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Keywords:

  • SLE;
  • lupus;
  • copy number variation;
  • HIN200

Summary

  1. Top of page
  2. Summary
  3. Introduction
  4. Subjects and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Author Contributions
  9. Funding
  10. Conflict of Interest
  11. References
  12. Supporting Information

We undertook a candidate locus study of the HIN200 gene cluster on 1q21-23 in UK systemic lupus erythematosus (SLE) families. To date, despite mounting evidence demonstrating the importance of these proteins in autoimmune disease, cancer, apoptosis, inflammation, and cell cycle arrest, there has been a dearth of data with respect to the genetic characterisation of the HIN200 locus in SLE or any other disease. We typed 83 single nucleotide polymorphisms (SNPs) across 317 kb of the HIN200 cluster in 428 UK SLE families and sought replication from a European-American lupus cohort. We do not find strong evidence of SNP association in either cohort. Interestingly, we do observe a trend for association with certain HIN200 SNPs and serologic subphenotypes in UK SLE that parallels the association of lupus antibodies with the orthologous murine locus. Furthermore, we find the HIN200 locus to be unexpectedly complex in terms of genetic structural organisation. We have identified a number of copy number variants (CNVs) in this region in healthy French males, HapMap samples, and UK SLE families. In summary, candidate interferon signalling genes show evidence of common CNV in human SLE and healthy subjects. The impact of these CNVs in health and disease remains to be determined.


Introduction

  1. Top of page
  2. Summary
  3. Introduction
  4. Subjects and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Author Contributions
  9. Funding
  10. Conflict of Interest
  11. References
  12. Supporting Information

Systemic lupus erythematosus (SLE/lupus [MIM 152700]) is a genetically complex, chronic, and clinically heterogeneous multi-system autoimmune disease primarily affecting women of childbearing age. The disease is characterised by the production of affinity-matured immunoglobulin G (IgG) autoantibodies to a wide spectrum of nuclear and cell surface antigens, complement activation, and upregulation of interferon (IFN)-associated pathways.

There is overwhelming evidence implicating the type 1 IFN pathway in the pathogenesis of SLE (Crow, 2005; Banchereau & Pascual, 2006). Early studies demonstrated elevated levels of IFN-α in lupus patient sera compared to controls (Hooks et al., 1979; Preble et al., 1982; Ytterberg & Schnitzer, 1982). Subsequently, it was observed that a minority of patients who received IFN-α therapy for a variety of indications including viral hepatitis developed autoantibodies, SLE, and other autoimmune diseases (Ronnblom et al., 1991; Gota & Calabrese, 2003). In addition, gene expression profiling studies demonstrate that the peripheral blood lymphocytes of most patients with lupus show upregulation of IFN-α responsive genes, the so-called “IFN signature.” Furthermore, it is now well established that polymorphisms in genes involved in the type I IFN pathway, such as TYK2 (tyrosine kinase 2) and IRF5 (IFN regulatory factor 5), are associated with human SLE (Sigurdsson et al., 2005; Graham et al., 2007).

The HIN200 (haematopoietic IFN-inducible nuclear proteins with 200 amino acid repeat) gene cluster on 1q21-23 spans 263 kb and comprises four genes encoded in tandem: myeloid cell nuclear differentiation antigen (MNDA), pyrin and HIN domain family, member 1/IFN-inducible protein X (PYHIN1/IFIX), IFN, gamma-inducible protein 16 (IFI16), and absent in melanoma 2 (AIM2) (Ludlow et al., 2005) (Fig. 1). The genes of the HIN200 cluster are grouped together as a family because they share a number of common features: chromosomal proximity, sequence homology, predominant nuclear localisation, and induction of expression by types I and II IFNs. Contrary to their nomenclature, their expression is not limited to haematopoietic cells (Ludlow et al., 2005).

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Figure 1. Location and genomic organisation of the HIN200 gene cluster. The figure illustrates the location and organization of the HIN200 gene cluster on chromosome 1q23. A giemsa stain of chromosome 1 in metaphase is shown at the top of the figure. The HIN200 cluster is expanded below and is shown to encompass approximately 263 kb of DNA comprising four genes in tandem: MNDA, PYHIN1, IFI16, and AIM2. The arrows indicate the direction of gene transcription. The genomic positions relate to NCBI Build 35.

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Several lines of evidence support a role for the HIN200 gene cluster in SLE. Human linkage studies have implicated the 1q23 region in SLE (Moser et al., 1998; Shai et al., 1999; Tsao et al., 2002). Recent studies have shown that AIM2 recognises cytosolic dsDNA and activates caspase-1 through the formation of a novel inflammasome (Hornung et al., 2009; Fernandes-Alnemri et al., 2009). Furthermore, AIM2 has shown differential methylation in monozygotic twins discordant for SLE, corresponding to increased gene expression in affected individuals (Javierre et al., 2010). Linkage studies in murine models of lupus demonstrate that genetic contributions arise from loci on distal chromosome 1 orthologous with human 1q21-23. This interval also contains other genes involved in the immune response, such as the FCGR locus (where copy number variation [CNV] has already been established in lupus susceptibility), the SLAM locus and the gene, CRP (Aitman et al., 2006). The Nba2 interval, located on distal chromosome 1 in NZB mice, is linked with murine lupus and encodes the Ifi200 genes, which are orthologous to the human HIN200 genes. This murine locus is linked with autoantibody production (Vyse et al., 1997; Vyse et al., 1998; Rozzo et al., 2001). Expression profiling of Nba2 congenic mouse splenocytes has demonstrated differential expression of Ifi200 genes compared to wild-type splenocytes thus confirming the human orthologs as candidates in SLE (Rozzo et al., 2001) (Rigby, RJ & Vyse, TJ, pers. comm.).

Given the data outlined above, we wanted to investigate the genetic contribution of the HIN200 gene cluster in human SLE by fine mapping the locus using a SNP-based study in UK SLE families.

Subjects and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Subjects and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Author Contributions
  9. Funding
  10. Conflict of Interest
  11. References
  12. Supporting Information

Study Cohorts

UK SLE families

Four hundred and twenty-eight complete UK SLE trios were studied from a collection that has been previously described (Russell et al., 2004). All study participants were of European ancestry on the basis of grandparental origin. All lupus probands (396 female and 32 male) fulfilled the revised American College of Rheumatology (ACR) criteria for SLE (Hochberg, 1997). Thirty-seven percent of probands had a diagnosis of lupus nephritis. Written consent was obtained from all study participants, and ethical approval for this study was obtained from the Multi-Centre Research Ethics Committee (MREC 2 June 1998).

European-American case–control cohort

The second lupus population under study comprised 1310 cases and 7857 controls (3607 male and 5560 female) (Hom et al., 2008). All cases fulfilled the 1997 revised ACR criteria for SLE (Hochberg, 1997). Written consent was obtained from all study participants, and ethical approval was obtained according to local guidelines.

