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Different Species Common Arthritis

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Different Species Common Arthritis The Journal of Immunology High Resolution Mapping of Cia3: A Common Arthritis Quantitative Trait Loci in Different Species1 Xinhua Yu, Haidong Teng, Andreia Marques, Farahnaz Ashgari, and Saleh M. Ibrahim2 Murine collagen induced arthritis (CIA) is a widely used model of rheumatoid arthritis (RA). Identification of CIA susceptibility genes will aid in the understanding of RA pathogenesis and development of therapeutic targets. This study aims to identify and refine ؋ quantitative trait loci (QTL) controlling CIA. Major CIA clinical traits were evaluated in both (DBA/1 FVB/N) F2 and advanced intercross line (AIL) mice; QTLs were confirmed and refined in AIL. To search for candidate genes, we applied multiple approaches, including gene expression profiling, identification of nonsynonymous polymorphism, and comparative genomic mapping. We identified six suggestive QTLs controlling CIA clinical traits in the F2 progeny; one of these was confirmed and refined in AIL. This QTL is located on chromosome 6 and overlaps with Cia3, which was identified previously. We refined the 2-log support interval of Cia3 into a 5.6 Mb genomic region; 15 of 77 genes are differentially expressed or carry nonsynonymous polymorphisms between two parental strains. The counterpart genomic region of Cia3 on the rat and human genomes are linked to RA. Twenty-nine of 77 genes are located in the arthritis-linked genomic regions of all three species. Five of those 29 genes are differentially expressed or carry nonsynonymous poly- morphisms between parental strains: Timp4, Tmem40, Mbd4, Cacna1c, and Lrtm2. Taken together, we refined Cia3 into a 5.6 Mb genomic region on mouse chromosome 6 and identified candidate genes. This will aid in the search for susceptibility gene(s) controlling arthritis development within Cia3 and its counterpart regions in rat and human genomes. The Journal of Immunology, 2009, 182: 3016–3023. heumatoid arthritis (RA)3 is a chronic inflammatory auto- defined as a QTL. Therefore, the number of susceptibility genes could immune joint disease influenced by genetic and environ- be much larger than the number of the identified QTLs. On the other R mental factors (1). The genetic contribution to RA suscep- hand, identification of susceptibility genes within the QTLs is still a tibility is estimated to be as much as 60%, of which the HLA DRB1 challenging task, with the exceptions of few genes with very strong locus is thought to account for 30–50% (2, 3). However, identification effect on the disease, e.g., NCF1 (7). In most cases, a single quanti- of non-MHC RA susceptibility genes has been challenging due to tative trait gene contributes only mildly or moderately to the outcome genetic heterogeneity and incomplete penetrance, as well as the effect of the complex traits. To accelerate progress in the identification of of environmental factors on RA development. Presently, only a few susceptibility genes, several complementary approaches have been genes have been convincingly showed to be associated with RA, in- suggested, such as identification of polymorphisms in coding or reg- cluding PADI4, PTPN22, and CTLA4 (4, 5, 6). Genetic analysis of ulatory region, in vitro functional studies, transgenesis, knock-in mod- well-defined experimental models of autoimmune arthritis provides els, deficiency-complementation testing, mutational analysis, and ho- an alternative strategy to study the genetic basis of RA. A good ex- mology searches (10). In addition, advanced progress in mouse ample is identification of NCF1 as a novel susceptibility gene in au- genetics also accelerates progress in the identification of the quanti- toimmune arthritis (7). Animal models of RA have been used to iden- tative trait genes. For example, genomes of the 16 commonly used tify susceptibility genes, and multiple quantitative trait loci (QTLs) mouse inbred strains have been recently sequenced, and 8.27 million have been identified (see Ref. 8, 9). SNPs have been identified (11). Therefore, polymorphisms within a Despite the many advantages of animal models, identification of QTL identified in those 16 strains or their substrains can be obtained, susceptibility genes in animal models is limited by two factors. On which will considerably help in the identification of candidate genes. one hand, linkage analysis is not as powerful as case-control associ- Previously we performed a genome-wide linkage analysis in a F2 ation studies. As a consequence, a genomic region containing a sus- progeny to identify QTLs controlling collagen-induced arthritis (CIA) ceptibility gene that has very small effect on disease might not reach and generated an advanced intercross line (AIL) to refine those QTLs the significant threshold of the linkage analysis, and thus will not be (12, 13). In the F2 progeny, we identified one QTL with a strong effect on CIA clinical traits, Cia2, that contributes to only 16% of the phe- Section of