Abstract
Objective
Accumulating evidence shows that shared autoimmunity is critical for the pathogenesis of many autoimmune diseases. Systemic sclerosis (SSc) belongs to the connective tissue disorders, and recent data have highlighted strong associations with autoimmunity genes shared with other autoimmune diseases. To determine whether novel risk loci associated with systemic lupus erythematosus or multiple sclerosis may confer susceptibility to SSc, we tested single-nucleotide polymorphisms (SNP) from ITGAM, ITGAX, and CD58 for associations.
Methods
SNP harboring associations with autoimmune diseases, ITGAM rs9937837, ITGAX rs11574637, and CD58 rs12044852, were genotyped in 2 independent cohorts of European Caucasian ancestry: 1031 SSc patients and 1014 controls from France and 1038 SSc patients and 691 controls from the USA, providing a combined study population of 3774 individuals. ITGAM rs1143679 was additionally genotyped in the French cohort.
Results
The 4 polymorphisms were in Hardy-Weinberg equilibrium in the 2 control populations, and allelic frequencies were similar to those expected in European Caucasian populations. Allelic and genotypic frequencies for these 3 SNP were found to be statistically similar in SSc patients and controls. Subphenotype analyses for subgroups having diffuse cutaneous subtype disease, specific autoantibodies, or fibrosing alveolitis did not reveal any difference between SSc patients and controls.
Conclusion
These results obtained through 2 large cohorts of SSc patients of European Caucasian ancestry do not support the implication of ITGAM, ITGAX, and CD58 genes in the genetic susceptibility of SSc, although they were recently identified as autoimmune disease risk genes.
Key Indexing Terms: SYSTEMIC SCLEROSIS, SYSTEMIC LUPUS ERYTHEMATOSUS, AUTOIMMUNITY SINGLE NUCLEOTIDE POLYMORPHISM, ITGAM, ITGAX, CD58
Systemic sclerosis (SSc) is a chronic autoimmune disease with a complex pathogenesis that is driven by a combination of genetic risk factors and environmental events1.
Accumulating data have demonstrated shared autoimmunity pathways and genetic susceptibility factors among various autoimmune diseases. Most of these genetic susceptibility factors are frequently replicated in different diseases such as insulin-dependent diabetes mellitus, multiple sclerosis (MS), systemic lupus erythematosus (SLE), rheumatoid arthritis (RA), juvenile idiopathic arthritis, celiac disease, and others2.
Regarding SSc, recent data have shown that the main shared genetic factors that contribute the most to susceptibility are the major histocompatibility complex (MHC), IRF5, STAT4, BANK1, PTPN22, and TNFAIP33,4. These genes and pathways are, strikingly, all known to contribute to susceptibility to SLE.
In SLE, some new risk loci have recently been identified. Among these, ITGAM and ITGAX were identified first in association studies performed in large cohorts. Proteins encoded by these latter genes all belong to the integrin family. Among integrin molecules, very late antigen-4 (VLA-4) and lymphocyte function associated-1 (LFA-1) have been implicated in both SLE and SSc5,6. Some hypotheses suggest their participation in maintaining the pathogenic cells in targeted tissues, thereby promoting tissue damage7.
ITGAM, also known as CD11b, is located in chromosome 16p11.2 and encodes for the α-chain of the αMβ2– integrin. This leukocyte-specific integrin regulates cell activation and adhesion of neutrophils and monocytes, permitting endothelium stimulation and phagocytosis of complement-coated particles. Particular involvement in immune complex clearance can be linked to the demonstrated impairment of this function in SLE8. Indeed, a deficiency of ITGAM leads to enhanced production of interleukin 6 by antigen-presenting cells9. rs9937837 and other genetic variants located on chromosome 16p11.12 near the gene ITGAM were found to contribute to SLE susceptibility in a genome-wide association study (OR 1.28, p = 7 × 10−7)10. At the same time, another strong genetic variant of ITGAM rs1143679 was reported to be associated with SLE (OR 1.78, p = 1.7 × 10−17)11. A metaanalysis strengthened these results and a strong association of ITGAM rs9937837 (OR 0.47) and rs1143679 (OR 3.04) was shown to influence disease severity12,13,14. This latter finding was convincingly reported as the putative causal variant15.