Healthy French controls used in array comparative genomic hybridization (CGH) and sequencing experiments

DNA from 26 of 50 unrelated, healthy males of northern French origin was used for sequencing the regions around the SNPs, rs856089 and rs856142, from a cohort previously described by de Smith et al. (de Smith et al., 2007). These data were compared with array CGH data at the HIN200 locus in the same subjects in order to determine the relationship between genotype and putative copy number (assessed by log2 ratios between subject and reference array CGH data).

SNP Genotyping

UK SLE families

SNPs for this fine-mapping study were selected from dbSNP and HapMap based on the likely functional impact of the variant (exonic SNPs in preference to intronic SNPs for example), validation, minor allele frequency (MAF), and location (to ensure adequate coverage of the locus). Eighty-six SNPs were put forward for genotyping in our fine-mapping study (see Table S1). Of note, a number of the SNPs chosen for genotyping had not been well characterised previously, particularly as all exonic variants were put forward for genotyping irrespective of MAF. The SNPs encompassed 317 kb of the HIN200 locus from rs7550055 that lies 5′ of MNDA to rs2518569 that is 3′ of the cluster.

All SNPs were typed in 30 HapMap CEU (United States residents with northern and western European ancestry collected by the Centre d'Etude du Polymorphisme Humain) trios prior to typing in the UK SLE cohort in order to assess assay reliability. SNPs that failed Sequenom typing were redesigned and retyped on the same platform. All variants were typed in the entire cohort (n= 1284). SNP genotyping was performed at the Broad Institute of MIT and Harvard and at Imperial College London by matrix-assisted laser desorption/ionisation time-of-flight (MALDI-TOF) mass spectrometry using the Sequenom MassARRAY® platform as previously described (Jurinke et al., 2002).

European-American case–control cohort

There were 52 SNPs located within the HIN200 interval (155,550–155,950k, NCBI Build 34/May 2004) in this cohort. All the markers were typed on the Illumina 550k chip within the context of a genome-wide association study (Hom et al., 2008). The raw genotype data were analysed using PLINK (Table S2).

SNP Sequencing

The regions surrounding the two SNPs showing the greatest number of Mendelian errors in UK SLE families, rs856089 and rs856142, were polymerase chain reaction (PCR) amplified from genomic DNA and sequenced using BigDye® Terminator chemistry on an Applied Biosystems 3730xl DNA analyzer. The sequences of the amplification and nested sequencing primers and the specific PCR reaction conditions are provided in Supplementary Table S3.

PCR cycling conditions for rs856142 were as follows: initial denaturation step at 94°C for 3 min, followed by 33 amplification cycles (denature at 94°C for 30 s, anneal at 50°C for 30 s, extension at 72°C for 1 min), and a final elongation step at 72°C for 10 min. The PCR conditions for SNP rs856089 were the same as SNP rs856142 except that the annealing temperature was 52°C. Each 10 μl forward and reverse sequencing reaction contained 30–90 ng per 1 kb of PCR product with 3.2 pmol of the relevant primer.

Assessment of CNV at the HIN200 Locus

Array CGH in healthy French males

Evidence for CNV at the HIN200 locus was assessed by mining array CGH data from 50 unrelated, healthy males of northern French ancestry (de Smith et al., 2007). Specifically, the data derive from two genome-wide Agilent CGH arrays (Agilent Technologies, Santa Clara, CA, USA). The first array comprised 185,000 probes, spaced evenly across the genome, approximately every 16 kb, with a bias towards known genes. The second array was a higher density, custom-designed array that comprised 244,000 validated probes chosen to target 2475 putative CNVs from the first array and 2148 CNV loci that were listed in the October 2006 build of the TCAG database of genomic variants (http://projects.tcag.ca/variation/) (de Smith et al., 2007). Potential CNVs at the HIN200 locus were identified in two ways: firstly, putative deletions or duplications were determined at regions with a log2 fluorescence ratio between each test sample and the reference sample of ≤0.3 or >0.3, respectively (with an expected ratio of 0 for no copy number differences). Secondly, we used CGH Analytics 3.4 software to call aberrations, whereby regions of statistically significant variation in copy number were determined using the ADM-2 algorithm, with a threshold of 4 (Agilent Technologies, http://www.chem.agilent.com/Library/usermanuals/Public/CGH_3.4_QuickStart.pdf) (Agilent Technologies, Santa Clara, CA, USA). This algorithm determines CNV between test and reference samples based on log2 ratios of the fluorescent signal from probes in the interval, with consideration of log-ratio error information and incorporation of quality information about each probe measurement (for further details see de Smith et al., 2007).

High-density array CGH data from HapMap CEU and YRI individuals at the HIN200 locus

The CNV Discovery Project, undertaken by The Genome Structural Variation Consortium (http://www.sanger.ac.uk/humgen/cnv/42mio/), has used high-resolution array CGH to identify common CNVs, greater than 500 bp, in 20 female CEU HapMap samples and 20 female YRI HapMap samples against a common male reference sample. A total of 42 million probes from 21 2.1 million NimbleGen arrays were tiled across the genome in this experiment (approximately 1 probe per 50 bp) (Roche NimbleGen, Inc., Madison, WI, USA). The normalized intensity data for each probe, in the form of log2 ratios between sample and reference, from this project are freely available in 5 Mb region downloads (http://www.sanger.ac.uk/cgi-bin/humgen/cnv/42mio/downloadBigDB.cgi). In addition, there has been a recent provisional data release of “validated” copy number variants (CNVs) called from these normalized data (http://www.sanger.ac.uk/humgen/cnv/42mio/download42miocalls.html). The data made available are the chromosomal start and end coordinates of 8599 CNV events (CNVEs) using NCBI Build 36 positions. Each of these CNVEs has some level of independent validation, either by an independent platform or by overlap with other published datasets. These data were mined for evidence of CNVE in the HIN200 region using the coordinates: chromosome 1:156,950,000 to 157,400,000 of NCBI Build 36. A selected number of putative CNVs were then typed by array-CGH in 450 HapMap samples. These data are publicly available in the form of integer-value copy numbers indexed by CNV name and HapMap sample ID.

SNP-CNV Correlation

The cohort of 50 French male controls used for array CGH was also genotyped on the Illumina Human 1M BeadArray (Illumina, Inc., San Diego, CA, USA). The relationship between SNPs within 100 kb of each of the three putative CNVs at the HIN200 locus was investigated by assessing the correlation (expressed as r2), and also the statistical significance of this correlation, between the B allele frequency of Illumina SNPs and the log2 fluorescence ratio between sample and reference at the array CGH probes.

Data Analysis

UK SLE families and European-American SLE case–control cohort

Quality control statistics and analyses were performed using PLINK (Purcell et al., 2007). SNPs or samples were excluded from analysis using the following criteria: SNPs >10% missing genotype data, samples with >10% missing genotype data, SNPs with >9 Mendel errors (MEs), families with >10 ME, SNPs with MAF <1% (Table S1). SNPs demonstrating deviation from Hardy–Weinberg estimates obtained from founder chromosomes were excluded from further analysis (defined as HWE p < 10−3).

