DOI: 10.1111/exd.12708
Original Article
www.wileyonlinelibrary.com/journal/EXD
Genome-wide association study identifies new susceptibility loci for cutaneous lupus erythematosus € nig2, Arne Schillert2, Jochen Kruppa2, Andreas Ziegler2, Harald Grallert3,4, Manfred Kunz1, Inke R. Ko 5-7 € ller-Nurasyid , Wolfgang Lieb8, Andre Franke9, Annamari Ranki10, Jaana Panelius10, Martina Mu € nn14, Jan C. Simon1, Enno Schmidt15, Sari Koskenmies10, Taina Hasan11, Juha Kere12,13, Ann-Charlotte Ro 16 16 16 € ting , Jennifer Landsberg , Tanja Zeller17, Stefan Blankenberg17, Joerg Wenzel , Thomas Tu 18 €ser , Nikolaos Patsinakidis19, Annegret Kuhn20 and Saleh M. Ibrahim15 Regine Gla 1 Department of Dermatology, Venereology and Allergology, University of Leipzig, Leipzig, Germany; 2Institut f€ ur Medizinische Biometrie und Statistik, und Zentrum f€ ur Klinische Studien, Universit€at zu L€ ubeck, Universit€atsklinikum Schleswig-Holstein, L€ ubeck, Germany; 3Research unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum M€ unchen – German Research Center for Environmental Health, Neuherberg, Germany; 4German Center for Diabetes Research, Helmholtz Zentrum M€ unchen – German Research Center for Environmental Health, Neuherberg, Germany; 5Institute of Genetic Epidemiology, Helmholtz Zentrum M€ unchen – German Research Center for Environmental Health, Neuherberg, Germany; 6Department of Medicine I, Ludwig Maximilian University Munich, Munich, Germany; 7German Center for Cardiovascular Research, Munich Heart Alliance, Munich, Germany; 8Institute for Epidemiology and Biobank popgen, Christian-AlbrechtsUniversity of Kiel, Kiel, Germany; 9Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany; 10Department of Dermatology and Allergology, Skin and Allergy Hospital, Helsinki University Central Hospital, Helsinki, Finland; 11Department of Dermatology, Tampere University Central Hospital, University of Tampere, Tampere, Finland; 12Department of Biosciences and Nutrition, Karolinska Institute, Huddinge, Sweden; 13Department of Medical Genetics, Folkh€alsan Institute of Genetics, University of Helsinki, Helsinki, Finland; 14Clinical Research Center, Karolinska University Hospital, Huddinge, Sweden; 15Department of Dermatology, Allergology and Venereology, University of Schleswig-Holstein, L€ ubeck, Germany; 16Department of Dermatology and Allergy, University of Bonn, Bonn, Germany; 17University Heart Center Hamburg, Clinic for General and Interventional Cardiology, German Center for Cardiovascular Research (DZHK), Hamburg, Germany; 18 Department of Dermatology and Allergology, University of Schleswig-Holstein, Kiel, Germany; 19Department of Dermatology, Venereology and Allergology, Ruhr-University of Bochum, Bochum, Germany; 20Division of Immunogenetics, German Cancer Research Center, Heidelberg, Germany Correspondence: Manfred Kunz, MD, Department of Dermatology, Venereology and Allergology, University of Leipzig, Philipp-Rosenthal-Str. 23, 04103 Leipzig, Germany, Tel: +49-341-9718610, Fax: +49-341-9718609, e-mail: [email protected]
Abstract: Cutaneous lupus erythematosus (CLE) is a chronic autoimmune disease of the skin with typical clinical manifestations. Here, we genotyped 906 600 single nucleotide polymorphisms (SNPs) in 183 CLE cases and 1288 controls of Central European ancestry. Replication was performed for 13 SNPs in 219 case subjects and 262 controls from Finland. Association was particularly pronounced at 4 loci, all with genomewide significance (P < 5 9 10 8): rs2187668 (PGWAS = 1.4 9 10 12), rs9267531 (PGWAS = 4.7 9 10 10), rs4410767 (PGWAS = 1.0 9 10 9) and rs3094084 (PGWAS = 1.1 9 10 9). All mentioned SNPs are located within the major histocompatibility complex (MHC) region of chromosome 6 and near genes of known immune functions or associations with other autoimmune diseases such as HLA-DQ alpha chain 1
(HLA-DQA1), MICA, MICB, MSH5, TRIM39 and RPP21. For example, TRIM39/RPP21 read through transcript is a known mediator of the interferon response, a central pathway involved in the pathogenesis of CLE and systemic lupus erythematosus (SLE). Taken together, this genomewide analysis of disease association of CLE identified candidate genes and genomic regions that may contribute to pathogenic mechanisms in CLE via dysregulated antigen presentation (HLA-DQA1), apoptosis regulation, RNA processing and interferon response (MICA, MICB, MSH5, TRIM39 and RPP21).
Introduction
been defined more recently and termed LE tumidus (LET) (3). In the revised classification system, LET is described as an intermittent subtype of CLE (ICLE) (4). A small percentage of patients with cutaneous disease subsequently develop systemic manifestations (5). It is well known that in addition to environmental triggers, a genetic predisposition plays an important role in the aetiology of systemic lupus erythematosus (SLE) and CLE (6–15). Besides the well-known association with the human leucocyte antigen (HLA) region for SLE and CLE, more recent genomewide association
Cutaneous lupus erythematosus (CLE) is an autoimmune disease with highly variable clinical spectrum, presenting as single or multiple erythematous macules and papules, as well as annular or serpiginous lesions with a characteristic histopathological picture (1). In principle, CLE is divided into three categories based on the clinical picture, histological changes, laboratory abnormalities and the duration of skin lesions, acute CLE (ACLE), subacute CLE (SCLE) and chronic CLE (CCLE) (2). Another subtype with characteristic clinical, histological and photobiological features has
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Key words: autoimmune diseases – genetics – lupus – single nucleotide polymorphisms
Accepted for publication 26 March 2015
ª 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Experimental Dermatology, 2015, 24, 510–515
Cutaneous lupus susceptibility loci
studies (GWAS) have identified that genetic variants in the TNFinduced protein 3 (TNFAIP3) and signal transducer and activator of transcription 4 (STAT4) regions are associated with SLE (7,16,17). TNFAIP3 encodes the intra-cellular ubiquitin-editing protein A20 which exerts a negative feedback activity in NF-jB signalling (18). STAT4 has been implicated in the differentiation of Th17 cells, which are major regulators of autoimmune processes and are known to be involved in lupus pathogenesis (19). Two further genetic loci in SLE encoding B lymphocyte kinase (BLK) and two integrins (ITGAM–ITGAX) were described in a recently published report which may contribute to the risk of SLE (8). It is well understood that CLE has a genetic association with the HLA region, the TNF-a promoter and the complement region (20,21). The major associations in discoid lupus erythematosus (the major subtype of CCLE) include the HLA-A1, HLA-B8, HLA-DR3 and also the HLA-B7, HLA-DR2 haplotypes (20). Recently described associations of interferon regulatory factor 5 (IRF5) with SLE are suggestive for a significant role of type 1 interferons (IFNs) in SLE susceptibility (7,16,22). Type 1 IFNs have also been reported in the pathogenesis of CLE (23). In recent genetic association studies, the question was addressed whether genetic loci associated with susceptibility for SLE may also be risk factors for CLE (13,24–26). Among major susceptibility loci, TYK2, IRF5 and CTLA4 genes were shown to also confer risk for CLE (24–26). However, large comprehensive genomewide association studies on the genetics of CLE are still missing. In the present report, we used a genomewide approach to identify genetic susceptibility loci for CLE in two different European samples.
