire F2 population (for MHC-linked QTLs) or the BB(DR) TNF-subset population (for non-MHC QTLs) was divided into three groups of animals based on genotype at the peak marker of the QTL. Within each of these groups, the median scores of females and males were compared using the Mann–Whitney rank sum test.
Evaluation of the clustering of autoimmune loci among rats, mice and humans
Genetic linkage maps were generated using data obtained in this study, the ARB Rat Genetic Database (http://www.nih.gov/niams/scientific/ratgbase/index.htm ), the OTLEF Project Database (http://ratmap.ims.u-tokyo.ac.jp ), Mouse Genome Informatics (http://www.informatics.jax.org ) and the Genome Database (http://www.gdb.org ). Rat, mouse and human homologies were determined by comparison of mapped genes. An extensive literature search was performed to identify mapped loci that regulate autoimmune diseases in rats, mice or humans. Inter- and intraspecies comparisons were made between the QTLs identified in this [BB(DR) x BN]F2 analysis, and autoimmune trait loci identified from the literature.
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ACKNOWLEDGEMENTS |
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We acknowledge the funding support provided by the Arthritis Foundation and the Department of Veteran’s Affairs Biomedical Research Fund for part of this work.
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FOOTNOTES |
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+ These authors contributed equally to this work
§ To whom correspondence should be addressed. Tel: +1 301 496 6499; Fax: +1 301 402 0012; Email: wilderr@exchange.nih.gov
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REFERENCES |
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