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Arthritis Rheum. Author manuscript; available in PMC Oct 1, 2013.
Published in final edited form as:
PMCID: PMC3425721
NIHMSID: NIHMS369426
Meta-analysis in granulomatosis with polyangiitis reveals shared susceptibility loci with rheumatoid arthritis
Sharon A. Chung, MD, MAS,1 Gang Xie, MD, PhD,2 Delnaz Roshandel, PhD,2 Richard Sherva, PhD,3 Jeffrey C. Edberg, PhD,4 Megan Kravitz, BA,5 Paul F. Dellaripa, MD,6 Gary S. Hoffman, MD,7 Alfred D. Mahr, MD, PhD,5,8 Philip Seo, MD,9 Ulrich Specks, MD,10 Robert F. Spiera, MD,11 E. William St. Clair, MD,12 John H. Stone, MD, MPH,13 Robert M. Plenge, MD, PhD,6 Katherine A. Siminovitch, MD,2 Peter A. Merkel, MD, MPH,5 and Paul A. Monach, MD, PhD5
1Rosalind Russell Medical Research Center for Arthritis, Division of Rheumatology, University of California, San Francisco, CA
2Samuel Lunenfeld Research Institute, Mount Sinai Hospital, Toronto, Canada
3Section of Biomedical Genetics, Boston University School of Medicine, Boston, MA
4Division of Clinical Immunology and Rheumatology, University of Alabama at Birmingham, Birmingham, AB
5Vasculitis Center, Section of Rheumatology, Boston University School of Medicine, Boston, MA
6Division of Rheumatology, Immunology and Allergy, Brigham and Women’s Hospital, Boston, MA
7Center for Vasculitis Care and Research, Cleveland Clinic, Cleveland, OH
8Department of Internal Medicine, Hôpital Saint-Louis, Assistance Publique-Hôpitaux de Paris, University Paris 7-Paris Diderot, Paris, France
9Division of Rheumatology, Johns Hopkins University, Baltimore, MD
10Division of Pulmonary and Critical Care Medicine, Mayo Clinic College of Medicine, Rochester, MN
11Rheumatology Division, Hospital for Special Surgery, New York, NY
12Division of Rheumatology and Immunology, Duke University, Durham, NC
13Rheumatology Unit, Massachusetts General Hospital, Boston, MA
Correspondence: Paul A. Monach, MD, PhD, 72 East Concord Street, E-533, Boston, MA 02118, Phone: 617-414-2503; Fax: 617-414-2510, pmonach/at/bu.edu
Objectives
To examine the association of previously identified autoimmune disease susceptibility loci with granulomatosis with polyangiitis (GPA, formerly known as Wegener’s granulomatosis), and determine whether genetic susceptibility profiles of other autoimmune diseases are associated with GPA
Methods
Genetic data from two cohorts were meta-analyzed. Genotypes for 168 previously identified single nucleotide polymorphisms (SNPs) associated with susceptibility to different autoimmune diseases were ascertained for a total of 880 GPA cases and 1969 controls of European descent. Single marker associations were identified using additive logistic regression models. Multi-SNP associations with GPA were assessed using genetic risk scores based on susceptibility loci for Crohn’s disease, type 1 diabetes, systemic lupus erythematosus, rheumatoid arthritis, celiac disease, and ulcerative colitis. Adjustment for population substructure was performed in all analyses using ancestry informative markers and principal components analysis.
Results
Genetic polymorphisms in CTLA4 were significantly associated with GPA in the single-marker meta-analysis (OR 0.79. 95% CI 0.70–0.89, p=9.8×10−5). A genetic risk score based on rheumatoid arthritis susceptibility markers was significantly associated with GPA (OR 1.05 per 1-unit increase in genetic risk score, 95% CI 1.02–1.08, p=5.1×10−5).
Conclusions
Rheumatoid arthritis and GPA may arise from a similar genetic predisposition. Aside from CTLA4, other loci previously found to be associated with common autoimmune diseases were not statistically associated with GPA in this study.
Keywords: genetics, vasculitis, granulomatosis with polyangiitis, rheumatoid arthritis, CTLA4
Granulomatosis with polyangiitis (GPA, Wegener’s) is a severe, multi-system inflammatory disease with a prevalence of about 1 in 10,000–40,000 persons of European ancestry (1). GPA is thought to be an autoimmune disease, since it is highly associated with autoantibodies to proteinase-3 (PR3), which are rare in the general population (24). It is unclear to what extent genetics contributes to risk of GPA. Family studies suggest a slight increase in risk (estimated at 1.5 – 3-fold) among close relatives, but this estimate is imprecise due to the rarity of the disease (5, 6).
Two genetic associations with GPA are well-established. One is in the HLA region, specifically HLA-DPB1 (7), and this finding provides further support for considering GPA to be fundamentally an autoimmune disease. The other is a null allele in alpha-1-antitrypsin (A1AT or SERPINA) (810). However, because these null alleles are uncommon, haploinsufficiency of A1AT accounts for only about 7% of cases of GPA (8). Many other polymorphisms have been investigated on the basis of knowledge of the role of the associated gene in immunity, but only two associations (in CD226 and FCGR3B) have been confirmed in more than one cohort (11, 12).