ITGAX encodes the integrin α-X chain protein, which forms by association with β-chain, another leukocyte-specific integrin that overlaps the properties of ITGAM. ITGAM variants have been found to be associated with SLE (OR 1.3). However, linkage disequilibrium data with ITGAM have questioned its role as an independent signal10. This assumption was emphasized by the role of rs114367915.
MS and RA also share genetic susceptibility factors with other autoimmune diseases. Another new risk locus shown to be associated with MS is CD58, also known as LFA-3. It encodes a member of the immunoglobulin superfamily, a ligand of the T lymphocyte CD2 protein, and has been implicated in adhesion and activation of T lymphocytes. The rs12044852 variant of CD58 was found to be associated in a large genome-wide association study (OR 1.48)16 in MS and was independently replicated17. Another CD58 variant was also found to be associated with RA (OR 1.14)18.
Taking into account (1) the autoimmune background of SSc; (2) the contribution of shared autoimmunity in this condition; (3) the recent report of new autoimmune susceptibility risk factors belonging to integrin genes for autoimmune diseases10; and (4) implication of integrins in SSc, we investigated whether ITGAM, ITGAX, and CD58 variants may confer susceptibility to SSc.
MATERIALS AND METHODS
We performed a large case-control association study in 2 independent cohorts of European Caucasian ancestry: a French cohort consisting of 1031 SSc patients compared to 1014 healthy unrelated controls and a US cohort including 1038 SSc patients and 691 controls. For all SSc patients, LeRoy’s cutaneous subtype was determined19 and phenotypic assessment was carried out, as recommended20. These cohorts have been described in detail4,21.
The study was approved by all the necessary local institutional review boards, and written informed consent was obtained from all subjects. Genotyping. We selected the following 3 SNP, for which the most convincing association signals have been reported in autoimmune diseases: rs9937837 ITGAM10, rs11574637 ITGAX10, and rs12044852 CD5816. Another SNP at the ITGAM locus, nonsynonymous rs1143679 (R77H) located in exon 312, was studied only in the French cohort, as being more recently reported, and was not initially included in this study. These SNP were genotyped using a competitive allele-specific polymerase chain reaction system (Kaspar Genotyping, Kbioscience, Hoddeston, UK) for the French cohort, as reported22, and a predesigned TaqMan SNP genotyping assay (Applied Biosystems, Foster City, CA, USA) in the US cohort21. The average genotype completeness for these SNP polymorphisms was 99% for the SSc samples and the controls. The accuracy was > 99%, according to duplicate genotyping of 10% of all samples using the Taqman SNP genotyping assay-allelic discrimination method (Applied Biosystems).
Statistical analyses
The statistical analyses were performed using the R software (version 2.10.0). The level of significance for all the tests corresponds to a type I error-rate α = 5%. Tests for conformity with Hardy-Weinberg equilibrium were performed using a standard chi-square test (1 degree of freedom). Individual analyses of association of the 4 SNP with SSc were performed by comparing cases and controls by Fisher’s exact test on genotype distribution. The same procedure was applied in subgroups stratified according to SSc phenotypes. Bonferroni’s correction was applied to all tests of SNP marker associations with the disease (the p value multiplied by n SNP) and to all “hypothesis-generating steps” when comparing the SSc subgroups and control (10 phenotypic subsets). P values adjusted for multiple testing are indicated in the tables and identified as Padj in the text.
In case an association signal was detected in one population, the combined data for the 2 populations were analyzed by calculating the homogeneity of odds ratios between cohorts by the Breslow-Day and Woolf Q methods; and by calculating the pooled odds ratios under a fixed-effects model (Mantel-Haenszel metaanalysis) or a random-effects model (DerSimonian-Laird), as appropriate. The linkage disequilibrium structure of the loci of interest was scrutinized and linkage disequilibrium blocks defined using the expectation-maximization (EM) algorithm, as implemented in the haplo.stats R library.
Power calculation
Statistical power was assessed by a standard noncentral chi-square approximation, as described23. For ITGAM, taking into account the expected frequency of the rare allele of rs9937837, the set has a power of 98% and 99%, respectively, in French and combined cases for detecting an association between SSc and this variant, with an OR of 1.5 at the 5% significance level. For the other SNP of ITGAM rs1143679, the French set has a power of 88% with an OR of 1.5. Similarly, the power for ITGAX rs11574637 was at 96% in the French SSc set and 99% in the combined populations. Finally, statistical power was 77% and 99% in French and combined populations for CD58 rs12044852, respectively.
