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Analysis of the IL28RA locus as genetic risk factor for multiple sclerosis
Journal of Neuroimmunology 245 (2012) 98–101
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Analysis of the IL28RA locus as genetic risk factor for multiple sclerosis A. Lopez de Lapuente a, I. Alloza a, R. Goertsches b, U.K. Zettl b, E. Urcelay c, R. Arroyo c, M. Comabella d, X. Montalban d, A. Antigüedad e, K. Vandenbroeck a, f,⁎ a
Neurogenomiks Group, Universidad del País Vasco (UPV/EHU), Leioa, Spain University of Rostock, Department of Neurology, Rostock, Germany Immunology and Neurology departments, Hospital Clínico S. Carlos, Instituto de Investigaciones Sanitarias S. Carlos (IdISSC), Madrid, Spain d Centre d'Esclerosi Múltiple de Catalunya, CEM-Cat Unitat de Neuroimmunologia Clínica, Hospital Universitari Vall d'Hebron, Barcelona, Spain e Servicio de Neurología, Hospital de Basurto, Bilbao, Spain f IKERBASQUE, Basque Foundation for Science, Bilbao, Spain b c
a r t i c l e
i n f o
Article history: Received 15 December 2011 Received in revised form 24 January 2012 Accepted 6 February 2012 Keywords: Interleukin-28 receptor alpha Interferon-λ Multiple sclerosis Polymorphism
a b s t r a c t Recently, we reported an association between a SNP in IL28RA and MS. Here, we performed a fine-mapping of the IL28RA locus by genotyping 10 haplotype-tagging SNPs in a Basque-Spanish population. In addition, based on shared genetic risk loci between autoimmune diseases, a psoriasis-associated SNP located at this locus, rs4649203, was genotyped in four independent populations, comprising a total of 2582 cases and 2614 controls. We did not find any consistent association between IL28RA and MS in these populations, suggesting that, although it may play a role in other autoimmune diseases, this gene is unlikely of general relevance to MS pathogenesis. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system with a prominent inflammatory component and probable autoimmune pathogenesis. The etiology of the disorder is still not completely understood, although it is widely accepted that it results from the interaction of several as yet unknown environmental factors with a range of genetic determinants. Apart from the well known HLA-DRB1*15:01-carrying risk haplotype on chromosome 6p21.3 (Jersild et al., 1972; Fogdell et al., 1995), genome-wide (GWAS) and candidate gene association studies have led to the discovery of about 50 non-HLA genes that exert moderate effects on the risk for the disorder (odds ratios 1.2-1.3), and many of these are related to inflammation and the immune system (Oksenberg and Baranzini, 2010; Sawcer et al., 2011). Some of the SNPs that have been found associated with MS are also associated with other autoimmune diseases, suggesting common underlying etiologic mechanisms (Oksenberg and Baranzini, 2010). Cytokine (receptor) genes feature pronouncedly among genetic risk factors for autoimmune disease, with more than 35 such loci emerging from GWAS on >15 autoimmune disorders (Vandenbroeck, in press).
⁎ Corresponding author at: Neurogenomiks Laboratory, Universidad del País Vasco (UPV-EHU), Edificio 205, planta − 1, Parque Tecnológico de Bizkaia, 48170 Zamudio (Bizkaia), Spain. Tel.: + 34 946018291; fax: + 34 946018289. E-mail address: [email protected] (K. Vandenbroeck). 0165-5728/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.jneuroim.2012.02.005
IL28RA codes for a transmembrane protein that heterodimerizes with another subunit, IL-10RB, to form a type II cytokine receptor, which binds IL-28A, IL-28B and IL-29, also known as class III or lambda interferons. These ligands, which are distantly related to class I interferons, are activated upon viral infection and trigger the JAK-STAT signaling pathway to exert antiviral activity (Kotenko et al., 2003; Sheppard et al., 2003; Dumoutier et al., 2004). The class III interferon pathway is likely to influence susceptibility to various inflammatory and infectious diseases, and polymorphisms in genes integrating this pathway have been related to several conditions, including MS, hepatitis C (Fortunato et al., 2008), hepatitis