The contribution of many common genetic variants to risk for more common autoimmune diseases, such as rheumatoid arthritis, type 1 diabetes, and inflammatory bowel disease, has been established through genome-wide association studies (GWAS) and meta-analyses thereof (1327). Some polymorphisms appear to confer risk to multiple autoimmune diseases. Although candidate gene studies in GPA have often investigated genes related to immunity, they have usually followed hypotheses about the functions of particular genes of interest rather than focusing on polymorphisms that have already been shown to predispose to other diseases, with few exceptions (28, 29).
Support for pursuing the hypothesis that genes that predispose to other autoimmune diseases are also risk alleles for GPA comes from two sources. First, studies of familial associations between GPA and other autoimmune diseases have concluded that first-degree relatives of persons with GPA have a modest increase in risk of common autoimmune diseases in general (relative risk 1.32), and of rheumatoid arthritis, multiple sclerosis, psoriatic arthritis, and Sjogren’s syndrome in particular (6, 30). Calculated associations with lupus, inflammatory bowel disease, and ankylosing spondylitis were of similar magnitude but did not reach statistical significance, since these diseases were less common in the cohort (6). Second, several polymorphisms that have each been associated with risk of GPA in 1–2 cohorts have also been associated with other autoimmune diseases (11, 12, 28, 29, 31, 32).
We performed a candidate gene study in GPA of 168 single-nucleotide polymorphisms (SNPs) associated with one or more autoimmune diseases, with two goals: i) identify individual SNPs associated with GPA using a case-control design in two cohorts, and ii) test multi-SNP models of genetic risk (genetic risk scores, GRSs) developed for individual autoimmune diseases for their ability to predict increased risk of GPA, regardless of the statistical significance of the component SNPs. The study was more rigorous than most candidate gene studies, because we utilized ancestry-informative markers (AIMs) and principal components analysis to control for population stratification.
Study Subjects
Two cohorts were analyzed independently and then together by meta-analysis. All patients were enrolled using protocols approved by Institutional Review/Ethics Boards at the participating sites.
In the first cohort, 431 GPA cases and 392 healthy controls enrolled in the Wegener’s Granulomatosis Genetics Repository (WGGER) (8) and of self-identified European descent were genotyped. Subjects were recruited at 8 US centers between 2001 and 2005, and clinical data from cases were recorded using a standardized form. These data were reviewed to ensure that all cases met American College of Rheumatology (ACR) 1990 classification criteria for GPA (33). Controls were unrelated to cases and denied a personal or family history of autoimmune inflammatory diseases. Demographic data collected from cases and controls included age, sex, and race/ethnicity. In this sample, 47% of cases and 60% of controls were female, and mean age was 53.1 years (range 18–87) in cases and 49.5 (range 18–85) in controls. To increase the statistical power of this initial cohort, 82 individuals with northern and western European ancestry genotyped in the International HapMap Project (www.hapmap.org) from the CEPH (Centre d’Etude du Polymorphisme Humain) collection were included with the healthy controls in this study (see below). Thus, the total sample size for this cohort was 431 GPA cases and 473 controls.
A second cohort of 464 GPA cases was assembled in Toronto between 2001 and 2010 from multiple sites (50% US, 40% Canada, 10% Europe, less than 1% other locations), through physician contacts and online advertisement. Information about symptoms, organ involvement, and c-ANCA levels was garnered from physician records, and all cases met modified 1990 ACR criteria for GPA. Mean age was 52.8 years (range 14–85), and 55% of cases were female.
Controls for the Toronto cohort (n=1503) were derived from two sources: 380 volunteers from the Toronto metropolitan area (mean age 40 years, range 23–91, 82% female), and 1123 healthy persons recruited into the M.D. Anderson Cancer Center Lung Cancer Study (ongoing since 1999) from the Kelsey-Seibold Clinics in the Houston metropolitan area (mean age 61.1 years, 43% female). Controls reported no history of autoimmune disease, and all cases and controls were of European descent by self-report.
SNP Selection
A custom set of 384 SNPs, including 192 associated with autoimmune diseases and 192 ancestry informative markers (AIMs) (3436) was chosen for genotyping the WGGER cohort. All autoimmune disease-associated SNPs were outside of the HLA region. After application of quality-control filters and imputation of SNPs missing in the Toronto cohort (see below), 168 SNPs associated with autoimmune diseases remained (Supplementary Table 1): 58 with Crohn’s disease (13, 14, 23, 27, 37, 38), 32 with type I diabetes (15, 16, 3942), 23 with systemic lupus erythematosus (1721, 4347), 24 with rheumatoid arthritis (22, 36, 4850), 12 with ulcerative colitis (2325, 27, 38, 51), 8 with psoriasis (26, 52), 15 with celiac disease (5355), 2 with multiple sclerosis (5658), 2 with ankylosing spondylitis (59), and 1 with primary biliary cirrhosis (60). Some of these SNPs have been associated with more than one of the listed diseases, explaining why the numbers associated with individual diseases add to more than 168. The AIMs genotyped for the subjects in WGGER are informative for both continental and intra-European ancestry (Supplementary Table 1).