Materials and methods Case subjects included 183 patients with different clinical subtypes of CLE (CCLE 44.8%, SCLE 40.4%, LET 14.2%). DNA samples for the GWAS study were obtained from outpatient clinics of the Departments of Dermatology at the Universities of L€ ubeck, Kiel, M€ unster, Bonn and Munich (all Germany). The European origin of all cases was determined by self-report. In all cases, the diagnosis of CLE was confirmed by review of medical records, based on clinical findings and histopathology of skin lesions and by written documentation of the treating dermatologists. The study was approved by the ethical committee of the University Hospital of Schleswig-Holstein, Campus L€ ubeck (AZ 09-056). The institutional review boards at each centre approved the study. All patients gave informed written consent, and the Declaration of Helsinki protocols were followed. Clinical data were reviewed at each institution. Mean follow-up of patients after initial diagnosis of CLE was 7.94 (7.38) years (follow-up information was not available for 34 of the 183 patients), ranging from 1 to 30 years, during which period none of the patients developed systemic disease. Control data of 810 healthy individuals were provided by KORA (Kooperative Gesundheitsforschung in der Region Augsburg) from the Helmholtz Centre, Neuherberg, Germany, and of 478 individuals from the population-based Biobank popgen, University of Schleswig-Holstein, Campuses L€ ubeck and Kiel, Germany. To validate our results, DNA from an independent collection of 177 patients with DLE and 42 patients with SCLE and 262 healthy control individuals from Finland was genotyped (24). For the collection of this material, all patients with clinical
ª 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Experimental Dermatology, 2015, 24, 510–515
diagnosis of DLE and SCLE attending the Departments of Dermatology at Helsinki and Tampere University Central Hospitals during 1995–2005 were identified from the corresponding hospital registries and contacted by mail or phone. The study was approved by the medical ethical review board of Helsinki and Uusimaa joint authority (Dnro 62/2009), and the participants volunteered after a written informed consent. The clinical and demographic features of these patients have been described previously (24,27). Unaffected family members (spouses or commons in law) from the case–control families and the original Finnish family study (28) were asked to participate as control subjects, and an existing collection of one hundred unrelated individuals was also used as controls. The participating patients were clinically examined by staff dermatologists (SK, TH, JP from list of authors) and interviewed using a structured questionnaire (27). Further information about German and Finnish samples and controls is given in Table S1. The obvious differences in positive testing for antinuclear antibodies (ANA) may in part be explained by significantly higher percentages of patients with SCLE in the GWAS samples compared with the Finnish validation sample (40% vs 19%). It is known that patients with SCLE show a higher percentage of positive ANA titres (1).
Genotyping Genotyping was performed on all GWAS cases (German sample) and controls between July 2009 and July 2010 using the Affymetrix Genome-wide Human SNP 6.0 Array (Affymetrix, Santa Clara, CA, USA). Processing of DNA samples and hybridization was performed in accordance with the manufacturers’ standard recommendations (Affymetrix). Case samples were genotyped at the Department of Internal Medicine at the University of Mainz, and genotypes of controls were derived from KORA and popgen biobank. The analysis included more than 906 600 single nucleotide polymorphisms (SNPs). Genotypes were determined using the Birdseed v2 calling algorithm. Quality control on case sample level comprised exclusion of samples with a call rate ≤97%, deviation from expected heterozygosity by more than three standard deviations and relatedness based on identity by state distance measures. As a result, data of 151 cases were available for analysis. On marker level, we excluded polymorphisms with a call rate ≤98% in cases and controls, minor allele frequency ≤0.01 and deviation from Hardy–Weinberg equilibrium (P ≤ 0.0001). Cluster plots were inspected for all markers with P < 0.001 in the GWAS analysis. Genotyping of the Finnish validation sample was performed at the Mutation Analysis Facility at Karolinska University Hospital, Huddinge, Sweden, using iPLEX Gold chemistry and MassARRAY mass spectrometry system (29) (Sequenom, San Diego, CA, USA). Multiplexed assays were designed using MassARRAY Assay Design v4.0 Software (Sequenom). The genotyping was validated using a set of 14 trio families, in total 42 individuals, with genotype data available through the HapMap Consortium (HapMap data release #28). For three of the trio families genotyped, only data from one SNP were available (rs3094067). Concordance analysis with the HapMap data showed concordance rates of 100% for all analysed SNPs. Parent–offspring compatibility analysis was performed, and one Mendel error was observed in the genotyped trio families for rs2844559; however, the genotype data for that family were not available in the HapMap database. Assays had a success rate of >98% (mean 98.8%). The 50% fail
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rate cut-off was met by all but two study samples (1512 and L_206), and 97.3% of the 481 samples had a 100% success rate for all assays. Additionally, re-genotyping of 18% of the study samples resulted in 100% concordance.
Statistical analysis The extent of population stratification was estimated using principal component analysis (PCA) based on IBS (identity by state) information of 25 000 randomly selected LD-pruned autosomal markers. The genomic inflation factor was 1.04. Further highly similar samples (estimated kinship coefficient >0.5) were excluded. The combined PCA of cases and controls showed no deviance. The statistical analysis was based on an additive model without adjustments using logistic regression. In addition, logistic regression models adjusting for sex were computed. The primary analysis was performed in the German sample, and SNPs were selected for analysis in the Finnish sample. Here, also an additive model without adjustment was used for analysis. To account for multiple testing, SNPs with a P-value 0.05 were defined, all of which were located in the MHC region. Thirteen SNPs representing these regions were genotyped as validation in the Finnish sample in 219 cases (177 DLE and 42 SCLE patients) and 262 controls. Twelve of these 13 SNPs nominally reached genomewide significance (P < 5 9 10 8) in the combined analysis of data from both samples (Table S2). Most prominent SNPs from the combined analysis for both samples are given in Table 1. The results highlight the possible role of several new molecules in CLE pathogenesis. Four prominent SNPs located close to
Figure 1. Identification of major loci associated with cutaneous lupus erythematosus in a genomewide association study. Data represent 906,600 variants of single nucleotide polymorphisms (SNPs) genotyped in 151 cases and 1288 controls. The distribution of test statistics at genotyped SNPs across the genome is shown. A logistic regression model was used to compare genotype frequencies in cases and controls in an additive model. The resulting –log P values are plotted across the genome. Genes associated with loci of the top 10 SNPs with genomewide significance (P ≤ 5 9 10 8) which were also confirmed regarding association in the validation sample (Table 1) are indicated. The SNPs on chromosome 7 and 10 did not reach genomewide significance.