B (Gong et al., 2009) or allergic rhinitis (Chae et al., 2006). Recently, a genome-wide association study (Strange et al., 2010) found one SNP in IL28RA, rs4649203, associated with psoriasis, an autoimmune disease that shares some susceptibility loci with MS (Ban et al., 2009; Strange et al., 2010). IL28RA is located on chromosome 1p36.11, only 11 kb away from IL22RA1, another gene coding for a cytokine receptor. In a recent study, we reported association of one SNP, rs1416834, with MS (Vandenbroeck et al., 2012), as a result of a comprehensive cytokine and cytokine-receptor association screen including 9 SNPs in a 67.5Kb interval encompassing the IL22RA1-IL28RA gene cluster. This SNP presented an opposite pattern of allelic association in a population from Bilbao, in northern Spain, to that observed in cohorts from Madrid and Barcelona, in central and eastern Spain, respectively. Given the reported genetic separation between the Basque and other European populations (Rodríguez-Ezpeleta et al., 2010), we hypothesized that this “flip-flop” association could be due to population-based
A. Lopez de Lapuente et al. / Journal of Neuroimmunology 245 (2012) 98–101
differences in interlocus correlation with the actual causative variant in this region (Lin et al., 2007; and Clarke and Cardon, 2010). In order to elucidate the relationship between IL28RA and MS risk, we carried out a fine mapping of a 67-kb area surrounding this locus. Using a haplotype-tagging approach, we genotyped 10 additional SNPs in the Bilbao cohort. We also genotyped rs4648203, which has been found associated with psoriasis (Strange et al., 2010), in MS patients and controls from Bilbao, Barcelona and Madrid (Spain) and Rostock (Germany). 2. Material and methods 2.1. Patients and controls A summary of the clinical and demographic details of the populations used for this study is given in Table 1. Fine mapping of IL28RA region was completed in the full Bilbao cohort. This sample size provided a minimum statistical power of 90% to detect a 1.38 fold difference in risk with a significance level of p = 0.05 under a multiplicative model (OR cut-off based on the observed OR for rs1416834 in the primary screen (Vandenbroeck et al., 2012)). Patients of the Bilbao cohort were recruited at the Basurto Hospital, and healthy controls were provided by the Basque Biobank of the Fundación Vasca de Innovación e Investigación Sanitaria. Rs4649203 was also genotyped in three further sample sets: Barcelona (Hospital Vall d'Hebron; 708 cases and 825 controls), Madrid (Hospital Clínico S Carlos; 715 cases and 646 controls), and Rostock (Neurology Department, University of Rostock; 571 cases and 576 controls). Combining the 4 cohorts, we achieved a minimum statistical power of 97% to detect a 1.2 fold difference in risk with a significance level of p = 0.05 under a multiplicative model. All patients were diagnosed with definite MS (Poser et al., 1983; McDonald et al., 2001). Samples were collected on the basis of written informed consent, and the study was approved by the local ethics committees. 2.2. Selection and genotyping of SNPs 10 haplotype-tagging SNPs were selected using the Multimarker Tagger Algorithm implemented in the HapMap website (www. hapmap.org), based on data from the CEU + TSI population (r 2 cutoff = 0.8, MAF = 0.2, HapMap release #27). Rs4649203 was selected for genotyping based on the evidence of association with psoriasis (Strange et al., 2010). All SNPs were in Hardy-Weinberg equilibrium in controls (p > 0.05). Haplotype-tagging SNPs were genotyped in the Bilbao cohort using the iPLEX Sequenom MassARRAY platform in the Spanish National Genotyping Center (CEGEN, Santiago de Compostela, www. cegen.es). In addition, the top-scoring SNP from the previous screen (Vandenbroeck et al., 2012), rs1416834, was re-typed to assess genotyping concordance between the Sequenom technology used in this study and the Illumina Bead Array Matrix SNP panel used in the previous one, with a genotyping concordance rate of 99.2%. Genotyping of rs4649203 in all cohorts was performed using Taqman® Genotyping Assays, following the manufacturer's instructions.