Genotyping, Data Quality Filters, and Imputation
Genotyping of the WGGER samples was performed at the Broad Institute (Cambridge, MA) using the BeadXpress platform from Illumina (San Diego, CA). Genotypes of the autoimmunity-associated SNPs in the Toronto cohort were determined using data from a genome-wide association study (GWAS) that had been performed previously using the Illumina HumanCNV370-quad v3 (464 cases and 380 controls) and HumanHap370 BeadChip (1123 controls) platforms (K. Siminovitch et al., submitted).
The following data quality filters were applied separately to the WGGER and Toronto cohorts: SNPs were removed from analysis if they had greater than 10% missing genotypes, a minor allele frequency less than 1%, or evidence of deviation from Hardy Weinberg equilibrium (HWE) in the controls (p<0.0001). Subjects were removed from analysis if their overall genotyping rate was < 90% or were population outliers (more than 6 standard deviations from the mean along any of the first 10 principal components, see below). Duplicate individuals were identified using identity-by-state measures calculated in PLINK v1.07 (61) (http://pngu.mgh.harvard.edu/purcell/plink/) between all of the samples in this study using the 218 genotyped SNPs that overlapped between the WGGER and Toronto cohorts, and individuals who were enrolled in both studies were retained in the WGGER cohort.
Ten SNPs were removed from the WGGER cohort for failing the data quality filters described above. Thus, 374 SNPs (187 autoimmunity-associated and 187 AIMs) were used in subsequent steps. Eleven samples (7 cases and 4 controls) were excluded on the basis of poor genotyping rates, leaving 424 cases and 469 controls with an average call rate of 99.7%.
In the Toronto cohort, 92 of the 187 candidate SNPs were successfully genotyped. Five duplicate GPA cases were identified (pi_hat≈1.0) and 6 genetic outliers were removed from the Toronto cohort, leaving 456 cases and 1500 controls. The remaining 95 candidate SNPs not genotyped in the Toronto cohort were imputed using Impute version 2 (http://mathgen.stats.ox.ac.uk/impute/impute_v2.html) (62), using the 283 European samples from Phase I of the 1000 Genomes Project (2010.08.04 sequence index) as the reference. After filtering based on an info score of >0.80, 76 of the 95 SNPs were successfully imputed. Thus, 168 autoimmunity-associated SNPs were used for the final analysis.
Analysis for Population Substructure
Principal components analysis (PCA) was performed on the WGGER cohort using EIGENSTRAT (63) (http://genepath.med.harvard.edu/~reich/Software.htm) and data from all 187 AIMs. No genetic outliers were identified. Visualization of the first 2 principal components (PCs) showed that all 424 cases and 387 controls self-identified as non-Hispanic European descent clustered with the 82 European (CEPH) subjects in HapMap Phase 3 included in the study.
PCA was also used to assess for population substructure for the Toronto cohort. After removal of SNPs in regions with extensive linkage disequilibrium on chromosomes 5 (44–51.5 Mb), 6 (25–33.5 Mb), 8 (8–12 Mb),11 (45–57 Mb), and 17 (40–43 Mb), all remaining SNPs on the genome-wide genotyping platform were used to calculate PCs using EIGENSTRAT. Six cases were removed as genetic outliers (more than 6 standard deviations from the mean of any of the first 10 PCs).
Association Study and Meta-Analysis
For the WGGER cohort and for candidate SNPs that had been genotyped in the Toronto cohort, association of each SNP genotype with GPA disease status was assessed separately in each cohort using logistic regression assuming additive genetic models using PLINK v1.07. The first two PCs specific to each cohort were included in all logistic regression models to adjust for population substructure. For SNPs imputed in the Toronto cohort, association with GPA was assessed using the score method in SNPTEST (v2.2.0). For these analyses, probabilistic genotypes were utilized assuming additive genetic models in logistic regression analyses, which also included the first two PCs to adjust for population substructure.
To produce an overall estimate of the association for each marker in the two cohorts, meta-analysis combining the results for each SNP was performed using PLINK v1.07. Results of fixed-effects models are reported, but random-effects models were also generated and produced identical results for the 10 SNPs with the lowest P-values. No significant heterogeneity was observed in the meta-analysis results.
P-values were adjusted for the false discovery rate (FDR) (64) based on the ranked P-values of 168 simultaneous tests, and an adjusted P-value < 0.05 was interpreted as significant.
Genetic Risk Scores (GRS)
For each subject, separate genetic risk scores for Crohn’s disease (CD, 57 SNPs), type 1 diabetes (T1D, 32 SNPs), systemic lupus erythematosus (SLE, 22 SNPs), rheumatoid arthritis (RA, 23 SNPs), celiac disease (14 SNPs), and ulcerative colitis (UC, 11 SNPs) were calculated using the SNPs genotyped or imputed in this study that have previously been associated with those diseases (Supplementary Table 1). For each disease-specific GRS, the numbers of risk alleles present in each GPA case or control were added in an unweighted manner, and homozygous risk alleles were counted twice. Each missing genotype was replaced with the mean risk allele frequency for a given SNP among cases or controls. Probabilistic genotypes were utilized for imputed SNPs. For SNPs in linkage disequilibrium associated with the same disease (e.g., rs2070197 and rs10488631 (r2=0.93) in IRF5 which are both associated with SLE), the SNP with the most statistically significant association with GPA was retained in the GRS calculations. The distributions of GRS scores among cases and controls were compared by logistic regression, with the disease-specific GRS (as a continuous variable) and the first two PCs as the predictor variables and case/control status as the outcome variable. The WGGER and Toronto cohorts were analyzed separately and then combined in meta-analysis as above. Fixed- and random-effects models yielded identical results. All GRS analyses were performed using STATA 9.0/SE (College Station, TX, USA).