Eighty-three of 86 SNPs put forward for genotyping were assayed in UK SLE trios: three SNPs failed Mendelian inheritance checks in CEU trios. Of the remaining 83 variants, 18 failed QC thresholds: five were monomorphic, eight had MAF <1%, two SNPs failed Mendelian inheritance checks in UK SLE families, one deviated from HWE, and two SNPs failed tests for HWE and Mendelian inheritance. Thus, 65 SNPs were put forward for association analysis (Table S1). The mean call rate post-QC was 98.64%.

Family-based association analyses and case–control association tests were performed in PLINK using the transmission disequilibrium test (TDT) and χ2 test, respectively. The data are represented as nominal and permuted (10,000 permutations) p values together with odds ratios (ORs) with 95% confidence intervals (CIs). Haplotypes were generated using Haploview (Barrett et al., 2005).

SNP imputation in UK SLE families across the HIN200 locus

SNP imputation analysis was performed in the UK SLE family cohort and the European-American SLE case–control cohort in an attempt to capture as much genetic variation across the HIN200 gene cluster as possible. The family data were imputed using the software package, BEAGLE, with CEU HapMap data as reference (Browning & Browning, 2007, 2009). Specifically, BEAGLE 3.0 was used to impute missing genotype calls and un-typed genotypes over the range chromosome 1:155,567,886 to 155,886,798 (NCBI Build 35); that is from SNPs, rs857847 to rs2852723– the boundaries of typed SNPs in the datasets under study, located 5′ and 3′ of the HIN200 region. BEAGLE 3.0 uses a haplotype clustering algorithm and applies a Hidden Markov Model (HMM) approach to inferring missing genotypes. The methodology for inferring haplotype phase and sporadic missing data is described in (Browning & Browning, 2007) and that for imputing ungenotyped markers and phasing parent–offspring data are described in (Browning & Browning, 2009). In the UK SLE family cohort, there were 65 genotyped SNPs that passed QC thresholds that were used for imputation. There were 469 SNPs in the UK SLE family dataset post-imputation from 776 parental chromosomes (from 388 trios).

SNP imputation in European-American case–control SLE cohort across the HIN200 locus

SNP imputation in the European-American case–control SLE cohort across the HIN200 locus was performed using the software package, IMPUTE, with CEU HapMap data as reference (Marchini et al., 2007). IMPUTE is a program for imputing unobserved genotypes in case–control studies based on a set of known haplotypes (such as the HapMap Phase II haplotypes). The range of imputation was identical to that used for the family data described above. 52 SNPs were genotyped and used for imputation in this cohort. There were 347 SNPs in the dataset post-imputation.

Subphenotype Analysis in UK SLE Families

Given the association of the murine Ifi200 genes with autoantibody production, subphenotype analyses were conducted in the UK SLE probands for anti-dsDNA antibodies, anti-Ro, anti-La, anti-Sm, anti-RNP, and IgG and IgM anticardiolipin antibodies. The probands were also stratified for presence or absence of renal disease – a marker of disease severity. All analyses were performed using the χ2 test in PLINK.

Results

  1. Top of page
  2. Summary
  3. Introduction
  4. Subjects and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Author Contributions
  9. Funding
  10. Conflict of Interest
  11. References
  12. Supporting Information

Non-Mendelian Inheritance at the HIN200 Locus in UK SLE Families

Figure 2 is a diagrammatic representation of the SNPs typed across the HIN200 locus in UK SLE trios. There is a clearly defined cluster of SNPs demonstrating non-Mendelian inheritance from the 3′ region of PYHIN1 to the intergenic region between PYHIN1 and IFI16 in the UK SLE dataset as well as a further cluster of SNPs observed in CEU trios around the MNDA gene (also see Table S1). The latter group of SNPs was specifically excluded from genotyping in the UK SLE cohort due to assay failure in CEU trios. Previous work from our group, investigating the role of the FCGR locus in lupus susceptibility, demonstrated that clusters of MEs in families can be indicative of copy variable repeat sequences (Aitman et al., 2006). Because of ME clustering in a region of paralogous genes, we were keen to further investigate the possibility of CNV at this locus.

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Figure 2. Eighty-six SNPs typed across the HIN200 locus in UK SLE families. This is a scaled figure illustrating the location of the SNPs typed across the HIN200 locus in UK SLE families. The positions of the genes are shown at the top of the figure and the locations of the SNPs are shown below. The arrows identify SNPs that deviated from Mendelian inheritance in CEU trios (black arrows) and UK SLE trios (orange arrows). The dotted orange arrow represents a SNP that significantly deviated from Hardy–Weinberg equilibrium in the UK SLE cohort (also see Table S1).

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SNP Sequencing in UK SLE Families Demonstrating Non-Mendelian Inheritance

Non-Mendelian inheritance states can arise in family-based genetic association studies as a result of ex-paternity, genotyping error, or CNV. The former can be excluded on the basis of other SNPs outside this locus in UK SLE families. We sought to determine the cause of the non-Mendelian clustering of SNPs in this study by sequencing the region surrounding the two SNPs showing the greatest number of MEs: rs856089 in PYHIN1, and rs856142, located in the interval between PYHIN1 and IFI16. Specifically, sequencing for rs856089 and rs856142 was performed in UK SLE trios demonstrating non-Mendelian inheritance at these SNPs to determine the accuracy of the initial Sequenom genotyping.

The genotyping discrepancies in UK SLE families showing non-Mendelian inheritance were resolved by resequencing, thereby excluding ex-paternity issues and implicating either genotyping error or possible CNV as the likely cause of the observed phenomenon (Table 1).

Table 1.  Sequencing results for the regions flanking SNPs, rs856089, and rs856142 in representative UK SLE trios. Thumbnail image of

Identification of Additional Variants in Regions of Putative CNV

The sequencing experiments demonstrated that the flanking regions of the SNPs, rs856089 and rs856142, contained further polymorphisms that were previously unknown (Fig. S1). Specifically, SNPs were identified in each of the Sequenom primers for rs856089 (−29A/G and +60C/T from rs856089) and at position +43C/T. There was a SNP in one of the Sequenom primers for rs856142 (at −31A/G) and an additional SNP observed at −223C/T. These novel polymorphisms could represent paralogous sequence variants (PSVs) within a copy variable repeat or simple SNPs in a non-copy variable sequence. Regardless of cause, some of these polymorphisms likely result in differential probe binding with consequent genotyping error.

Array CGH Identifies Putative CNV at the HIN200 Locus in a Healthy French Cohort

To investigate possible CNV at the HIN200 locus, we mined array CGH data from a cohort of 50 healthy French males (see Subjects and Methods). Interrogation of these data did indeed demonstrate evidence of CNV at the HIN200 locus (Fig. 3). We identified three potential CNV regions: the first is upstream of MNDA (L1), the second is in the PYHIN1-IFI16 intergenic region (L2), and the third is within the IFI16 gene itself (L3). All three regions showed possible CNV by evaluation of signal ratios, but only L3 was actually called as a statistically significant aberration by the ADM2 algorithm in CGH Analytics. The frequency of putative insertion or deletion at each locus in this healthy cohort is 54% (21/50 putative deletion, 6/50 putative insertion), 18% (2/50 putative deletion, 7/50 putative insertion), and 48% (5/50 putative deletion, 19/50 putative insertion) for L1, L2, and L3, respectively.