99
2.3. Statistical analysis PLINK genetic analysis toolset, v 1.07 (Purcell et al., 2007) was used for data management and statistical analysis. An allelic chisquare test was applied to ascertain associations. Stratified analysis of the data from different populations was performed by means of the Cochran-Mantel-Haenzel test, and homogeneity of the odd ratios was assessed by the Breslow-Day test. A chi-squared test was used to check for Hardy-Weinberg equilibrium. For the haplotype analysis, Haploview v.4.2 was employed (Barrett et al., 2005). The haplotype blocks were determined by the confidence interval method implemented in Haploview (Gabriel et al., 2002). Only the samples that had genotyping data available for all the SNPs were used for the haplotype calculation (765 samples, 351 cases and 414 controls). All p values are uncorrected. Statistical power was calculated using the CATS power calculator at www.sph.umich.edu/csg/abecasis/CaTS/ (Skol et al., 2006). The linkage disequilibrium patterns between SNPs were analyzed with the SNP annotation and Proxy Search tool at http://www.broadinstitute.org/mpg/snap/ (Johnson et al., 2008). 3. Results and discussion A fine mapping of the IL28RA region was carried out by genotyping 10 haplotype-tagging SNPs in the Bilbao collection, which for this purpose was increased to include an extra 126 cases and 97 controls compared to the original Bilbao cohort of the first screening (Table 1; Vandenbroeck et al., 2012). In addition to these 10 SNPs, the IL28RA SNP that showed the highest association in the first screening, rs1416834, was re-typed to check for genotyping concordance (see Materials and methods), which was higher than 99%. As a result of this exercise, we observed that the inclusion of 223 extra samples resulted in a decrease of the p value with respect to that seen in the primary screen (primary screen p = 0.0008, present study p = 0.002, Table 2). Of the 10 new SNPs genotyped, we observed significant p values for two, rs10903035 and rs7524076, but none of the SNPs exhibited a more significant association than rs1416834 (Table 2). Recently, a SNP in IL28RA, rs4649203, emerged with genome-wide significance [p = 6.46 × 10 − 6, OR (95%CI) =1.22 (1.12–1.32)] from a GWAS on psoriasis (Strange et al., 2010). This finding reinforced the notion that IL28RA might represent a true susceptibility gene for MS, given the known sharing of several susceptibility loci between psoriasis and MS, including IL12B chr5q33.3 (Strange et al., 2010; Sawcer et al., 2011) and TYK2 on chr19p13.2 (Ban et al., 2009; Strange et al., 2010). rs4649203 was genotyped in the four available collections (Table 3). Although it displayed a weak association in the Bilbao cohort (p = 0.03), this could not be confirmed in any of the other populations. Stratified analysis showed no significant association when considering all the cohorts combined (Table 3). These results seem to indicate that rs4649203 is not the principal variant that determines association of IL28RA with MS, as seen in the Spanish Basque cohort. We had data on 6 SNPs in IL22RA1 (rs3795300, rs3795299, rs12093987, rs11249201, rs11577442 and rs4486393) available from our initial screening in the Bilbao cohort (Vandenbroeck et al.,
Table 1 Clinical and demographic features of patients and controls. Population
Bilbao Barcelona Madrid Rostock 1
Controls
Cases
Number
Male/Female/ND1 (%)
Number
Male/Female/ND1 (%)
RR & SP/PP/other/ND1
Age at onset (average ± S.D.)
EDSS (mean ± S.D.)
567 825 646 576
30/70/0 46.5/53.5/0 41.5/52.6/5.9 28/72/0
588 708 715 571
29/71/0 36.7/63.3/0 34.2/63.6/2.2 27.3/72.5/0.2
87.4/10/1.5/1.1 78/21.2/0.8 79.2/9.4/0.5/10.9 89/8.6/2.3/0.1
30.5 ± 10.5 30.4 ± 10.8 28.8 ± 8.8 35.7 ± 11.7
2.9 ± 2.3 4.3 ± 2.7 2.9 ± 2.1 3.2 ± 2.2
ND, not determined.
100
A. Lopez de Lapuente et al. / Journal of Neuroimmunology 245 (2012) 98–101
Table 2 Fine mapping of the IL22RA1-IL28RA cluster in the Bilbao cohort. SNP
Chromosome position (bp)1
RAF3 controls
P value
OR4 (95% CI)
Intron 1 0.3374 Intergenic region 0.7735
0.3208 0.7653
0.4005 0.6423
1.078 (0.904-1.285) 1.047 (0.861-1.274)
3’ UTR 3’ UTR
0.3115 0.3062
0.255 0.2715
Intron 4 Intron 3 Intron 1 Intron 1 Intron 1 5’ flanking region 5’ flanking region
0.3904 0.4403 0.348 0.5862 0.3491 0.522
0.3298 0.4256 0.3354 0.5432 0.3232 0.4946
0.002986 1.322 (1.009-1.590) 0.068 1.184 (0.98751.420) 0.002089 1.301 (1.100-1.541) 0.4801 1.062 (0.899-1.258) 0.5295 1.057 (0.888-1.258) 0.03857 1.192 (1.009-1.402) 0.1921 1.123 (0.943-1.338) 0.1933 1.116 (0.946-1.317)
0.1964
0.1867
0.5591
Major/minor alleles2
Risk allele
Gene
Location in gene
rs4648936 24341048 rs11579657 24349473
A/G A/G
G A
rs10903035 24354527 rs11249006 24355061
A/G G/A
G A
IL22RA1 IL22RA1IL28RA IL28RA IL28RA
rs1416834 rs11249017 rs6683433 rs7524076 rs10903047 rs11587500
24359247 24369249 24380361 24381297 24381661 24389467
A/G T/C T/C A/G T/A G/A
G C C A A A
IL28RA IL28RA IL28RA IL28RA IL28RA IL28RA
rs870549
24398583
C/T
T
IL28RA
RAF3 cases
1.064 (0.863-1.312)
1
SNPs are ordered according to chromosome position, NCBI reference assembly, genome build 36.3. Significantly associated SNPs are highlighted. Major and minor alleles in unaffected controls; reference alleles according to NCBI reference sequence. RAF, risk allele frequency. 4 OR is calculated for the risk allele. 2 3
Table 3 Genotyping results for the psoriasis-associated SNP rs4649203 in the 4 available MS cohorts. Population
Major/minor alleles2
Risk allele
RAF3 cases
RAF3 controls
P value
OR (95% CI)
P_Breslow-Day
Bilbao Madrid Barcelona Rostock Combined1
A/G A/G A/G A/G A/G
A A G G A
0.764 0.7514 0.2515 0.2774 0.747
0.7245 0.7477 0.25 0.2535 0.743
0.03137 0.8223 0.9263 0.1975 0.6414
1.231 (1.019-1.487) 1.02 (0.857-1.214) 1.008 (0.852-1.193) 1.13 (0.938-1.362) 1.021 (0.934-1.117)
0.1052
1
For the combined dataset, Cochran-Mantel-Haenzel p value is indicated. 2 Major and minor alleles in unaffected controls; reference alleles according to NCBI reference sequence. 3 RAF, risk allele frequency.