RESULTS
Demographic data and disease characteristics of SSc patients and controls are shown in Table 1.
Table 1.
Clinical and serologic characteristics of patients with systemic sclerosis.
| Characteristic | French Caucasian N = 1014 (%) |
US Caucasian N = 691 (%) |
|---|---|---|
| Controls | ||
| Sex | ||
| Female | 646 (64.2) | 329 (50.5) |
| Male | 360 (35.8) | 322 (49.5) |
| Systemic sclerosis | ||
| Sex | N = 1031 (%) | N = 1038 (%) |
| Female | 875 (85.7) | 918 (88.4) |
| Male | 146 (14.3) | 120 (11.6) |
| Skin involvement | N = 971 (%) | N = 983 (%) |
| Limited systemic sclerosis | 650 (66.9) | 600 (61.0) |
| Diffuse systemic sclerosis | 321 (33.1) | 383 (39.0) |
| Autoantibodies | N = 928 (%) | N = 653 (%) |
| Anti-centromere | 377 (40.6) | 293 (44.9) |
| Anti-topoisomerase I | 253 (27.3) | 172 (26.3) |
All the SNP were in Hardy-Weinberg equilibrium in the control populations. Allelic frequencies were found to be in good agreement with those previously reported in the European population10,11,17.
In the French cohort, the ITGAM rs9937837 G allele was found on 30% of chromosomes of SSc patients compared to 27.8% of controls (p = nonsignificant; Table 2). The ITGAM rs1143679, the other SNP tested in only the French cohort, did not show genotypic or allelic associations to SSc (allelic frequency 13.5% in SSc cases, 12.6% in controls). The ITGAX rs11574637 C minor allele frequency was found, respectively, on 20.4% and 18.9% of SSc case and control chromosomes (Table 3). Regarding the third locus, the CD58 rs12044852 A allele was found on 10.3% of chromosomes from SSc cases compared to 9.5% from controls.
Table 2.
Distribution of ITGAM rs9937837 in patients with SSc and healthy controls.
| No. | Genotype, % | G Allele, % | Allelic Association | ||||
|---|---|---|---|---|---|---|---|
| GG | GT | TT | p | OR (95% CI) | |||
| French Caucasian | |||||||
| Controls | 971 | 8.5 | 38.7 | 52.8 | 27.8 | ||
| Patients with SSc | 1001 | 9.2 | 41.7 | 49.1 | 30.0 | 0.13 | 1.1 (0.97–1.3) |
| Limited SSc | 630 | 8.4 | 42.7 | 48.9 | 29.8 | 0.23 | 1.1 (0.9–1.3) |
| Diffuse SSc | 312 | 10.9 | 40.7 | 48.4 | 31.3 | 0.10 | 1.18 (0.97–1.4) |
| Autoantibodies | |||||||
| Anti-centromere | 363 | 10.5 | 40.8 | 48.7 | 30.9 | 0.12 | 1.16 (0.96–1.4) |
| Anti-topoisomerase I | 248 | 8.5 | 47.2 | 44.3 | 32.1 | 0.06 | 1.23 (0.99–1.5) |
| US Caucasian | |||||||
| Controls | 574 | 8.7 | 37.5 | 53.8 | 27.4 | ||
| Patients with SSc | 1029 | 8.0 | 43.9 | 48.1 | 29.9 | 0.14 | 1.13 (0.96–1.3) |
| Limited SSc | 591 | 8.5 | 43.7 | 47.9 | 30.3 | 0.13 | 1.15 (0.96–1.4) |
| Diffuse SSc | 384 | 7.0 | 45.1 | 47.9 | 29.6 | 0.31 | 1.11 (0.9–1.4) |
| Autoantibodies | |||||||
| Anti-centromere | 290 | 9.7 | 42.4 | 47.9 | 30.9 | 0.14 | 1.18 (0.9–1.5) |
| Anti-topoisomerase I | 170 | 5.3 | 50.6 | 44.1 | 30.6 | 0.26 | 1.17 (0.9–1.5) |
Table 3.