Immunogenetics, University of Rostock, Germany notype variant (12). This suggests that there could be additional sus- ceptibility gene(s) whose effect is masked by Cia2, and thus failed to Received for publication September 10, 2008. Accepted for publication December 24, 2008. reach a significant threshold. In this study, we investigated six The costs of publication of this article were defrayed in part by the payment of page genomic regions that showed suggestive level of linkage to CIA in F2 charges. This article must therefore be hereby marked advertisement in accordance mice. We used the AIL to confirm those suggestive QTLs and refine with 18 U.S.C. Section 1734 solely to indicate this fact. the positive(s) into a small genomic region. Also, we investigated the 1 This study was supported by the EU FP6 contract MRTN-CT-2004-005693 candidate genes for one confirmed and refined QTL by defining dif- (EURO-RA). ferentially expressed genes, identifying the nonsynonymous polymor- 2 Address correspondence and reprint requests to Dr. Saleh M. Ibrahim at the current address: Genetics Group, Department of Dermatology, University of Lu¨beck, Ratzeburger phisms, and performing comparative genomic mapping. Allee 160, 23538 Lu¨beck, Germany. E-mail address: [email protected] 3 Abbreviations used in this paper: RA, rheumatoid arthritis; QTL, quantitative Materials and Methods trait loci; CIA, collagen-induced arthritis; AIL, advanced intercross line; chr., Phenotypic traits of CIA chromosome; SNP, single nucleotide polymorphism. ϫ Two mouse populations used in this study, 290 (DBA/1 FVB/N)F2 ϫ Copyright © 2009 by The American Association of Immunologists, Inc. 0022-1767/09/$2.00 mice and 308 (DBA/1 FVB/N)F11/12 AIL mice, were generated www.jimmunol.org/cgi/doi/10.4049/jimmunol.0803005 The Journal of Immunology 3017 Table I. List of QTLs controlling clinical traits of CIA Chr. Marker LOD Score Traits Susceptible Allele Overlap with CIA QTLs severity, onset, susceptibility DBA/1 Cia2, Cia4 ءءD2Mit81 10.4 2 severity FVB/N Cia3 ءD6Mit328 2.37 6 severity FVB/N ءD7Mit248 2.12 7 severity DBA/1 Cia8 ءD10Mit261 2.1 10 severity FVB/N Cia40 ءD11Mit126 2.08 11 susceptibility FVB/N ءD18Mit222 2.43 18 onset FVB/N ءD19Mit90 2.66 19 .suggestive ,ء highly significant and ,ءء previously in our laboratory. Detailed information of mice characteris- reevaluated using the scoring system that was applied in AIL mice (13). tics and induction of CIA were described previously (12, 13). Three The onset trait of the F2 and AIL mice were calculated previously (12, clinical traits of CIA were used for linkage analysis: severity, onset, and 13). Susceptibility is a qualitative trait, with a score of 0 and 1 for the susceptibility. The CIA severity (maximal score) in the F2 progeny was healthy and diseased mice, respectively. Table II. ANOVA analysis of chromosomes with evidence of linkage in F2 and AIL F2 mice AIL mice Chr. Markers Position (Mb) F p value Markersa Position (Mb) F p value 6 D6Mit67 97.7 2.92 0.053000 D6Mit67 97.7 0.63 0.531 D6Mit328 112.7 5.52 0.004400 D6Mit328 112.7 3.56 0.029 D6MIt10 113.2 3.95 0.02 D6Mit329 114.1 3.96 0.02 D6Mit366 115.2 5.96 0.00278 D6Mit115 116.7 8.7 0.00021 rs51294806 117.6 6.12 0.00264 rs6295683 118.5 5.77 0.00345 rs30265977 119.7 2.51 0.082 rs50344715 123.5 1.12 0.327 D6Mit335 127.5 2.78 0.0638 D6Mit14 145.6 1.35 0.261000 D6Mit14 145.6 0.47 0.624 7 D7Mit228 47.3 2.69 0.070900 D7Mit228 47.3 0.94 0.392 D7Mit229 52.9 2.13 0.12 D7Mit193 57 1.66 0.191 D7Mit83 59.1 1.39 0.249 D7Mit295 63.6 1.52 0.219 D7Mit88 67.3 1.49 0.226 D7Mit248 73 5.17 0.006200 D7Mit248 73 1.94 0.144 D7Mit122 82.4 0.76 0.467 D7Mit350 90.7 2.59 0.076000 D7Mit350 90.7 0.96 0.382 D7Mit183 101.6 0.58 0.561 D7Mit323 108 1.26 0.285 10 D10Mit20 66.5 2.94 0.054000 D10Mit20 66.5 1.53 0.217 D10Mit32 69.1 1.91 0.148 D10Mit186 75.3 1.08 0.341 D10Mit174 75.7 0.54 0.582 D10Mit132 83.6 0.56 0.569 D10Mit261 85.1 4.88 0.008100 D10Mit261 85.1 1.47 0.231 D10Mit94 87.7 0.32 0.722 D10Mit161 90.2 0.83 0.436 D10Mit41 93.7 0.12 0.887 D10Mit96 99.1 3.24 0.041000 D10Mit96 99.1 0.97 0.378 D10Mit70 103.5 0.348 0.706 11 D11Mit285 89.7 3.21 0.041700 D11Mit285 89.7 0.47 0.493 D11Mit70 93.9 1.75 0.175 D11Mit289 94.7 0.84 0.432 D11Mit145 97.5 3.2 0.041 D11Mit126 103.7 5 0.007300 D11Mit126 103.7 0.59 0.551 D11Mit58 104.4 0.81 0.447 rs27054829 105.5 0.86 0.425 rs27004424 106.4 0.14 0.873 rs27010185 107.4 2.54 0.08 D11Mit100 110 3.41 0.0344 D11Mit214 114.9 4.68 0.009900 D11Mit214 114.9 1.7 0.183 18 D18Mit67 12.1 0.93 0.396 D18Mit222 14.7 5.63 0.003900 D18Mit222 14.7 0.91 0.404 D18Mit230 17.8 1.65 0.193 D18Mit22 25.1 1.2 0.302 D18Mit12 36 2.75 0.065000 D18Mit12 36 0.6 0.548 19 D19Mit40 25.4 1.74 0.176 D19Mit46 32.7 1.21 0.297 D19Mit88 37.3 5.32 0.005300 D19Mit88 37.3 1.62 0.197 D19Mit90 42.2 6.58 0.001600 D19MIt11 42 1.18 0.308 D19Mit38 47 0.09 0.91 rs31054271 53.1 0.94 0.389 D19Mit84 56 1.27 0.28 rs37383437 57.3 1.83 0.161 D19Mit71 59.6 6.35 0.001900 D19Mit71 59.6 4.57 0.011 rs46580758 60.9 2.83 0.06 a Markers showing significant linkage are marked in bold.
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