2012). None of these SNPs showed a significant p value, therefore, we discarded IL22RA1 as a genetic risk factor in our population. However, given the proximity of the two genes, we decided to consider both together for the haplotype analysis. For this analysis, in addition to the SNPs genotyped for this study, we also took into account the SNPs in IL28RA that were genotyped in the primary screen (rs1416834, rs7552086 and rs7520329), resulting in a total of 20 SNPs. The LD structure and recombination rates of the region encompassing IL22RA1 and IL28RA are shown in Fig. 1. The association of the haplotypes formed by the SNPs in LD blocks did not explain the association better than single SNPs in IL28RA (Table 4).
In our previous study, we had genotyped rs1416384 in the Barcelona and Madrid cohorts and found significant association in both of these albeit with opposite risk alleles when compared to the Bilbao cohort. The identification of a SNP with a more significant association than rs1416834 in the Bilbao collection after the present fine-mapping exercise (Table 2) would thus have justified a follow-up in the rest of the cohorts; however, this was not the case. Moreover, the genotyping of a potentially more important SNP, like rs4649203, which had already demonstrated association with another autoimmune disease (Strange et al., 2010), yielded weakly positive results in the Bilbao cohort and negative results in the rest of the populations. In view of these findings,
Fig. 1. SNPs genotyped in the Bilbao cohort. IL28RA and IL22RA1 gene structure is shown. In the lower panel, LD pattern of the IL22RA1-IL28RA region, as derived from data of the 20 SNPs genotyped in the Bilbao population, is shown. LD blocks, as calculated by the confidence intervals algorithm implemented in Haploview (Gabriel et al., 2002; Barrett et al., 2005) are highlighted. The numbers inside the squares correspond to r2 values, and darker shades of grey represent stronger correlation between SNPs. Above the LD plot, recombination rate (cM/Mb) along the region is plotted (recombination data retrieved from the Hapmap project, release #22, rates estimated from the CEU, YRI and JPT + CHB populations. www.hapmap.org).
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Table 4 Haplotype analysis of all the SNPs in the IL22RA1-IL28RA locus in the Bilbao cohort. Block1
Haplotype2
Frequency
Case,Control Frequencies
OR (95% CI)
P Value
AC GG AG
0.451 0.361 0.188
0.457, 0.446 0.360, 0.362 0.182, 0.192
1.05 (0.92-1.14) 0.99 (0.88-1.15) 0.94 (0.72-1.21)
0.6492 0.9379 0.6284
AGG GAG AAA AAG
0.46 0.234 0.172 0.131
0.426, 0.234, 0.185, 0.150,
0.78 1.00 1.18 1.37
(0.63-0.95) (0.79-1.27) (0.9-1.54) (1.02-1.85)
0.0156 0.9785 0.2283 0.0369
AA GA AG
0.437 0.33 0.232
0.431, 0.442 0.334, 0.327 0.235, 0.229
0.95 (0.78-1.17) 1.03 (0.84-1.28) 1.03 (0.81-1.31)
0.6442 0.7595 0.7994
GAA AGG GGA
0.637 0.288 0.064
0.594, 0.674 0.309, 0.269 0.080, 0.051
0.71 (0.57-0.87) 1.21 (0.97-1.52) 1.62 (1.07-2.45)
0.0012 0.0867 0.0208
rs3795300 + rs3795299
rs11249201 + rs11577442 + rs4486939 0.488 0.233 0.161 0.114
rs4648936 + rs11579657
rs11249006 + rs1416834 + rs7552086
1 2
Haplotype blocks were calculated using the confidence interval algorithm implemented in Haploview 4.2 (Gabriel et al., 2002; Barrett et al., 2005). For the haplotype analysis, only samples that had genotyping data for all 20 SNPs were taken into account (765 samples, 351 cases and 414 controls).