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interesting immunoregulatory genes within this region and are described in more detail: rs2187668, rs9267531, rs4410767 and rs3094084. The strongest association was observed for rs2187668 (PGWAS = 1.4 9 10 12, OR = 2.93, 95% confidence interval (CI) = 2.18–3.95; Poverall = 3.6 9 10 10) (Fig. 2; Table 1, Table S3). Sex-adjusted P values differed only slightly from not sexadjusted values and are given in Table 1 and Table S2. rs2187668 is in strong linkage disequilibrium with rs3129716 OR = 2.85, 95% CI = 2.11–3.84). (PGWAS = 8.0 9 10 12, rs2187668 is located within the gene encoding the HLA class II complex HLA-DQ alpha chain 1 (HLA-DQA1). In an earlier study, SLE association with HLA class II region was delimited to a 180 kb region encompassing the alleles HLA-DRB1*0301, HLADQA1*0501 and HLA-DQB1*0201 (30). Furthermore, in a metaanalysis using genotypes for 7199 SNPs within the MHC region, the best SLE association was found for classical HLA loci (HLADRB1*0301, HLA-DRB1*0801 and HLA-DQA1*0102) and two SNPs, rs8192591 (in class III region, upstream of NOTCH4) and rs2246618 (MICB in class I) (31). In a recent association study, rs2187668 showed highly significant association (P = 8.0 9 10 93) for three different populations of French, Dutch and British patients suffering from idiopathic membranous nephropathy (32). One of the hallmarks of both idiopathic membranous nephropathy and lupus nephritis is the presence of glomerular deposits of immunoglobulin and complement components. As immunoglobulin deposits in the skin are a hallmark of CLE, this SNP may also support the development of skin disease. So, rs2187668 association might not be indicative for renal involvement but rather immunoglobulin deposition. In a study on SLE, evidence was provided by analysis of expressed quantitative trait loci (eQTL) that the rs2187668 SNP is associated with enhanced HLA-DQA1 expression (33). Strongly associated SNPs rs9267531 (PGWAS = 4.7 9 10 10, OR = 2.62, 95% CI = 1.93–3.54; Poverall = 3.3 9 10 14) and rs3131379 (PGWAS = 5.30 9 10 10, OR = 2.61, 95% CI = 1.93– 3.53; Poverall = 2.3 9 10 14) (Fig. 2) are located in a region of high gene content. rs9267531 is located within an intronic region of the CSNK2B gene encoding for casein kinase 2 (CK2), beta polypeptide. Interestingly, a cDNA microarray analysis on renal biopsies specimens from lupus nephritis identified CK2a, the catalytic subunit of CK2, as a glomerulonephritis-related gene (34). rs3131379, which is strongly linked to rs9267531, maps to an intronic region of the MutS homologue 5 (MSH5) gene. MSH5 is involved in DNA mismatch repair and meiotic recombination. In a transancestral SNP mapping approach, MSH5 has been reported as an SLE-associated gene in United Kingdom families (35) and also in a study on patients with SLE of African American background (36). A further SNP strongly linked to rs9267531 was rs2844559 (PGWAS = 5.5 9 10 10, OR = 2.53, 95% CI = 1.89–3.39; Poverall = 9.1 9 10 15) together with closely located and strongly associated SNP rs3099844 (PGWAS = 5.7 9 10 9, OR = 2.44, 95% CI = 1.81– 3.29; Poverall = 4.4 9 10 10). rs2844559 is located ~27 kb proximal of MHC class I chain-related A (MICA) gene and ~120 kb proximal of the MICB gene. rs3099844 maps ~15 kb proximal of the MICB gene. A recent study characterized 1610 Caucasian SLE cases and 1470 parents for 1974 MHC SNPs (9). Conditional
ª 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Experimental Dermatology, 2015, 24, 510–515
Cutaneous lupus susceptibility loci
Table 1. Loci with strongest evidence of association with cutaneous lupus erythematosus in the discovery and validation samples Discovery sample (151 cases, 1288 controls) Validation sample (219 cases, 262 controls) Minor MAF MAF P value* GWAS MAF MAF P value SNP Chr Position allele cases controls (sex adjusted) OR (95% CI) cases controls (validation) OR CI OR 1.44 9 10 12 (2.27 9 10 11) 4.72 9 10 10 (2.79 9 10 9)
2.93 (2.18–3.95) 2.62 (1.93–3.54)
0.258 0.107
2.46 9 10
4
1.98 1.35–2.93 3.6 9 10
10
0.172 0.084
3.58 9 10
05
2.34 1.53–3.64 3.3 9 10
14
5.25 9 10 10 (3.79 9 10 9) 5.50 9 10 10 (1.62 9 10 9) 1.03 9 10 9 (2.52 9 10 9)
2.61 (1.93–3,53) 2.53 (1.89–3.39) 0.39 (0.28–0.52)
0.176 0.085
2.08 9 10
05
2.36 1.55–3.64 2.3 9 10
14
0.196 0.092
7.08 9 10
06
2.32 1.57–3.48 9.1 9 10
15
–
–
0.302 0.154
1.10 9 10 9 (5.37 9 10 9)
2.30 (1.76–3.01)
0.217 0.139
2.03 9 10
3
1.71 1.20–2.46 1.5 9 10
11
31.556.955 A
0.236 0.112
2.05 9 10
6
2.56 1.69–3.93 4.0 9 10
10
0.228 0.112
2.44 (1.81–3.29) 2.30 (1.71–3.11) 2.32 (1.68–3.20)
0.192 0.088
30.871.270 A
5.71 9 10 9 (2.35 9 10 8) 4.55 9 10 8 (9.55 9 10 8) 2.93 9 10 7 (6.42 9 10 7)
0.164 0.067
1.38 9 10
6
2.83 1.79–4.55 1.2 9 10
13
FLOT1
0.153 0.071
4.53 9 10
5
2.46 1.56–3.93 2.3 9 10
11
2.65 9 10 7 (5.35 9 10 7) 3.26 9 10 7 (1.92 9 10 6) 3.50 9 10 6 (4.54 9 10 6)
2.05 (1.56–2.70) 1.91 (1.49–2.44) 2.20 (1.58–3.08)
0.217 0.132
4.88 9 10
4
1.85 1.29–2.68 4.00 9 10
0.385 0.300
6.84 9 10
3
1.45 1.10–1.91 2.0 9 10
8
TRIM39/ RPP21 (intronic) PSORS1C1 (intronic) HLA-DQA1
0.119 0.050
1.17 9 10
4
2.60 1.55–4.47 7.7 9 10
10
rs2187668 6
32.713.862 T
0.258 0.107
rs9267531 6
31.744.721 G
0.228 0.100
rs3131379 6
31.829.012 A
0.228 0.100
rs2844559 6
31.448.054 T
0.240 0.107
rs4410767 6
32.556.107 C
0.185 0.376
rs3094084 6
31.055.488 T
rs3099844 6 rs3131060 6 rs3094067 6
30.407.224 G
0.197 0.096
rs3130564 6
31.209.653 T
0.287 0.163
rs9272219 6
32.710.247 T
0.440 0.292
rs1233491 6
Genes1
Comb p
29.569.709 C
0.174 0.088
–
–
–
–
10
HLA-DQA1 (intronic) CSNK2B (intronic), MSH5 MSH5 (intronic) MICA HLA-DRB3 (intronic) HLA-DRA MUC21, TRIM39, RPP21 MICB
MAS1L
Table includes only loci achieving a genomewide level of significance (P < 5 9 10 8) in the combined analysis. MAF, minor allele frequency *P values are from logistic regression models using an additive model for the GWAS and validation, and from a Cochran–Mantel–Haenszel test for the combination 1 Position of each SNP relative to notable nearby genes is given. Intronic indicates that the SNP overlaps the gene in an intronic area. Gene abbreviations: CSNK2B, casein kinase 2, beta polypeptide; MSH5, MutS homologue 5; MICB, MHC class I polypeptide-related sequence B; MUC21, mucin 21, cell surface associated; TRIM39, tripartite motif-containing protein 39; RPP21, ribonuclease P/MRP 21 kDa subunit; PSORS1C1, psoriasis susceptibility 1 candidate 1; MAS1L, MAS1 oncogene-like.
haplotype analyses demonstrated that variations within MICB contribute to SLE risk independent of the common SLE marker HLADRB1*0301. Moreover, rs3099844 showed the strongest association of 17 significant associations with cardiac neonatal lupus in a study on 116 children of European ancestry (37). Cardiac manifestations of neonatal lupus occur in foetuses exposed to anti-Ro/ SSA antibodies, a common feature of SCLE. MICA and MICB encode proteins that serve as ligands for the NKG2D type 2 receptors on natural killer cells (38). Several reports provided evidence for an association of the MICA gene with SLE (39–41). Interestingly, in one of these studies, the frequency of the transmembrane (TM) alanine-encoding GCT repeat A9 in MICA (so-called MICA A9 allele) was higher in SLE patients with skin involvement than in patients without this manifestation (16.6% vs 7.7%) (40). When the MICA 129Met;A9 variant protein was incubated with natural killer cells, it suppressed NK cell-mediated cytotoxicity but stimulated the release of IFNc (41). In line with this, natural killer cell activity is known to be suppressed in SLE (42). Thus, MICA and MICB might play a role in both SLE and CLE. A further independent SNP with highly significant association was rs4410767 (PGWAS = 1.0 9 10 9, OR = 0.39, 95% CI = 0.28– 0.52), located in the HLA-DR region, in particular HLA-DRB1, which is known for its high association with SLE (13) (Fig. 2). Closely located HLA-DRB5 gene showed association with SLE in a Thai cohort, as demonstrated in a recent study (43). In the mentioned report of Deng and co-workers on functional SNP (eQTL) analyses, several SLE-associated SNPs such as rs264712, rs7192,
ª 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Experimental Dermatology, 2015, 24, 510–515
rs9268832 and 9275224 close to the HLA-DQB1 locus were associated with differential expression of HLA-DR in LCL cells and monocytes (33). Data about the functional impact of rs4410767 on HLA-DR expression have not been published yet. The fourth SNP with strong CLE association was rs3094084 (PGWAS = 1.1 9 10 9, OR = 2.30, 95% CI = 1.76–3.01; Poverall = 1.5 9 10 11) (Fig. 2). rs3094084 and closely located rs3131060 (PGWAS = 4.6 9 10 8, OR 2.30, 95% CI = 1.71–3.11; Poverall = 1.2 9 10 13) were sites of validated association. A closely located SNP cluster includes rs3094067, rs3130350 and rs3094057. All three SNPs are located in a gene region encoding for tripartite motif-containing protein 39 (TRIM39), ribonuclease P protein subunit 21 (RPP21) and TRIM39/RPP21 (Fig. 2). TRIM39 is a ubiquitin ligase. It stabilizes modulator of apoptosis protein 1 (MOAP-1), an enhancer of activation of proapoptotic Bax protein which is induced by DNA damage (44,45). Overall, TRIM39 is known to play an important role in apoptosis regulation (45). In line with this, dysregulated apoptosis or increased apoptosis sensitivity is regarded as a central pathogenic mechanism in patients with CLE, in particular after UV radiation of the skin (15, 46–48). Interestingly, a polymorphism in the TRIM39 gene (rs2074474, in exon 9) was shown to be associated with Behcßet’s disease in a Japanese cohort of 384 patients (49). Recent data showed that TRIM39R, the TRIM39/RPP21 read through transcript, but not TRIM39 itself is a mediator of interferon response, a major pathogenic cytokine response in SLE and CLE (50).