Distribution of ITGAX rs11574637 in patients with SSc and healthy controls.
| No. | Genotype, % | G Allele, % | Allelic Association | ||||
|---|---|---|---|---|---|---|---|
| GG | GT | TT | p | OR (95% CI) | |||
| French Caucasian | |||||||
| Controls | 993 | 3.3 | 31.1 | 65.6 | 18.9 | ||
| Patients with SSc | 1011 | 4.0 | 32.9 | 63.1 | 20.4 | 0.22 | 1.1 (0.9–1.3) |
| Limited SSc | 636 | 3.9 | 33.5 | 62.6 | 20.7 | 0.21 | 1.1 (0.9–1.3) |
| Diffuse SSc | 315 | 3.8 | 32.1 | 64.1 | 19.8 | 0.59 | 1.06 (0.85–1.3) |
| Autoantibodies | |||||||
| Anti-centromere | 367 | 4.4 | 33.2 | 62.4 | 21.0 | 0.22 | 1.1 (0.9–1.4) |
| Anti-topoisomerase I | 246 | 4.1 | 30.9 | 65.0 | 19.5 | 0.75 | 1.0 (0.8–1.3) |
| US Caucasian | |||||||
| Controls | 561 | 3.0 | 28.0 | 69.0 | 17.0 | ||
| Patients with SSc | 1013 | 3.9 | 30.9 | 65.2 | 19.4 | 0.1 | 1.17 (0.97–1.4) |
| Limited SSc | 584 | 3.9 | 31.7 | 64.4 | 19.8 | 0.09 | 1.2 (0.97–1.5) |
| Diffuse SSc | 377 | 4.2 | 30.0 | 65.8 | 19.2 | 0.22 | 1.16 (0.9–1.5) |
| Autoantibodies | |||||||
| Anti-centromere | 287 | 2.4 | 32.8 | 64.8 | 18.8 | 0.36 | 1.13 (0.9–1.5) |
| Anti-topoisomerase I | 166 | 5.4 | 33.1 | 61.4 | 22.0 | 0.039 | 1.37 (1.0–1.9) |
Very congruent results were obtained in the US cohort. Indeed, the G allele of ITGAM rs9937837 was found on 29.9% of SSc cases versus 27.4% on controls (p = non-significant; Table 2). The C minor allele of ITGAX rs11574637 was found in 19.4% of SSc case chromosomes and did not deviate from the frequency observed in the controls (17%; p = nonsignificant; Table 3). For the third locus, the CD58 rs12044852 A allele was found on 18.3% of chromosomes from SSc cases compared to 23.3% of controls.
Therefore, no significant evidence of allelic or genotypic association was detected for the ITGAM, ITGAX, and CD58 SNP (Tables 2, 3, and 4). Secondary analyses with adjustment for age and sex did not show any signal of association. Regarding linkage disequilibrium structure at the ITGAM/ITGAX locus, we found that r2 between the ITGAM rs9937837 and ITGAX rs11574637 was 0.26 and 0.25, respectively, between the 2 ITGAM rs9937837 and rs1143679 SNP in the French control population. Further, regarding SSc subphenotypes, intracohort comparisons also failed to detect any association. One signal for association was suggested in the US anti-topoisomerase I subset for ITGAM rs9937837, but this was not confirmed in the French sample. This led us to perform a metaanalysis, which also did not find any association (p = 0.31). Regarding CD58, the minor allele frequency differed between the 2 cohorts with respect to controls as well as SSc patients (Table 4). Although a trend for allelic association was observed for rs12044852 in the US cohort, the association signal was dropped after correction for multiple testing. There was no association in the French cohort (Table 4).
Table 4.