After implementing data quality measures, 168 SNPs in at least 141 candidate genes (Supplementary Table 1) were studied in a total of 880 GPA cases and 1969 controls of European descent between the WGGER (424 cases and 469 controls) and Toronto cohorts (456 cases and 1500 controls).
Association Study of Autoimmunity-Associated SNPs with GPA
In the WGGER cohort, twelve markers showed nominal evidence of association (punadjusted <0.05), but none of the associations was significant after FDR correction. The most statistically significant association was with rs11618775 (OR 1.34, 95% CI 1.08–1.66, punadjusted=0.0073), which does not have a known gene within 100 kb upstream or downstream. This SNP was poorly imputed in the Toronto cohort, and thus was not included in further analyses. Out of the 168 SNPs analyzed in the Toronto cohort, 11 SNPs showed nominal evidence of association (punadjusted <0.05). An imputed SNP, rs3087243 (CTLA4), was the most strongly associated with GPA (OR 0.78, 95% CI 0.67–0.91, punadjusted=0.0014). The most strongly associated genotyped SNP was rs2476601 in PTPN22 (OR 1.41, 95% CI 1.12–1.79, p=0.0042). Neither marker was statistically significant after FDR correction.
Meta-analysis yielded a statistically significant association with GPA for rs3087243 in CTLA4, with 15 additional SNPs showing unadjusted p<0.05 (Table 1 and Supplementary Table 2). Three additional SNPs, in CTLA4, PTPN22, and CD40, narrowly missed the pre-specified significance cut-off, and the next six SNPs in order of significance were notable for involving pairs of SNPs in moderate to strong linkage disequilibrium in 3 regions (in or near PARK7, IL27, or NKX2-3).
Table 1
Table 1
SNPs associated with GPA, listed in order of P-value.
Genetic Risk Scores Associated with GPA
As shown in Table 2, the GRS score derived from RA was slightly but significantly higher in GPA patients than in controls in both the WGGER and Toronto cohorts individually, and by meta-analysis (OR 1.05 per 1-unit increase in GRS, 95% CI 1.02–1.08, p=5.1E-05). Having an RA GRS score greater than the median was associated with a 37% greater odds of having GPA, compared to having a GRS below the median (OR 1.37 (95% CI 1.16–1.62, p=2.6E-06). After exclusion of the 3 top-ranked SNPs in the study (all of which are associated with RA, in CTLA4 and PTPN22), GRS scores for RA remained slightly higher in cases than controls (OR from meta-analysis 1.04 per 1-unit increase in GRS, 95% CI 1.01–1.07, p=0.017), indicating that these two genes did not account completely for the GRS result. GRS scores for T1D were higher in GPA cases than controls in the Toronto cohort but not WGGER. Given the substantial heterogeneity of the T1D findings, meta-analysis was not felt to be appropriate; thus, results for the T1D GRS were inconclusive. GRSs derived from celiac disease, CD, SLE, and UC did not differ significantly in either cohort separately nor by meta-analysis, nor did scores comprised of the smaller numbers of risk SNPs (n=2–8) associated with the AS, MS, or psoriasis (data not shown).
Table 2
Table 2
Genetic risk scores derived from different autoimmune diseases, in patients with GPA compared to controls.
Analysis of the distribution of OR’s for all risk alleles used in the GRSs did not provide any additional evidence of skewing of autoimmunity-associated SNPs toward association with GPA: the mean OR of 1.01 (SD 0.09) was not significantly different from the null distribution.
In this study, one of the largest genetic studies of GPA to date, we investigated the comparability of genetic risk factors of GPA with other autoimmune diseases by examining single-marker associations as well as composite genetic risk scores of previously identified autoimmune disease susceptibility loci.
In single marker analyses, we confirmed an association of GPA with genetic variation in CTLA4. The 2 SNPs in this gene found to be associated with GPA in this study, rs3087243 and rs231735, have been previously associated with RA and T1D (39, 49, 65). rs3087243 does not appear to be significantly linked to previously identified GPA-associated CTLA4 polymorphisms rs5742909 (−319C/T) or rs231775 (+49A/G), with r2<0.1, but rs231735 shows moderate linkage with rs231775 (r2=0.6) (29, 66, 67). These findings suggest that CTLA4 may harbor multiple genetic variants contributing to disease risk. rs3087243 has been suggested to influence CTLA4 mRNA stability, since it is located ~300 bp downstream from the major 3′ poly-A tail, while rs231735 is located ~40 kb upstream of CTLA4 and does not have a known functional effect. The PTPN22 polymorphism that showed some evidence of association in this study, rs2476601, has been previously associated with GPA (28) and with multiple other autoimmune diseases (13, 15, 21, 65, 68). This non-synonymous polymorphism induces an amino acid change from arginine to tryptophan at codon 620, and is thought to increase its degradation leading to lymphocyte hyper-responsiveness (69).