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(a)
(c)
(b)
(d)
Figure 2. Associations with cutaneous lupus erythematosus risk across four loci. Regional association plots demonstrate strength of association given by log10 P values. Plots are centred on the most significant SNPs (diamond). Values are plotted with coloured circles for all SNPs, shaded form blue to red by the degree of LD (R2). The most significant and validated SNPs are given as a larger violet diamond. rs4410767 was not validated in the Finnish cohort. Black arrows with gene abbreviations below the plots indicate genes and their orientations. (a) HLA-DQA1 locus; (b) CSNK2B locus with associated loci for MICA, MICB and MSH5; (c) HLA-DRA/ HLA-DRB locus; (d) MUC21 locus with associated loci for TRIM39/RPP21.
Rpp21 is a protein subunit of human nuclear ribonuclease P (RNase P) (51). RNase P protein subunits Rpp21 and Rpp29, together with catalytic RNA (H1 RNA), are involved in processing and endonucleolytic cleavage of precursor tRNA (52). Recently, it was also shown that RNase P is involved in the inhibition of degradation of non-coding long RNAs (53). Patients suffering from Aicardi–Goutieres syndrome (AGS) show many symptoms of SLE (54). AGS is an autosomal recessive disease linked to mutations in five genes, including DNA exonuclease 1 TREX1 and ribonuclease H2 (55). Recent experimental evidence showed that mice with RNase H2 mutations developed lupus-like disease (56). Thus, altered RNA processing via TRIM39/RPP21 might be a pathogenically relevant mechanism for both SLE and CLE (14, 57). Because the four above-described polymorphisms rs2187668, rs9267531, rs4410767 and rs3094084 are closely located to each other, a conditional analysis was performed. There is a low to moderate linkage disequilibrium between the mentioned SNPs. The maximum R2 value was observed between rs2187668 and rs9267531 (0.7) which was markedly lower for other pairs. Conditional analyses indicated a dependence of the signals, so that it is, at this stage, difficult to decide whether there are one or several underlying signals. Further studies with larger samples are required to clarify this. rs876039 is located on chromosome 7 with close to genomewide significance of association (P = 8.4 9 10 7, OR = 0.48, 95% confidence interval (CI) = 0.36–0.64; and P = 1.1 9 10 6, OR = 0.48, 95% confidence interval (CI) = 0.36–0.65, respectively). rs876039 was not validated in the Finnish validation
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sample. rs876039 and another SNP in this region, rs4917014, are located ~36 and 41 kB, respectively, proximal of the IKZF1 gene. In a recent study on a Chinese Han population suffering from SLE, rs4917014 was associated with malar rash, that is classical facial skin lesions of patients with CLE (58). In a consecutive study, the mRNA expression levels of IKZF1 in PBMC from patients with SLE were significantly decreased compared with healthy controls (59). Thus, decreased expression of IKZF1 might be related to SLE and CLE pathogenesis. Interestingly, IKZF1 has also been described as a susceptibility gene (rs2366293) in a UK data set of 870 SLE cases and 5,551 controls (60). The IKZF1 gene encodes Ikaros, a DNA-binding zinc finger protein involved in chromatin remodelling (61). Ikzf1 knockout mice suffer from multiple hematopoietic cell defects and lymphoid cell defects (62). However, a lupus-like phenotype has not yet been observed. In a very recent study that combined high-throughput glycomics with GWAS data to analyse genetic associations of the plasma IgG N-glycome in more than 4000 individuals, IKZF1, IL6ST-ANKRD55 and ABCF2-SMARCD3 were newly identified to be implicated in IgG glycosylation patterns (63). Further analysis of IgG isolated from Ikzf1 heterozygous knockout mice showed that a number of alterations in the IgG N-glycome composition were consistent with a role of IKZF1 in downregulating fucosylation and upregulating and the addition of bisecting GlcNAc to IgG glycan. Thus, the IKZF1 gene appears to impact on IgG glycosylation, a major mechanism for IgG function and stability. The IRF5 SNP rs10954213 A allele showed a significant association with DLE and SCLE in one of the mentioned studies (24). Notably, a recent paper showed a direct interaction between IRF5 and IKZF1 in a mouse model (64). IRF5-regulated transcriptional expression of IgG2a/c was mediated by decreased Ikaros expression. The IRF site in Ikzf1 promoter binds IRF5, IRF4 and IRF8. Overall, the IRF5–Ikaros axis seems to be a critical modulator of IgG2a/c class switching. Due to class switching and variable region Ab hypermutation, previously naive B cells may become autoreactive (65, 66). Taken together, the present report identified a series of new genetic polymorphisms associated with CLE. For some of the closely linked genes such as HLA-DQA1, MICA/B and IKZF, association has also been described for SLE. CLE-linked genes like TRIM39/RPP21 interfere with apoptosis regulation and interferon response, which are known to play a role in CLE and may thereby help to explain the deregulated interferon and apoptosis response in CLE. CLE-associated MICA and IKZF genes also show association with skin involvement in SLE. Overall, these data suggest that different but also partly overlapping genes underlie CLE and SLE, emphasizing the notion of different diseases with partly overlapping clinical features. Follow-up analyses with genomewide association scans in larger sample sets and large-scale analyses of rarer variants may lead to identification of additional susceptibility loci.
Acknowledgements This work was funded by the Deutsche Forschungsgemeinschaft (DFG) Cluster of Excellence ‘Inflammation at Interfaces’ (grant EXC306 to WI, AF, SMI). Popgen received infrastructure support through the DFG Cluster of Excellence ‘Inflammation at Interfaces’ (grants EXC306 and EXC306/2) and was supported by the German Ministry of Education and Research (BMBF) through the e:Med sysINFLAME grant and the PopGen 2.0
ª 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Experimental Dermatology, 2015, 24, 510–515
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network (01EY1103). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We are grateful to Gerald Messer, Department of Dermatology, Ludwig Maximilian University, Munich, Germany, for helpful discussion and provision of lupus patient samples. Author contributions: MK, AR, JP, SK, TH, JK, ACR, JCS and SMI performed the research; MK, SMI, AR and
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IRK designed the research study; IRK, AS, JK, AZ, TZ and SB analysed the data; HG, MMN, WL, AF, ES, JW, TT, JL, RG, NP and AK contributed patient samples, clinical and serological information; and MK, IRK and SMI wrote the paper.
Conflict of interest All authors declare that there are no financial, personal or professional interests that could be construed to have influenced the paper.
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Supporting Information Additional supporting data may be found in the supplementary information of this article. Table S1. Summary and description of the samples after quality control. Table S2. Detailed description of all associations with P < 5 9 10 6 in the lupus GWAS and validation sample. Table S3. Genes omitted in region plots of Fig. 2.