Distribution of CD58 rs12044852 in patients with SSc and healthy controls.
| No. | Genotype, % | A Allele, % | Allelic Association | |||||
|---|---|---|---|---|---|---|---|---|
| AA | AC | CC | p | Corrected padj | OR (95% CI) | |||
| French Caucasian | ||||||||
| Controls | 995 | 1.2 | 16.5 | 82.3 | 9.5 | |||
| Patients with SSc | 1015 | 1.0 | 18.5 | 80.5 | 10.3 | 0.40 | NA | 1.1 (0.89–1.3) |
| Limited SSc | 640 | 0.8 | 19.4 | 79.8 | 10.5 | 0.34 | NA | 1.1 (0.89–1.4) |
| Diffuse SSc | 316 | 1.3 | 17.4 | 81.3 | 10.0 | 0.70 | NA | 1.1 (0.79–1.4) |
| Autoantibodies | ||||||||
| Anti-centromere | 373 | 0.6 | 18.2 | 81.2 | 9.7 | 0.87 | NA | 1.0 (0.77–1.4) |
| Anti-topoisomerase I | 247 | 2.0 | 17.8 | 80.2 | 10.9 | 0.32 | NA | 1.2 (0.85–1.6) |
| US Caucasian | ||||||||
| Controls | 691 | 1.6 | 20.1 | 78.3 | 23.3 | |||
| Patients with SSc | 1038 | 0.9 | 16.6 | 82.6 | 18.3 | 0.017 | 0.051 | 0.76 (0.6–0.96) |
| Limited SSc | 600 | 1.0 | 17.0 | 82.0 | 19.0 | 0.08 | 0.8 | 0.80 (0.6–1.03) |
| Diffuse SSc | 383 | 0.5 | 15.7 | 83.8 | 16.7 | 0.017 | 0.17 | 0.69 (0.5–0.95) |
| Autoantibodies | ||||||||
| Anti-centromere | 293 | 1.0 | 14.3 | 84.6 | 16.4 | 0.023 | 0.23 | 0.68 (0.5–0.96) |
| Anti-topoisomerase I | 172 | 1.7 | 14.5 | 83.7 | 18.0 | 0.16 | NA | 0.75 (0.5–1.1) |
DISCUSSION
Although rare, SSc presents a major medical challenge, being one of the most severe connective tissue disorders in terms of its prognosis24. Shared autoimmunity pathways among SSc, SLE, and other autoimmune diseases are well illustrated by many common genetic susceptibility factors25. This led us to test for associations of these new autoimmune loci in SSc. Our results from 2 large independent cohorts showed that the studied polymorphisms of ITGAM, ITGAX, and CD58 do not contribute to susceptibility to SSc or its subphenotypes in European Caucasians. Some concerns have been raised regarding the linkage disequilibrium structure of the ITGAM/ITGAX locus, leading us to genotype another SNP of ITGAM, rs1143679, that could be the causal variant in different ethnic groups11,13,15,26. The calculation in our sample did not reveal linkage disequilibrium between ITGAM rs9937837 and rs1143679 or between ITGAM rs9937837 and ITGAX rs11574637, suggesting that they represent independent loci. The functional SNP rs1143679 that may be the causal variant of association in lupus was not associated with SSc in our study; although the genotyping was restricted to the French population, the statistical power reasonably suggests the lack of association in this sample. Furthermore, similar data were reported in RA27, suggesting a specific role of ITGAM in SLE. However, more dense SNP genotyping is required before association with SSc can be definitely ruled out.
Methodological limitations of genetic studies must always be considered. Appropriate sample sizes for case and control cohorts are critical to provide sufficient statistical power28. In our study, the 2 large sample sizes of the cohorts provided a strong rationale for ruling out type II statistical bias. Further, the genetic background of the studied populations should be as homogeneous as possible, thereby limiting bias by population stratification. To avoid this bias, ethnicity was taken into account and we focused on Caucasian individuals. Moreover, the 2 cohorts were very homogeneous in particular for proportions of SSc subphenotypes including autoantibodies. Available genetic data in SSc and autoimmune disease suggest that some critical immune factors contribute to autoimmunity, and these findings support the evolving concept that common risk genes underlie multiple autoimmune disorders. However, they also highlight that further specific, downstream biological mechanisms must be involved to generate the respective phenotypes. Integrins are central in maintaining the homeostasis of the cellular microenvironment permitted by extracellular matrix. They are also critical in mediating specific signaling events and function as master effectors of transforming growth factor-β activation that play a central role in any fibrotic process29,30. However, our results suggest that genetic variants of integrin coding genes may not be involved in SSc, despite playing a role in some autoimmune diseases.
The genotyping of 3 risk loci for autoimmune diseases (ITGAM, ITGAX, and CD58) in 2 large cohorts of European Caucasian ancestry from France and the USA did not reveal any allelic or genotypic association with SSc or its main subphenotypes.