Our findings also suggest that the risk of GPA and RA share a common genetic background, which was not observed for CD, SLE, T1D, or UC. This finding is supported by a previous epidemiologic study showing an increase in RA among offspring of patients with GPA (30). This finding is not intuitive, since the pulmonary and renal manifestations of GPA are not common in RA, and inflammatory arthritis, the hallmark of RA, is not present in all patients with GPA and is rarely destructive. Having a similar genetic background implies that the two diseases may share similar pathogenic mechanisms, and the shared association with alleles in CTLA4 and PTPN22 suggests that this mechanism involves the threshold for activation or deactivation of autoreactive T cells.
The major strength of this analysis is the relatively large sample size represented by the meta-analysis when compared to other candidate gene studies for GPA, which improved statistical power to test a relative large number of candidate genes. However, this study still had limited power to detect associations of modest effect sizes, and thus, there may be additional associations that have not been identified. Another strength is that careful adjustment for population stratification was performed, which is not always accounted for in candidate gene studies. Finally, not all of the associated loci for these autoimmune diseases were genotyped. Therefore, other loci may be shared between GPA and SLE, T1D, CD, and/or UC, and the genetic background for these diseases may be more similar to GPA than what was found in this study.
Further delineation of the genetic contribution to risk of GPA will likely require a combination of GWAS studies and an ongoing hypothesis-driven search for rare variants (such as null alleles in A1AT/SERPINA) that would be missed by such screens. A prediction of the current study might be that outside of HLA-DPB1, CTLA4, and perhaps a few other polymorphisms associated with multiple autoimmune diseases, most genes found to predispose to GPA will reflect the unique pathophysiology of this disease rather than more generic disruption of immune homeostasis.
Supplementary Material
Supp Table S1
Acknowledgments
Funding: Supported by an Arthritis Investigator Award from the Arthritis Foundation (Dr. Monach); NIH/National Institute of Arthritis and Musculoskeletal and Skin Diseases grant R01 AR 047799 (Drs. Edberg and Merkel); a grant from the Vasculitis Foundation (USA and Canada), the Ontario Research Fund (RE01-061), and a Canada Research Chair and Sherman Family Chair in Genomic Medicine (Dr. Siminovitch); the Vasculitis Clinical Research Consortium (NIH U54-RR-019497) and a grant from the Société Nationale Française de Médecine Interne (SNFMI) (Dr. Mahr); an NIH-NIAMS Mid-Career Development Award in Clinical Investigation (K24-AR-02224)(Dr. Merkel); and the Rosalind Russell Medical Research Center for Arthritis and NIH grant 5 KL2 RR024130 (Dr. Chung).
Footnotes
Financial Conflict of Interest: None.
1. Mahr AD, Neogi T, Merkel PA. Epidemiology of Wegener’s granulomatosis: Lessons from descriptive studies and analyses of genetic and environmental risk determinants. Clin Exp Rheumatol. 2006;24(2 Suppl 41):S82–91. [PubMed]
2. Hoffman GS, Specks U. Antineutrophil cytoplasmic antibodies. Arthritis Rheum. 1998;41(9):1521–37. [PubMed]
3. Rao JK, Weinberger M, Oddone EZ, Allen NB, Landsman P, Feussner JR. The role of antineutrophil cytoplasmic antibody (c-ANCA) testing in the diagnosis of Wegener granulomatosis. A literature review and meta-analysis. Ann Intern Med. 1995;123(12):925–32. [PubMed]
4. Choi HK, Liu S, Merkel PA, Colditz GA, Niles JL. Diagnostic performance of antineutrophil cytoplasmic antibody tests for idiopathic vasculitides: metaanalysis with a focus on antimyeloperoxidase antibodies. J Rheumatol. 2001;28(7):1584–90. [PubMed]
5. Knight A, Sandin S, Askling J. Risks and relative risks of Wegener’s granulomatosis among close relatives of patients with the disease. Arthritis Rheum. 2008;58(1):302–7. [PubMed]
6. Knight A, Sandin S, Askling J. Increased risk of autoimmune disease in families with Wegener’s granulomatosis. J Rheumatol. 2010;37(12):2553–8. [PubMed]
7. Heckmann M, Holle JU, Arning L, Knaup S, Hellmich B, Nothnagel M, et al. The Wegener’s granulomatosis quantitative trait locus on chromosome 6p21. 3 as characterised by tagSNP genotyping. Ann Rheum Dis. 2008;67(7):972–9. [PubMed]