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Original Article
www.wileyonlinelibrary.com/journal/EXD
Genome-wide association study identifies new susceptibility loci for cutaneous lupus erythematosus € nig2, Arne Schillert2, Jochen Kruppa2, Andreas Ziegler2, Harald Grallert3,4, Manfred Kunz1, Inke R. Ko 5-7 € ller-Nurasyid , Wolfgang Lieb8, Andre Franke9, Annamari Ranki10, Jaana Panelius10, Martina Mu € nn14, Jan C. Simon1, Enno Schmidt15, Sari Koskenmies10, Taina Hasan11, Juha Kere12,13, Ann-Charlotte Ro 16 16 16 € ting , Jennifer Landsberg , Tanja Zeller17, Stefan Blankenberg17, Joerg Wenzel , Thomas Tu 18 €ser , Nikolaos Patsinakidis19, Annegret Kuhn20 and Saleh M. Ibrahim15 Regine Gla 1 Department of Dermatology, Venereology and Allergology, University of Leipzig, Leipzig, Germany; 2Institut f€ ur Medizinische Biometrie und Statistik, und Zentrum f€ ur Klinische Studien, Universit€at zu L€ ubeck, Universit€atsklinikum Schleswig-Holstein, L€ ubeck, Germany; 3Research unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum M€ unchen – German Research Center for Environmental Health, Neuherberg, Germany; 4German Center for Diabetes Research, Helmholtz Zentrum M€ unchen – German Research Center for Environmental Health, Neuherberg, Germany; 5Institute of Genetic Epidemiology, Helmholtz Zentrum M€ unchen – German Research Center for Environmental Health, Neuherberg, Germany; 6Department of Medicine I, Ludwig Maximilian University Munich, Munich, Germany; 7German Center for Cardiovascular Research, Munich Heart Alliance, Munich, Germany; 8Institute for Epidemiology and Biobank popgen, Christian-AlbrechtsUniversity of Kiel, Kiel, Germany; 9Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany; 10Department of Dermatology and Allergology, Skin and Allergy Hospital, Helsinki University Central Hospital, Helsinki, Finland; 11Department of Dermatology, Tampere University Central Hospital, University of Tampere, Tampere, Finland; 12Department of Biosciences and Nutrition, Karolinska Institute, Huddinge, Sweden; 13Department of Medical Genetics, Folkh€alsan Institute of Genetics, University of Helsinki, Helsinki, Finland; 14Clinical Research Center, Karolinska University Hospital, Huddinge, Sweden; 15Department of Dermatology, Allergology and Venereology, University of Schleswig-Holstein, L€ ubeck, Germany; 16Department of Dermatology and Allergy, University of Bonn, Bonn, Germany; 17University Heart Center Hamburg, Clinic for General and Interventional Cardiology, German Center for Cardiovascular Research (DZHK), Hamburg, Germany; 18 Department of Dermatology and Allergology, University of Schleswig-Holstein, Kiel, Germany; 19Department of Dermatology, Venereology and Allergology, Ruhr-University of Bochum, Bochum, Germany; 20Division of Immunogenetics, German Cancer Research Center, Heidelberg, Germany Correspondence: Manfred Kunz, MD, Department of Dermatology, Venereology and Allergology, University of Leipzig, Philipp-Rosenthal-Str. 23, 04103 Leipzig, Germany, Tel: +49-341-9718610, Fax: +49-341-9718609, e-mail: [email protected]
Abstract: Cutaneous lupus erythematosus (CLE) is a chronic autoimmune disease of the skin with typical clinical manifestations. Here, we genotyped 906 600 single nucleotide polymorphisms (SNPs) in 183 CLE cases and 1288 controls of Central European ancestry. Replication was performed for 13 SNPs in 219 case subjects and 262 controls from Finland. Association was particularly pronounced at 4 loci, all with genomewide significance (P < 5 9 10 8): rs2187668 (PGWAS = 1.4 9 10 12), rs9267531 (PGWAS = 4.7 9 10 10), rs4410767 (PGWAS = 1.0 9 10 9) and rs3094084 (PGWAS = 1.1 9 10 9). All mentioned SNPs are located within the major histocompatibility complex (MHC) region of chromosome 6 and near genes of known immune functions or associations with other autoimmune diseases such as HLA-DQ alpha chain 1
(HLA-DQA1), MICA, MICB, MSH5, TRIM39 and RPP21. For example, TRIM39/RPP21 read through transcript is a known mediator of the interferon response, a central pathway involved in the pathogenesis of CLE and systemic lupus erythematosus (SLE). Taken together, this genomewide analysis of disease association of CLE identified candidate genes and genomic regions that may contribute to pathogenic mechanisms in CLE via dysregulated antigen presentation (HLA-DQA1), apoptosis regulation, RNA processing and interferon response (MICA, MICB, MSH5, TRIM39 and RPP21).
Introduction
been defined more recently and termed LE tumidus (LET) (3). In the revised classification system, LET is described as an intermittent subtype of CLE (ICLE) (4). A small percentage of patients with cutaneous disease subsequently develop systemic manifestations (5). It is well known that in addition to environmental triggers, a genetic predisposition plays an important role in the aetiology of systemic lupus erythematosus (SLE) and CLE (6–15). Besides the well-known association with the human leucocyte antigen (HLA) region for SLE and CLE, more recent genomewide association
Cutaneous lupus erythematosus (CLE) is an autoimmune disease with highly variable clinical spectrum, presenting as single or multiple erythematous macules and papules, as well as annular or serpiginous lesions with a characteristic histopathological picture (1). In principle, CLE is divided into three categories based on the clinical picture, histological changes, laboratory abnormalities and the duration of skin lesions, acute CLE (ACLE), subacute CLE (SCLE) and chronic CLE (CCLE) (2). Another subtype with characteristic clinical, histological and photobiological features has
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Key words: autoimmune diseases – genetics – lupus – single nucleotide polymorphisms
Accepted for publication 26 March 2015
ª 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Experimental Dermatology, 2015, 24, 510–515
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studies (GWAS) have identified that genetic variants in the TNFinduced protein 3 (TNFAIP3) and signal transducer and activator of transcription 4 (STAT4) regions are associated with SLE (7,16,17). TNFAIP3 encodes the intra-cellular ubiquitin-editing protein A20 which exerts a negative feedback activity in NF-jB signalling (18). STAT4 has been implicated in the differentiation of Th17 cells, which are major regulators of autoimmune processes and are known to be involved in lupus pathogenesis (19). Two further genetic loci in SLE encoding B lymphocyte kinase (BLK) and two integrins (ITGAM–ITGAX) were described in a recently published report which may contribute to the risk of SLE (8). It is well understood that CLE has a genetic association with the HLA region, the TNF-a promoter and the complement region (20,21). The major associations in discoid lupus erythematosus (the major subtype of CCLE) include the HLA-A1, HLA-B8, HLA-DR3 and also the HLA-B7, HLA-DR2 haplotypes (20). Recently described associations of interferon regulatory factor 5 (IRF5) with SLE are suggestive for a significant role of type 1 interferons (IFNs) in SLE susceptibility (7,16,22). Type 1 IFNs have also been reported in the pathogenesis of CLE (23). In recent genetic association studies, the question was addressed whether genetic loci associated with susceptibility for SLE may also be risk factors for CLE (13,24–26). Among major susceptibility loci, TYK2, IRF5 and CTLA4 genes were shown to also confer risk for CLE (24–26). However, large comprehensive genomewide association studies on the genetics of CLE are still missing. In the present report, we used a genomewide approach to identify genetic susceptibility loci for CLE in two different European samples.