Acknowledgments
Supported by Association des Sclérodermiques de France, INSERM; and by Groupe Français de Recherche sur la Sclérodermie and Agence Nationale pour la Recherche (grant no. R07094KS). The US studies were supported by NIH/NIAMS Scleroderma Family Registry and DNA Repository (N01-AR-0-2251) and NIH/NIAMS Center of Research Translation in Scleroderma (1P50AR054144).
For providing DNA samples from the control population, we thank EFS, Dr. Joelle Benessiano, CRB Bichat Claude Bernard. For DNA samples from the Lille Scleroderma population, our thanks to Dr. Isabelle Fajardy, Molecular Biology and Biochemistry Centre, Lille CHRU.
B. Coustet, Fellow, Université Paris Descartes, Rhumatologie A, Hôpital Cochin, APHP, INSERM U1016; S.K. Agarwal, MD, PhD; P. Gourh, MD, Division of Rheumatology and Clinical Immunogenetics, Department of Internal Medicine, University of Texas Health Science Center at Houston; M. Guedj, PhD, UMR CNRS-8071/ INRA-1152, Université d’Evry Val d’Essonne; M. Mayes, MD, Division of Rheumatology and Clinical Immunogenetics, Department of Internal Medicine, University of Texas Health Science Center at Houston; P. Dieude, MD, PhD, Université Paris 7, Rhumatologie, Hôpital Bichat; J. Wipff, MD, PhD; J. Avouac, MD, PhD, Université Paris Descartes, Rhumatologie A, Hôpital Cochin, APHP, INSERM U1016; E. Hachulla, MD, PhD, Université Lille II, Médecine Interne; E. Diot, MD, INSERM EMI-U 00-10, Médecine Interne, CHU Bretonneau; J.L. Cracowski, MD, PhD, INSERM CIC3, CHU Grenoble; K. Tiev, MD, PhD, Université Pierre et Marie Curie, Hôpital Saint Antoine; J. Sibilia, MD, PhD, Université Louis Pasteur, Rhumatologie, Hôpital Hautepierre; L. Mouthon, MD, PhD, Université Paris Descartes, Médecine Interne, Hôpital Cochin, APHP; C. Frances, MD, Université Paris 6, Dermatologie, Hôpital Tenon; Z. Amoura, MD, PhD, Université Paris 6, Médecine Interne, Pitié Salpêtrière; P. Carpentier, MD, Clinique Universitaire de Médecine Vasculaire, Pôle Pluridisciplinaire de Médecine, Centre Hospitalier Universitaire Grenoble; O. Meyer, MD, PhD, Université Paris 7, Rhumatologie, Hôpital Bichat; A. Kahan, MD, PhD, Université Paris Descartes, Rhumatologie A, Hôpital Cochin, APHP; C. Boileau, PharmD, PhD, Université Versailles Saint Quentin Yvelines, Laboratoire de Biochimie Hormonale et Génétique, Hôpital Ambroise Paré, APHP; F.C. Arnett, MD, Division of Rheumatology and Clinical Immunogenetics, Department of Internal Medicine, University of Texas Health Science Center at Houston; Y. Allanore, MD, PhD, Université Paris Descartes, Rhumatologie A, Hôpital Cochin, APHP, INSERM U1016.