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Figure 3. Array-CGH plots of the HIN200 locus from 50 healthy French males. Panel A represents array-CGH data across the entire HIN200 locus to scale. The locations of the genes are shown as grey bars below the probe data. Each column of dots represents the location of a probe. Each dot represents single probe data from a single individual. The black dots represent individuals that do not show evidence of copy number variation at the probe of interest. Red dots represent individuals with evidence of an insertion (log2 ratio >0.3), and green dots represent individuals with evidence of a deletion (log2 ratio ≤0.3) at the specific probe. These data suggest that there are three putative CNVs within the HIN200 locus, L1 (position: 155609139), L2 (position: 155782977), and L3 (position: 155814642). Each putative CNV region is expanded in panels B, C, and D, respectively.

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Comparison of SNP Sequencing with Putative CNV in Healthy French Males

In order to assess the association between the above CNVs and SNPs showing non-Mendelian inheritance in UK SLE families, we sequenced the regions surrounding rs856089 and rs856142 in 26 of the 50 healthy French males where array CGH data were available.

Table 2 summarizes the results comparing putative CNVs at L2 and L3 with SNP sequencing for rs856089 and rs856142 in healthy French males. Essentially, heterozygosity for the novel polymorphisms flanking rs856142 and rs856089 appears to be a marker of both putative CNVs, suggesting that they are indeed PSVs.

Table 2.  Sequencing results for the regions flanking SNPs, rs856089, and rs856142 in 26 healthy French males. Thumbnail image of

High-density Array CGH Identifies Multiple CNVs at the HIN200 Locus in HapMap Individuals

Preliminary data released by the CNV Discovery Project (CNVDP) demonstrates six so-called CNVEs in and around the HIN200 region in the HapMap population (Table 3). The initial data are derived from normalized genome-wide, high-density array CGH (NimbleGen) probe ratios from 20 HapMap CEU and 20 HapMap YRI females against a common male reference. Further “genotyping” of selected CNVs was performed in 450 HapMap samples by array CGH. Integer-value copy numbers are indexed by CNV name and sample ID. Two of the six CNVEs appear to overlap with two of the three CNVs identified by the initial Agilent array CGH performed in healthy French males. The remaining four of the six CNVEs was not represented by probes on the Agilent array and so could not be identified even if present in the latter cohort. The PYHIN1-IFI16 intergenic CNV (L2) corresponds to CNVR377.1 and the IFI16 CNV (L3) corresponds to CNVR378.1. The two CNVEs (CNVR374.1 and CNVR375.1) located 5′ of the HIN200 cluster near the gene, OR6K6, seem to be distinct from the CNV upstream of MNDA (L1). Five of the six CNVEs are annotated in the Database of Genomic Variants; the exception being the AIM2-CADM3 intergenic CNVE (http://projects.tcag.ca/variation/). Five of the six CNVEs were selected for study in 450 HapMap samples comprising 180 CEU samples, 180 YRI samples (from the Yoruba people of Ibadan, Nigeria), and 90 CHB (Han Chinese individuals from Beijing, China) and JPT (individuals from Tokyo, Japan) samples. The data are summarized in Supplementary Table S4. CNV across the HIN200 locus is similar in the CEU and YRI populations, while the CHB and JPT populations show much less variability. The impact of such differences on gene expression is not known.

Table 3.  Comparison of copy number variation events (CNVEs) identified by The Copy Number Variation Discovery Project and putative CNVs identified by an Agilent CGH array across the HIN200 region. Thumbnail image of

There are two putative CNVs common to both the initial Agilent array-CGH performed in healthy French males and the CNVDP data from HapMap samples: L2/CNVR377.1 (intergenic PYHIN1 and IFI16) and L3/CNVR378.1 (IFI16). The frequency with which each CNV occurs is different when comparing French Agilent data and CEU CNVDP data. For example, 18% of the French cohort harboured a putative insertion or deletion for L2/CNVR377.1, while a greater proportion (32%) exhibited putative deletions only in CEU. Conversely, the frequency of insertions or deletions was less in CEU (18%) compared to the French cohort (48%) at the L3/CNVR378.1 locus. The differences observed between the Agilent and NimbleGen array CGH data may reflect differences in cohort size (50 French males and 180 CEU) or population and hence frequency variation in CNVs as well as technological issues such as probe density and calling algorithms.

SNP Association at the HIN200 Locus in UK and US SLE Cohorts

Quality control analyses of the SNP genotyping data across the HIN200 gene cluster in UK SLE trios identified possible CNV in this region. Having investigated the region for evidence of CNV (described above), we sought to further characterize the genetic contribution of the HIN200 gene cluster in human SLE using family-based SNP association analyses. Eighty-three SNPs were selected and typed in 428 UK SLE families. Sixty-five SNPs passed QC thresholds and were put forward for TDT analysis in 425 UK SLE trios. The results of the single marker analysis are summarized in Table 4. Essentially, only one SNP, rs11590937, located within intron 8 of PYHIN1 showed evidence of significant association with UK SLE (nominal p= 0.00012, permuted p= 0.0045, OR = 0.51, CI 0.35–0.72). Haplotypic analyses did not demonstrate evidence of significant association.

Table 4.  Single marker association analysis for 65 SNPs in 425 UK SLE trios in the context of known copy number variation across the HIN200 locus. Thumbnail image of

Next, we used a distinct case–control European-American lupus cohort, to further evaluate SNP association at the HIN200 locus in SLE. There were 52 SNPs located within the HIN200 interval that passed QC thresholds in this dataset (chromosome 1 position: 155,500,000 to 155,950,000, NCBI Build 35). All the SNPs were typed on the Illumina 550k chip within the context of a genome-wide association study (Hom et al., 2008). The post-QC genotype data were tested for evidence of allelic and haplotypic association with SLE using PLINK and Haploview, respectively. These results are summarized in Supplementary Table S2 and Figure 4 and show no evidence of significant association with SLE in this cohort. In particular, the associated variant in UK SLE families, rs11590937, was directly typed in the dataset and was not found to be associated with SLE. Hence, there is no evidence of SNP association in either UK or US cohort, apart from SNP, rs11590937, in the UK SLE cohort that is likely a false positive due to genotyping error in a region of CNV.

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Figure 4. SNP association at the HIN200 locus in two independent SLE cohorts. This figure shows the SNP association results for UK SLE trios (green triangles) and the European-American SLE case–control cohort (red circles). The approximate locations of the HIN200 genes are shown below (blue boxes); the grey boxes represent pseudogenes. There is no evidence of SNP association in either cohort, apart from SNP, rs11590937, in the UK SLE cohort that is likely a false positive due to genotyping error in a region of CNV.