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Analysis of the IL28RA locus as genetic risk factor for multiple sclerosis A. Lopez de Lapuente a, I. Alloza a, R. Goertsches b, U.K. Zettl b, E. Urcelay c, R. Arroyo c, M. Comabella d, X. Montalban d, A. Antigüedad e, K. Vandenbroeck a, f,⁎ a
Neurogenomiks Group, Universidad del País Vasco (UPV/EHU), Leioa, Spain University of Rostock, Department of Neurology, Rostock, Germany Immunology and Neurology departments, Hospital Clínico S. Carlos, Instituto de Investigaciones Sanitarias S. Carlos (IdISSC), Madrid, Spain d Centre d'Esclerosi Múltiple de Catalunya, CEM-Cat Unitat de Neuroimmunologia Clínica, Hospital Universitari Vall d'Hebron, Barcelona, Spain e Servicio de Neurología, Hospital de Basurto, Bilbao, Spain f IKERBASQUE, Basque Foundation for Science, Bilbao, Spain b c
a r t i c l e
i n f o
Article history: Received 15 December 2011 Received in revised form 24 January 2012 Accepted 6 February 2012 Keywords: Interleukin-28 receptor alpha Interferon-λ Multiple sclerosis Polymorphism
a b s t r a c t Recently, we reported an association between a SNP in IL28RA and MS. Here, we performed a fine-mapping of the IL28RA locus by genotyping 10 haplotype-tagging SNPs in a Basque-Spanish population. In addition, based on shared genetic risk loci between autoimmune diseases, a psoriasis-associated SNP located at this locus, rs4649203, was genotyped in four independent populations, comprising a total of 2582 cases and 2614 controls. We did not find any consistent association between IL28RA and MS in these populations, suggesting that, although it may play a role in other autoimmune diseases, this gene is unlikely of general relevance to MS pathogenesis. © 2012 Elsevier B.V. All rights reserved.
1. Introduction Multiple sclerosis (MS) is a demyelinating disorder of the central nervous system with a prominent inflammatory component and probable autoimmune pathogenesis. The etiology of the disorder is still not completely understood, although it is widely accepted that it results from the interaction of several as yet unknown environmental factors with a range of genetic determinants. Apart from the well known HLA-DRB1*15:01-carrying risk haplotype on chromosome 6p21.3 (Jersild et al., 1972; Fogdell et al., 1995), genome-wide (GWAS) and candidate gene association studies have led to the discovery of about 50 non-HLA genes that exert moderate effects on the risk for the disorder (odds ratios 1.2-1.3), and many of these are related to inflammation and the immune system (Oksenberg and Baranzini, 2010; Sawcer et al., 2011). Some of the SNPs that have been found associated with MS are also associated with other autoimmune diseases, suggesting common underlying etiologic mechanisms (Oksenberg and Baranzini, 2010). Cytokine (receptor) genes feature pronouncedly among genetic risk factors for autoimmune disease, with more than 35 such loci emerging from GWAS on >15 autoimmune disorders (Vandenbroeck, in press).
⁎ Corresponding author at: Neurogenomiks Laboratory, Universidad del País Vasco (UPV-EHU), Edificio 205, planta − 1, Parque Tecnológico de Bizkaia, 48170 Zamudio (Bizkaia), Spain. Tel.: + 34 946018291; fax: + 34 946018289. E-mail address: [email protected] (K. Vandenbroeck). 0165-5728/$ – see front matter © 2012 Elsevier B.V. All rights reserved. doi:10.1016/j.jneuroim.2012.02.005
IL28RA codes for a transmembrane protein that heterodimerizes with another subunit, IL-10RB, to form a type II cytokine receptor, which binds IL-28A, IL-28B and IL-29, also known as class III or lambda interferons. These ligands, which are distantly related to class I interferons, are activated upon viral infection and trigger the JAK-STAT signaling pathway to exert antiviral activity (Kotenko et al., 2003; Sheppard et al., 2003; Dumoutier et al., 2004). The class III interferon pathway is likely to influence susceptibility to various inflammatory and infectious diseases, and polymorphisms in genes integrating this pathway have been related to several conditions, including MS, hepatitis C (Fortunato et al., 2008), hepatitis B (Gong et al., 