References
- 1.Allanore Y, Wipff J, Kahan A, Boileau C. Genetic basis for systemic sclerosis. Joint Bone Spine. 2007;74:577–83. doi: 10.1016/j.jbspin.2007.04.005. [DOI] [PubMed] [Google Scholar]
- 2.Gregersen PK, Behrens TW. Genetics of autoimmune diseases—disorders of immune homeostasis. Nat Rev Genet. 2006;7:917–28. doi: 10.1038/nrg1944. [DOI] [PubMed] [Google Scholar]
- 3.Allanore Y, Dieude P, Boileau C. Updating the genetics of systemic sclerosis. Curr Opin Rheumatol. 2010;22:665–70. doi: 10.1097/BOR.0b013e32833d110a. [DOI] [PubMed] [Google Scholar]
- 4.Dieude P, Guedj M, Wipff J, Ruiz B, Riemekasten G, Matucci-Cerinic M, et al. Association of the TNFAIP3 rs5029939 variant with systemic sclerosis in the European Caucasian population. Ann Rheum Dis. 2010;69:1958–64. doi: 10.1136/ard.2009.127928. [DOI] [PubMed] [Google Scholar]
- 5.Sollberg S, Peltonen J, Uitto J, Jimenez SA. Elevated expression of beta 1 and beta 2 integrins, intercellular adhesion molecule 1, and endothelial leukocyte adhesion molecule 1 in the skin of patients with systemic sclerosis of recent onset. Arthritis Rheum. 1992;35:290–8. doi: 10.1002/art.1780350307. [DOI] [PubMed] [Google Scholar]
- 6.Takeuchi T, Amano K, Sekine H, Koide J, Abe T. Upregulated expression and function of integrin adhesive receptors in systemic lupus erythematosus patients with vasculitis. J Clin Invest. 1993;92:3008–16. doi: 10.1172/JCI116924. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Crow MK. Developments in the clinical understanding of lupus. Arthritis Res Ther. 2009;11:245. doi: 10.1186/ar2762. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Hepburn AL, Mason JC, Wang S, Shepherd CJ, Florey O, Haskard DO, et al. Both Fc-gamma and complement receptors mediate transfer of immune complexes from erythrocytes to human macrophages under physiological flow conditions in vitro. Clin Exp Immunol. 2006;146:133–45. doi: 10.1111/j.1365-2249.2006.03174.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Ehirchiou D, Xiong Y, Xu G, Chen W, Shi Y, Zhang L. CD11b facilitates the development of peripheral tolerance by suppressing Th17 differentiation. J Exp Med. 2007;204:1519–24. doi: 10.1084/jem.20062292. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Hom G, Graham RR, Modrek B, Taylor KE, Ortmann W, Garnier S, et al. Association of systemic lupus erythematosus with C8orf13-BLK and ITGAM-ITGAX. N Engl J Med. 2008;358:900–9. doi: 10.1056/NEJMoa0707865. [DOI] [PubMed] [Google Scholar]
- 11.Nath SK, Han S, Kim-Howard X, Kelly JA, Viswanathan P, Gilkeson GS, et al. A nonsynonymous functional variant in integrin-alpha(M) (encoded by ITGAM) is associated with systemic lupus erythematosus. Nat Genet. 2008;40:152–4. doi: 10.1038/ng.71. [DOI] [PubMed] [Google Scholar]
- 12.Fan Y, Li LH, Pan HF, Tao JH, Sun ZQ, Ye DQ. Association of ITGAM polymorphism with systemic lupus erythematosus: a meta-analysis. J Eur Acad Dermatol Venereol. 2010 Jul 13; doi: 10.1111/j.1468-3083.2010.03776.x. [Epub ahead of print] [DOI] [PubMed] [Google Scholar]
- 13.Yang W, Zhao M, Hirankarn N, Lau CS, Mok CC, Chan TM, et al. ITGAM is associated with disease susceptibility and renal nephritis of systemic lupus erythematosus in Hong Kong Chinese and Thai. Hum Mol Genet. 2009;18:2063–70. doi: 10.1093/hmg/ddp118. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Kim-Howard X, Maiti AK, Anaya JM, Bruner GR, Brown E, Merrill JT, et al. ITGAM coding variant (rs1143679) influences the risk of renal disease, discoid rash and immunological manifestations in patients with systemic lupus erythematosus with European ancestry. Ann Rheum Dis. 2010;69:1329–32. doi: 10.1136/ard.2009.120543. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Han S, Kim-Howard X, Deshmukh H, Kamatani Y, Viswanathan P, Guthridge JM, et al. Evaluation of imputation-based association in and around the integrin-alpha-M (ITGAM) gene and replication of robust association between a non-synonymous functional variant within ITGAM and systemic lupus erythematosus (SLE) Hum Mol Genet. 2009;18:1171–80. doi: 10.1093/hmg/ddp007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Hafler DA, Compston A, Sawcer S, Lander ES, Daly MJ, De Jager PL, et al. Risk alleles for multiple sclerosis identified by a genomewide study. N Engl J Med. 2007;357:851–62. doi: 10.1056/NEJMoa073493. [DOI] [PubMed] [Google Scholar]