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Subphenotype Analysis

In view of the linkage demonstrated between the murine Nba2 locus and lupus autoantibodies, we undertook a subphenotype analysis of this region in the UK SLE family cohort. The results of the HIN200 subphenotype analysis are summarized in Supplementary Table S5. The SNPs, rs856077 and rs4657618, in the region between PYHIN1 and IFI16, show a trend for association with IgG anticardiolipin antibodies (nominal p= 0.006 and 0.005, respectively, permuted p= NS), although no significant association was observed for any SNPs and IgM anticardiolipin antibodies. The intronic PYHIN1 SNPs, rs2820187 and rs861319, also show a trend for association with anti-RNP antibodies (p= 0.01 and 0.001, respectively, permuted p= NS). As anti-RNP antibodies are only present in 15% of the present dataset, a larger cohort is required to fully assess the nature of this suggestive association. Furthermore, we found that SNPs in and around the MNDA gene were associated with anti-dsDNA and anti-Sm antibodies. The SNP showing the greatest association with antibodies to dsDNA is rs2261107 (nominal p= 0.002), while anti-Sm antibodies are most correlated to rs857868 (nominal p= 0.006). No significant SNP associations were found with renal, anti-Ro, or anti-La subsets. There were no significant haplotypic associations with UK lupus subphenotypes. These data should be interpreted with caution given that most of the SNPs showing association with autoantibody subphenotypes are located in regions of putative CNV (see following section). Subphenotype analysis for ribonuclear proteins as a whole did not show evidence of association in the US cohort.

SNP-CNV Correlation

Next, we wanted to assess whether there was a correlation between flanking SNPs and the putative CNVs at the HIN200 locus in the healthy French cohort. There is no evidence of significant single marker or haplotypic association with SNPs at this locus in the two lupus cohorts under study. However, association due to CNV that is not tagged by SNPs cannot be excluded. The SNP-CNV analyses show that the putative CNV upstream of MNDA (L1) was weakly correlated with SNP rs857791 (r2= 0.33, p= 0.0167). This SNP was not typed directly in the UK SLE trios; however, examination of HapMap CEU data revealed that two other SNPs, which have been typed in the lupus families, rs857868 and rs2820184 were in moderate LD with rs857791 (r2= 0.745 and 0.717, respectively). These SNPs displayed weak evidence of overall disease association (nominal p= 0.02 and 0.01 for rs857868 and rs2820184, respectively, permuted p= not significant [NS] for either SNP), but stronger association with anti-Sm antibody subsets (nominal p= 0.006 and 0.008, permuted p= NS) and also antibodies to dsDNA (nominal p= 0.003 and 0.01, permuted p= NS) (Table 4). The SNP, rs857791, was directly typed in the replication dataset and showed no evidence of disease association (Table S2).

Interestingly, the putative PYHIN1-IFI16 CNV (L2) did not show correlation with any flanking SNPs in the healthy French cohort. Hence, the role of this novel CNV in lupus susceptibility remains to be determined. The third potential CNV (L3), located within IFI16, demonstrated strong association with surrounding SNPs, the best being SNP, rs856055 (r2= 0.78, p= 2.22 × 10−16). Again, this SNP was not specifically typed in UK SLE trios. However, there were a number of surrogate markers for this SNP in HapMap CEU samples. Three such markers, rs1057024, rs11265133, rs1057027, all with an r2 equal to 1 with rs856055, had been typed in UK SLE families. None of these SNPs showed evidence of association with SLE, nor any of the subphenotypes examined in this study. None of the four tag SNPs for rs856055 were typed in the replication dataset.

SNP Imputation and Association Analysis at the HIN200 Locus in UK SLE Family Data and European-American SLE Case–control Data Reveals No Evidence of Significant Association in Regions Outside Those of Putative CNV

In an attempt to capture as much genetic information at the HIN200 locus as possible, the genotype data from the UK SLE family cohort and the European-American SLE case–control cohort were separately imputed to HapMap with a view to combining the data to perform a meta-analysis. To ensure that the two datasets were comparable, we calculated the genomic inflation factor, λGC, between untransmitted UK parental chromosomes and US control data using PLINK. This analysis showed significant inflation (λGC 3.62) indicating significant differences between the two control datasets (λGC should be approximately 1.0 if there are no significant differences between two distinct datasets). Further examination of the data revealed that 78 of the total 244 SNPs (32%) showed significant differences in allele frequency between the two control datasets (p < 0.05). Fifty-five of the 78 SNPs were wholly imputed, whereas 23 of the 78 SNPs had been genotyped in at least one of the cohorts. Moreover, the majority of the 78 SNPs contributing to the inflated λGC were in regions of putative CNV or in LD with these regions. The λGC remained inflated but improved to 1.92 following exclusion of the aforementioned 78 SNPs from the analysis. It is possible that the inflated λGC post removal of the 78 “failing” SNPs may be caused by errors in SNP imputation in the remaining dataset consequent upon spurious genotyping at the “failing” SNPs.

Single marker analysis of these two imputed datasets did not reveal any convincing evidence of SNP association at the HIN200 locus in regions outside those of putative CNV (data not shown). Inconsistent genotyping within and between the two cohorts likely due to CNV suggests that genetic association in the regions of putative CNV at the HIN200 locus cannot be accurately assessed by means of SNP association, imputation, or combined analysis at the present time.

Discussion

  1. Top of page
  2. Summary
  3. Introduction
  4. Subjects and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Author Contributions
  9. Funding
  10. Conflict of Interest
  11. References
  12. Supporting Information

Given the persuasive murine data implicating the Ifi200 genes in lupus susceptibility and the central role of the type 1 IFN pathway in human lupus, we undertook a candidate locus study of the HIN200 family of genes located on chromosome 1 in UK SLE families. To date, despite mounting evidence demonstrating the importance of these proteins in autoimmune disease, cancer, apoptosis, inflammation, and cell cycle arrest, there has been a dearth of data with respect to the genetic characterization of the HIN200 locus in SLE or any other disease in humans (Choubey & Panchanathan, 2008; Ludlow et al., 2008; Burckstummer et al., 2009; Fernandes-Alnemri et al., 2009; Hornung et al., 2009; Roberts et al., 2009).