Materials and methods Case subjects included 183 patients with different clinical subtypes of CLE (CCLE 44.8%, SCLE 40.4%, LET 14.2%). DNA samples for the GWAS study were obtained from outpatient clinics of the Departments of Dermatology at the Universities of L€ ubeck, Kiel, M€ unster, Bonn and Munich (all Germany). The European origin of all cases was determined by self-report. In all cases, the diagnosis of CLE was confirmed by review of medical records, based on clinical findings and histopathology of skin lesions and by written documentation of the treating dermatologists. The study was approved by the ethical committee of the University Hospital of Schleswig-Holstein, Campus L€ ubeck (AZ 09-056). The institutional review boards at each centre approved the study. All patients gave informed written consent, and the Declaration of Helsinki protocols were followed. Clinical data were reviewed at each institution. Mean follow-up of patients after initial diagnosis of CLE was 7.94 (7.38) years (follow-up information was not available for 34 of the 183 patients), ranging from 1 to 30 years, during which period none of the patients developed systemic disease. Control data of 810 healthy individuals were provided by KORA (Kooperative Gesundheitsforschung in der Region Augsburg) from the Helmholtz Centre, Neuherberg, Germany, and of 478 individuals from the population-based Biobank popgen, University of Schleswig-Holstein, Campuses L€ ubeck and Kiel, Germany. To validate our results, DNA from an independent collection of 177 patients with DLE and 42 patients with SCLE and 262 healthy control individuals from Finland was genotyped (24). For the collection of this material, all patients with clinical
ª 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Experimental Dermatology, 2015, 24, 510–515
diagnosis of DLE and SCLE attending the Departments of Dermatology at Helsinki and Tampere University Central Hospitals during 1995–2005 were identified from the corresponding hospital registries and contacted by mail or phone. The study was approved by the medical ethical review board of Helsinki and Uusimaa joint authority (Dnro 62/2009), and the participants volunteered after a written informed consent. The clinical and demographic features of these patients have been described previously (24,27). Unaffected family members (spouses or commons in law) from the case–control families and the original Finnish family study (28) were asked to participate as control subjects, and an existing collection of one hundred unrelated individuals was also used as controls. The participating patients were clinically examined by staff dermatologists (SK, TH, JP from list of authors) and interviewed using a structured questionnaire (27). Further information about German and Finnish samples and controls is given in Table S1. The obvious differences in positive testing for antinuclear antibodies (ANA) may in part be explained by significantly higher percentages of patients with SCLE in the GWAS samples compared with the Finnish validation sample (40% vs 19%). It is known that patients with SCLE show a higher percentage of positive ANA titres (1).
Genotyping Genotyping was performed on all GWAS cases (German sample) and controls between July 2009 and July 2010 using the Affymetrix Genome-wide Human SNP 6.0 Array (Affymetrix, Santa Clara, CA, USA). Processing of DNA samples and hybridization was performed in accordance with the manufacturers’ standard recommendations (Affymetrix). Case samples were genotyped at the Department of Internal Medicine at the University of Mainz, and genotypes of controls were derived from KORA and popgen biobank. The analysis included more than 906 600 single nucleotide polymorphisms (SNPs). Genotypes were determined using the Birdseed v2 calling algorithm. Quality control on case sample level comprised exclusion of samples with a call rate ≤97%, deviation from expected heterozygosity by more than three standard deviations and relatedness based on identity by state distance measures. As a result, data of 151 cases were available for analysis. On marker level, we excluded polymorphisms with a call rate ≤98% in cases and controls, minor allele frequency ≤0.01 and deviation from Hardy–Weinberg equilibrium (P ≤ 0.0001). Cluster plots were inspected for all markers with P < 0.001 in the GWAS analysis. Genotyping of the Finnish validation sample was performed at the Mutation Analysis Facility at Karolinska University Hospital, Huddinge, Sweden, using iPLEX Gold chemistry and MassARRAY mass spectrometry system (29) (Sequenom, San Diego, CA, USA). Multiplexed assays were designed using MassARRAY Assay Design v4.0 Software (Sequenom). The genotyping was validated using a set of 14 trio families, in total 42 individuals, with genotype data available through the HapMap Consortium (HapMap data release #28). For three of the trio families genotyped, only data from one SNP were available (rs3094067). Concordance analysis with the HapMap data showed concordance rates of 100% for all analysed SNPs. Parent–offspring compatibility analysis was performed, and one Mendel error was observed in the genotyped trio families for rs2844559; however, the genotype data for that family were not available in the HapMap database. Assays had a success rate of >98% (mean 98.8%). The 50% fail
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rate cut-off was met by all but two study samples (1512 and L_206), and 97.3% of the 481 samples had a 100% success rate for all assays. Additionally, re-genotyping of 18% of the study samples resulted in 100% concordance.
Statistical analysis The extent of population stratification was estimated using principal component analysis (PCA) based on IBS (identity by state) information of 25 000 randomly selected LD-pruned autosomal markers. The genomic inflation factor was 1.04. Further highly similar samples (estimated kinship coefficient >0.5) were excluded. The combined PCA of cases and controls showed no deviance. The statistical analysis was based on an additive model without adjustments using logistic regression. In addition, logistic regression models adjusting for sex were computed. The primary analysis was performed in the German sample, and SNPs were selected for analysis in the Finnish sample. Here, also an additive model without adjustment was used for analysis. To account for multiple testing, SNPs with a P-value 0.05 were defined, all of which were located in the MHC region. Thirteen SNPs representing these regions were genotyped as validation in the Finnish sample in 219 cases (177 DLE and 42 SCLE patients) and 262 controls. Twelve of these 13 SNPs nominally reached genomewide significance (P < 5 9 10 8) in the combined analysis of data from both samples (Table S2). Most prominent SNPs from the combined analysis for both samples are given in Table 1. The results highlight the possible role of several new molecules in CLE pathogenesis. Four prominent SNPs located close to
Figure 1. Identification of major loci associated with cutaneous lupus erythematosus in a genomewide association study. Data represent 906,600 variants of single nucleotide polymorphisms (SNPs) genotyped in 151 cases and 1288 controls. The distribution of test statistics at genotyped SNPs across the genome is shown. A logistic regression model was used to compare genotype frequencies in cases and controls in an additive model. The resulting –log P values are plotted across the genome. Genes associated with loci of the top 10 SNPs with genomewide significance (P ≤ 5 9 10 8) which were also confirmed regarding association in the validation sample (Table 1) are indicated. The SNPs on chromosome 7 and 10 did not reach genomewide significance.