8. Mahr AD, Edberg JC, Stone JH, Hoffman GS, St Clair EW, Specks U, et al. Alpha-antitrypsin deficiency-related alleles Z and S and the risk of Wegener’s granulomatosis. Arthritis Rheum. 2010;62(12):3760–7. [PMC free article] [PubMed]
9. Elzouki AN, Segelmark M, Wieslander J, Eriksson S. Strong link between the alpha 1-antitrypsin PiZ allele and Wegener’s granulomatosis. J Intern Med. 1994;236(5):543–8. [PubMed]
10. Lhotta K, Vogel W, Meisl T, Buxbaum M, Neyer U, Sandholzer C, et al. Alpha 1-antitrypsin phenotypes in patients with anti-neutrophil cytoplasmic antibody-positive vasculitis. Clin Sci (Lond) 1994;87(6):693–5. [PubMed]
11. Wieczorek S, Hoffjan S, Chan A, Rey L, Harper L, Fricke H, et al. Novel association of the CD226 (DNAM-1) Gly307Ser polymorphism in Wegener’s granulomatosis and confirmation for multiple sclerosis in German patients. Genes Immun. 2009 [PubMed]
12. Fanciulli M, Norsworthy PJ, Petretto E, Dong R, Harper L, Kamesh L, et al. FCGR3B copy number variation is associated with susceptibility to systemic, but not organ-specific, autoimmunity. Nat Genet. 2007;39(6):721–3. [PMC free article] [PubMed]
13. Barrett JC, Hansoul S, Nicolae DL, Cho JH, Duerr RH, Rioux JD, et al. Genome-wide association defines more than 30 distinct susceptibility loci for Crohn’s disease. Nat Genet. 2008;40(8):955–62. [PMC free article] [PubMed]
14. Franke A, McGovern DP, Barrett JC, Wang K, Radford-Smith GL, Ahmad T, et al. Genome-wide meta-analysis increases to 71 the number of confirmed Crohn’s disease susceptibility loci. Nat Genet. 2010;42(12):1118–25. [PMC free article] [PubMed]
15. Barrett JC, Clayton DG, Concannon P, Akolkar B, Cooper JD, Erlich HA, et al. Genome-wide association study and meta-analysis find that over 40 loci affect risk of type 1 diabetes. Nat Genet. 2009;41(6):703–7. [PMC free article] [PubMed]
16. Todd JA, Walker NM, Cooper JD, Smyth DJ, Downes K, Plagnol V, et al. Robust associations of four new chromosome regions from genome-wide analyses of type 1 diabetes. Nat Genet. 2007;39(7):857–64. [PMC free article] [PubMed]
17. Graham RR, Hom G, Ortmann W, Behrens TW. Review of recent genome-wide association scans in lupus. J Intern Med. 2009;265(6):680–8. [PubMed]
18. Gateva V, Sandling JK, Hom G, Taylor KE, Chung SA, Sun X, et al. A large-scale replication study identifies TNIP1, PRDM1, JAZF1, UHRF1BP1 and IL10 as risk loci for systemic lupus erythematosus. Nat Genet. 2009;41(11):1228–33. [PMC free article] [PubMed]
19. Yang W, Shen N, Ye DQ, Liu Q, Zhang Y, Qian XX, et al. Genome-wide association study in Asian populations identifies variants in ETS1 and WDFY4 associated with systemic lupus erythematosus. PLoS Genet. 2010;6(2):e1000841. [PMC free article] [PubMed]
20. Han JW, Zheng HF, Cui Y, Sun LD, Ye DQ, Hu Z, et al. Genome-wide association study in a Chinese Han population identifies nine new susceptibility loci for systemic lupus erythematosus. Nat Genet. 2009;41(11):1234–7. [PubMed]
21. Harley JB, Alarcon-Riquelme ME, Criswell LA, Jacob CO, Kimberly RP, Moser KL, et al. Genome-wide association scan in women with systemic lupus erythematosus identifies susceptibility variants in ITGAM, PXK, KIAA1542 and other loci. Nat Genet. 2008;40(2):204–10. [PMC free article] [PubMed]
22. Stahl EA, Raychaudhuri S, Remmers EF, Xie G, Eyre S, Thomson BP, et al. Genome-wide association study meta-analysis identifies seven new rheumatoid arthritis risk loci. Nat Genet. 2010 [PubMed]
23. McGovern DP, Gardet A, Torkvist L, Goyette P, Essers J, Taylor KD, et al. Genome-wide association identifies multiple ulcerative colitis susceptibility loci. Nat Genet. 2010;42(4):332–7. [PMC free article] [PubMed]
24. Silverberg MS, Cho JH, Rioux JD, McGovern DP, Wu J, Annese V, et al. Ulcerative colitis-risk loci on chromosomes 1p36 and 12q15 found by genome-wide association study. Nat Genet. 2009;41(2):216–20. [PMC free article] [PubMed]
25. Barrett JC, Lee JC, Lees CW, Prescott NJ, Anderson CA, Phillips A, et al. Genome-wide association study of ulcerative colitis identifies three new susceptibility loci, including the HNF4A region. Nat Genet. 2009;41(12):1330–4. [PMC free article] [PubMed]
26. Nair RP, Duffin KC, Helms C, Ding J, Stuart PE, Goldgar D, et al. Genome-wide scan reveals association of psoriasis with IL-23 and NF-kappaB pathways. Nat Genet. 2009;41(2):199–204. [PMC free article] [PubMed]
27. Anderson CA, Boucher G, Lees CW, Franke A, D’Amato M, Taylor KD, et al. Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47. Nat Genet. 2011;43(3):246–52. [PMC free article] [PubMed]