2009) or allergic rhinitis (Chae et al., 2006). Recently, a genome-wide association study (Strange et al., 2010) found one SNP in IL28RA, rs4649203, associated with psoriasis, an autoimmune disease that shares some susceptibility loci with MS (Ban et al., 2009; Strange et al., 2010). IL28RA is located on chromosome 1p36.11, only 11 kb away from IL22RA1, another gene coding for a cytokine receptor. In a recent study, we reported association of one SNP, rs1416834, with MS (Vandenbroeck et al., 2012), as a result of a comprehensive cytokine and cytokine-receptor association screen including 9 SNPs in a 67.5Kb interval encompassing the IL22RA1-IL28RA gene cluster. This SNP presented an opposite pattern of allelic association in a population from Bilbao, in northern Spain, to that observed in cohorts from Madrid and Barcelona, in central and eastern Spain, respectively. Given the reported genetic separation between the Basque and other European populations (Rodríguez-Ezpeleta et al., 2010), we hypothesized that this “flip-flop” association could be due to population-based
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differences in interlocus correlation with the actual causative variant in this region (Lin et al., 2007; and Clarke and Cardon, 2010). In order to elucidate the relationship between IL28RA and MS risk, we carried out a fine mapping of a 67-kb area surrounding this locus. Using a haplotype-tagging approach, we genotyped 10 additional SNPs in the Bilbao cohort. We also genotyped rs4648203, which has been found associated with psoriasis (Strange et al., 2010), in MS patients and controls from Bilbao, Barcelona and Madrid (Spain) and Rostock (Germany). 2. Material and methods 2.1. Patients and controls A summary of the clinical and demographic details of the populations used for this study is given in Table 1. Fine mapping of IL28RA region was completed in the full Bilbao cohort. This sample size provided a minimum statistical power of 90% to detect a 1.38 fold difference in risk with a significance level of p = 0.05 under a multiplicative model (OR cut-off based on the observed OR for rs1416834 in the primary screen (Vandenbroeck et al., 2012)). Patients of the Bilbao cohort were recruited at the Basurto Hospital, and healthy controls were provided by the Basque Biobank of the Fundación Vasca de Innovación e Investigación Sanitaria. Rs4649203 was also genotyped in three further sample sets: Barcelona (Hospital Vall d'Hebron; 708 cases and 825 controls), Madrid (Hospital Clínico S Carlos; 715 cases and 646 controls), and Rostock (Neurology Department, University of Rostock; 571 cases and 576 controls). Combining the 4 cohorts, we achieved a minimum statistical power of 97% to detect a 1.2 fold difference in risk with a significance level of p = 0.05 under a multiplicative model. All patients were diagnosed with definite MS (Poser et al., 1983; McDonald et al., 2001). Samples were collected on the basis of written informed consent, and the study was approved by the local ethics committees. 2.2. Selection and genotyping of SNPs 10 haplotype-tagging SNPs were selected using the Multimarker Tagger Algorithm implemented in the HapMap website (www. hapmap.org), based on data from the CEU + TSI population (r 2 cutoff = 0.8, MAF = 0.2, HapMap release #27). Rs4649203 was selected for genotyping based on the evidence of association with psoriasis (Strange et al., 2010). All SNPs were in Hardy-Weinberg equilibrium in controls (p > 0.05). Haplotype-tagging SNPs were genotyped in the Bilbao cohort using the iPLEX Sequenom MassARRAY platform in the Spanish National Genotyping Center (CEGEN, Santiago de Compostela, www. cegen.es). In addition, the top-scoring SNP from the previous screen (Vandenbroeck et al., 2012), rs1416834, was re-typed to assess genotyping concordance between the Sequenom technology used in this study and the Illumina Bead Array Matrix SNP panel used in the previous one, with a genotyping concordance rate of 99.2%. Genotyping of rs4649203 in all cohorts was performed using Taqman® Genotyping Assays, following the manufacturer's instructions.