Our fine-mapping study of the HIN200 locus in UK SLE families has shown the region to be unexpectedly complex in terms of genetic structural organisation. Specifically, we have presented data to support the existence of a number of CNVs in this region. The impact of such genetic variability in health and disease remains to be fully elucidated. It appears that one of the putative CNVs, in the gene, IFI16, (L3) is efficiently tagged by a number of SNPs and is not associated with lupus or any disease subphenotype tested in this study. It is likely, therefore, that this CNV is inherited on a stable genetic background that is not prone to recombination or mutation. However, the functional consequences and specific breakpoints of this CNV, as well as those for the other variants, await further investigation. The PYHIN1-IFI16 CNV (L2) shows poor SNP-CNV correlation in the French control cohort and also appears to be present in the CNVDP data. Moreover, a CNV between PYHIN1 and IFI16 is also present on the TCAG database of genomic variants, where it has been detected in three studies (http://projects.tcag.ca/variation/). Interestingly, a SNP in this region, rs11590737, demonstrated the only statistically significant association at the HIN200 locus in UK SLE families. It appears that this was a false positive result and may have occurred due to spurious genotyping as a result of the CNV, given the lack of replication in a case–control lupus cohort of European-American origin. The CNV upstream of MNDA (L1) shows poor correlation with flanking SNPs and therefore should be investigated further, particularly as these SNPs show a trend for association with SLE per se, and anti-Sm and anti-dsDNA autoantibody subsets, although these results did not withstand permutation testing. These results are particularly interesting in view of the linkage shown between the orthologous murine locus, Nba2, with nearly all lupus autoantibodies studied thus far, such as IgG antibodies to chromatin, DNA, histones, and gp70 (Vyse et al., 1997, 1997). Furthermore, there is a deletion between MNDA and PYHIN1 on the TCAG database that is approximately 2.4 kb in size and found in three separate studies that correspond to CNVR376.1 in the CNVDP, and a cluster of SNPs showing non-Mendelian inheritance in CEU in our UK family study indicating that this CNV is likely to be true.

Interestingly, all but one of the five CNVs characterised in HapMap populations as part of the CNVDP are either not present or occur at much lower frequency in CHB and JPT populations in comparison to CEU and YRI (Table S4). Furthermore, two recent genome-wide association scans in lupus populations of Chinese ancestry have not shown significant association with SNPs in the HIN200 region (Han et al., 2009; Yang et al., 2010).

Current estimates suggest that approximately half of all CNVs may be tagged by SNPs (Redon et al., 2006), and common CNVs (>5%) can be effectively tagged by SNPs of similar frequency (McCarroll, 2008). This means that alternative methods must be used to interrogate the genome to assess the remaining CNVs. Future genetic studies will therefore need to incorporate strategies that allow assessment of SNP variation as well as CNV. Initial data from the International Haplotype Project have shown that two randomly chosen genomes differed by 0.1% with regard to SNP diversity (The International HapMap Consortium, 2003). The impact of CNV on genomic variation has revised this figure upwards such that a substantial proportion is now thought to derive from CNV (Conrad et al., 2010).

In summary, candidate IFN signalling genes initially demonstrated in murine lupus show evidence of common CNV in human SLE and healthy subjects, as well as possible serologic subphenotype association in human SLE. The impact of these CNVs on gene expression in health and disease remains to be determined. Further study of this locus may well enhance the understanding of the mechanisms that underpin genetic susceptibility in lupus and other diseases, particularly in relation to the type 1 IFN pathway, as well as providing diagnostic and prognostic information.

Author Contributions

  1. Top of page
  2. Summary
  3. Introduction
  4. Subjects and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Author Contributions
  9. Funding
  10. Conflict of Interest
  11. References
  12. Supporting Information

TJV conceived the study design. SNP genotyping was performed by MMAF and at the Broad Institute Centre for Genotyping and Analysis. MMAF performed the sequencing experiments. PF and AB provided and AdeS analysed aCGH data in healthy French controls. LC performed the SNP-CNV correlation analyses. DLM imputed family data. PF provided DNA from healthy French controls for sequencing. RR and TWB provided the European-American SLE case–control data and contributed to subphenotype analysis. MMAF and TJV analysed the data with assistance from JM, AdeS, and LC. MMAF and TJV wrote the manuscript with contributions from AdeS, LC and AB.

Funding

  1. Top of page
  2. Summary
  3. Introduction
  4. Subjects and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Author Contributions
  9. Funding
  10. Conflict of Interest
  11. References
  12. Supporting Information

TJV was funded through a Wellcome Trust Senior Fellowship and MMAF was funded through a Clinical Research Fellowship from Arthritis Research UK. The Broad Institute Centre for Genotyping and Analysis is supported by Grant U54 RR020278 from the National Centre for Research Resources. This study makes use of data generated by the Genome Structural Variation Consortium (PIs Nigel Carter, Matthew Hurles, Charles Lee and Stephen Scherer) whom we thank for pre-publication access to their CNV discovery and genotyping data, made available through the websites http://www.sanger.ac.uk/humgen/cnv/42mio/ and http://projects.tcag.ca/variation/ as a resource to the community. Funding for the project was provided by the Wellcome Trust [Grant No. 077006/Z/05/Z], Canada Foundation of Innovation and Ontario Innovation Trust, Canadian Institutes of Health Research, Genome Canada/Ontario Genomics Institute, the McLaughlin Centre for Molecular Medicine, Ontario Ministry of Research and Innovation, the Hospital for Sick Children Foundation, the Department of Pathology at Brigham and Women's Hospital and the National Institutes of Health grants HG004221 and GM081533.