28. Jagiello P, Aries P, Arning L, Wagenleiter SE, Csernok E, Hellmich B, et al. The PTPN22 620W allele is a risk factor for Wegener’s granulomatosis. Arthritis Rheum. 2005;52(12):4039–43. [PubMed]
29. Zhou Y, Huang D, Paris PL, Sauter CS, Prock KA, Hoffman GS. An analysis of CTLA-4 and proinflammatory cytokine genes in Wegener’s granulomatosis. Arthritis Rheum. 2004;50(8):2645–50. [PubMed]
30. Hemminki K, Li X, Sundquist J, Sundquist K. Familial associations of rheumatoid arthritis with autoimmune diseases and related conditions. Arthritis Rheum. 2009;60(3):661–8. [PubMed]
31. Carr EJ, Clatworthy MR, Lowe CE, Todd JA, Wong A, Vyse TJ, et al. Contrasting genetic association of IL2RA with SLE and ANCA-associated vasculitis. BMC Med Genet. 2009;10:22. [PMC free article] [PubMed]
32. Yu X, Wieczorek S, Franke A, Yin H, Pierer M, Sina C, et al. Association of UCP2 -866 G/A polymorphism with chronic inflammatory diseases. Genes Immun. 2009 [PubMed]
33. Fries JF, Hunder GG, Bloch DA, Michel BA, Arend WP, Calabrese LH, et al. The American College of Rheumatology 1990 criteria for the classification of vasculitis. Summary Arthritis Rheum. 1990;33(8):1135–6. [PubMed]
34. Kosoy R, Nassir R, Tian C, White PA, Butler LM, Silva G, et al. Ancestry informative marker sets for determining continental origin and admixture proportions in common populations in America. Hum Mutat. 2009;30(1):69–78. [PMC free article] [PubMed]
35. Price AL, Butler J, Patterson N, Capelli C, Pascali VL, Scarnicci F, et al. Discerning the ancestry of European Americans in genetic association studies. PLoS Genet. 2008;4(1):e236. [PubMed]
36. Kurreeman F, Liao K, Chibnik L, Hickey B, Stahl E, Gainer V, et al. Genetic basis of autoantibody positive and negative rheumatoid arthritis risk in a multi-ethnic cohort derived from electronic health records. Am J Hum Genet. 2011;88(1):57–69. [PubMed]
37. Anderson CA, Massey DC, Barrett JC, Prescott NJ, Tremelling M, Fisher SA, et al. Investigation of Crohn’s disease risk loci in ulcerative colitis further defines their molecular relationship. Gastroenterology. 2009;136(2):523–9. e3. [PMC free article] [PubMed]
38. Thompson AI, Lees CW. Genetics of ulcerative colitis. Inflamm Bowel Dis. 2010;17(3):831–48. [PubMed]
39. Cooper JD, Smyth DJ, Smiles AM, Plagnol V, Walker NM, Allen JE, et al. Meta-analysis of genome-wide association study data identifies additional type 1 diabetes risk loci. Nat Genet. 2008;40(12):1399–401. [PMC free article] [PubMed]
40. Heinig M, Petretto E, Wallace C, Bottolo L, Rotival M, Lu H, et al. A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk. Nature. 2010;467(7314):460–4. [PMC free article] [PubMed]
41. Qu HQ, Grant SF, Bradfield JP, Kim C, Frackelton E, Hakonarson H, et al. Association of RASGRP1 with type 1 diabetes is revealed by combined follow-up of two genome-wide studies. J Med Genet. 2009;46(8):553–4. [PMC free article] [PubMed]
42. Swafford AD, Howson JM, Davison LJ, Wallace C, Smyth DJ, Schuilenburg H, et al. An allele of IKZF1 (Ikaros) conferring susceptibility to childhood acute lymphoblastic leukemia protects against type 1 diabetes. Diabetes. 2011;60(3):1041–4. [PMC free article] [PubMed]
43. Kawasaki A, Furukawa H, Kondo Y, Ito S, Hayashi T, Kusaoi M, et al. TLR7 single-nucleotide polymorphisms in the 3’ untranslated region and intron 2 independently contribute to systemic lupus erythematosus in Japanese women: a case-control association study. Arthritis Res Ther. 2011;13(2):R41. [PMC free article] [PubMed]
44. Lessard CJ, Adrianto I, Kelly JA, Kaufman KM, Grundahl KM, Adler A, et al. Identification of a systemic lupus erythematosus susceptibility locus at 11p13 between PDHX and CD44 in a multiethnic study. Am J Hum Genet. 2011;88(1):83–91. [PubMed]
45. Meziani R, Yamada R, Takahashi M, Ohigashi K, Morinobu A, Terao C, et al. A trans-ethnic genetic study of rheumatoid arthritis identified FCGR2A as a candidate common risk factor in Japanese and European populations. Mod Rheumatol. 2011 [PubMed]
46. Sawalha AH, Webb R, Han S, Kelly JA, Kaufman KM, Kimberly RP, et al. Common variants within MECP2 confer risk of systemic lupus erythematosus. PLoS One. 2008;3(3):e1727. [PMC free article] [PubMed]
47. 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(3):R69. [PMC free article] [PubMed]
48. Freudenberg J, Lee HS, Han BG, Shin HD, Kang YM, Sung YK, et al. Genome-wide association study of rheumatoid arthritis in Koreans: population-specific loci as well as overlap with European susceptibility loci. Arthritis Rheum. 2011;63(4):884–93. [PubMed]