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interesting immunoregulatory genes within this region and are described in more detail: rs2187668, rs9267531, rs4410767 and rs3094084. The strongest association was observed for rs2187668 (PGWAS = 1.4 9 10 12, OR = 2.93, 95% confidence interval (CI) = 2.18–3.95; Poverall = 3.6 9 10 10) (Fig. 2; Table 1, Table S3). Sex-adjusted P values differed only slightly from not sexadjusted values and are given in Table 1 and Table S2. rs2187668 is in strong linkage disequilibrium with rs3129716 OR = 2.85, 95% CI = 2.11–3.84). (PGWAS = 8.0 9 10 12, rs2187668 is located within the gene encoding the HLA class II complex HLA-DQ alpha chain 1 (HLA-DQA1). In an earlier study, SLE association with HLA class II region was delimited to a 180 kb region encompassing the alleles HLA-DRB1*0301, HLADQA1*0501 and HLA-DQB1*0201 (30). Furthermore, in a metaanalysis using genotypes for 7199 SNPs within the MHC region, the best SLE association was found for classical HLA loci (HLADRB1*0301, HLA-DRB1*0801 and HLA-DQA1*0102) and two SNPs, rs8192591 (in class III region, upstream of NOTCH4) and rs2246618 (MICB in class I) (31). In a recent association study, rs2187668 showed highly significant association (P = 8.0 9 10 93) for three different populations of French, Dutch and British patients suffering from idiopathic membranous nephropathy (32). One of the hallmarks of both idiopathic membranous nephropathy and lupus nephritis is the presence of glomerular deposits of immunoglobulin and complement components. As immunoglobulin deposits in the skin are a hallmark of CLE, this SNP may also support the development of skin disease. So, rs2187668 association might not be indicative for renal involvement but rather immunoglobulin deposition. In a study on SLE, evidence was provided by analysis of expressed quantitative trait loci (eQTL) that the rs2187668 SNP is associated with enhanced HLA-DQA1 expression (33). Strongly associated SNPs rs9267531 (PGWAS = 4.7 9 10 10, OR = 2.62, 95% CI = 1.93–3.54; Poverall = 3.3 9 10 14) and rs3131379 (PGWAS = 5.30 9 10 10, OR = 2.61, 95% CI = 1.93– 3.53; Poverall = 2.3 9 10 14) (Fig. 2) are located in a region of high gene content. rs9267531 is located within an intronic region of the CSNK2B gene encoding for casein kinase 2 (CK2), beta polypeptide. Interestingly, a cDNA microarray analysis on renal biopsies specimens from lupus nephritis identified CK2a, the catalytic subunit of CK2, as a glomerulonephritis-related gene (34). rs3131379, which is strongly linked to rs9267531, maps to an intronic region of the MutS homologue 5 (MSH5) gene. MSH5 is involved in DNA mismatch repair and meiotic recombination. In a transancestral SNP mapping approach, MSH5 has been reported as an SLE-associated gene in United Kingdom families (35) and also in a study on patients with SLE of African American background (36). A further SNP strongly linked to rs9267531 was rs2844559 (PGWAS = 5.5 9 10 10, OR = 2.53, 95% CI = 1.89–3.39; Poverall = 9.1 9 10 15) together with closely located and strongly associated SNP rs3099844 (PGWAS = 5.7 9 10 9, OR = 2.44, 95% CI = 1.81– 3.29; Poverall = 4.4 9 10 10). rs2844559 is located ~27 kb proximal of MHC class I chain-related A (MICA) gene and ~120 kb proximal of the MICB gene. rs3099844 maps ~15 kb proximal of the MICB gene. A recent study characterized 1610 Caucasian SLE cases and 1470 parents for 1974 MHC SNPs (9). Conditional
ª 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Experimental Dermatology, 2015, 24, 510–515
Cutaneous lupus susceptibility loci
Table 1. Loci with strongest evidence of association with cutaneous lupus erythematosus in the discovery and validation samples Discovery sample (151 cases, 1288 controls) Validation sample (219 cases, 262 controls) Minor MAF MAF P value* GWAS MAF MAF P value SNP Chr Position allele cases controls (sex adjusted) OR (95% CI) cases controls (validation) OR CI OR 1.44 9 10 12 (2.27 9 10 11) 4.72 9 10 10 (2.79 9 10 9)
2.93 (2.18–3.95) 2.62 (1.93–3.54)
0.258 0.107
2.46 9 10
4
1.98 1.35–2.93 3.6 9 10
10
0.172 0.084
3.58 9 10
05
2.34 1.53–3.64 3.3 9 10
14
5.25 9 10 10 (3.79 9 10 9) 5.50 9 10 10 (1.62 9 10 9) 1.03 9 10 9 (2.52 9 10 9)
2.61 (1.93–3,53) 2.53 (1.89–3.39) 0.39 (0.28–0.52)
0.176 0.085
2.08 9 10
05
2.36 1.55–3.64 2.3 9 10
14
0.196 0.092
7.08 9 10
06
2.32 1.57–3.48 9.1 9 10
15
–
–
0.302 0.154
1.10 9 10 9 (5.37 9 10 9)
2.30 (1.76–3.01)
0.217 0.139
2.03 9 10
3
1.71 1.20–2.46 1.5 9 10
11
31.556.955 A
0.236 0.112
2.05 9 10
6
2.56 1.69–3.93 4.0 9 10
10
0.228 0.112
2.44 (1.81–3.29) 2.30 (1.71–3.11) 2.32 (1.68–3.20)
0.192 0.088
30.871.270 A
5.71 9 10 9 (2.35 9 10 8) 4.55 9 10 8 (9.55 9 10 8) 2.93 9 10 7 (6.42 9 10 7)
0.164 0.067
1.38 9 10
6
2.83 1.79–4.55 1.2 9 10
13
FLOT1
0.153 0.071
4.53 9 10
5
2.46 1.56–3.93 2.3 9 10
11
2.65 9 10 7 (5.35 9 10 7) 3.26 9 10 7 (1.92 9 10 6) 3.50 9 10 6 (4.54 9 10 6)
2.05 (1.56–2.70) 1.91 (1.49–2.44) 2.20 (1.58–3.08)
0.217 0.132
4.88 9 10
4
1.85 1.29–2.68 4.00 9 10
0.385 0.300
6.84 9 10
3
1.45 1.10–1.91 2.0 9 10
8
TRIM39/ RPP21 (intronic) PSORS1C1 (intronic) HLA-DQA1
0.119 0.050
1.17 9 10
4
2.60 1.55–4.47 7.7 9 10
10
rs2187668 6
32.713.862 T
0.258 0.107
rs9267531 6
31.744.721 G
0.228 0.100
rs3131379 6
31.829.012 A
0.228 0.100
rs2844559 6
31.448.054 T
0.240 0.107
rs4410767 6
32.556.107 C
0.185 0.376
rs3094084 6
31.055.488 T
rs3099844 6 rs3131060 6 rs3094067 6
30.407.224 G
0.197 0.096
rs3130564 6
31.209.653 T
0.287 0.163
rs9272219 6
32.710.247 T
0.440 0.292
rs1233491 6
Genes1
Comb p
29.569.709 C
0.174 0.088
–
–
–
–
10
HLA-DQA1 (intronic) CSNK2B (intronic), MSH5 MSH5 (intronic) MICA HLA-DRB3 (intronic) HLA-DRA MUC21, TRIM39, RPP21 MICB
MAS1L
Table includes only loci achieving a genomewide level of significance (P < 5 9 10 8) in the combined analysis. MAF, minor allele frequency *P values are from logistic regression models using an additive model for the GWAS and validation, and from a Cochran–Mantel–Haenszel test for the combination 1 Position of each SNP relative to notable nearby genes is given. Intronic indicates that the SNP overlaps the gene in an intronic area. Gene abbreviations: CSNK2B, casein kinase 2, beta polypeptide; MSH5, MutS homologue 5; MICB, MHC class I polypeptide-related sequence B; MUC21, mucin 21, cell surface associated; TRIM39, tripartite motif-containing protein 39; RPP21, ribonuclease P/MRP 21 kDa subunit; PSORS1C1, psoriasis susceptibility 1 candidate 1; MAS1L, MAS1 oncogene-like.
haplotype analyses demonstrated that variations within MICB contribute to SLE risk independent of the common SLE marker HLADRB1*0301. Moreover, rs3099844 showed the strongest association of 17 significant associations with cardiac neonatal lupus in a study on 116 children of European ancestry (37). Cardiac manifestations of neonatal lupus occur in foetuses exposed to anti-Ro/ SSA antibodies, a common feature of SCLE. MICA and MICB encode proteins that serve as ligands for the NKG2D type 2 receptors on natural killer cells (38). Several reports provided evidence for an association of the MICA gene with SLE (39–41). Interestingly, in one of these studies, the frequency of the transmembrane (TM) alanine-encoding GCT repeat A9 in MICA (so-called MICA A9 allele) was higher in SLE patients with skin involvement than in patients without this manifestation (16.6% vs 7.7%) (40). When the MICA 129Met;A9 variant protein was incubated with natural killer cells, it suppressed NK cell-mediated cytotoxicity but stimulated the release of IFNc (41). In line with this, natural killer cell activity is known to be suppressed in SLE (42). Thus, MICA and MICB might play a role in both SLE and CLE. A further independent SNP with highly significant association was rs4410767 (PGWAS = 1.0 9 10 9, OR = 0.39, 95% CI = 0.28– 0.52), located in the HLA-DR region, in particular HLA-DRB1, which is known for its high association with SLE (13) (Fig. 2). Closely located HLA-DRB5 gene showed association with SLE in a Thai cohort, as demonstrated in a recent study (43). In the mentioned report of Deng and co-workers on functional SNP (eQTL) analyses, several SLE-associated SNPs such as rs264712, rs7192,
ª 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Experimental Dermatology, 2015, 24, 510–515
rs9268832 and 9275224 close to the HLA-DQB1 locus were associated with differential expression of HLA-DR in LCL cells and monocytes (33). Data about the functional impact of rs4410767 on HLA-DR expression have not been published yet. The fourth SNP with strong CLE association was rs3094084 (PGWAS = 1.1 9 10 9, OR = 2.30, 95% CI = 1.76–3.01; Poverall = 1.5 9 10 11) (Fig. 2). rs3094084 and closely located rs3131060 (PGWAS = 4.6 9 10 8, OR 2.30, 95% CI = 1.71–3.11; Poverall = 1.2 9 10 13) were sites of validated association. A closely located SNP cluster includes rs3094067, rs3130350 and rs3094057. All three SNPs are located in a gene region encoding for tripartite motif-containing protein 39 (TRIM39), ribonuclease P protein subunit 21 (RPP21) and TRIM39/RPP21 (Fig. 2). TRIM39 is a ubiquitin ligase. It stabilizes modulator of apoptosis protein 1 (MOAP-1), an enhancer of activation of proapoptotic Bax protein which is induced by DNA damage (44,45). Overall, TRIM39 is known to play an important role in apoptosis regulation (45). In line with this, dysregulated apoptosis or increased apoptosis sensitivity is regarded as a central pathogenic mechanism in patients with CLE, in particular after UV radiation of the skin (15, 46–48). Interestingly, a polymorphism in the TRIM39 gene (rs2074474, in exon 9) was shown to be associated with Behcßet’s disease in a Japanese cohort of 384 patients (49). Recent data showed that TRIM39R, the TRIM39/RPP21 read through transcript, but not TRIM39 itself is a mediator of interferon response, a major pathogenic cytokine response in SLE and CLE (50).