References

  1. Top of page
  2. Summary
  3. Introduction
  4. Subjects and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Author Contributions
  9. Funding
  10. Conflict of Interest
  11. References
  12. Supporting Information
  • Aitman, T. J., Dong, R., Vyse, T. J., Norsworthy, P. J., Johnson, M. D., Smith, J., Mangion, J., Roberton-Lowe, C., Marshall, A. J., Petretto, E., Hodges, M. D., Bhangal, G., Patel, S. G., Sheehan-Rooney, K., Duda, M., Cook, P. R., Evans, D. J., Domin, J., Flint, J., Boyle, J. J., Pusey, C. D. & Cook, H. T. (2006) Copy number polymorphism in Fcgr3 predisposes to glomerulonephritis in rats and humans. Nature 439, 851855.
  • Banchereau, J. & Pascual, V. (2006) Type I interferon in systemic lupus erythematosus and other autoimmune diseases. Immunity 25, 383392.
  • Barrett, J. C., Fry, B., Maller, J. & Daly, M. J. (2005) Haploview: Analysis and visualization of LD and haplotype maps. Bioinformatics 21, 263265.
  • Browning, B. L. & Browning, S. R. (2009) A unified approach to genotype imputation and haplotype-phase inference for large data sets of trios and unrelated individuals. Am J Hum Genet 84, 210223.
  • Browning, S. R. & Browning, B. L. (2007) Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Hum Genet 81, 10841097.
  • Burckstummer, T., Baumann, C., Bluml, S., Dixit, E., Durnberger, G., Jahn, H., Planyavsky, M., Bilban, M., Colinge, J., Bennett, K. L. & Superti-Furga, G. (2009) An orthogonal proteomic-genomic screen identifies AIM2 as a cytoplasmic DNA sensor for the inflammasome. Nat Immunol 10, 266272.
  • Choubey, D. & Panchanathan, R. (2008) Interferon-inducible Ifi200-family genes in systemic lupus erythematosus. Immunol Lett 119, 3241.
  • Conrad, D. F., Pinto, D., Redon, R., Feuk, L., Gokcumen, O., Zhang, Y., Aerts, J., Andrews, T. D., Barnes, C., Campbell, P., Fitzgerald, T., Hu, M., Ihm, C. H., Kristiansson, K., Macarthur, D. G., Macdonald, J. R., Onyiah, I., Pang, A. W., Robson, S., Stirrups, K., Valsesia, A., Walter, K., Wei, J., Tyler-Smith, C., Carter, N. P., Lee, C., Scherer, S. W. & Hurles, M. E. (2010) Origins and functional impact of copy number variation in the human genome. Nature 464, 704712.
  • Crow, M. K. (2005) Interferon pathway activation in systemic lupus erythematosus. Curr Rheumatol Rep 7, 463468.
  • De Smith, A. J., Tsalenko, A., Sampas, N., Scheffer, A., Yamada, N. A., Tsang, P., Ben-Dor, A., Yakhini, Z., Ellis, R. J., Bruhn, L., Laderman, S., Froguel, P. & Blakemore, A. I. (2007) Array CGH analysis of copy number variation identifies 1284 new genes variant in healthy white males: Implications for association studies of complex diseases. Hum Mol Genet 16, 27832794.
  • Fernandes-Alnemri, T., Yu, J. W., Datta, P., Wu, J. & Alnemri, E. S. (2009) AIM2 activates the inflammasome and cell death in response to cytoplasmic DNA. Nature 458, 509513.
  • Gota, C. & Calabrese, L. (2003) Induction of clinical autoimmune disease by therapeutic interferon-alpha. Autoimmunity 36, 511518.
  • Graham, R. R., Kyogoku, C., Sigurdsson, S., Vlasova, I. A., Davies, L. R., Baechler, E. C., Plenge, R. M., Koeuth, T., Ortmann, W. A., Hom, G., Bauer, J. W., Gillett, C., Burtt, N., Cunninghame Graham, D. S., Onofrio, R., Petri, M., Gunnarsson, I., Svenungsson, E., Ronnblom, L., Nordmark, G., Gregersen, P. K., Moser, K., Gaffney, P. M., Criswell, L. A., Vyse, T. J., Syvanen, A. C., Bohjanen, P. R., Daly, M. J., Behrens, T. W. & Altshuler, D. (2007) Three functional variants of IFN regulatory factor 5 (IRF5) define risk and protective haplotypes for human lupus. Proc Natl Acad Sci USA 104, 67586763.
  • Han, J. W., Zheng, H. F., Cui, Y., Sun, L. D., Ye, D. Q., Hu, Z., Xu, J. H., Cai, Z. M., Huang, W., Zhao, G. P., Xie, H. F., Fang, H., Lu, Q. J., Li, X. P., Pan, Y. F., Deng, D. Q., Zeng, F. Q., Ye, Z. Z., Zhang, X. Y., Wang, Q. W., Hao, F., Ma, L., Zuo, X. B., Zhou, F. S., Du, W. H., Cheng, Y. L., Yang, J. Q., Shen, S. K., Li, J., Sheng, Y. J., Zuo, X. X., Zhu, W. F., Gao, F., Zhang, P. L., Guo, Q., Li, B., Gao, M., Xiao, F. L., Quan, C., Zhang, C., Zhang, Z., Zhu, K. J., Li, Y., Hu, D. Y., Lu, W. S., Huang, J. L., Liu, S. X., Li, H., Ren, Y. Q., Wang, Z. X., Yang, C. J., Wang, P. G., Zhou, W. M., Lv, Y. M., Zhang, A. P., Zhang, S. Q., Lin, D., Low, H. Q., Shen, M., Zhai, Z. F., Wang, Y., Zhang, F. Y., Yang, S., Liu, J. J. & Zhang, X. J. (2009) Genome-wide association study in a Chinese Han population identifies nine new susceptibility loci for systemic lupus erythematosus. Nat Genet 41, 12341237.
  • Hochberg, M. C. (1997) Updating the American College of Rheumatology revised criteria for the classification of systemic lupus erythematosus. Arthritis Rheum 40, 1725.
  • Hom, G., Graham, R. R., Modrek, B., Taylor, K. E., Ortmann, W., Garnier, S., Lee, A. T., Chung, S. A., Ferreira, R. C., Pant, P. V., Ballinger, D. G., Kosoy, R., Demirci, F. Y., Kamboh, M. I., Kao, A. H., Tian, C., Gunnarsson, I., Bengtsson, A. A., Rantapaa-Dahlqvist, S., Petri, M., Manzi, S., Seldin, M. F., Ronnblom, L., Syvanen, A. C., Criswell, L. A., Gregersen, P. K. & Behrens, T. W. (2008) Association of systemic lupus erythematosus with C8orf13-BLK and ITGAM-ITGAX. N Engl J Med 358, 900909.
  • Hooks, J. J., Moutsopoulos, H. M., Geis, S. A., Stahl, N. I., Decker, J. L. & Notkins, A. L. (1979) Immune interferon in the circulation of patients with autoimmune disease. N Engl J Med 301, 58.
  • Hornung, V., Ablasser, A., Charrel-Dennis, M., Bauernfeind, F., Horvath, G., Caffrey, D. R., Latz, E. & Fitzgerald, K. A. (2009) AIM2 recognizes cytosolic dsDNA and forms a caspase-1-activating inflammasome with ASC. Nature 458, 514518.
  • Javierre, B. M., Fernandez, A. F., Richter, J., Al-Shahrour, F. Martin-Subero, J. I., Rodriguez-Ubreva, J., Berdasco, M., Fraga, M. F., O’hanlon, T. P., Rider, L. G., Jacinto, F. V., Lopez-Longo, F. J., Dopazo, J., Forn, M., Peinado, M. A., Carreno, L., Sawalha, A. H., Harley, J. B., Siebert, R., Esteller, M., Miller, F. W. & Ballestar, E. (2010) Changes in the pattern of DNA methylation associate with twin discordance in systemic lupus erythematosus. Genome Res 20, 170179.
  • Jurinke, C., Van Den Boom, D., Cantor, C. R. & Koster, H. (2002) The use of MassARRAY technology for high throughput genotyping. Adv Biochem Eng Biotechnol 77, 5774.