49. Gregersen PK, Amos CI, Lee AT, Lu Y, Remmers EF, Kastner DL, et al. REL, encoding a member of the NF-kappaB family of transcription factors, is a newly defined risk locus for rheumatoid arthritis. Nat Genet. 2009;41(7):820–3. [PMC free article] [PubMed]
50. Plenge RM, Seielstad M, Padyukov L, Lee AT, Remmers EF, Ding B, et al. TRAF1-C5 as a risk locus for rheumatoid arthritis--a genomewide study. N Engl J Med. 2007;357(12):1199–209. [PMC free article] [PubMed]
51. De Marco EV, Annesi G, Tarantino P, Nicoletti G, Civitelli D, Messina D, et al. DJ-1 is a Parkinson’s disease susceptibility gene in southern Italy. Clin Genet. 2010;77(2):183–8. [PubMed]
52. Capon F, Di Meglio P, Szaub J, Prescott NJ, Dunster C, Baumber L, et al. Sequence variants in the genes for the interleukin-23 receptor (IL23R) and its ligand (IL12B) confer protection against psoriasis. Hum Genet. 2007;122(2):201–6. [PubMed]
53. Dubois PC, Trynka G, Franke L, Hunt KA, Romanos J, Curtotti A, et al. Multiple common variants for celiac disease influencing immune gene expression. Nat Genet. 2010;42(4):295–302. [PMC free article] [PubMed]
54. van Heel DA, Franke L, Hunt KA, Gwilliam R, Zhernakova A, Inouye M, et al. A genome-wide association study for celiac disease identifies risk variants in the region harboring IL2 and IL21. Nat Genet. 2007;39(7):827–9. [PMC free article] [PubMed]
55. Hunt KA, Zhernakova A, Turner G, Heap GA, Franke L, Bruinenberg M, et al. Newly identified genetic risk variants for celiac disease related to the immune response. Nat Genet. 2008;40(4):395–402. [PMC free article] [PubMed]
56. De Jager PL, Jia X, Wang J, de Bakker PI, Ottoboni L, Aggarwal NT, et al. Meta-analysis of genome scans and replication identify CD6, IRF8 and TNFRSF1A as new multiple sclerosis susceptibility loci. Nat Genet. 2009;41(7):776–82. [PMC free article] [PubMed]
57. Mero IL, Lorentzen AR, Ban M, Smestad C, Celius EG, Aarseth JH, et al. A rare variant of the TYK2 gene is confirmed to be associated with multiple sclerosis. Eur J Hum Genet. 2009;18(4):502–4. [PMC free article] [PubMed]
58. Thompson SD, Sudman M, Ramos PS, Marion MC, Ryan M, Tsoras M, et al. The susceptibility loci juvenile idiopathic arthritis shares with other autoimmune diseases extend to PTPN2, COG6, and ANGPT1. Arthritis Rheum. 2010;62(11):3265–76. [PMC free article] [PubMed]
59. Burton PR, Clayton DG, Cardon LR, Craddock N, Deloukas P, Duncanson A, et al. Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants. Nat Genet. 2007;39(11):1329–37. [PMC free article] [PubMed]
60. Hirschfield GM, Liu X, Xu C, Lu Y, Xie G, Gu X, et al. Primary biliary cirrhosis associated with HLA, IL12A, and IL12RB2 variants. N Engl J Med. 2009;360(24):2544–55. [PMC free article] [PubMed]
61. Purcell S, Neale B, Todd-Brown K, Thomas L, Ferreira MA, Bender D, et al. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet. 2007;81(3):559–75. [PubMed]
62. Howie BN, Donnelly P, Marchini J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 2009;5(6):e1000529. [PMC free article] [PubMed]
63. Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38(8):904–9. [PubMed]
64. Benjamini Y, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. J Royal Stat Soc B. 1995;57(1):289–300.
65. Plenge RM, Padyukov L, Remmers EF, Purcell S, Lee AT, Karlson EW, et al. Replication of putative candidate-gene associations with rheumatoid arthritis in >4,000 samples from North America and Sweden: association of susceptibility with PTPN22, CTLA4, and PADI4. Am J Hum Genet. 2005;77(6):1044–60. [PubMed]
66. Huang D, Giscombe R, Zhou Y, Lefvert AK. Polymorphisms in CTLA-4 but not tumor necrosis factor-alpha or interleukin 1beta genes are associated with Wegener’s granulomatosis. J Rheumatol. 2000;27(2):397–401. [PubMed]
67. Giscombe R, Wang X, Huang D, Lefvert AK. Coding sequence 1 and promoter single nucleotide polymorphisms in the CTLA-4 gene in Wegener’s granulomatosis. J Rheumatol. 2002;29(5):950–3. [PubMed]
68. Lee YH, Rho YH, Choi SJ, Ji JD, Song GG, Nath SK, et al. The PTPN22 C1858T functional polymorphism and autoimmune diseases--a meta-analysis. Rheumatology (Oxford) 2007;46(1):49–56. [PubMed]
69. Zhang J, Zahir N, Jiang Q, Miliotis H, Heyraud S, Meng X, et al. The autoimmune disease-associated PTPN22 variant promotes calpain-mediated Lyp/Pep degradation associated with lymphocyte and dendritic cell hyperresponsiveness. Nat Genet. 2011;43(9):902–7. [PubMed]