513
Kunz et al.
(a)
(c)
(b)
(d)
Figure 2. Associations with cutaneous lupus erythematosus risk across four loci. Regional association plots demonstrate strength of association given by log10 P values. Plots are centred on the most significant SNPs (diamond). Values are plotted with coloured circles for all SNPs, shaded form blue to red by the degree of LD (R2). The most significant and validated SNPs are given as a larger violet diamond. rs4410767 was not validated in the Finnish cohort. Black arrows with gene abbreviations below the plots indicate genes and their orientations. (a) HLA-DQA1 locus; (b) CSNK2B locus with associated loci for MICA, MICB and MSH5; (c) HLA-DRA/ HLA-DRB locus; (d) MUC21 locus with associated loci for TRIM39/RPP21.
Rpp21 is a protein subunit of human nuclear ribonuclease P (RNase P) (51). RNase P protein subunits Rpp21 and Rpp29, together with catalytic RNA (H1 RNA), are involved in processing and endonucleolytic cleavage of precursor tRNA (52). Recently, it was also shown that RNase P is involved in the inhibition of degradation of non-coding long RNAs (53). Patients suffering from Aicardi–Goutieres syndrome (AGS) show many symptoms of SLE (54). AGS is an autosomal recessive disease linked to mutations in five genes, including DNA exonuclease 1 TREX1 and ribonuclease H2 (55). Recent experimental evidence showed that mice with RNase H2 mutations developed lupus-like disease (56). Thus, altered RNA processing via TRIM39/RPP21 might be a pathogenically relevant mechanism for both SLE and CLE (14, 57). Because the four above-described polymorphisms rs2187668, rs9267531, rs4410767 and rs3094084 are closely located to each other, a conditional analysis was performed. There is a low to moderate linkage disequilibrium between the mentioned SNPs. The maximum R2 value was observed between rs2187668 and rs9267531 (0.7) which was markedly lower for other pairs. Conditional analyses indicated a dependence of the signals, so that it is, at this stage, difficult to decide whether there are one or several underlying signals. Further studies with larger samples are required to clarify this. rs876039 is located on chromosome 7 with close to genomewide significance of association (P = 8.4 9 10 7, OR = 0.48, 95% confidence interval (CI) = 0.36–0.64; and P = 1.1 9 10 6, OR = 0.48, 95% confidence interval (CI) = 0.36–0.65, respectively). rs876039 was not validated in the Finnish validation
514
sample. rs876039 and another SNP in this region, rs4917014, are located ~36 and 41 kB, respectively, proximal of the IKZF1 gene. In a recent study on a Chinese Han population suffering from SLE, rs4917014 was associated with malar rash, that is classical facial skin lesions of patients with CLE (58). In a consecutive study, the mRNA expression levels of IKZF1 in PBMC from patients with SLE were significantly decreased compared with healthy controls (59). Thus, decreased expression of IKZF1 might be related to SLE and CLE pathogenesis. Interestingly, IKZF1 has also been described as a susceptibility gene (rs2366293) in a UK data set of 870 SLE cases and 5,551 controls (60). The IKZF1 gene encodes Ikaros, a DNA-binding zinc finger protein involved in chromatin remodelling (61). Ikzf1 knockout mice suffer from multiple hematopoietic cell defects and lymphoid cell defects (62). However, a lupus-like phenotype has not yet been observed. In a very recent study that combined high-throughput glycomics with GWAS data to analyse genetic associations of the plasma IgG N-glycome in more than 4000 individuals, IKZF1, IL6ST-ANKRD55 and ABCF2-SMARCD3 were newly identified to be implicated in IgG glycosylation patterns (63). Further analysis of IgG isolated from Ikzf1 heterozygous knockout mice showed that a number of alterations in the IgG N-glycome composition were consistent with a role of IKZF1 in downregulating fucosylation and upregulating and the addition of bisecting GlcNAc to IgG glycan. Thus, the IKZF1 gene appears to impact on IgG glycosylation, a major mechanism for IgG function and stability. The IRF5 SNP rs10954213 A allele showed a significant association with DLE and SCLE in one of the mentioned studies (24). Notably, a recent paper showed a direct interaction between IRF5 and IKZF1 in a mouse model (64). IRF5-regulated transcriptional expression of IgG2a/c was mediated by decreased Ikaros expression. The IRF site in Ikzf1 promoter binds IRF5, IRF4 and IRF8. Overall, the IRF5–Ikaros axis seems to be a critical modulator of IgG2a/c class switching. Due to class switching and variable region Ab hypermutation, previously naive B cells may become autoreactive (65, 66). Taken together, the present report identified a series of new genetic polymorphisms associated with CLE. For some of the closely linked genes such as HLA-DQA1, MICA/B and IKZF, association has also been described for SLE. CLE-linked genes like TRIM39/RPP21 interfere with apoptosis regulation and interferon response, which are known to play a role in CLE and may thereby help to explain the deregulated interferon and apoptosis response in CLE. CLE-associated MICA and IKZF genes also show association with skin involvement in SLE. Overall, these data suggest that different but also partly overlapping genes underlie CLE and SLE, emphasizing the notion of different diseases with partly overlapping clinical features. Follow-up analyses with genomewide association scans in larger sample sets and large-scale analyses of rarer variants may lead to identification of additional susceptibility loci.
Acknowledgements This work was funded by the Deutsche Forschungsgemeinschaft (DFG) Cluster of Excellence ‘Inflammation at Interfaces’ (grant EXC306 to WI, AF, SMI). Popgen received infrastructure support through the DFG Cluster of Excellence ‘Inflammation at Interfaces’ (grants EXC306 and EXC306/2) and was supported by the German Ministry of Education and Research (BMBF) through the e:Med sysINFLAME grant and the PopGen 2.0
ª 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd Experimental Dermatology, 2015, 24, 510–515
Cutaneous lupus susceptibility loci
network (01EY1103). The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript. We are grateful to Gerald Messer, Department of Dermatology, Ludwig Maximilian University, Munich, Germany, for helpful discussion and provision of lupus patient samples. Author contributions: MK, AR, JP, SK, TH, JK, ACR, JCS and SMI performed the research; MK, SMI, AR and
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IRK designed the research study; IRK, AS, JK, AZ, TZ and SB analysed the data; HG, MMN, WL, AF, ES, JW, TT, JL, RG, NP and AK contributed patient samples, clinical and serological information; and MK, IRK and SMI wrote the paper.
Conflict of interest All authors declare that there are no financial, personal or professional interests that could be construed to have influenced the paper.
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Supporting Information Additional supporting data may be found in the supplementary information of this article. Table S1. Summary and description of the samples after quality control. Table S2. Detailed description of all associations with P < 5 9 10 6 in the lupus GWAS and validation sample. Table S3. Genes omitted in region plots of Fig. 2.
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