  • Ludlow, L. E., Hii, L. L., Thorpe, J., Newbold, A., Tainton, K. M., Trapani, J. A., Clarke, C. J. & Johnstone, R. W. (2008) Cloning and characterisation of Ifi206: A new murine HIN-200 family member. J Cell Biochem 103, 12701282.
  • Ludlow, L. E., Johnstone, R. W. & Clarke, C. J. (2005) The HIN-200 family: More than interferon-inducible genes? Exp Cell Res 308, 117.
  • Marchini, J., Howie, B., Myers, S., Mcvean, G. & Donnelly, P. (2007) A new multipoint method for genome-wide association studies by imputation of genotypes. Nat Genet 39, 906913.
  • McCarroll, S. A. (2008) Extending genome-wide association studies to copy-number variation. Hum Mol Genet 17, R135142.
  • Moser, K. L., Neas, B. R., Salmon, J. E., Yu, H., Gray-Mcguire, C., Asundi, N., Bruner, G. R., Fox, J., Kelly, J., Henshall, S., Bacino, D., Dietz, M., Hogue, R., Koelsch, G., Nightingale, L., Shaver, T., Abdou, N. I., Albert, D. A., Carson, C., Petri, M., Treadwell, E. L., James, J. A. & Harley, J. B. (1998) Genome scan of human systemic lupus erythematosus: evidence for linkage on chromosome 1q in African-American pedigrees. Proc Natl Acad Sci U S A 95, 1486914874.
  • Preble, O. T., Black, R. J., Friedman, R. M., Klippel, J. H. & Vilcek, J. (1982) Systemic lupus erythematosus: presence in human serum of an unusual acid-labile leukocyte interferon. Science 216, 429431.
  • Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A., Bender, D., Maller, J., Sklar, P., De Bakker, P. I., Daly, M. J. & Sham, P. C. (2007) PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet 81, 559575.
  • Redon, R., Ishikawa, S., Fitch, K. R., Feuk, L., Perry, G. H., Andrews, T. D., Fiegler, H., Shapero, M. H., Carson, A. R., Chen, W., Cho, E. K., Dallaire, S., Freeman, J. L., Gonzalez, J. R., Gratacos, M., Huang, J., Kalaitzopoulos, D., Komura, D., Macdonald, J. R., Marshall, C. R., Mei, R., Montgomery, L., Nishimura, K., Okamura, K., Shen, F., Somerville, M. J., Tchinda, J., Valsesia, A., Woodwark, C., Yang, F., Zhang, J., Zerjal, T., Zhang, J., Armengol, L., Conrad, D. F., Estivill, X., Tyler-Smith, C., Carter, N. P., Aburatani, H., Lee, C., Jones, K. W., Scherer, S. W. & Hurles, M. E. (2006) Global variation in copy number in the human genome. Nature 444, 444454.
  • Roberts, T. L., Idris, A., Dunn, J. A., Kelly, G. M., Burnton, C. M., Hodgson, S., Hardy, L. L., Garceau, V., Sweet, M. J., Ross, I. L., Hume, D. A. & Stacey, K. J. (2009) HIN-200 proteins regulate caspase activation in response to foreign cytoplasmic DNA. Science 323, 10571060.
  • Ronnblom, L. E., Alm, G. V. & Oberg, K. E. (1991) Autoimmunity after alpha-interferon therapy for malignant carcinoid tumors. Ann Intern Med 115, 178183.
  • Rozzo, S. J., Allard, J. D., Choubey, D., Vyse, T. J., Izui, S., Peltz, G. & Kotzin, B. L. (2001) Evidence for an interferon-inducible gene, Ifi202, in the susceptibility to systemic lupus. Immunity 15, 435443.
  • Russell, A. I., Cunninghame Graham, D. S., Shepherd, C., Roberton, C. A., Whittaker, J., Meeks, J., Powell, R. J., Isenberg, D. A., Walport, M. J. & Vyse, T. J. (2004) Polymorphism at the C-reactive protein locus influences gene expression and predisposes to systemic lupus erythematosus. Hum Mol Genet 13, 137147.
  • Shai, R., Quismorio Jr, F. P., Li, L., Kwon, O. J., Morrison, J., Wallace, D. J., Neuwelt, C. M., Brautbar, C., Gauderman, W. J. & Jacob, C. O. (1999) Genome-wide screen for systemic lupus erythematosus susceptibility genes in multiplex families. Hum Mol Genet 8, 639644.
  • Sigurdsson, S., Nordmark, G., Goring, H. H., Lindroos, K., Wiman, A. C., Sturfelt, G., Jonsen, A., Rantapaa-Dahlqvist, S., Moller, B., Kere, J., Koskenmies, S., Widen, E., Eloranta, M. L., Julkunen, H., Kristjansdottir, H., Steinsson, K., Alm, G., Ronnblom, L. & Syvanen, A. C. (2005) Polymorphisms in the tyrosine kinase 2 and interferon regulatory factor 5 genes are associated with systemic lupus erythematosus. Am J Hum Genet 76, 528537.
  • The International Hapmap Consortium (2003) The International HapMap Project. Nature 426, 789796.
  • Tsao, B. P., Cantor, R. M., Grossman, J. M., Kim, S. K., Strong, N., Lau, C. S., Chen, C. J., Shen, N., Ginzler, E. M., Goldstein, R., Kalunian, K. C., Arnett, F. C., Wallace, D. J. & Hahn, B. H. (2002) Linkage and interaction of loci on 1q23 and 16q12 may contribute to susceptibility to systemic lupus erythematosus. Arthritis Rheum 46, 29282936.
  • Vyse, T. J., Rozzo, S. J., Drake, C. G., Appel, V. B., Lemeur, M., Izui, S., Palmer, E. & Kotzin, B. L. (1998) Contributions of Ea(z) and Eb(z) MHC genes to lupus susceptibility in New Zealand mice. J Immunol 160, 27572766.
  • Vyse, T. J., Rozzo, S. J., Drake, C. G., Izui, S. & Kotzin, B. L. (1997) Control of multiple autoantibodies linked with a lupus nephritis susceptibility locus in New Zealand black mice. J Immunol 158, 55665574.
  • Yang, W., Shen, N., Ye, D. Q., Liu, Q., Zhang, Y., Qian, X. X., Hirankarn, N., Ying, D., Pan, H. F., Mok, C. C., Chan, T. M., Wong, R. W., Lee, K. W., Mok, M. Y., Wong, S. N., Leung, A. M., Li, X. P., Avihingsanon, Y., Wong, C. M., Lee, T. L., Ho, M. H., Lee, P. P., Chang, Y. K., Li, P. H., Li, R. J., Zhang, L., Wong, W. H., Ng, I. O., Lau, C. S., Sham, P. C. & Lau, Y. L. (2010) Genome-wide association study in Asian populations identifies variants in ETS1 and WDFY4 associated with systemic lupus erythematosus. PLoS Genet 6, e1000841.
  • Ytterberg, S. R. & Schnitzer, T. J. (1982) Serum interferon levels in patients with systemic lupus erythematosus. Arthritis Rheum 25, 401406.

Supporting Information

  1. Top of page
  2. Summary
  3. Introduction
  4. Subjects and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. Author Contributions
  9. Funding
  10. Conflict of Interest
  11. References
  12. Supporting Information

Figure S1 Consensus sequence for region surrounding SNPs, rs856089 and rs856142.

Table S1 Quality control information for all 86 SNPs put forward for genotyping at the HIN200 locus in UK SLE trios.

Table S2 Single marker association analysis for 52 SNPs across the HIN200 locus in a European-American SLE case–control cohort.

Table S3 HIN200 sequencing primers for SNPs rs856089 and rs856142.

Table S4 Comparison of copy number variation events (CNVEs) identified by The Copy Number Variation Discovery Project across the HIN200 region in three HapMap populations.

Table S5 Subphenotype association analysis across the HIN200 locus in UK SLE trios.

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