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2.3. Statistical analysis PLINK genetic analysis toolset, v 1.07 (Purcell et al., 2007) was used for data management and statistical analysis. An allelic chisquare test was applied to ascertain associations. Stratified analysis of the data from different populations was performed by means of the Cochran-Mantel-Haenzel test, and homogeneity of the odd ratios was assessed by the Breslow-Day test. A chi-squared test was used to check for Hardy-Weinberg equilibrium. For the haplotype analysis, Haploview v.4.2 was employed (Barrett et al., 2005). The haplotype blocks were determined by the confidence interval method implemented in Haploview (Gabriel et al., 2002). Only the samples that had genotyping data available for all the SNPs were used for the haplotype calculation (765 samples, 351 cases and 414 controls). All p values are uncorrected. Statistical power was calculated using the CATS power calculator at www.sph.umich.edu/csg/abecasis/CaTS/ (Skol et al., 2006). The linkage disequilibrium patterns between SNPs were analyzed with the SNP annotation and Proxy Search tool at http://www.broadinstitute.org/mpg/snap/ (Johnson et al., 2008). 3. Results and discussion A fine mapping of the IL28RA region was carried out by genotyping 10 haplotype-tagging SNPs in the Bilbao collection, which for this purpose was increased to include an extra 126 cases and 97 controls compared to the original Bilbao cohort of the first screening (Table 1; Vandenbroeck et al., 2012). In addition to these 10 SNPs, the IL28RA SNP that showed the highest association in the first screening, rs1416834, was re-typed to check for genotyping concordance (see Materials and methods), which was higher than 99%. As a result of this exercise, we observed that the inclusion of 223 extra samples resulted in a decrease of the p value with respect to that seen in the primary screen (primary screen p = 0.0008, present study p = 0.002, Table 2). Of the 10 new SNPs genotyped, we observed significant p values for two, rs10903035 and rs7524076, but none of the SNPs exhibited a more significant association than rs1416834 (Table 2). Recently, a SNP in IL28RA, rs4649203, emerged with genome-wide significance [p = 6.46 × 10 − 6, OR (95%CI) =1.22 (1.12–1.32)] from a GWAS on psoriasis (Strange et al., 2010). This finding reinforced the notion that IL28RA might represent a true susceptibility gene for MS, given the known sharing of several susceptibility loci between psoriasis and MS, including IL12B chr5q33.3 (Strange et al., 2010; Sawcer et al., 2011) and TYK2 on chr19p13.2 (Ban et al., 2009; Strange et al., 2010). rs4649203 was genotyped in the four available collections (Table 3). Although it displayed a weak association in the Bilbao cohort (p = 0.03), this could not be confirmed in any of the other populations. Stratified analysis showed no significant association when considering all the cohorts combined (Table 3). These results seem to indicate that rs4649203 is not the principal variant that determines association of IL28RA with MS, as seen in the Spanish Basque cohort. We had data on 6 SNPs in IL22RA1 (rs3795300, rs3795299, rs12093987, rs11249201, rs11577442 and rs4486393) available from our initial screening in the Bilbao cohort (Vandenbroeck et al.,
Table 1 Clinical and demographic features of patients and controls. Population
Bilbao Barcelona Madrid Rostock 1
Controls
Cases
Number
Male/Female/ND1 (%)
Number
Male/Female/ND1 (%)
RR & SP/PP/other/ND1
Age at onset (average ± S.D.)
EDSS (mean ± S.D.)
567 825 646 576
30/70/0 46.5/53.5/0 41.5/52.6/5.9 28/72/0
588 708 715 571
29/71/0 36.7/63.3/0 34.2/63.6/2.2 27.3/72.5/0.2
87.4/10/1.5/1.1 78/21.2/0.8 79.2/9.4/0.5/10.9 89/8.6/2.3/0.1
30.5 ± 10.5 30.4 ± 10.8 28.8 ± 8.8 35.7 ± 11.7
2.9 ± 2.3 4.3 ± 2.7 2.9 ± 2.1 3.2 ± 2.2
ND, not determined.
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Table 2 Fine mapping of the IL22RA1-IL28RA cluster in the Bilbao cohort. SNP
Chromosome position (bp)1
RAF3 controls
P value
OR4 (95% CI)
Intron 1 0.3374 Intergenic region 0.7735
0.3208 0.7653
0.4005 0.6423
1.078 (0.904-1.285) 1.047 (0.861-1.274)
3’ UTR 3’ UTR
0.3115 0.3062
0.255 0.2715
Intron 4 Intron 3 Intron 1 Intron 1 Intron 1 5’ flanking region 5’ flanking region
0.3904 0.4403 0.348 0.5862 0.3491 0.522
0.3298 0.4256 0.3354 0.5432 0.3232 0.4946
0.002986 1.322 (1.009-1.590) 0.068 1.184 (0.98751.420) 0.002089 1.301 (1.100-1.541) 0.4801 1.062 (0.899-1.258) 0.5295 1.057 (0.888-1.258) 0.03857 1.192 (1.009-1.402) 0.1921 1.123 (0.943-1.338) 0.1933 1.116 (0.946-1.317)
0.1964
0.1867
0.5591
Major/minor alleles2
Risk allele
Gene
Location in gene
rs4648936 24341048 rs11579657 24349473
A/G A/G
G A
rs10903035 24354527 rs11249006 24355061
A/G G/A
G A
IL22RA1 IL22RA1IL28RA IL28RA IL28RA
rs1416834 rs11249017 rs6683433 rs7524076 rs10903047 rs11587500
24359247 24369249 24380361 24381297 24381661 24389467
A/G T/C T/C A/G T/A G/A
G C C A A A
IL28RA IL28RA IL28RA IL28RA IL28RA IL28RA
rs870549
24398583
C/T
T
IL28RA
RAF3 cases
1.064 (0.863-1.312)
1
SNPs are ordered according to chromosome position, NCBI reference assembly, genome build 36.3. Significantly associated SNPs are highlighted. Major and minor alleles in unaffected controls; reference alleles according to NCBI reference sequence. RAF, risk allele frequency. 4 OR is calculated for the risk allele. 2 3
Table 3 Genotyping results for the psoriasis-associated SNP rs4649203 in the 4 available MS cohorts. Population
Major/minor alleles2
Risk allele
RAF3 cases
RAF3 controls
P value
OR (95% CI)
P_Breslow-Day
Bilbao Madrid Barcelona Rostock Combined1
A/G A/G A/G A/G A/G
A A G G A
0.764 0.7514 0.2515 0.2774 0.747
0.7245 0.7477 0.25 0.2535 0.743
0.03137 0.8223 0.9263 0.1975 0.6414
1.231 (1.019-1.487) 1.02 (0.857-1.214) 1.008 (0.852-1.193) 1.13 (0.938-1.362) 1.021 (0.934-1.117)
0.1052
1
For the combined dataset, Cochran-Mantel-Haenzel p value is indicated. 2 Major and minor alleles in unaffected controls; reference alleles according to NCBI reference sequence. 3 RAF, risk allele frequency.