- 17.Rubio JP, Stankovich J, Field J, Tubridy N, Marriott M, Chapman C, et al. Replication of KIAA0350, IL2RA, RPL5 and CD58 as multiple sclerosis susceptibility genes in Australians. Genes Immun. 2008;9:624–30. doi: 10.1038/gene.2008.59. [DOI] [PubMed] [Google Scholar]
- 18.Raychaudhuri S, Remmers EF, Lee AT, Hackett R, Guiducci C, Burtt NP, et al. Common variants at CD40 and other loci confer risk of rheumatoid arthritis. Nat Genet. 2008;40:1216–23. doi: 10.1038/ng.233. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.LeRoy EC, Black C, Fleischmajer R, Jablonska S, Krieg T, Medsger TA, et al. Scleroderma (systemic sclerosis): classification, subsets and pathogenesis. J Rheumatol. 1988;15:202–5. [PubMed] [Google Scholar]
- 20.Valentini G, Matucci-Cerinic M. Disease-specific quality indicators, guidelines and outcome measures in scleroderma. Clin Exp Rheumatol. 2007;25 (Suppl):159–62. [PubMed] [Google Scholar]
- 21.Gourh P, Agarwal SK, Martin E, Divecha D, Rueda B, Bunting H, et al. Association of the C8orf13-BLK region with systemic sclerosis in North American and European populations. J Autoimmun. 2010;34:155–62. doi: 10.1016/j.jaut.2009.08.014. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Dieude P, Guedj M, Wipff J, Ruiz B, Hachulla E, Diot E, et al. STAT4 is a genetic risk factor for systemic sclerosis having additive effects with IRF5 on disease susceptibility and related pulmonary fibrosis. Arthritis Rheum. 2009;60:2472–9. doi: 10.1002/art.24688. [DOI] [PubMed] [Google Scholar]
- 23.Guedj M, Della-Chiesa E, Picard F, Nuel G. Computing power in case-control association studies through the use of quadratic approximations: application to meta-statistics. Ann Hum Genet. 2007;71:262–70. doi: 10.1111/j.1469-1809.2006.00316.x. [DOI] [PubMed] [Google Scholar]
- 24.Karassa FB, Ioannidis JP. Mortality in systemic sclerosis. Clin Exp Rheumatol. 2008;26 (Suppl):S85–93. [PubMed] [Google Scholar]
- 25.Allanore Y, Dieude P, Boileau C. Genetic background of systemic sclerosis: autoimmune genes take centre stage. Rheumatology. 2010;49:203–10. doi: 10.1093/rheumatology/kep368. [DOI] [PubMed] [Google Scholar]
- 26.Suarez-Gestal M, Calaza M, Endreffy E, Pullmann R, Ordi-Ros J, Sebastiani GD, et al. Replication of recently identified systemic lupus erythematosus genetic associations: a case-control study. Arthritis Res Ther. 2009;11:R69. doi: 10.1186/ar2698. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Phipps-Green AJ, Topless RK, Merriman ME, Dalbeth N, Gow PJ, Harrison AA, et al. No evidence for association of the systemic lupus erythematosus-associated ITGAM variant, R77H, with rheumatoid arthritis in the Caucasian population. Rheumatology. 2009;48:1614–5. doi: 10.1093/rheumatology/kep254. [DOI] [PubMed] [Google Scholar]
- 28.Chanock SJ, Manolio T, Boehnke M, Boerwinkle E, Hunter DJ, Thomas G, et al. Replicating genotype-phenotype associations. Nature. 2007;447:655–60. doi: 10.1038/447655a. [DOI] [PubMed] [Google Scholar]
- 29.Munger JS, Huang X, Kawakatsu H, Griffiths MJ, Dalton SL, Wu J, et al. The integrin alpha v beta 6 binds and activates latent TGF beta 1: a mechanism for regulating pulmonary inflammation and fibrosis. Cell. 1999;96:319–28. doi: 10.1016/s0092-8674(00)80545-0. [DOI] [PubMed] [Google Scholar]
- 30.Chizzolini C, Brembilla NC, Montanari E, Truchetet ME. Fibrosis and immune dysregulation in systemic sclerosis. Autoimmun Rev. 2010 Sep 21; doi: 10.1016/j.autrev.2010.09.016. [Epub ahead of print] [DOI] [PubMed] [Google Scholar]