2012). None of these SNPs showed a significant p value, therefore, we discarded IL22RA1 as a genetic risk factor in our population. However, given the proximity of the two genes, we decided to consider both together for the haplotype analysis. For this analysis, in addition to the SNPs genotyped for this study, we also took into account the SNPs in IL28RA that were genotyped in the primary screen (rs1416834, rs7552086 and rs7520329), resulting in a total of 20 SNPs. The LD structure and recombination rates of the region encompassing IL22RA1 and IL28RA are shown in Fig. 1. The association of the haplotypes formed by the SNPs in LD blocks did not explain the association better than single SNPs in IL28RA (Table 4).
In our previous study, we had genotyped rs1416384 in the Barcelona and Madrid cohorts and found significant association in both of these albeit with opposite risk alleles when compared to the Bilbao cohort. The identification of a SNP with a more significant association than rs1416834 in the Bilbao collection after the present fine-mapping exercise (Table 2) would thus have justified a follow-up in the rest of the cohorts; however, this was not the case. Moreover, the genotyping of a potentially more important SNP, like rs4649203, which had already demonstrated association with another autoimmune disease (Strange et al., 2010), yielded weakly positive results in the Bilbao cohort and negative results in the rest of the populations. In view of these findings,
Fig. 1. SNPs genotyped in the Bilbao cohort. IL28RA and IL22RA1 gene structure is shown. In the lower panel, LD pattern of the IL22RA1-IL28RA region, as derived from data of the 20 SNPs genotyped in the Bilbao population, is shown. LD blocks, as calculated by the confidence intervals algorithm implemented in Haploview (Gabriel et al., 2002; Barrett et al., 2005) are highlighted. The numbers inside the squares correspond to r2 values, and darker shades of grey represent stronger correlation between SNPs. Above the LD plot, recombination rate (cM/Mb) along the region is plotted (recombination data retrieved from the Hapmap project, release #22, rates estimated from the CEU, YRI and JPT + CHB populations. www.hapmap.org).
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Table 4 Haplotype analysis of all the SNPs in the IL22RA1-IL28RA locus in the Bilbao cohort. Block1
Haplotype2
Frequency
Case,Control Frequencies
OR (95% CI)
P Value
AC GG AG
0.451 0.361 0.188
0.457, 0.446 0.360, 0.362 0.182, 0.192
1.05 (0.92-1.14) 0.99 (0.88-1.15) 0.94 (0.72-1.21)
0.6492 0.9379 0.6284
AGG GAG AAA AAG
0.46 0.234 0.172 0.131
0.426, 0.234, 0.185, 0.150,
0.78 1.00 1.18 1.37
(0.63-0.95) (0.79-1.27) (0.9-1.54) (1.02-1.85)
0.0156 0.9785 0.2283 0.0369
AA GA AG
0.437 0.33 0.232
0.431, 0.442 0.334, 0.327 0.235, 0.229
0.95 (0.78-1.17) 1.03 (0.84-1.28) 1.03 (0.81-1.31)
0.6442 0.7595 0.7994
GAA AGG GGA
0.637 0.288 0.064
0.594, 0.674 0.309, 0.269 0.080, 0.051
0.71 (0.57-0.87) 1.21 (0.97-1.52) 1.62 (1.07-2.45)
0.0012 0.0867 0.0208
rs3795300 + rs3795299
rs11249201 + rs11577442 + rs4486939 0.488 0.233 0.161 0.114
rs4648936 + rs11579657
rs11249006 + rs1416834 + rs7552086
1 2
Haplotype blocks were calculated using the confidence interval algorithm implemented in Haploview 4.2 (Gabriel et al., 2002; Barrett et al., 2005). For the haplotype analysis, only samples that had genotyping data for all 20 SNPs were taken into account (765 samples, 351 cases and 414 controls).
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